RESULTS OF THE THIRD JOINT US-USSR
BERING & CHUKCHI SEAS EXPEDITION

(BERPAC)

SUMMER 1988

UNITED STATES DEPARTMENT OF THE INTERIOR / Fish and Wndlife Service

KJ

<^

era

CO

8 Ss^iJ3

• •• O M

a

IS"!

L (V

Woods ^-^^i Ju-^nographic

\ -

tieMco

RESULTS OF THE THIRD JOINT US-USSR
BERING & CHUKCHI SEAS EXPEDITION

(BERPAC)

'. r~

; _D

; =0
: CD

: O

: r^

; a
I m

; D

SUMMER 1988

^wOQS VIC -u-^w >-■--• •

T Li3P.Ar(Y ,

Results of the Third Joint

US-USSR Bering & Chukchi Seas

Expedition (BERPAC)

Summer 1988

John F. Turner
Director, US Fish and

WildHfe Service,
Washington, DC

Yuriy A. Izrael
Chairman, USSR State

Committee for Hydrometeorology
Moscow, USSR

Harold J. O'Connor

Project Leader, USA

US Fish and Wildlife Service

Patuxent Wildlife Research Center

Laurel, Maryland

Alia V. Tsyban

Project Leader, USSR

Institute of Global Climate and Ecology

State Committee for Hydrometeorology

Academy of Sciences

Moscow, USSR

Copies of this publication may be obtained from the Publications Unit, US Fish and Wildlife
Service, 1849 C Street, NW. Mail Stop 130— ARLSQ. Washington, DC 20240.

Suggested Citation:

Nagel. P. A. (ed.) (1992). Results of the ThinlJoint US-USSR Bering & Chukchi Seas

Expedition (BERPAC), Summer 1988. US Fish and Wildlife Service, Washington, DC.

Disclaimer:

The opinions and recommendations expressed in this report are those of the authors and do not necessarily reflect the
views of the US Fish and Wildlife Service, nor does the mention of trade names constitute endorsement or
recomiTiendation for use by the Federal Government.

Foreword

In the last few years, an ever-growing anthropogenic
impact on different natural ecosystems and the adverse effects
resulting from this impact have led humanity to reali/e the real
threat of potential global ecological disasters and to give a high
priority to environmental protection.

Natural factors cause the bulk of nearly all man-made
chemicals to eventually enter the World Ocean, which, owing
to this, can be considered a tremendous reservoir/accumulator
of contaminants. Elimination of these contaminants through
natural processes of the ocean (i. e.. self-purification) occurs
through a complex system of physical, chemical, and biological
processes taking place in the ocean. However, conditions
favorable for the existence of certain hydrobionts that were
established over whole geological epochs are being disturbed
by these anthropogenic impacts. For these reasons, it is
obvious that while studying ocean pollution and its ecological
consequences, it becomes necessary to have complex physical,
chemical, and biological investigations, which calls for
principally new, interdisciplinary approaches to the solution of
this problem.

The protection of the marine environment against the
undesirable influence of anthropogenic factors are global
problems common to all mankind. They can, and must, be
solved by joint efforts of scientists from different countries.
For this reason, and taking into consideration that the Bering
and Chukchi Seas wash the US and USSR coasts (countries
equally interested in the further fate of these unique regions of
the World Ocean), it was considered appropriate that the efforts
and knowledge of scientists of both countries be joined to study
the state of the ecosystems of these seas.

It is important to note that 1992 is the 20th anniversary of
the US-USSR Agreement on "Cooperation in the Field of the
Protection of the Environment" and the 1 5th anniversary of the
beginning of joint US-USSR research within the framework of
the special subproject "The Bering Sea." In 1977, 1984, and
1988, US-USSR integrated ecological expeditions aimed at
investigations of Bering Sea ecosystems were carried out
within the framework of the above agreement. These expeditions
enabled scientists of both countries to add to the volume of
knowledge of this poorly understood body of water. The
following are the major research thrusts: a more detailed study
of the oceanographic regime; accumulation of data on the
spatial (horizontal and vertical) variability of nutrient
concentrations; the study of the dynamics of arrival and
elimination of the most important pollutants; acquisition of
data on the structural and functional characteristics of planktonic
and benthic communities; a more detailed study of the
microbiological regime; and determination of the role of
microorganisms in the biogeochemical cycles of elements in
the destruction of organic pollutants.

Long-term integrated investigations in the Bering Sea
began on the first US-USSR expedition on board the R/V
Volna in 1977. The scientific results of the expedition were
presented in joint monographs published in the US (US Fish
and Wildlife Service, 1982) and USSR (Izrael & Tsyban,
1 983 ). These investigations were further developed during the
expedition canied out by Soviet scientists in 1981 on board the
R/V Akademik Shirshov. New scientific data were obtained on
the characteristics of the state of the Bering Sea ecosystem, the
composition and physiological activity of bacterial populations,
quantitative and qualitative composition of microzooplankton,
and, investigated for the first time, the biogeochemical cycle
of polyaromatic hydrocarbons (using the benzo(a)pyrene as
the model compound). Scientific results of the expedition were
published in the monograph Comprehensive Analysis of the
Bering Seci Ecosystem (Izrael & Tsyban, 1987).

The Second Joint US-USSR Bering Sea Expedition was
carried out on board the RA' Akademik Korolev in 1984.
During this expedition, a broad spectrum of questions were
studied; they are considered in joint monographs published in
the US (Roscigno, 1990) and the USSR (Izrael & Tsyban,
1990).

The Third Joint US-USSR Bering & Chukchi Seas
Expedition also took place on board the R/V Akademik Korolev
in the summer of 1988. During the expedition, the Bering Sea
(already investigated in 1981 and 1984), the Gulf of Anadyr,
the Chirikov basin, and the southern Chukchi Sea were
investigated (see Protocol of the Third Joint US-USSR Bering
& Chukchi Seas Expedition . . . ). In the course of the third
expedition, comprehensive studies of the state of Bering Sea
ecosystems were continued and investigations in the Chukchi
Sea were initiated. The present monograph contains scientific
results obtained during the expedition and results which were
obtained through //( situ laboratory experiments on samples
collected during this expedition.

The scope of problems elucidated in the monograph is
wide: it includes the study of oceanographic aspects,
hydrochemical conditions, variability of the spatial structure of
planktonic biocenoses, microbial oxidation of organic
pollutants, effect of toxic substances on the state of planktonic
communities in conditions near to in situ, assessment of the
elements of the ecosystem biotic balance, determination of the
ratio between the processes of new formation and destruction
of organic matter in the Bering Sea ecosystem, and determination
of the elements of the biogeochemical cycles of organic
pollutants in the Bering and Chukchi Seas.

The investigations made it possible to conclude that, at
present, the ecosystems of the Bering and Chukchi Seas are in
a relatively favorable state. However, to maintain this state
under conditions of ever-growing anthropogenic impacts from

111

both countries, a careful scientific approach is necessary to
prevent exploitation of the natural resources of this unique area
of the World Ocean. Scientific information obtained in the
course of these joint ecological expeditions contributes to the
development of such an approach.

In conclusion, it should be noted that fundamental studies
of northern polar marine ecosystems now have become even
more important considering the newly emerging problems of
global climate change. Ecological consequences of the predicted

climate change on marine ecosystems may first manifest
themselves in arctic areas of the ocean and affect fundamental
natural phenomena, such as biogeochemical carbon cycling,
sea level rise, production/destruction processes of organic
matter, and others. Thus, these joint investigations of the role
of arctic ecosystems in global climate formation processes,
which were started by Soviet and American scientists, need
continued extension and development.

References

Izrael, Yu. A. & Tsyban, A. V. (eds. ) ( 1983). Research on the

Bering Sea Ecosystem. Gidrometeoizdat Publishers.

Leningrad, 157 pp. (in Russian)
Izrael. Yu. A. & Tsyban, A. V. (eds. ) ( 1987). Comprehensive

Analysis of the Bering Sea Ecosystem. Gidrometeoizdat

Publishers. Leningrad. 264 pp. (in Russian)
Izrael, Yu. A. & Tsyban, A. V. (eds. ) ( 1990). Research on the

Bering Sea Ecosystem. In Results of the Soviet-American

E.xpeilition. The 37th Cruise of the Research Vessel Akademik
Korolev. June-September, 1984. Gidrometeoizdat
Publishers, Leningrad, 344 pp. (in Russian)

Roscigno, P. F. (ed. ) ( 1990). Residts of the Second Jomi US-
USSR Bering Sea E.xpedition. Summer 1984. US Fish and
Wildlife Service Biological Report 90( 13). 347 pp.

US Fish and Wildlife Service (1982). Joint USA-USSR
Ecosystem Investigations of the Bering Sea. July-August
1977. Library of Congress #82-0845 13. Washington. D.C.,
271 pp.

IV

Protocol of the Third Joint US-USSR

Bering & Chukchi Seas Expedition

on the RA^ Akademik Korolev

In accordance with the memorandum of the 1 1th meeting
of the US-USSR Joint Committee on the Environment
Protection (Moscow, USSR, February 1988), the
recommendation of the "Soviet-American Conference on the
Ecology of the Bering Sea" ( Batumi, USSR, March 1988), and
the plan of the joint bilateral activity of 02.07-2101
"Comprehensive Analysis ofMarine Ecosystems and Ecological
Problems of the World Ocean", the Third Joint US-USSR
Bering & Chukchi Seas Expedition was held on 26 July-
2 September 1 988 on board the Soviet research wtsi^eX Akademik
Korolev. The delegation was headed by Prof. Alia V. Tsyban
and Mr. Harold J. O'Connor (Project Leaders 02.07-2101 ).

The Soviet delegates were represented by participants in
the cruise from the USSR State Committee for
Hydrometeorology and Control of Natural Environment; the
Academy of Sciences from the USSR; and the Academies of
Sciences from Ukraine, Belyorussia, and Estonia. A list of
participants is given as Appendix A.

The American delegates were represented by participants
from the US Department of the Interior, Fish and Wildlife
Service; University of Texas; Texas A&M University;
University of Alaska; University of New England (Maine);
University of Washington; University of South Carolina;
Skidaway Institute of Oceanography; and Lamont-Doherty
Geological Observatory. A list of participants is given as
Appendix A.

The principal objective of the Third Joint US-USSR
Expedition was to characterize the contemporary condition of
the fundamental oceanographic, hydrochemical (including
pollution levels), and the hydrobiological parameters of marine
ecosystems and to assess their assimilative capacity for marine
pollution. This research was undertaken both on the polygons
of long term investigations and in new areas of the Bering Sea
(Gulf of Anadyr, Chirikov basin, and the Bering Strait ) and the
southern portion of the Chukchi Sea.

The main scientific tasks were

1. Biological, chemical . and physical fundamental data were
collected to provide a comprehensive ecological and
oceanographic profile of the Bering and Chukchi Seas.

2. Studies of the physiological and ecological characteristics
of plankton organisms were conducted.

3. The ecological health of the Bering Sea was assessed.

In accordance with protocols of the Joint American-
Soviet meeting (Batumi, Mar. 1988), the research vessel
Akademik Korolev. with the Soviet participants on board,
arrived in Dutch Harbor. USA, on 24 July 1988. During a
three-day port of call, the American specialists and their
scientific equipment were taken on board. The Third US-
USSR Expedition started on 27 July with the transit to the East
Polygon.

Complex ecological investigations in the Bering and
Chukchi Seas were accomplished in four stages. In the first
stage, work was started in the East Polygon (Stations 1-6) and
was completed in the Gulf of Anadyr ( Stations 6-43). The next
stage studied the areas of the southern Chukchi Sea (Stations
6—13) andincludedatransect of the Bering Strait. After a port
of call to Nome, Alaska (USA, 17-18 August), investigations
were continued in the Chirikov basin from the Bering Strait to
St. Lawrence Island. The final stage of the expedition consisted
of six stations (109-1 13)including the South Polygon. Complex
ecological studies (see Frontispiece) were conducted in 113
stations of the transects and of three polygons (East, North, and
South ). A map and station locations are found in the Frontispiece.
The joint work and debarkation was completed on 2 September
1988 in Dutch Harbor. The entire duration of the Third US-
USSR Expedition to the Bering and Chukchi Seas was 42 days.

In accordance with specialties of the expedition's
participants, working groups were organized (Appendix A).
At these meetings, work schedules, joint studies, and model
experiments were planned. During the expedition, several
meetings of the Scientific Council Board were held.

Examined were:
/. ecological problems of monitoring studies of highly
productive regions of the World Ocean;

2. the contemporary state of the knowledge of the Bering and
Chukchi Seas' ecosystem; and

3. preliminary scientific results of the Third US-USSR Bering
& Chukchi Seas Expedition.

In the course of the meeting, scientific reports to the
American and Soviet specialists were presented.

During the Third Joint US-USSR Bering & Chukchi Seas
Expedition, the following preliminary results were obtained:
the research was undertaken in five different ecosystems in the
Bering and Chukchi Seas. Two ecosystems were situated in the
East and South Polygons and they have the characteristics of
deep-water ecosystems. Three ecosystems were in shallow-
water areas of the Bering Sea (Gulf of Anadyr, Bering Strait,
Chirikov basin) and the Chukchi Sea (southern portion) and
were typical shelf ecosystems.

The structure of the water mass on the East Polygon
consisted of the shelf s boundary and was influenced greatly by
the Bering Current tlowing along the continental shelf-slope.
Analysis of the distribution of temperature revealed the existence
of two water layers. The minimum temperature was found at
the depth of 150-250 m (boundary of the shelf- water of the
Bering Current), and the maximum temperature was found at
the depth of 400-500 m ( intermediate water of the Bering Sea).
We must note that both the minimum ( 1 .6°C ) and the maximum
(8.9°C) temperatures were approximately 0.3-0.5°C higher
than the average long term data for the region.

The distribution of nutrients ot the East Polygon was
typical of such a shelf-slope region. In the surface layers the
nutrients concentration was found to be low and their
concentration increased slowly below 100 m.

The microbiological community was characterized by
variability ofwater mass in the East Polygon. The development
of the heterotrophic, saprophytic microflora proved to be lower
in total numbers in the deepwater stations 1 and 3 at the depth
of 500 m (the indicator fonns were completely absent). There
were upper and lower layers where the number of saprophytic
bacteria varied from cells/ml to 10' cells/ml.

Preliminary data indicated that microbial community
structure on the East Polygon did not change in comparison
with the 1984 results. The highest quantity and biomass of
neuston organisms was found on the East Polygon (in
comparison with the other investigated areas). The average
biomass was found to be four times higher than those results
reported in 1984.

Very interesting experiments were undertaken for the first
time in the northern regions of the Bering (Gulf of Anadyr) and
Chukchi Seas. The ecosystems of the northern areas of the sea
are some of the most productive in the World Ocean. Results
of primary production showed values more than 12 g C/m-d '.
High concentrations of nutrients in the water masses are
responsible for the high primary production. Significantly, the
water mass is enriched with nutrients transported from the Gulf
of Anadyr through the Chirikov basin and the Bering Strait to
the southern area of the Chukchi Sea. This constant tlow fuels
the increase of phytoplankton numbers and production occurs
at the boundaries of these water masses.

During the expedition, three local areas that had high
phytoplankton production were discovered along the axis of
the current. At these areas, the increase in biogenic sedimentation
was also observed with the particulate matter settling from the
euphotic zone containing more than 1.5% biogenic carbon.

The lowest temperature (-1.6°C) was discovered in the
Gulfof Anadyr. Such low temperatures have not been observed
here during the last 20 years. In spite of the low temperatures,
significant phytoplankton biomass was found in the Gulf of
Anadyr. The highest values of chlorophyll « in the gulf reached
55 mg/nr\ The only values that were higher were those found
in the Chukchi Sea.

In the coastal area of the Gulf of Anadyr, a high quantity
and biomass of microzooplankton and benthos were observed.
Biomass of benthic organisms reached !.()()() g/nr in several
investigated stations. The ecosystems in the Chirikov basin
depend greatly on the Anadyr Current, which carries into the
gulf different amounts of nutrients that are necessary for thte
growth of phytoplankton. In turn, large amounts of nutrients
were carried from the Chirikov basin through the Bering Strait
to the Chukchi Sea.

The southern area of the Chukchi Sea, bemg intluenced by
Bering Sea waters, was rich in nutrients and unstudied until
this time. Also, new practical knowledge of oceanographic
features such as mass circulation, temperature, salinity
distribution, and the general structural and functional
characteristics of the ecitsystems was dclcrniined.

During the expedition, we noticed that the function of the
ecosystems of the Chukchi Sea was determined by at least two
currents. High-salinity, nutrient-enriched, water masses are
transported from south to north. They are carried by a flow that
exits from the Gulf of Anadyr, crosses the Chirikov basin,
flows through the Bering Strait, and ends in the Chukchi Sea.
There is one more current, formed from the cold and relatively
high salinity coastal Siberian waters, that is also enriched with
nutrients. This current flows from northwest to southeast.
These two flows of nutrients, discovered in the Chukchi Sea,
determine the high biological productivity of this ecosystem.
The merging of these two currents formed a wide area in the
southeastern part of the sea. This area is characterized by the
following: 1. concentrations of chlorophyll a reaches 77 mg/m'
(a phytoplankton bloom was noticed at Station 45); 2. the
average number of neuston organisms was
4,000 specimens/m-; 3. the number of infusoria of the Chukchi
Sea was much larger than in the Bering Sea; 4. a maximum
number of mesozooplankton was in the larvae of benthic
organisms, which was dominated in the metazooplankton; and
5. high average biomass of benthic organisms — about
900 g/m- — was found, reaching 1,500 g/m- and even
2.000 g/m- at some individual stations.

New species, which were not known before in the Chukchi
Sea (testaceous moUusks, some echinodermata, and others)
were found during the expedition. Many birds and mammals
were also observed.

From various investigations, the data indicate that the
biological productivity is high in the Bering Sea and higher still
in the Chukchi Sea. In spite of the fact that the investigated
regions are far away from industrial areas, an array of
anthropogenic organic contaminants ( polychlorinated biphenyls
(PCB"s). hexachlorocyclohexane, chlordane. and DDT) were
found in the surt'ace waters of these seas. The average measured
concentration of hexachlorocyclohexane in the surface waters
of both seas was more than 10 times the values of other
anthropogenic contaminants (2.5 ng/1 isomer and 1.2 ng/1
isomer). Such levels of toxicants in the Bering and Chukchi
Seas are potentially hazardous for the vulnerable arctic
ecosystems. Analysis of the atmospheric samples produced
similar results: concentrations of benzene hexachloride
averaged 0.25 ng/m' and that for the isomer. 0. 12 ng/m'.

The process of the degradation of the PCB's by natural
microbial populations of the Bering and Chukchi Seas was
studied. The preliminary results indicated that during the
exposure (21 days) at temperate 6-10°C, the microorganisms
oxidized up to 18% dichlorobiphenyl, up to 6%
trichlorobiphenyl, 1% tetrachlorobiphenyl, and <1%
penta/n-hexachlorobiphenyl (as compared to total amounts of
these compounds compared in industrial mixtures of PCB ). It
is important to note that the toxic compound
2, 3, 6, 2', 3', 6'-hexachlorobiphenyl was degraded by 50-70%
by various bacterial populations for 2 1 days. Altogether these
facts indicated thai a considerable part of chlorinated
hydrocarbons may be retained and may accumulate in this
arctic environment. This cau,ses serious concern as these
pol I Litanls ha\ e known negative effects on biological processes.

VI

Experiments were conducted to study the photochemical
decomposition of polyaromatic hydrocarbons (PAH's). For
example, only a 3-hour exposure to sunlight of benzo(a)pyrene
already showed a significant quantitative breakdown of this
carcinogenic chemical.

From the results of these studies, and from previous
estimates of the accumulation of these compounds in the
marine ecosystem, one needs to determine in detail the intensity
of microbial destruction of pollutants; establish a "critical"
concentration of individual pollutants that affect the ecological
system; and study factors that affect important processes of the
ecosystem. For example, the new formation of organic pollutants
from the metabolic activity of microorganisms should be
examined.

During the period of the expedition, joint American-
Soviet experiments were conducted. Preliminary results of
these experiments allowed us to assess the range of "critical"
concentrations of pollutants for microzooplankton in the Bering
and Chukchi Seas. The range varied as follows:
Benzo(a)pyrene 0.1-1 |ig/l

Copper 2-8 ng/1

PCB 10-40 ng/1

Cadmium 20-40 [ig/l

It is important to note that the established critical
concentrations were l.OOOx higher that those found in natural
seawater.

With the results of the joint, multidisciplinary experiments,
we have demonstrated that separate combinations of low
concentration of nitrogen and phosphorus, which were typical
for natural for natural water masses, not only do not stimulate
but inhibit the growth of plankton communities.

Most of the collected biological and chemical samples
during the expedition need a prolonged series of studies in a
laboratory with special equipment and instrumentation for
final results to be obtained. However, even incomplete
preliminary results obtained on board the ship, allowed us to
assess the ecological structure and function in the Bering and
Chukchi Seas as being intact, with both of these areas
remaining as highly productive as any region in the World
Ocean.

Altogether, the distribution of chlorinated hydrocarbons
(PCB, biphenyls, HCH) observed in the surface waters of these
seas were probably transported by global atmospheric processes.

At the end of the Joint Expedition on board the Akademik
Korolev. there was an exchange of preliminary data. The future

exchange of the joint analysis of data between American and
Soviet scientists will occur in a series of three exchanges:
/. 1 March 1988; 2. 1 June 1988; and 3. 1 October 1989.

The two sides had agreed that the obtained data and results
of the analyses belong to both sides. Any publications based on
these materials should indicate that the results were generated
during the Third Joint US-USSR Bering & Chukchi Seas
Expedition. Both sides considered it useful to prepare and
publish the joint manuscript containing the final analysis of the
American-Soviet research of the 1 988 Expedition to the Bering
and Chukchi Seas.

American and Soviet participants expressed their interest
in further development of joint research and consider it
worthwhile to carry out further joint expeditions aimed to the
fundamental studies of the ecological situation and the
oceanographic regimes of the Bering and Chukchi Seas.
Separate proposals for future joint research should be considered
by the appropriate institutions in the respective countries. With
this aim, the participants of the Third Joint US-USSR Bering
& Chukchi Seas Expedition recommended that planning begin
for the Fourth US-USSR Expedition to the Bering & Chukchi
Seas, and the central Pacific Ocean in 1990. It is recommended
also by the American-Soviet participants that a joint five-year
program of ecological and oceanographic investigations for
the Bering and Chukchi Seas will be jointly developed and
published during 1989.

Both sides note with satisfaction the friendly and
constructive atmosphere of the expedition's work and the
effectiveness of joint observations allowing for a variety of
oceanographic and ecological studies.

The American delegation would like to express their
sincerest thanks and gratitude to the Captain and crew of the
Akademik Korolev for their hospitality and cooperativeness.

The American delegation thanks the Soviet delegation for
providing an atmosphere of mutual respect, productive
collaboration, and fruitful exchange of data. The associations
established on this cruise will result in the exchange of data and
information for many years to come.

The Soviet participants of the expedition express their
sincere gratitude and thanks to the American specialists for the
fruitful and productive cooperation during the joint
investigations of the Bering and Chukchi Seas.

This protocol was written in English and Russian and was
signed on board the research vessel Akademik Korolev,
2 September 1988. Both texts are equally authentic.

For American side:

The Leader of Project for the

American Side
Director,

Patuxent Wildlife Research Center
US Fish and Wildlife Service
US Department of the Interior

For Soviet side:

Head of Expedition

The Leader of the Project
for the USSR Side

Deputy Director of Laboratory for

Environmental and Climate Monitoring
Laboratory, Goskomgidromet
and USSR Academy of Sciences

Mr. H. J. O'Connor Professor A. V. Tsyban

(This text is a reproduction of the protocol written on board the RA' Akademik Korolev in 1 988. The original was signed by both project leaders.)

vii

Acknowledgments

We gratefully acknowledge and thank the many individuals without whose participation this monograph
may not have been published with the same quality, accuracy, and clarity.

We thank the US Fish and Wildlife Service and the USSR State Committee for Hydrometeorology

for their continued support.

Steven Kohl and Stephanie Miller. theCoordinatorand Associate Coordinator of US-USSR Programs,
US Fish and Wildlife Service (Office of International Affairs), have provided invaluable assistance
throughout every phase of this project. Their enthusiasm and energy given to this project, and the people
involved with this project, are outstanding.

Without each participant of the expedition and each author of research results, there would be no need
for a monograph. There are far too many to name here; however, their names are listed with each subchapter
and in Appendix A in this volume. It is their interest and excitement for the research presented here, and
their spirit of cooperation so necessary for an international project, that provide the essence of the scientific
accomplishments.

We are indebted to each of the US and USSR chapter editors for their help and their patience with the
seemingly endless questions and tasks assigned to them and, last but certainly not least, for their sense of
humor, which is often the only saving grace in putting together a volume of this magnitude. Their names
are listed alphabetically below:

Sergei M. Chernyak

Lawrence K. Coachman

Gennady V. Panov
Clifford P. Rice

Boris V. Glebov

Viktor V. Shigaev

Jacqueline M. Grebmeier

Gregory J. Smith

Roger B. Hanson

Alia V. Tsvban

Cameron B. Kepler

Yuriy L. Volodkovich

Mikhael N. Korsak

Terry E. Whitledge

Alexander E. Lukin

Stephen I. Zeeman

C. Peter McRoy

The "Production Team" at Patuxent Wildlife Research Center — Kinard Boone. Patricia A. Holt,
Susan A. Liga, Robert E. Munro, Patricia A. Nagel, and John C. Sauer — deserves recognition
for their dedication to meeting the challenge of producing a quality volume in time for it to be
distributed to participants on the 1992 expedition.

Harold J. O'Connor

Alia V. Tsyban

VIU

Table of Contents

Page

Foreword iii

Protocol of the Third Joint US-USSR Bering & Chukchi Seas Expedition on the RA' Akademik Korolev v

Acivnowledgements viii

Frontispiece xii

Chapter 1 : GENERAL ECOLOGY 1

1 . 1 Program on Long-Term Ecological Investigations of the Bering Sea and Other Pacific

Ocean Ecosystems (BERPAC Program) 3

1.2 Polar Marine Ecosystems and Climate 7

Chapter 1 References 13

Chapter!: OCEANOGRAPHY 15

2.1 Northern Bering-Chukchi Sea Ecosystem: The Physical Basis 17

2.2 Water Mass Modification from the Bering into the Chukchi Sea 27

Chapter 2 References 35

Chapter 3: HYDROCHEMISTRY 37

3.1 Biogenic Nutrient Content 39

Chapter 3 References 49

Chapter 4: MICROORGANISMS AND MICROBIOLOGICAL PROCESSES 51

4. 1 General Characteristics of the Bacterial Populations 53

4.1.1 Total Number. Biomass and Activity of Bacterioplankton 55

4. 1 .2 Thymidine Incorporation, Frequency of Dividing Cells and Growth Rates of
Bacterioplankton 60

4. 1 .3 Bacterial Production and Destruction of Organic Matter 75

4.2 Heterotrophic Saprophytic Microflora 79

4.2.1 Distribution of Indicator Groups of Marine Heterotrophic Microorganisms 81

4.2.2 Taxonomic Composition of Heterotrophic Bacteria 87

4.3 Microbiological Transformation of Organic Matter 91

4.3.1 Transformation of Benzo(a)pyrene 93

4.3.2 Transformation of Polychlorinated Biphenyls by Marine Bacterioplankton 95

4.4 Biologic Characteristics of Marine Microorganisms 101

4.4. 1 Biological Features and Genotoxic Properties of Microorganisms 103

Chapter 4 References 1 1 1

Chapters: PLANKTON 117

5.1 Phytoplankton 119

5.1.1 Certain Characteristics of Phytoplankton 121

5.1.2 Phytoplankton Biomass Distribution in the Northern Bering Sea and Southern

Chukchi Sea 123

5. 1 .3 Distributions of Algal Pigments in Near-surface Waters 127

5.1.4 Complex Hydrooptic Researches 135

5.2 Zooplankton 153

5.2.1 Ciliate Protozoa in Plankton 155

5.2.2 Characteristics of Zooplankton Communities 161

5.2.3 Some Characteristic Features of Epipelagic Necrozooplankton Distribution 172

5.2.4 Carbon Isotope Ratios in Zooplankton as Markers of Aging and Habitat Usage for

the Bowhead Whale (Balaena Mysticetus) 177

5.2.5 Zooneuston 184

5.3 Icthyoplankton 193

5.3.1 Larval Fish Distribution 195

5.4 Modeling 199

5.4.1 Complex Ecological Evaluation of Planktonic Communities of the Pelagic Zone 201

Chapter 5 References 209

Chapter 6: PRIMARY PRODUCTION 213

6.1 Primary Production of Organic Matter 215

6.2 The Importance of Primary Production and CO, 2 1 8

6.3 Intensity of Biosedimentation Processes 224

6.4 Humic Acids 231

Chapter 6 References 237

Chapter 7: BENTHIC PROCESSES & BOTTOM FAUNA 241

7.1 Benthic Processes on the Shallow Continental Shelf 243

7.2 Characteristics of Benthic Biocenoses of the Chukchi and Bering Seas 251

Chapter 7 References 259

Chapter 8: BIOGEOCHEMIC AL CYCLES 263

8.1 Fate of Chlorinated Hydrocarbons 265

8.1.1 Long Range Transport of Atmospheric Organochlorine Pollutants and Air-Sea
Exchange of Hexachlorocyclohexane 267

8. 1 .2 Migratory and Bioaccumulative Peculiarities in the Biogeochemical Cycling of
Chlorinated Hydrocarbons 279

8.1.3 Organochlorine Contamination of Sediments, Fish, and Invertebrates 285

8.2 Fate of Petroleum Hydrocarbons 291

8.2.1 Distribution and Sources of Sedimentary Hydrocarbons 293

8.2.2 Distribution of PAH'S 301

8.2.3 Distribution of Benzo(a)pyrene and other Polycyclic Aromatic Hydrocarbons 308

8.3 Fate of Heavy Metals 315

8.3.1 Heavy Metals in Water and Sediment 317

8.3.2 Baseline Levels of Certain Trace Metals in Sediment and Biota 319

8.4 Distribution of Radionuclides 325

8.4.1 Investigation of Cesium-137 Distribution in Seawater 327

8.5 Distribution of Organic Matter 331

8.5.1 Characterization of Sediment Organic Matter 333

8.6 Abiotic Processes of Decomposition of Some Organic Contaminants 339

8.6.1 Solar Oxidation of Benzo(a)pyrene 341

8.6.2 Influence of Ultraviolet Radiation on the Fate of PCBs 343

Chapter 8 References 347

Chapter 9: ECOTOXICOLOGY 353

9.1 Effects of Pollutants on Plankton Communities 355

9. 1 . 1 Investigation of Negative Effects and Critical Concentrations of Some Toxic
Substances on the Plankton Community 357

9. 1 .2 Effects of Hexachlorocyclohexane on Nitrogen Cycling in Natural Plankton
Communities 364

9.2 Toxicity of Sediments to Test Organisms 371

9.2.1 Acute Toxicity Testing of Sediments 369

Chapter 9 References 377

Chapter 10: MARINE BIRDS 379

10.1 Water Masses and Seabird Distributions in the Southern Chukchi Sea 381

10.2 Associations Between Seabirds and Water Masses in the Northern Bering Sea 388

Chapter 10 References 397

Summary 399

General Conclusions 405

Appendix A 407

-68N

-66N

-64N

■-62N

180W

Frontispiece. Sampling stations of the Third Joint US-USSR Bering-Chukchi Seas Expedition,
Summer 1988. aboard the research vessel Akademic Korolev.

Coordinates of the sampling stations on the Expedition.

Station

Latitude

Longitude

1

57°53'67"N

174°49'85"W

2

57°49'97"N

175°5r83"W

3

57°94'50"N

175°07'50"W

4

58°50'83"N

174°50'33"W

5

58°50'00"N

1 75°50'{M)"W

6

59°50'00"N

179°30'00"W

7

60°47'43"N

177°87'03"W

8

60°93'53"N

I76°94'62"W

9

61°33'52"N

l76^1(r27"W

Station

Latitude

Longitude

10

61°25'00"N

177^^76'00"W

11

61°58'33"N

178°65'00"W

12

61°88'17"N

179°42'00"W

13

62°18'33"N

179°85'00"E

14

62°83'68"N

179°5r08"W

15

62°55'00"N

178°50'00"W

16

62°34'I7"N

177°33'17"W

17

62°16'67"N

I76°33'33"W

18

62°(K)'42"N

175°00'00"W

Xll

Coordinates of the sampling stations on the expedition - vouiinucd

Station

Latitude

Longitude

19

62°4r67"N

174°00'00"W

20

62°3470"N

175°03'50"W

21

62°73'33"N

176°18'33"W

22

63°00'67"N

177°00'17"W

23

63°36'67"N

177°83'33"W

24

63°68'00"N

178°4735"W

25

64°00'00"N

179°33'33"W

26

65°00'00"N

178°66'67"W

27

64°74'00"N

177°77'50"W

28

64°25'00"N

177°50'00"W

29

63°83'00"N

176°97'33"W

30

64°17'33"N

175°96'83"W

31

64°33'33"N

175°00'00"W

32

64°00'00"N

175°00'00"W

33

63°50'00"N

175°00'00"W

34

63°16'67"N

174°00'00"W

35

63°00'00"N

173°00'00"W

36

63°42'83"N

172°16'67"W

37

63°66'17"N

172°82'67"W

38

63°91'67"N

173°58'33"W

39

64"=22'83"N

172°70'00"W

40

64°13'33"N

172°50'00"W

41

64°02'83"N

172°21'17"W

42

63°92'00"N

172°07'33"W

43

63°49'60"N

171°55'00"W

44

67°36'67"N

173°33'33"W

45

67°73'33"N

172°83'33"W

46

67°9r67"N

171°75'00"W

47

68°10'00"N

170°88'33"W

48

68°26'67"N

170°00'00"W

49

68°46'67"N

169°13'33"W

50

68°66'17"N

168°33'33"W

51

68°16'17"N

168°73'50"W

52

68°08'33"N

167°00'00"W

53

67°42'00"N

165°43'10"W

54

67°76'33"N

167°3r50"W

55

67°73'50"N

168°44'00"W

56

67°73'67"N

169°92'67"W

57

67°7r00"N

171°34'50"W

58

67^\50'00"N

172°20'00"W

59

67°15'33"N

172°00'00"W

60

67°26'17"N

170°82'67"W

61

67°33'33"N

169°75'00"W

62

67°33'33"N

168°7r67"W

63

67°34'17"N

167°73'33"W

64

67°29'67"N

166°7r00"W

65

67°33'33"N

165°00'00"W

66

66°92'50"N

165°9r83"W

Station

Latitude

Longitude

67

66°93'33"N

166°83'33"W

68

66°9r67"N

167°83'33"W

69

66°90'75"N

168°9r08"W

70

66°9r67"N

169°9r67"W

71

66°9r67"N

171°00'00"W

72

66°55'00"N

170°16'67"W

73

66°55'00"N

169°3r67"W

74

66°55'00"N

168°60'00"W

75

66°55'00"N

167°23'33"W

76

65°93'33"N

169°58'33"W

77

65°9r67"N

169°36'67"W

78

65°85'00"N

169°2r67"W

79

65°70'33"N

168°67'50"W

80

65°66'67"N

168°50'00"W

81

65°63'33"N

168°35'00"W

82

65°63'83"N

168°33'33"W

83

65°67'13"N

168°49'83"W

84

65°7ri7"N

168°68'33"W

85

65°83'33"N

169°16'67"W

86

65°93'83"N

169°38'17"W

87

65°40'83"N

170°35'83"W

88

65°36'00"N

169°98'83"W

89

65°23'33"N

169°33'33"W

90

65°17'50"N

168°65'83"W

91

65°22'67"N

168°01'33"W

92

64°67'33"N

I67°69'33"W

93

64°75'00"N

I68°43'33"W

94

64°85'00"N

I69°20'00"W

95

64°97'00"N

169°97'67"W

96

65°08'33"N

170°7333"W

97

64^^74'83"N

171°49'50"W

98

64°7r83"N

170°87'33"W

99

64°53'33"N

170°0r67"W

100

64°38'33"N

169°15'00"W

101

64°23'33"N

168°3170"W

102

64°08'67"N

167°38'83"W

103

63°66'67"N

168°33'33"W

104

63°84'50"N

169°20'50"W

105

64°03'33"N

170°08'50"W

106

64°22'33"N

170°98'17"W

107

64°38'33"N

171°65'00"W

108

54°49'33"N

I76°49'17"E

109

54°53'83"N

175°47'50"E

110

53°95'00"N

176°01'17"E

111

53°52'67"N

175°53'17"E

112

53°I8'67"N

177°30'17"W

113

53°I3'67"N

177°19'50"W

Chapter 1:

GENERAL ECOLOGY

Editors:

ALLA V. TSYBAN &
TERRY E. WHITLEDGE

1.1 Program on Long-term Ecological

Investigations of the Bering Sea and Other
Pacific Ocean Ecosystems (BERPAC
Program)

HAROLD J. O'CONNOR' . YURI Y A. IZRAEL^ , ALLA V. TSYBAN*. TERRY E. WHITLEDGE", C. PETER McROY , and
LAWRENCE K. COACHMAN'

'US Fish and Wildlife Service, Patu.xeiU Wildlife Research Center. Laurel. Maiylaml. USA
' USSR State Committee for Hydrometeorology and Natural Environmental Control. Moscow, USSR
^Institute of Global Climate and Ecoloi^y. State Committee for Hydrometeorology and Academy of
Sciences. Moscow. USSR

"Marine Science Institute. University of Texas. Port Aransas. Texas, USA
Institute of Marine Science. University of Alaska. Fairbanks. Alaska. USA
'School of Oceanography. University of Washington, Seattle, Washington, USA

Introduction

Deterioration of ecosystems on a large scale threatens
many functional equilibria in the biosphere. This problem is
particularly urgent for the World Ocean, which is the sink for
many different pollutants that can produce significant ecological
impacts.

The ocean is able to assimilate a certain amount of
anthropogenic compounds due to "self-purification" without
visible deterioration of the ecosystem. However, continuous
increase in the tlux of pollutants to the ocean creates the need
for study of the resistance of marine ecosystems to anthropogenic
impacts. Investigations of ecological consequences and
elucidation of causal relationships between the impact levels
and adverse biological effects are only poorly understood for
the marine environment. The study of these interactions and
responses is interdisciplinary in character and covers different
fields of biology, ecology, chemistry, and physics of the sea.

The dynamics of marine ecosystems, including biological
and physical processes and biogeochcmical cycles, are closely
related to changes in the climate of the Earth. The predicted
global warming may have a pronounced effect on certain vital
processes in the World Ocean, especially the resistance of its
ecosystems to anthropogenic contamination. This is because
the living ocean determines, to a great degree, the normal
functions of the Earth's climatic system.

Long-terni observations of physical, geochemical and
hydrobiological processes are necessary for the assessment of
ecological consequences of contamination in the ocean
environment and isolation of local anthropogenic effects
compared to the effect of climatic variability.

The Bering Sea is located between the coasts of the Soviet
Far East (USSR) and Alaska (USA ) and. naturally, an interest
in the study of its ecosystems has been shown by Soviet and
American scientists (Izrael & Tsyban, 1983a, 1977, 1990;
Roscigno, 1990).

In spite of comprehensive studies carried out in the Bering
Sea in the last few years (Izrael et al. , 1 988b; Izrael & Tsyban,
1989, 1990; Coachman, 1990; Roscigno. 1990), a number of
the oceanographic, hydrochemical. and biological parameters
determining its ecosystem functions are as yet poorly known,
when compared with, for instance, the Baltic, Mediterranean,
and Black Seas. For example, the joint bilateral program of
Bering/Chukchi investigations have been carried out for more
than 13 years with the production of three monographs of
cruise results. However, the as yet inadequate data on the
characteristics and processes occurring in the ecosystems of
the Bering Sea and North Pacific waters have led to the
organization and implementation of an international program:
Long-term Ecological Research of the Marine Ecosystems in
the Arctic and Pacific Oceans (BERPAC Program).

Goals, Objectives, and Scientific Basis of the BERPAC
Program

Goals

The goal of the BERPAC Program is to examine the status
of marine ecosystems of the Pacific Ocean, Bering Sea, and
Chukchi Sea and to assess their role in determining global
climate. BERPAC will study the dynamics ofthe.se ecosystems
related to conditions ofglobal climate change and anthropogenic
contamination.

Objectives and Scientific Basis of the BERPAC Program

Objectives of the BERPAC Program consist of the study
of the biogeochcmical cycles of contaminants, related
oceanographic processes, and food-web interactions in the
North Pacific waters that flow through the Bering/Chukchi
Seas, including study of the behavior of organic pollutants at
the water/sediment interface since sediments are sources of the
secondary pollution of ecosystems. Important topics of study
are the control and the accumulation of pollutants in bottom

deposits and the study of their migration within the sediments
and their exchange with overlying waters .

1. Assessment of Ecological Consequences of Contamination
Progressively severe changes in chemical contamination

of the ocean biosphere are on the increase. Anthropogenic
impacts influence not only the biotic component of the marine
environment but different abiotic components as well. Such
impacts lead to even more significant changes in the World
Ocean and in the biosphere as a whole.

Specific features of the Bering Sea and other ecosystems
with "background" levels of contamination are such that they
are especially vulnerable because of the continual input of
small doses of pollution. This leads to a gradual accumulation
of pollutants and may ultimately cause the degradation of the
ecosystems. Therefore, ecological investigations and
monitoring of the background regions of the ocean, especially
in such highly bioproductive zones as the Bering Sea. are of
great importance. In order to assess the ecological consequences
of the pollution and isolate anthropogenic effects from the
background of natural variability, it is necessary to make long-
term observations of fundamental physical, chemical, and
biological processes in selected areas of the above regions.
These regions differ in their geographical location as well as in
the subsystems of their ecosystems and are subjected to different
anthropogenic impacts.

2. Study of the Processes Determining the Assimilative
Capacity for Contaminants in Marine Ecosystems

In the marine environment various physical, chemical, and
biological processes occur through which contaminants can be
eliminated from the ecosystem without serious disturbances of
the biogeochemical cycles of the elements or changes in the
biota. Diverse oceanological investigations carried out in the
last few years have shown that the biotic component is important
in the fluxes of pollutants.

The ability of an ecosystem to protect itself against a
foreign interference at the expense of many biological,
physical, and chemical processes is its natural
"immunity," and the measure of this immunity is its assimilative
capacity.

According to the contemporary interpretation (Izrael &
Tsyban, 1983b, 1989; Izrael et ai. I988b,c), the assimilative
capacity of a marine ecosystem is an integral function of its
existing environmental status that reflects the ability of physical,
chemical, and biological processes forelimination of pollutants
and their impacts on the biota.

When using the concept of assimilative capacity in practice,
it is necessary to bear in mind that a marine ecosystem occupies
a finite volume that may be isolated on the basis of the spatial
distribution of organisms of various trophic levels, groups of
ecologically similar species, and production/destruction
processes, as well as physical and chemical characteristics.
Hence, the assimilative capacity of each specific ecosystem
also has a value that objectively characterizes existing properties
of the marine environment. This value could be determined in
practice on the basis of integrated investigations and monitoring
of the marine environment carried out in accordance with
existing methodological recommendations (Izrael & Tsyban,
1983b, 1985, 1987, 1989; Izrael et ai, 1988b).

The use of this concept in the BERPAC studies will
include investigations of the following basic problems:
/. quantitative assessment of the balance of chemical elements
in the ecosystem and possible changes in residence times due
to disturbances; 2. assessment of adverse biological effects at
the level of population and communities; and .?. determination
of the critical concentrations at which contaminants adversely
impact the marine organisms and communities.

Thus, a conceptual model of the assimilative capacity,
based on a better understanding of the laws of marine ecosystem
functions, can serve as a theoretical basis for the development
of forecasts of both the immediate and long-range consequences
of anthropogenic and climatic impacts on the ocean ecosystems.
3. Study of the Elements of the Biogeochemical Carbon
Cycle and its Role in Global Climatic Processes

Global warming predicted in connection with the
developing greenhouse effect depends directly upon the
biogeochemical cycle of carbon — the most important process
forming the Earth's climate. The basic elements of this cycle
are carbon dioxide and other "greenhouse gases" exchanged
within the ocean-atmosphere system, the function of the
carbonate system, and the turnover of organic forms of carbon
in the ocean.

The most intensive uptake of atmospheric CO, occurs at
high latitudes as a result of favorable thermal and hydrological
conditions in the region (low sea surface temperature and
permanent downwelling). These peculiarities explain the
important role of the Bering Sea, a subarctic body of water
having a large area, in the global cycle of carbon dioxide.

The relationship between the rates and directions of CO,
flow within the ocean-atmosphere system directly affects the
functioning of the carbonate system. So, in the conditions
where global warming is induced by an increase in the
concentration of atmospheric CO,, a shift of the equilibrium
between carbonate forms of carbon in seawater might occur,
which will be accompanied by a decrease of pH and,
consequently, elevation of the lysocline.

Investigations of these processes, directly affecting the
sedimentation of organic carbon and the vital functions of
marine organisms, are only possible with direct determination
of all components of the carbonate system (i.e., HCO„ CO,,
H,CO„andCO,).

To fully understand all of the characteristics of the oceanic
portion of the global carbon cycle, it is necessary to study the
processes of the circulation of its organic forms in the
composition of dissolved and particulate matter and in the cells
of living organisms (Zaitsev, 1970, 1980, 1983).

The dynamic equilibrium of dissolved and particulate
organic matter, living matter, and the content of organic carbon
within water masses depends on the relations between
production/destruction processes established in the ecosystem.
In this connection, the predicted effects of global warming on
the bioproductivity of the Bering Sea ecosystem will influence
the organic carbon cycle. In order to study possible changes,
long-term observations of the concentrations of all organic
forms of carbon are necessary.

Thus, to establish the carbon balance in the Bering Sea
ecosystem, comprehensive long-tenn observations of all carbon

constituents in the aquatic interface and the study of quantitative
and qualitative composition of both the carbonate system and
organic forms of carbon are required.

4. Investigation of the Physical Mechanisms Related to
Climate Variations

Existing global physical models of the ocean-atmosphere
system do not make it possible to predict possible climate
changes on a regional scale because of the extreme complexity
of the modeled systems. Additional investigations of the
physical development of regional models, in particular of a
model for the Bering Sea, are an important need for long-term
climate forecasting at the present time.

This problem could be solved on the basis of long-term
oceanological observations, in different regions of the Bering
Sea, which are aimed at the acquisition of systematic information
on the vertical distribution of temperature, heat content of the
active layer and its variability with time, the structure and
variability of ocean circulation, heat transfer by the basic sea
currents, and heat and moisture tluxes across the sea surface.

To develop the above models it is necessary to know the
regularity of water mass formation in the deep basins of the
Bering Sea. The following issues are not yet clear: North
Pacific water must be involved in bottom water formation, but
given the topographic isolation of Bowers and the central
basins, how and where does this take place? Are sources the
same for the different basins? What are the flushing rates (e.g.,
residence times)?

There are three hypothetical mechanisms by which bottom
water might possibly be formed: /. modification of surface
(upper layer) water within the confines of the sea by cooling
and brine enhancement through ice formation, creating water
sufficiently dense to sink to the bottom; 2. subsurface mixings
of North Pacific water with appropriate Bering Sea waters as it
crosses the sills in the Aleutian-Komandorskiy island arc
passages; and 3. direct advection of deep North Pacific water
in through Kamchatka Strait and then sequentially through the
gaps into the other basins.

The BERPAC Program will investigate the mechanism of
deep water formation, renewal rates, and flushing of the basins.

Area of Investigations

While selecting the study areas and location of stations in
the Bering Sea, the diversity and contrast of ecological conditions
in different regions of the sea were taken into account.

In order to retlect a variety of ecological conditions in the
Bering Sea more completely, it seems appropriate that integrated
expeditions include work on polygons located in different
areas of the sea (with the purpose of obtaining representative
data on the structure and functions of the basic marine
ecosystems) and work across transects (with the purpose of
determining the space and time variations of the key ecological
parameters).

Investigations within the framework of BERPAC will be
conducted on four polygons where investigations were carried
out in 1981 (during the integratedecological expedition aboard
the research vessel \Rjy]Akademik Shirshov), and in 1 984 and

1 988 ( during the second and third Soviet- American ecological
expeditions aboard the RA' Akademik Korolev) (Izrael &
Tsyban, 1987, 1990; Izrael e/ a/., 1988a; Roscigno, 1990).

Deep stations will be repeated at four centered polygons in
the four deep basins. The center station of each polygon will
also be a location for a mooring containing sediment traps and
current meters, funding permitting. Four other mooring
locations will cover the entrance from the North Pacific (in the
deep channel northwest of Komandorskiy Island), the main
gaps in the ridges north of Attu, and a location on the east side
of the central basin under the Bering Slope current. The
mooring locations are also deep oceanographic stations, and 1 1
additional stations will provide continuity among the deep
waters.

In addition to polygons, observations are planned at stations
along the transects located in areas that are not yet completely
understood, such as the Gulf of Anadyr, the Chirikov basin, the
Gulf of Alaska, the northern portion of the Pacific Ocean, and
the deep-water central and southwestern areas of the sea.
Larger scale studies in the Chukchi Sea and central Pacific
ecosystems are also planned. The program for individual
expeditions will be discussed specifically during joint symposia.

Proposed Observations

Complex observations during the ecological expeditions
include meteorological (including aerological and geophysical
studies), oceanographical, and ecological observations.
Specifically, the following observations will be made:

A. Meteorological observations will include routine
observations of meteorological parameters, such as studies of
direct solar radiation intensity and ultraviolet irradiation, cloud
and cloud type studies, and collection of samples of atmospheric
precipitation for chemical analyses. Aerological and
geophysical observations will include temperature and wind
sounding with the aid of radiosondes. Air samples will be
collected for determination of sulfates and nitrogen oxides.
Visual observations of oil and oil product contamination on the
sea surface will be recorded.

B. Oceanographic observations at designated sampling depths
in the water column will include temperature, sahnity , nutrients,
oxygen content, water color and transparency, biogenic
elements, alkalinity, and petroleum hydrocarbons. Tracers for
water mass types will include stable isotope content of seawater
(oxygen, deuterium, tritium, freons, silica, and carbon 14). In
addition, current velocity and direction will be determined, and
sediment trap collections will be made.

C. Ecological observations will include studies of the
atmosphere, sea surface microlayer, water column, and bottom
deposits in the environment.

/. Atmosphere

In rainfall, pH and the content of organic contaminants will
be determined. In dust particles, the content of organic
contaminants and metals will be determined. In the air at the
sea surface, the content of "greenhouse" gases (CO,, nitrogen
oxides), oxygen, and chlorinated hydrocarbons will be
determined.

2. Sea Surface Microlaver. Water Column, and Bottom
Deposits

Water samples will be collected in the surface microlayer
and at standard hy drological depths and at selected experimental
depths (e.g.. themiocline. pycnoline. phyto- and zooplankton
maxima, and sediment-water interface) (Zaitsev, 1980).

a. In the surface microlayer. the following elements and
parameters will be determined:

- organic carbon

■ - contaminants (toxic metals, and aliphatic aromatic and
chlorinated hydrocarbons), the state of neustonic
communities; determination of the structural
characteristics of bacterioplankton; total numbers,
biomass of microorganisms, most probable numbers
(MPN) of indicator groups of bacteria (e.g., paraffin-
oxidizers, PCB-transforming and neurotrophic
saprophyte groups), and indices of phyto- and
zooneuston (numbers, biomass, species, size
composition, species mass, and indicator forms),
mutation (teratogenesis) of zooneuston organisms.
h. In the water column, the following parameters will be
determined:

- water optical indices

- contaminants (toxic metals, and aromatic, aliphatic, and
chlorinated hydrocarbons)

- the total concentrations of organic carbon and its
composition

- elements of the carbonate system (CO,, HCO„ CO,)

- characteristics of bacterioplankton (total numbers,
biomass, MPN, and distribution of indicator groups)
and their biochemical and genetic capacities

- structural characteristics of phyto-, microzoo-, and
mesozooplankton (numbers, biomass, size, and species
composition, species mass, and indicator forms)

- functional characteristics of planktonic communities
(heterotrophic CO. assimilation by bacteria, bacterial
production, phytoplankton productivity)

- biosedimentation rate of particulate matter.

c. In the biota, the following parameters will be determined:

- contaminants (toxic metals, and aromatic, chlorinated,
and aliphatic hydrocarbons

- organic carbon content, stable carbon, and nitrogen
isotope content.

(/. In bottom sediments, the following elements will be
determined:

- determinants (toxic metals, and aromatic, chlorinated,
and aliphatic hydrocarbons

- total organic carbon and nitrogen

- stable carbon and nitrogen isotopes

- structural characteristics of zoobenthos (numbers,
biomass. species composition, and species mass)

3. Higher Trophic Levels

During the expedition, zoological observations will be carried
out: numbers, distribution, and migratory patterns of fish,
birds, and marine mammals.

4. Model Experiments

Model experiments will be performed under conditions
similar to natural situations. During these experiments, the
following parameters will be studied:

- photochemical oxidation of organic contaminants

- biodegradation potential of bacterioplankton with
respect to organic contaminants (benzo( a )pyrene. PCB.
etc.)

- combined influence of contaminants on biological
"targets'" and establishment of "critical" concentrations
of the impact on plankton communities in the conditions
of controlled ecosystems (Izrael, et ciL. 1988a)

- sediment respiration and nutrient flux experiments.

Connection with other International Programs

The BERPAC Program has much in common with other
international programs, but at the same time it has its own
particular features mentioned earlier. Wide cooperation with
other similar international projects is built within the framework
of this program — in particular, in the preparation of joint
marine expeditions. Wide data exchange is also planned.

Schedule of Activities and Applications of Results

Since 1977, successful joint investigations of Soviet and
American scientists have been carried out in the Bering Sea
within the framework of the specific theme of the bilateral
cooperation "Bering Sea" (Project "Comprehensive
Environmental Analysis"; Suhproject "Comprehensive
Analysis of Marine Ecosystem State and Ecological Problems
of the World Ocean"). Important stages of this cooperation
were three joint ecological Soviet- American expeditions in the
Bering Sea on the RA' V()//(«( Summer. 1977 }dndRJ\' Akadcmlk
Korolev (Summer. 1984 and 1988). several symposia on the
preparation of scientific programs, and analyses of the results
of these expeditions, as well as three monographs
describing the results of long-term Soviet-American
investigations in the Bering Sea (Izrael & Tsyban. 1990;
Roscigno. 1990). It is expected that these expeditions will be
every four years and followed by international symposia and
joint publications.

Monographs on the results of future expeditions will be
published. It is expected that seminars and symposia within the
framework of the BERPAC Program will be conducted. Also
included in the plans are special intercalibrations. a wide
exchange of specialists, and joint experimental work.

1.2 Polar Marine Ecosystems and Climate

YURIY A. IZRAEL* , ALLA V. TSYBAN' , TERRY E. WHITLEDGE", C. PETER McROY", and

VIKTOR V. SHIGAEV*

'USSR State Committee for Hydrometeoroloiiy and Natural Environmental Control, Moscow, USSR

institute of Global Climate and Ecology, State Committee for Hydrometeorohgy and Academy of

Sciences, Moscow, USSR

'Marine Science Institute, University of Texas at Austin, Port Aransas, Texas, USA

' Institute of Marine Science, University of Alaska, Fairbanks, Alaska. USA

Introduction

The warming of the global climate predicted to have
occurred by the middle of the next century will have a profound
effect on the state of the World Ocean and, therefore, on the
entire realm of relations between it and man. The magnitude
and thrust of this effect may vary widely from one geographic
zone to another. Possible physicochemical, ecological, or
socioeconomic consequences will be detemiined by the specific
characterofmarine ecosystems functioning, by regional factors,
and by the roles played by particular regions in world and
national economies.

According to present predictions, the regions that will be
most significantly impacted by global warming are those in
higher latitudes (Roots, 1989), where most marked changes in
the functioning of marine ecosystems may occur. This fact
makes it a matter of urgency that we generalize the findings of
ongoing environmental observations with a view to diagnosing
the possible effects of global warming as early as is feasible.
The assessment of these effects on circumpolar and polar
marine ecosystems calls for the mobilization of a broad
assortment of scientific methods and approaches.

To this end, the present paper relies upon predictive
assessments made available by global circulation models
(GCM's) of the coupled ocean-atmosphere systems when
applied to high-latitude regions; upon results obtained by
modeling of the oceanic branch of carbon circulation in the
marine environment; upon analyses of long-term environmental
observations; and finally upon economic projections.

The concluding section of the paper draws on these methods
for an analysis of possible changes in the physicochemical
parameters of the Bering Sea ecosystem that are expected to
ensue as a result of the presumed warming of the world's
climate.

Effect on Physicochemical Processes

Effect of Global Warming on the Temperature Regime and
Water Circulation in the High-latitude Ocean

Given all of its diverse ramifications, evaluation of the
effect of global warming on the temperature regime and water
circulation in the World Ocean is tantamount to the task of
predicting possible changes in all fundamental natural processes
as a result of new climatic conditions.

Since changes in the composition of the atmosphere and its
circulation affect processes occurring in the ocean and vice
versa, dealing with the this problem requires consideration of
the operation of the ocean-atmosphere system in conditions of
a developing "greenhouse effect." In this connection, one of
the most promising methods of investigating the sensitivity of
the climatic system to the mix of gases constituting the
atmosphere involves performing numerical experiments using
models of global circulation in the unitary ocean-atmosphere
system (Manabe&Stouffer, 1980;Schlesinger, 1986). Results
obtained from such calculations make it possible to predict
changes in temperature over the entire air column and in the
surface layer of the ocean as a function of a given atmospheric
composition and more especially as a function of CO, levels in
the atmosphere.

Of the numerous GCM ' s presently available for describing
the behavior of the ocean-atmosphere system, we would
suggest that the models that are most carefully developed and
take into account the maximum number of factors affecting
circulation processes are those developed by Oregon State
University (Ghan, 1982; Schlesinger & Mitchell, 1987);
Goddard Institute for Space Studies (Hansen et al., 1983,
1988); and by the NOAA Fluid Dynamics Geophysical
Laboratory at Princeton (Manabe & Wetherald, 1980, 1987).

Considerable quantitative differences notwithstanding,
results obtained from numerical experiments run on the basis
of the above models have shown close qualitative agreement of
predicted trends in the behavior of the ocean-atmosphere
thermal balance in high-latitude regions in the event of a
doubling of the CO, content of the atmosphere. A constant
problem with such models is the extremely widespread ice
cover and the very weak thermohaline circulation in the northern
part of the North Atlantic and Arctic Oceans (Bryan et al.,
1988). According to calculations, the temperature of the lower
layers of the atmosphere may be expected to rise by from 1 .3°
to 4.2°C, with greater warming occurring over land than over
water; the surface waters of the ocean would become 0.2° to
2.5°C warmer. Analysis of the seasonal dynamics of the
temperature field with all three models indicate that maximum
warming would occur in the Arctic and Antarctic regions
during the winter period.

The particular importance of the latter factor for the
system of water circulation in the World Ocean should be
noted. Thus, significant warming in the polar latitudes would

be associated with a decrease in the temperature gradient
between the equator and the poles and, as a consequence, with
a decrease in the intensity of winds and oceanic currents
(Mitchell, 1988). This in turn could lead to a shrinkage of
oceanic upwelling areas and weakened upwelling.

In addition to its effect on the circulation of World Ocean
waters, warming in the Arctic and Antarctic region would have
a marked impact on the state of the Earth' s cryosphere (glaciers,
shelf and marine ice). Such changes would in turn affect the
functioning of the climatic system.

First, the ice that covers 1 1 % of the World Ocean's surface
area to a large extent determines heat transfer between ocean
water masses and the energy balance at the ocean-atmosphere
interface. These factors influence the intensity of oceanic
convection, which in turn establishes the time scale of processes
that extend to great depths (e.g., CO, circulation). In addition,
exposed ocean waters absorb considerably more solar radiation
than do ice-covered waters (Walsh, 1983). Hence, changes in
the extent of ocean ice cover would inevitably affect atmospheric
circulation and temperature.

Second, even minor changes in the Earth's cryosphere
would lead to a significant change in global sea level as
compared with current values.

The rise in air temperature expected to occur in the Arctic
would have considerable consequences for the extent of marine
ice cover. Thus, sunmiers could bring about the complete
melting of the ice cover around Svalbard, along the north coast
of Siberia, and along the Arctic coast of Canada. Nevertheless,
in our view the global warming predicted by the middle of the
2 1st century will not lead to a majordiminutionof the ice mass
of the Antarctic and Greenland ice shields. Indeed, recent
studies in the Northern Hemisphere have shown that the extent
of ice cover over the past decade has increased despite a small
rise in mean annual temperature (Bryan et uL, 1988). On the
otherhand, the warming by 4° to 5°C that is expected (Mitchell,
1988) may lead to an acceleration of the flow of continental ice
sliding into the ocean and, therefore, to some decrease in ice-
cover thickness in the western Antarctic (Bud'ko & Izrael,
1987).

It may be noted in summary that global warming would
very likely entail displacement of surface isotherms toward the
poles, changes in the functioning of upwelling areas, and some
shrinkage of ice cover in the Arctic. Melting of sea ice in the
Arctic may produce a freshening of waters in the northern
Atlantic with consequential changes in the formation of ocean-
bottom waters. This process may affect heat flow in a northerly
direction, which might ultimately result in a shift in global
oceanic circulation (Bi7an el <;/., 1988).

Changes in the Carbon Cycle

The doubling of the carbon dioxide content of the
atmosphere predicted for the year 2050 may well disrupt the
global carbon cycle and therefore involve severe consequences
for the formation of the Earth's climate. Assessment of these
consequences requires profound insight into the cause-and-
effect relationships that constrained the natural variability of
CO. content in past geologic ages.

It should be noted that the elevated solubility of carbonates
occasioned by the increased salinity of seawater resulting from

increased CO, levels produces increased alkalinity and therefore
augments the ocean's CO,-hoIding capacity (Boyle, 1988).
Furthermore, CO, absorption in upwelling areas occurs largely
through the photosynthctic activity of phytoplankton, whereas
in the higher latitudes considerable amounts of atmospheric
CO, are extracted by oceanic masses in the process of deep-
water formation, particularly in places where the deep waters
in question rise to the surface (Roots, 1989). In addition,
increased carbonate solubility (as a consequence of the
acidulation of the surface layer by increased amounts of
dissolved CO,) can raise the alkalinity of seawater and hence
enhance the ocean's ability to absorb CO, (Boyle, 1988).
Possible increases in the amount of organic matter deposited in
bottom sediments due to augmented entry into the marine
environment of biogenic elements due to sea level rise can also
be regarded as a probable mechanism of removal of human-
generated CO, from the atmosphere (Siegenthaler, 1989).

It is therefore evident that rises in the carbon dioxide
content of the atmosphere may result in a disruption of the
global carbon cycle. The scale and thrust of possible changes
would be determined largely by the particularities of upwelling
ecosystem functioning under global warming conditions.

Changes in Biogenic Elements

Increased releases into the atmosphere of gases and aerosols
containing nitrogen, phosphorus, and sulfur compounds as a
result of human activities in highly industrialized countries
such as those of the North Atlantic seaboard are increasing the
amount of these substances entering the ocean (Oppenheimer,
1989). This process is particularly significant in the case of
nitrogen and sulfur, whose entry into the photic zone of the
ocean through the atmosphere may be compared with its
delivery by diffusion convection (Duce, 1986). Rises of
nitrogen and sulfur levels of regional scale, especially in
impacted ocean areas, may be accompanied by rises in the
bioproductivity of the affected ecosystems. Such phenomena
have already been reported for the coastal marine areas of the
North Sea (Lancelot et al., 1987).

Sea level rises accompanied by flooding and soil erosion
would result in considerably augmented influx of N, P, and S
into coastal areas, which might well produce intensified
eutrophication processes in the ecosystems thus impacted.
One consequence of this may be an acceleration of the
biogeochemical cycles of all biogenic elements (Oppenheimer,
1 989). This would depend on regional circumstances, however.
In the Beaufort Sea, for example, the erosion-susceptible peat
might become an important source of organic carbon for the
food chain in adjacent coastal waters. On the other hand, most
continental high-latitude regions can expect increased
precipitation, which would tend to increase biogenic-element
input into the nearby ocean.

Changes in Polliiltnit Cycles

Being associated with the intensification of microbial
degradation processes, the rise in marine surface-water
temperature currently predicted for the higher latitudes could
result in the accelerated hiodegradation of globally occurring
pollutants (chlorinated and petrolic hydrocarbons, phenols,
etc.), which would, in turn, promote the decomposition of such

compounds down to their low-molecular-weight components
and their flushing from the photic layer of the ocean (Tanabe,
mSSJzraelera/., 1990). Ontheotherhand.highertemperatures
imply reduced absorption of organic pollutants on suspended
matter (Pierce et al., 1974), which would have the effect of
diminishing the amounts of pollutants deposited in sea-bottom
sediments.

The increased fluxes of U V-B radiation being predicted in
connection with the depletion of stratospheric ozone layer
would intensify photochemical processes, especially at that
ocean-atmosphere interface (Zika, 1989). This would enhance
the photodegradation of both chlorinated and petrolic
hydrocarbons, possibly reducing this type of pollution of
marine environments (Doskey & Andren, 1987). It should be
noted, however, that apart from this positive effect of promoting
the removal of organic pollutants from seawater, prolonged
UV-B irradiation may also prove very detrimental to any
number of marine organisms inhabiting the surface layer of the
ocean (US EPA, 1987).

It may be expected that rises in the concentration of
atmospheric CO, would produce a certain acidulation of surface
waters ( Wilson & Mitchell, 1987). Even though this would not
affect the behavior of hydrophobic organic pollutants, the
consequences might prove very tangible from the standpoint of
ionogenic compounds. Thus, lower pH values would tend to
increase the permeability of cell membranes with respect to
such compounds, and hence to the accumulation of the latter in
marine organisms (Landner, 1989). In addition, higher acidity
may reduce the stability of heavy metals hound by compounds
ofhumic origin (Mantoura& Riley, 1975; Paxeus, 1985). This
process could in turn exacerbate the toxic effects of heavy
metals on marine biota (Sunda & Lewis, 1 978; Sedlacek et ai,
1983).

Effects on Environmental Processes

The predicted changes in the physicochemical parameters
of the marine environment as a result of global warming would
no doubt have considerable impact on the intensity and balance
of the fundamental environmental processes occurring in marine
ecosystems, as well as on the condition of biological resources
both in coastal waters and in open sea and open ocean areas.

Changes in the Conditions of Habitation of Marine Organisms
As a rule, marine organisms possess considerable
environmental (genetic, behavioral, etc.) flexibility, which
enables them to adapt to continuously varying environmental
conditions. This adaptability of marine organisms accounts for
the relative stability of zoogeographic zonation with respect to
climatic fluctuations (Odum, 1986). It is to be expected that
global warming would be accompanied by directed ecological
succession that would enable communities to adapt to a warmer
climate; some high-latitude communities may acquire the
characteristics of boreal communities, while temperate zone
communities might become more like their subtropical
counterparts.

The processes described above could have serious
consequences for the formation and distribution of all marine

biological communities, including those of commercially
important fish species. The effect of warming would be
especially pronounced in subpolar-front regions ( Roots, 1 989),
where increases of even a few tenths of a degree in deep water
temperature can lead to a noticeable redistribution of both
pelagic and benthic communities. On the other hand, comparable
temperature rises in the tropical latitudes would have no
significant effect on the functioning of marine organisms.

It should be noted that temperature is not the only parameter
that would be decisive for the state of marine life communities
in the higher latitudes under global warming conditions. Another
set of factors of considerable importance would be associated
with possible changes in oceanic and atmospheric circulation
(Bakun, 1990), which is an important influence on the
distribution and density of marine populations.

Changes occurring in the open ocean and in coastal areas
might be associated with changes in species diversity. This
effect would probably be less in evidence in the open ocean
than in estuaries and tidal zones. Polar marine ecosystems in
open areas would move more readily into new geographic
zones, while coastal ecosystems would be more rigidly restricted
by the physical characteristics of the relevant shoreline.

This leads to the general conclusion that what one may
expect in conditions of global warming that can entail
considerable changes in the living condition of marine biota is
a redistribution of marine life communities with the inevitable
consequences for the fishing industry worldwide.

Changes in Production-Degradation Processes and Biogenic
Sedimentation

In contrast to tropical and temperate regions where
productivity is determined largely by biogenic-element levels
alone, the chief limiting factors in circumpolar and polar areas
are light and temperature. In this connection, the predicted
warming of surface waters would lengthen the phytoplankton
vegetation season, and therefore increase the productivity of
such areas.

On the other hand, temperature rises would be accompanied
by accelerated microbial decomposition of organic matter.
The most pronounced intensification of decomposition
processes (by a factor from 1.1 to 1.3) might be expected to
occur in the higher latitudes and more particularly in the shelf
waters and surficial water masses of the boreal zone (Odum,
1986;Izrael&Tsyban, 1989).

The rates of degradation processes in surface waters in the
lower latitudes is determined by the influx of organic matter
from the Arctic and Antarctic as intermediate and deep waters
arrive by meridional transfer. This is why the effect of
temperature on the rates of degradation processes in the
equatorial and tropical regions is negligible. The changes in
production-degradation parameters would have aconsiderable
effect on the course biosedimentation proces.ses.

According to one model ( Suess. 1 980), the magnitude and
velocity of the biosedimentary flux is increasing in direct
proportion to rising productivity. Given this circumstance,
climate warming could increa.se biosedimentary fluxes in coastal
upwelling areas where a significant rise in productivity is
expected to occur (Bakun, 1990). The same could happen in

coastal land areas that would be flooded as result of sea level
rise. One the other hand, the acceleration of biodegradation
processes in the higher latitudes would preclude any marked
increases in biosedimentary fluxes.

In addition to rising temperature, another factor that would
affect the formation of new organic matter in the ocean would
be the further intensification of ocean pollution due to human
activities. According to present estimates, pollutant levels in
the euphotic layer of the ocean by the middle of the next century
can be expected to rise from 25% to 30% above current values
(Izrael & Tsyban, 1989). Moreover, warming of water masses
coupled with the acceleration of chemical reaction could increase
the toxicity of pollutants for marine biota. This would necessarily
have an adverse effect on the productivity of polar oceanic
ecosystems (Patin, 1979; Tsyban et al.. 1985).

It should be noted in conclusion that primary production
values for a region do not constitute an adequate yardstick for
assessing commercial fish resources. What is more important,
as far as the fishing industry is concerned, would be the shifting
of the most productive zones of the World Ocean, and especially
of upwelling areas, as this would be fraught with serious
repercussions in terms of the distribution of commercial fish
stocks and fish resources replenishment.

The Role of Ice in Sustaining Marine Polar Ecosystems

Ice plays an important role in the development and
sustenance of marine polar ecosystems for the following reasons:
/. it is extremely important to the growth of the marine algae
that are the primary food source in marine ecosystems; 2. it
creates conditions conducive to primary-production synthesis
at the ice-water interface, allowing plants to bloom, thus
maintaining the abundance and species diversity of biological
communities; i. it is extremely important to the vital activity of
the organisms that ensure energy transfer from the primary-
production level ( algae and phytoplankton ) up to higher trophic
levels (fishes, marine birds and mammals); and 4. the latter
factor in turn operates to maintain existent numbers of marine
communities.

One of the possible consequences of global warming
might be the shrinkage and diminished stability of marine ice,
which would directly affect the productivity of polar ecosystems.
For example, the absence of ice over the continental shelf of the
Arctic Ocean would produce a sharp rise in the productivity of
this region, provided sufficient biogenic elements are available.

Polar mammals need ice to obtain their food and to
reproduce. For example, the extent of the polar bear's habitat
is determined by the maximum seasonal surface area of marine,
ice in a given year. This means that the disappearance of ice
would threaten the very survival of the polar bear and of certain
marine seals. Similarly, a reduction of ice cover would reduce
food supplies for penguins and walruses and increase their
vulnerability to natural predators and human hunters and
poachers. Should the ice cover shrink, animals such as the sea
otter would have to migrate to new territories. Furthermore, it
remains unclear how the contraction of ice cover would affect
the migration routes of animal (such as whales) that follow the
ice front.

Changes in water temperature and wind patterns as a result
of global warming would almost certainly affect the distribution
and size of the polynyas (unfrozen patches of water surrounded
by ice ), which are so vital to the maintenance of polar ecosystems.
In addition, changes in the extent and persistence of marine ice,
combined with changes in the characteristics of currents such
as the circumpolar current in the southern latitudes, could
influence the distribution, biomass, and volume of available
krill. Krill is an important link in the food chain of Antarctic
Ocean fauna and is also of great importance for commercial
fisheries. A proper understanding of the way in which the
productivity of the Antarctic Ocean would change under new
climatic conditions is essential in assessing the consequences
of global warming for the World Ocean environment.

Effects on Fish Stocks oi

Climate change is one of the paramount factors that
determine the fish reserves of the World Ocean, even though
the sensitivity to this factor of particular stocks varies
considerably from population to population and from region to
region.

Each population of a given species community is fitted to
a particular hydrody namic structure with definite temporal and
spatial characteristics. Given this fact, changes in ocean
circulation could lead to the disappearance of certain populations
or to the appearance of new ones. Most seriously affected
would be the populations localized in habitat boundary waters
(Troadec. 1989).

One of the promising avenues for predicting the possible
consequences of climate warming on the status offish fauna is
the method of historical analogies. This method involves
isolating salient features in the distribution and biomass offish
stocks over a number of past intervals such that each interval is
associated with specific climatic, and therefore environmental,
characteristics, the purpose being to draw further analogies.
The application of this method for describing the state of fish
resources over the present century has made it possible to
discern certain essential features. The warming that occurred
in the first half of the 20th century was accompanied by the
penetration of northern fish species into subarctic and arctic
seas, something that was observed both in the North Pacific and
the North Atlantic. Thus, a favorable change in environmental
conditions as a result of warming can generate new commercial
fish stocks. Moreover, the warming of the 1940"s and 1950"s
showed that warming of the marine environment can have
quite different consequences even for a single fish species,
depending on specific features of habitat. For example, this
period saw the most sizeable generations of
Atlantic-Scandinavian herring, while the number of North Sea
herring plummeted.

Recent studies in the North Atlantic have brought to light
a direct link between climatic variation on the one hand and the
distribution and replenishment of fish resources on the other.
Particularly noteworthy in this connection is the so-called
"1970's anomaly" (Jenkins & Ephraums, 1990), remarkable
for the concurrent effects it involved for several commercial
stocks. Originating off the coast of eastern Greenland in the

10

lale I96()"s, it went on to skirt Greenland and Labrador in the
direction of the North Atlantic current, reaching the Barents
Sea in 1979-80 (Dickson ('?«/., 1984). In the late I980"s.this
anomaly led to extremely low prevailing temperatures in the
waters off northern Iceland, which was probably the cause for
the drop in numbers of Atlantic-Scandinavian herring.

The above changes in fish resources were brought about
by relatively short-term tluctuations in the temperature of the
environment. Proceeding on the assumption that global wanning
would entail a long-term upward creep t)f temperatures, this
factor may be expected to have even more profound effects on
the fish resources of the ocean. A rise in the mean temperature
of polar and subpolar waters of the World Ocean of just l°C
could have a substantial influence on the distribution, growth,
and replenishment offish populations. Commercially valuable
fish stocks may acquire new spawning grounds, which would
entail considerable changes in their distribution patterns.

The strong homing instincts of salmonids in the Northern
Hemisphere would probably render changes in the geographic
distribution of these species to be fairly difficult. On the other
hand, salmonid populations may suffer considerable attrition
should geographic shifts of habitat become an absolute necessity
for thein.

A more complete assessment of the effects of global
warming on the state of fish resources in the high latitudes of
the World Ocean requires allowance not only for temperature
rises, but also for increased hard ultraviolet radiation fluxes.
The latter factor would impact first and foremost upon those
fishes whose early developmental stages live either in neuston
communities or in coastal ecosystems. It must be borne in mind
that notwithstanding the relative opaqueness of seawater to
ultraviolet radiation, the roe and fry floating and swimming
near the surface, together with the accompanying phyto- and
zooplanklon, corals, and algae of tidal /ones, would be subjected
to prolonged and intense irradiation, which may well increase
the mortality of young fish and adversely affect the gene pool
of the marine organisms in question.

Regional Aspects of the Problem (Using the Bering Sea as
an Example)

Taking into account all of the foregoing, we would draw
particular attention to the extensive body of information
concerning the functioning of the Bering Sea ecosystem built
up in the course of long-term joint US-USSR studies (the
project entitled Comprehensive Analysis of the Bering Sea
Ecosystem , under the "Bering Sea" Program).

According to predictions based on the use of GCM's, the
effect of global warming on the Bering Sea region could take
the fonri of a displacement of surface water isotherms toward
the North Pole (warming by 0.5°C over a single decade would
be accompanied by a shift in isotherms of over 30 km | Hansen
et ai, 19881 ). Temperature rises could lead to earlier vernal

blooming of phytoplanktt)n and to a lengthening of the entire
blooming season.

By present estiinates, primary production in the Bering
Sea averages 0.6.3 g C/m7day, attaining 7 g C/ni7day in some
places (McRoy&Goering, 1976; Izraelefa/., 1986;Whitledge
etai. 1988). The predicted advent ofconditions more conducive
to phytoplankton vegetation suggests increases of primary
production up to 0.75-0.90 g C/m'/day.

Starting from a current rate of degradation of organic
matter in the Bering Sea that averages 0.3 g C/mVyear (Izrael
et ai. 1986; Whitledge et ai, 1988), global warming might
bring this value up to 0.35-0.50 g C/mVyear.

The expected acceleration of microbiological and
photochemical processes would be accompanied by more
rapid decomposition of organic pollutants and, as a consequence,
by a reduction of levels of pollution of the given ecosystems by
human activities (Izrael et ai. 1990).

An intensiflcation of production-degradation processes
could also result in the acceleration of biosedimentation
processes, especially in coastal areas. According the latest
experimental assessments based on determinations of organic-
matter biosedimentation rates (Izrael et al., 1986),
1.6 X 10' tons of C settle to the bottom of the Bering Sea
annually. On condition that the balanced character of the
biogeochemical carbon cycle is maintained, this value can be
taken as the lower limit for the influx of atmospheric carbon
into the waters of the Bering. It is relevant in the connection to
mention that the total contribution of carbon to the World
Ocean is 53 x 10'* tons/year (Odum, 1986). These figures
confirm the significance of subarctic ecosystems in the overall
context of the global carbon cycle and point up their major role
in shaping the Earth's climate.

One of the inost significant consequences of global warming
may be the displacement of the subarctic front, which would
entail radical changes in the environment of pelagic and benthic
communities, including many valuable fish species. Since the
Bering Sea is a fishing area of enormous importance to a
number of countries that together catch 3 x lO*" tons of fish
annually (Wilimovsky, 1974), it is imperative to foresee possible
detrimental consequences of global warming in this region as
they impact upon the distribution and replenishment of many
valuable species offish, birds, and mammals. Elaboration of
prognoses of the state of living resources in the Bering Sea area
in conditions of global warming would greatly facilitate the
development of an effective system of adaptive responses for
this region.

The long-term studies in the Bering and Chukchi Sea
conducted over the past decade will continue and will in future
encompass the issues discussed in the present paper within the
context of BERPAC.

Efforts under BERPAC are part of the USSR's MONOK
program: The Integrated Ecological Ocean.

11

12

Chapter 1 References

Bakun, A. (1990). Global climate change and intensification
of coastal ocean upwelling. Scieme lAl . 198-201.

Boyle, E. A. (1988). Vertical oceanic nutrient fractionation
and glacial/interglacial CO, cycles. Nature 331, 55-56.

Biid'ko, M. 1. & Izrael, Yu. A. (eds. ) ( 1987). Anthropogenic
Change of Climate. Gidrometoizdat Publishers. Leningrad.
378 pp.

Coachman. L. K. (1990). Bering Sea ecosystem: Basic
characteristics and prospects for long-term research. In
Research on the Bering Sea Ecosystem. Results of the
Second Soviet - American E.xpedition. The 37th Cruise of
the Research Vessel Akademik Korolev, June - September
1984. Gidrometeoizdat Publishers, Leningrad, 2. (in Russian )

Dickson C, Meincke. M.. Malmberg. R. & Lee. G. ( 1 984). The
great salinity anomaly in the northern North Atlantic. Prog.
Oceanogr. 20, 2.

Doskey, P. V. & Andren. A. W. (1987). Modeling the flux of
atmospheric polychlorinated biphenyls across the air-water
interface. Environ. Sci. Technol. 15, 705-71 1.

Duce, R. A. (1986). The impact of atmospheric nitrogen,
phosphorus, and iron species on marine biological
productivity. The role of air-sea exchange in geochemical
cycling (P. Buat Menerd. ed. ). pp. 497-529.

Ghan. S. J. ( 1982). A documentation of the OSU two-level
atmospheric GCM model. CRl Report 35. Oregon State
University. 395 pp.

Hansen, J., Fung, 1., Lacis, A., Rind, D.. Lebedeff, S., Ruedy.
R. & Stone, D. (1988). Global climate change as a forecast
by Goddard Institute for Space Studies three-dimensional
model. / Geophys. Res. 93, 9341-9364.

Hansen, J., Russel, G., Rind, D., Stone, D., Lacis, A., Lebedeff,
S., Ruedly, R. & Travis, L. (1983). Efficient three-
dimensional global models for climate studies: Models 1 and
II. Mon. Wea. Rev. Ill, 609-622.

Izrael. Yu. A. & Tsyban. A. V. (1983b). Research on the
assimilative capacity of the World Ocean. Reports of the
USSR Academy of Sciences 272(3). 702-705 . (in Russian)

Izrael. Yu. A. & Tsyban. A. V. (eds. ) ( 1983a). Research on the
Bering Sea Ecosystem. Gidrometeoizdat Publishers,
Leningrad, 157 pp. (in Russian)

Izrael, Yu. A. & Tsyban, A. V. (1985). The ecology and
problems of global ocean monitoring. In Comprehensive
Global Ocean Monitoring 1, 19-48. Gidrometeoizdat
Publishers, Leningrad, (in Russian)

Izrael, Yu. A. & Tsyban, A. V. (eds. ) ( 1987). Comprehensive
Analysis of the Bering Sea Ecosystem. Gidrometeoizdat
Publishers, Leningrad, 264 pp. (in Russian)

Izrael, Yu. A. & Tsyban. A. V. ( 1989). Anthropogenic Ecology
of the Ocean. Gidrometeoizdat, Leningrad, 528 pp. (in
Russian)

Izrael, Yu. A. & Tsyban, A. V. (eds. ) ( 1990). Research on the
Bering Sea Ecosystem. In Results of the Soviet - American
E.xpedition. The 37th Crui.se of the Research Vessel Akademik
Korolev. June-September. 1984. Gidrometeoizdat
Publishers, Leningrad, 344 pp. (in Russian)

Izrael. Yu. A.. Tsyban. A. V.. Panov. G. V.. Korsak. M. N.,

Kudryatsev, V. M.. Volodkovich, Yu. L. & Chemyak, S. M.

(1986). Comprehensiveanalysisof the Bering Seaecosystem.

Monitoring and managing environmental impact: American

and Soviet perspectives (G. E. Schweitzer & A. S. Phillips,

eds. ). National Academy Press, pp. 58-88.
Izrael. Yu. A., Tsyban, A. V.. Panov. G. V., Korsak, M. N. et

al. (1988a). Comprehensive analysis of the Bering Sea

ecosystem. In Comprehensive Analysis of the Environment.

Proceedings from the Fifth USSR-US Symposium.

Gidrometeoizdat Publishers, Leningrad, 528 pp. (in Russian)
Izrael, Yu. A., Tsyban, A. V., Ventzel, M. V. & Shigaev, V. V.

( 1988b). Generalized model of the assimilative capacity of

a marine ecosystem. Reports of the USSR Academy of

Sciences 380(2) . (in Russian)
Izrael, Yu. A., Tsyban, A. V., Ventzel, M. V. & Shigaev, V. V.

( 1988c). Scientific basis for ecological standardization of

the anthropogenic impact on marine ecosystems (using the

example ofthe Baltic Seaecosystem. Oceanology2S(2). (in

Russian)
Izrael, Yu. A., Tsyban, A. V., Panov, G. V. & Chemyak, S. M.

(1990). Microbial transformation of polychlorinated

biphenyls in polar sea regions. DAN USSR (Reports ofthe

USSR Academy of Sciences) 310. 502-506 . (in Russian)
Jenkins, J. T. & Ephraums, J. J. (eds. ) ( 1990) Climate Change:

The IPCC Scientific Assessment. Cambridge University

Press, Cambridge. 26 pp.
Lancelot, C, Billen. G.. Sourina. A., Weisse. T.. Colijn, F.,

Veldhuis, M. J. W., Davies, A. & Wassman, P. (1987).

Phaeocystic blooms and nutrient environment in the

continental coastal zones ofthe North Sea. Ambio 16. 38^6.
Landner.L. (ed. )(1989). Chemicals in the aquatic environment:

Advanced hazard assessment. Springer Verlag. Berlin,

569 pp.
Manabe. S. & Stouffer. R. J. (1980). Sensitivity of a global

climate model to an increase in CO, concentration in the

atmosphere. J. Geophys. Res. 85, 5529-5554.
Manabe, S. & Wetherald, R. T. (1980). On the distribution of

climate change resulting from an increase in CO, content of

the atmosphere. J. Atmos. Sci. 37, 99-1 18.
Manabe, S. & Wetherald, R. T. ( 1 987). Large-scale changes of

soil wetness induced by an increase in atmospheric carbon

dioxide. J. Atmos. Sci. 44, 121 1-1235.
Mantoura. R. F. C. & Riley. J. P. (1975). The use of gel-
filtration in the study of metal binding of humic acids and

related compounds. Anal. Chim. Acta 78, 183-200.
McRoy, C. P. & Goering, J. J. (1976). Annual budget of

primary production in the Bering Sea. Mar. Sci. Comm. 2,

255-267.
Mitchell, J. F. B. ( 1988). Local effects of greenhouse gases.

Nature 332, 399-400.
Odum, G. ( 1986). Ecology, Vol. 2. Mir Publishers, Moscow,

359 pp. (in Russian)
Oppenheimer, M. ( 1 989). Climate change and environmental

pollution: Physical and biological interactions, dim. Change

15, 255-270.

13

Patin, S. A. (1979). The Impact of Pollution on Biological

Resources and Productivity of the World Ocean. Pishchevaya

Publishers, Moscow, I 1 1 pp. (in Russian)
Pa.xeus, N. (1985). Studies on aquatic humic substances.

Ph. D. thesis. University of Goetenburg, Sweden.
Pierce, R. H.. Jr. ( 1974). p, p'-DDT-adsorption to suspended

particulate matter in sea water. Geochim. Cosmochim. Acta

38, 1061-1073.
Roots, E. F. (1989). Climate change: High-latitude regions.

Clim. Change 15, 223-253.
Roscigno, P. F. (ed. ) ( 1990). Residts of the Second Joint US-
USSR Bering Sea Expedition. Summer 1984. US Fish Wild.

Serv. Biol. Rep. 90( 13), 347 pp.
Schlesinger, M. E. ( 1986). Equilibrium and transient climatic

warming induced by increased atmospheric CO,. Clim. Dyn.

1, 35-53.
Schlesinger, M. N. & Mitchell, J. F. B. ( 1987). Model projections

of the equilibrium climate response to increased carbon

dioxide. Rev. Geophxs. 25, 760-798.
Sedlacek. J., Kallquist, T. & Gjessing, E. (1983). Effect of

aquatic humus on uptake and toxicity of cadmium to

Selemistrum capricormitum. In Aquatic and Terrestrial

Humic Materials (R. F. Christmann & E. T. Gjessing, eds),

pp. 495-516. Printz, Ann Arbor, Michigan.
Siegenthaler, U. ( 1 989). Exchange of CO, between atmosphere

and ocean. UNESCO technical papers in marine science 56,

44-49.
Suess, E. (1980). Particulate organic carbon tlux in the

oceans — surface productivity and oxygen utilization. Nature

288, 260-263.
Sunda, W. G. & Lewis. J. A. M. ( 1 978). Effect of complexation

by natural organic ligands on the toxicity of copper to a

nmccWuVdx ^[gdiC.Monochreysisluthery. Limnol. Oceanogr.

23, 870-876.
Tanabe, S. ( 1 985 ). Distribution, behavior and fate of PCBs in

the marine environment. J. Oceanogr. Soc. Jpn. 41.

358-370.
Troadec, J. P. ( 1989). Report of the Climate and Fisheries

Workshop. Organized by M. H. Glantz, NCAR, Boulder,

Colorado, 7-8, 16.

Tsyban, A. V., Volodkovich, Yu. L. & Pfeiffere, M. Yu.
( 1985). Circulation of the contaminants in the Baltic Sea
ecosystem. Investigation of the Baltic Sea ecosystem,
pp. 244—257. Gidriimeteoizdut Publishers, Leningrad, (in
Russian)

US Environmental Protection Agency (1987). Chapter 12. An
assessment of the effects of ultra-violet-B radiation on
aquatic organisms (J. S. Hoffman, ed.), US EPA, 400-1-87-
001 C.

Walsh, J. E. ( 1983). The role of sea ice in climatic variability:
theories and evidence. Atmosphere and Ocean, March 2 1 .

Whitledge, T. E., Bidigare, R. R., Zeeman, S. L, Sambrotto, R.
N., Roscigno, P. F., Jensen, P. R., Brooks. J. M., Trees,
C. & Veidt, D. M. (1988). Biological measurements and
related chemical features in Soviet and United States regions
of the Bering Sea. Cont. Shelf Res. 8, 1299-1319.

Wilimovsky, N.J. ( 1974). Fishiesof the Bering Sea: The state
of existing knowledge and effort. In Oceanography of the
Bering Sea (D. W. Hood & E. J. Kelly, eds. ), pp. 243-256,
University of Alaska, Fairbanks.

Wilson. C. A. & Mitchell. J. F. B. (1987). A 2 x CO, climate
sensitivity experiment with a global climate model including
a simple ocean. J. Geophys. Res. 92(D1 1 ). 313-315.

Zaitsev, Yu. P. (1970). Marine Neustonology. Naukova
Dumka Publishers, Kiev, 264 pp. (in Russian)

Zaitsev. Yu. P. ( 1980). Zooneuston and methods for its study.
\n Methods for Biological Analysis of Sea Water and Bottom
Sediments, pp. 134-139. Gidrometeoizdat Publishers,
Leningrad, (in Russian)

Zaitsev, Yu. P. ( 1985). Biotic contours in ocean monitoring. In
Comprehensive Global Ocean Monitoring. Proceedings
from the First International Symposium 2, 76-83.
Gidrometeoizdat Publishers, Leningrad . (in Russian)

Zika, K. G. ( 1989). The role of photochemical processes in the
air/sea exchange of chemical species. UNESCO Technical
Report.

14

Chapter 2:

OCEANOGRAPHY

Editors:

LAWRENCE K. COACHMAN &
VIKTOR V. SHIGAEV

2.1 Northern Bering-Chukchi Sea Ecosystem:
The Physical Basis

LAWRENCE K. COACHMAN^ and VIKTOR V. SHIGAEV^

'School of Oceanography, University of Washington, Seattle, Washington, USA

• Institute of Global Climate and Ecology, State Committee for Hydrometeorology and Academy of Sciences, Moscow. USSR

Introduction

The northern Bering and Chukchi Seas, encompassing the
Bering Strait (Fig. 1 ). together constitute the most enormous
shelf sea of the World Ocean — that is, over 1,000 km in north-
south extent with depths less than 100 m. The longer-term
(>1 month) average flow is northward of Bering Sea water
across the whole area into the Arctic Ocean, providing the
Northern Hemisphere oceanic link between Pacific and Atlantic
Ocean systems. It has been known that North America and
Asia are separated by the Bering Strait since Simeon Dezhnev
transited the strait inadvertently (blown by a storm) in 1648;
and that the general flow of the water through the strait is
northward since the voyages of Bering and Cook in the 18th
century.

178* 180* 173" t7S*

164- I6r iW 158* ISA*

76' leO- I7B' 176* 174- 17;- 170" i68' i66- lei*

Fig. 1. Bathymetry of the northern Bering and Chukchi Seas.

Modem studies of the physical oceanography of various
parts of this large regime, begun in the 1930"s by G. E.
Ratmanov ( 19,^7a,b) and C. A. Barnes (Barnes & Thompson,
1938), were )iyn[he^izedinBering Strait: The Regional Physical
Oceanography {Coachman etal., 1975). This study summarized
the water masses, theirdistributions, something of the temporal
and spatial variations in properties and causes thereof, and
quantified the northward flow and its variations. It showed the

integrated nature of the whole system: that the waters and its
transported properties were intimately connected across the
entire shelf sea from the Bering Sea basin to the Arctic Ocean
and that the dominant property distribution inechanism is
everywhere is advection (with the generally northward flow).
Investigations of various biochemical properties within
the region, from which the production of organic matter and its
subsequent fate can be determined and explained, began much
later than the physical studies. These were also much more
piecemeal and limited in scope until the advent of the Inner
Shelf Transfer and Recycling Program (ISHTAR) in 1985
(Walsh et al.. 1990), which undertook an integrated
physical/chemical/biological study (i.e., ineasuremenls of all
fundamentals of the basic ecosystem) of those portions of the
region to which they had access, viz. the Chirikov basin and
eastern part of the Chukchi Sea. The results from ISHTAR,
after four years of intensive sampling and analysis, clearly
demonstrate that the whole region, integrated into one regime
by the north advection, is also integrated as an enormous
ecosystem containing some of the highest primary production
values ever measured in the World Ocean. The ecosystem is
sketched schematically in Fig. 2. The generally northward'
water flow is composed mostly of water from the northern
Bering Sea basin, which enters the region in the

Fig. 2. Schematic of the northern Bering Sea ecosystem. Open arrows
indicate advection along which ecosystem activity is aligned;
dashed Imes encompass the three production/deposition centers.

17

Gulf of Anadyr. The continuity of this flow, entirely through
the system into the Arctic Ocean, provides integration between
three serially-aligned production/deposition/regeneration
centers; the output of the upstream Gulf of Anadyr center
materially effects the biochemical activity of the Chirikov
basin center, which in turn feeds the center in the Chukchi Sea.
Confirmation of the integrated nature of the ecosystem is
provided by measurements made during the first synoptic
survey of the whole region from the Gulf of Anadyr through the
southern Chukchi. The opportunity arose from amalgamation
of ISHTAR into the Third Joint US-USSR Bering & Chukchi
Seas E.\pedition, 25 July-2 September 1988, on board the
research vessel (RfV ) Akademik Korolev (Korolev). The areal
distribution of integrated chlorophyll ( Fig. 3 ) clearly shows in
essence the ecosystem arrangement sketched in Fig. 2 — three
high-production centers arranged sequentially along the
pathway of flow of Bering Sea water from the northern Bering
through the Gulf of Anadyr, then the Chirikov basin and
Bering Strait, and on through the southern Chukchi. Thus, we
are dealing with a single ecosystem. It is the purpose of this
paper to describe, to the extent of current knowledge, the
physical basis of this ecosystem: the water masses and their
characteristics, the flow field, and the variabilities of the
physical features. The paper concludes with a discussion of the
downstream end of the system in the Chukchi Sea, about which
very little is as yet known.

175°

165°

160°

Fig.

}. Integrated chlorophyll from the cruise odheAkmleinik K(iroU'\\ August
1988. Notice the three major production centers, and the edge of a
fourth area of high chlorophyll biomass off Kolyuchm Bay in the
Chukchi Sea (after Springer, McRoy & Whitledge, in press).

Water Masses

Salinity is the variable delimiting the water masses because
in the colder high-latitude waters, it, rather than temperature,
has the primary influence on water density. Based on sources

and modifications, there are three water masses fundamental to
the sy.stem (Coachman el ai. 1975), and it is convenient to
define two others, more local products of modifications.

The three basic water masses, Alaskan Coastal, Bering
Shelf, and Anadyr Current, are arranged side-by-side in the
east-west direction. Identification ofthe water mas.ses obtained
at any particular time are done from T/S diagrams of stations
from sections crossing Anadyr and Shpanberg Straits; these
capture the characteristics of the three basic water masses at the
same time. Figure 4 shows an example. Typically, in the T/S
plane, values beneath the surface layer fall naturally into three
groups; a group with intermediate values of S but very cold;
and somewhat warmer groups to each side, both less and more
saline. Spatial continuity shows the least saline group ( Alaskan
Coastal) to occupy the eastern part of Shpanberg Strait, the
most saline group ( Anadyr Current ) are always stationed in the
western part of Anadyr Strait, while Bering Shelf water of
intermediate salinities can usually be found near both ends of
St. Lawrence Island. Thus, from Fig. 4, the ranges of salinity
for the three water masses were Anadyr Current — 33.0 to
32.75; Bering Shelf— 32.75 to 3 1 .9 ; Alaskan Coastal— <3 1 .9.

ALASKAN
COASTAL

31 32

SALINITY %o

Fig.

4. T/S diagram of stations crossing Anadyr and Shpanberg Straits,
illustrating the definition of the basic water masses. Station numbers
are at the bottom of each water mass curve. Notice the natural
separation into three salinity groups.

But salinity values of the water masses are not constant.
There is a seasonal cycle because runoff at these high latitudes
is markedly seasonal. Yukon River discharge peaks in June,
when the flow grows in about one month's time to two orders
of magnitude greater than in winter. The regional north flow is
insufficient to flush all of this freshwater from the system
immediately, so part of the freshwater accumulates over the
summer and is only completely flushed by late fall (Coachman
t'l ai. 1975). This effects primarily salinities of Alaskan

18

Coastal water and to a lesser extent Bering Shelf water; both
these water masses show a decrease in S over the summer,
which can amount to as much as one-half part per thousand.

There are also interannual variations in the water mass
salinities that are the same magnitude as those of the seasonal
cycle (about 0.5). Figure 5 showstherangesofS values for the
water masses for all the years when sections in June or early
July encompassing Anadyr and Shpanberg Straits have been
taken; similar times of year must be compared to avoid the
seasonal variations. We see that, interannually, the salinities
are not constant. Small year-to-year differences are probably
not significant because definition of water mass boundary
values can sometimes be somewhat fuzzy, but the long-term
variation with either a 10 or 20-year period is definitely real.
Anadyr Current water in the 1960"s frequently had S values
>33.0, but during the 1970's and beginning of the 1980's,
values this high were never observed; only in 1988 have
salinities >33 reappeared.

Similar sized interannual variations in S have also been
observed in the central shelf water of the southeast Bering Sea
Shelf; ranges of S observed there (Coachman, 1986) are also
plotted in Fig. 5. Clearly we are seeing the effects of large-scale
climatic fluctuation causing similar property variations ovei;
the entire Bering Sea Shelf. This variation effects also the
bottom water temperatures of central shelf waters, and the T
and S are correlated — wanner with more saline and colder
with fresher. The few measurements available of bottom water
temperatures in the central Gulf of Anadyr, where the coldest
water of the whole Bering Sea Shelf is always found (the so-
called "cold center" of the Bering Sea; Barnes & Thompson,
1938), suggest an interannual variation incoldestTof at least
2°C may obtain, not unlike that of T on the southeast shelf
(Fig. 5). The interannual climate variation is also manifested
in interannual variablity of ice cover of the Bering Shelf, which
is primarily responsible for establishing the T and S conditions
of bottom waters for the following year: minimum ice/warmer
bottom temperatures/more saline, and vice versa.

^m^ Southeast Central Shelf Bottom Woter T Ronge
J Southeast Central Shelf Water S Range

;^

I960 65

Fig. 5. Interannual variation ofsalinity ranges ofthclhrec basic water masses.
Over the 2.'i years of observations, water masses were most saline in the
late I960's, and least saline in the mid-mVO's. Temperatures and
salinities of southeastern Bering Shelf water suggest similar variations,
showing the changes to be part of a large-scale climatic variation.

The water mass sources are all to the south of the northern
shelf area, and the advection carries them northward. As
Alaskan Coastal, Bering Shelf, and Anadyr Current water
masses are arranged sequentially east to west and there is very
little lateral mixing or diffusion in the system, these waters
maintain their east to west relationship as they are advected
north. Figure 6 shows their distribution during August 1988,
based on the Korolev data. The water masses were distinguished
primarily by salinity of the deeper water, but temperature and
water column structure (depth and degree of layering) were
also considered. Anadyr Current water mass (Fig. 6, 1) originates
from water of the Bering Slope Current (Kinder et ai, 1975),
a branch of which enters the Gulf of Anadyr in the west near
Cape Navarin. This water hugs the western Siberian shore and
remains identifiable as a distinct entity to Bering Strait. North
of this strait, the water merges with and becomes
indistinguishable from Bering Shelf water.

"180

175°

170°

165°

160°

Fig. 6. Spatial distribution of water masses in August 1988 (Korolev liala).
I: Anadyr Current. II: Bering Shelf. Ill: Alaskan Coastal.
IV: Gulf of Anadyr. V: Siberian Coastal.

On the east side of the system, Alaskan Coastal water
(Fig. 6, III) originates well to the south of the region. It has the
lowest salinities because it is the recipient of runoff from all
along the coast, from the rivers of Bristol Bay and the
Kuskokwim River. As Alaskan Coastal water enters the
region, additions of Yukon River water near the east side of
Shpanberg Strait "reinforce" the low salinities, which happens
again when the water passes through Kotzebue Sound north of
Bering Strait. Thus some parts of this water mass can become
quite fresh in late summer (S<30), and its area expands westward,
but by the following winter the freshwater has flushed from the
system and Alaskan Coastal water salinities are again >32.

Bering Shelf water (Fig. 6, II) is the resident water mass
of the whole central shelf region south of St. Lawrence Island.
The waters filling the central shelf are basically mixtures of the
two extremes: least saline coastal water and the most saline

19

water from the Bering Sea basin Shelf edge. Advection is small
over the whole central shelf with water depths between 50 and
100 m (Coachman, 1986), so this water mass, intermediate in
salinity and with long residence times, is most strongly
conditioned by climatic factors such as brine rejection due to
freezing and degree days of frost (see discussion in Coachman,
1986). Furthermore, Bering Shelf water in the area immediately
south of St. Lawrence Island is directly influenced by special
freezing conditions associated with the large polynya always
found on its south side (Schumacher et al., 1983). In the area
of this polynya, the freezing over-winter of the equivalent of 8
to 10 m of ice causes a substantial increase in salinities of the
shallow watercolumns. Thus increased in density, some of this
water moves away to the southwest (in the direction of
deepening) into the central Gulf of Anadyr, where it can be
distinguished as a separate water mass we call Gulf of Anadyr
water (Fig. 6, IV); this is in fact the "cold center" water of
Barnes and Thompson because its temperatures over the summer
normally remain close to freezing (<- 1 .5°C) and are the coldest
observed anywhere on the whole Bering Sea Shelf.

Most of the year. Bering Shelf water (Fig. 6, II) moves
north around both ends of St. Lawrence Island and then
occupies the middle area between Alaskan Coastal and Anadyr
Current waters. In late summer, however, some years Alaskan
Coastal water expands to nearly fill Shpanberg Strait, as in late
August 1988, and northward transport of Bering Shelf at these
times is predominately through Anadyr Strait (Fig. 6). North
of Bering Strait, Anadyr Current water becomes so blended
with the shelf water it loses identity. Across the Chukchi Sea
we continue to identify this water mixture as Bering Shelf
water , because salinities are little altered by the admixture of
Anadyr water, and the name connotes its basic origin.

In the Chukchi Sea occurs another water mass, Siberian
Coastal water (Fig. 6. V), identified by values of salinity
greater than any entering the sea through Bering Strait
contemporaneously. For example, in August 1988, the
maximum observed S in Anadyr Current water was <33.0,
while salinities ofSiberian Coastal water were up to 33.6. This
water mass is associated with the Siberian Coastal Current.

Though lateral mixing is in general quite small in this
regime of strong advection, and relatively discrete boundaries
obtain between the water masses (transitions between two
water masses are typically complete in <10 km), there is some
lateral interaction. This almost always takes the form of
layering, the slightly heavier water mass on one side encroaches
under the neighboring water, which fonns a lighter surface
water layer; or, frequently, the lighter water mass is driven by
wind over the heavier.

Layering varies seasonally. In winter and spring there is
practically none; all the shallow watercolumns are well mixed.
Nomially only in deeper areas like the central Gulf of Anadyr
does a layered structure survive the winter cooling and freezing.
Layered water columns appear with the advent of freshwater
accumulation and some seasonal warming, usually late June
and July, and is most widespread at the end of summer before

fall cooling begins. The extent and degree of layering observed
in August 1988 (Fig. 7) is typical for late season. We make the
following points and interpretations:

/. Strong layering is typical of the boundary between
Alaskan Coastal and Bering Shelf water, particularly in the
Chirikov basin (cf Fig. 6).

2. Layering is minimal in very shallow near-shore waters,
(e.g., in eastern Kotzebue Sound).

3. Both the Gulf of Anadyr and Siberian Coastal are
basically layered water masses. In the Gulf of Anadyr depths
in the central part deepen to 100 m (Fig. 1 ). Here the very cold
water of the "cold center," with slightly enhanced salinities,
resides beneath Bering Shelf water; water columns are
sufficiently deep that the layering survives rigorous winter
cooling and freezing. During the summer along the Siberian
coast in the Chukchi Sea, runoff and ice melt create a very light,
low salinity surface layer over the high salinity water at bottom;
both layers are part of the Siberian Coastal Current.

4. Minimum stratification, even in late summer, is always
observed directly downstream from Anadyr and Bering Straits,
a consequence of turbulent energy generated in these
constrictions.

We can now positively show that all waters of the ecosystem
derive from a single source, the water of the Bering Slope
Current of the northern Bering Sea. During the Third Joint US-
USSR Bering & Chukchi Seas Expedition, samples from all the
water masses were analyzed for "O heavy oxygen isotope.
Two factors make these measurements diagnostic for water
mass analysis:

70'

SALINITY LAYERING
S130m) - SlOml. %o
AUGUST 1988

°I80

175°

170°

165°

160°

Fig. 7.

Salinity layering (S at 30 m minus S near-surface) in August 1988.
The distribution is typical: strong layering in the central Gulf of
Anadyr (deeper water), along the boundary between Bering Shelf and
Alaskan Coastal in the Chirikov basin, and in the Siberian Coastal
Current. Very little layering in shallow water near Alaska, and in two
plumes extending downstream from Anadyr and Bering Straits.

20

/. This stable isotope is most abundant in ocean water and least
abundant in fresh precipitation and runoff, and so mixtures
show intennediate values in proportion, just like salinity; and
2. the freezing process, which is important in increasing salinity
of the northern shelf waters, does not alter the isotope abundance.

The correlations between salinity and oxygen isotope for
the water masses are plotted in Fig. 8 (oxygen isotope data
from Grebmeier et ai, 1990). Isotope values are plotted as
deviations from standard mean ocean water ('^Osmow)- so that
most ocean waters have values close to and freshwater is
<-20 ppt. In Fig. 8, samples are plotted in two ways: as
individual point correlations for samples from the Bering Slope
Current (triangles), Alaskan Coastal (open circles) and Siberian
Coastal (solid circles) water masses, and as envelopes
encompassing many values for the other three.

All samples lie on or very close to a line from S = 35,
"*0 = (ocean water) and S = 0, '"O = -24.6 (freshwater), from
which we can conclude that all water masses are essentially
simple dilutions of the most saline Bering Slope Current water
by freshwater. The progression along the line is orderly. The

v'8.

S 0/SALINITY

ANADYR CURRENT

BERING SLOPE CURRENT

GULF OF ANADYR

•• SIBERIAN

COASTAL WATER

ALASKAN COASTAL
O

31 32 33 34

BOTTOM WATER SALINITY. 7oo

Fig. 8. Correlation of '"O with salinity. Koriilev cruise, August 1988. All
water masses of the Northern Bering Sea Ecosystem are dilutions to
varying degrees of Bering Slope Current water by freshwater. Gulf of
Anadyr and Siberian Coastal waters are modifications of Bering Shelf
water through salinity enhancement due to freezing. Arrows indicate
direction of water mass modification. Data from Grebmeier. Cooper
& DeNiro, 1990.

precursor water to the whole system from the Bering Slope
Current has both the highest salinities and abundances of
'"O: S ~ 33 to 33.2, '"O - -1.5. These values are, of course,
already slightly diluted from SMOW. In the ecosystem, the
first step in dilution is observed in the Anadyr Current, because
the current mixes to some extent with runoff (particularly the
Anadyr River) in its transit around the Gulf of Anadyr. |In
Fig. 8, the pathways of water mass modification are indicated
by arrows.] Furtherdilution of AnadyrCurrent water produces
the Bering Shelf water inass, ubiquitous to the whole northern
shelf. Not all AnadyrCurrent water transits Anadyr Strait, but
some is detlected to the south of St. Lawrence Island, where it
meets and mixes with fresher waters from the Alaskan side of
the system, forming this water mass with slightly reduced
salinities and '"O. Samples from the Alaskan Coastal water

mass show much greater and more variable dilutions because
of proximity to the high runoff along the eastern side of the
system. They also do not follow the dilution curve as closely
because selected areas are subject to strong local freezing and
brine rejection, for example within Norton Sound ( see Muench
et ill.. 1981 ). The value at -3.3/31.5 is a good case in point.

The two secondary water masses of the system. Gulf of
Anadyr and Siberian Coastal, are both created from Bering
Shelf water through salinity enhancement by freezing. The
polynya south of St. Lawrence Island, as discussed , is the focal
point for the salinity enhancement which turns Bering Shelf
water into Gulf of Anadyr water ; the overwinter freezing
increases salinities by about 0.5 but without changing "O.

The Siberian Coastal water mass is apparently created in
the same way. Bering Shelf water travels throughout the
system, well north into the Chukchi Sea, without appreciable
change in S. The whole system evidences very little lateral
diffusion and exchange between water masses, and the Bering
Shelf water, sandwiched in the middle, is effectively isolated
from runoff and hence dilution from both Alaska and Siberia.
In the Chukchi, vigorous freezing in certain areas in winter
causes substantial increases in S values without modifying '*0,
and this water is recirculated the following year as part of the
Siberian Coastal Current (see discussion below).

Flow Field

The Anadyr Current, the branch of the Bering Slope
Current that enters the Gulf of Anadyr near Cape Navarin and
continuously supplies the nutrients to fuel the ecosystem, is a
topographic boundary current of the eastern Bering Sea Shelf;
it is also, coincidentally, located along the western boundary of
the shelf. This was convincingly demonstrated by Kinder e/ al.
( 1986) who employed both laboratory models and numerical
simulations, achieving results in very close agreement with
what we know of the Anadyr Current.

The basic driving force is the sink for Bering Sea water
imposed by the northward flow through Bering Strait — that is,
the pressure head created by a -0.5 m height difference
between the Bering Sea and the Arctic Ocean (Stigebrandt,
1984). Thus, Bering Sea water must move northward across a
shoaling topography. In this situation, the topographic gradient,
f / h ~ 5 X 10 '' cm ' s ', is more than an order greater than the
variation of Coriolis parameter, (3 ~ 1 x 10" cm' s '. The
across-shelf flow is concentrated as a current along the lefthand
boundary facing upslope (Fig. 9). Notice in the simulations
that regardless of whether or not flow conditions are imposed
along the Bering Sea slope, the cross-shelf flow still forms the
same western boundary current on the shelL The numerical
simulations indicated a current width of 50 km and speeds of
10-20 cm s ', both in excellent agreement with available data
on the real current. Of course, within the Gulf of Anadyr, the
flow, being strongly steered along isobaths, actually circulates
clockwise around the gulf (cf. Fig. 1 ).

Variability in flow of the Anadyr current is unknown. It
seems probable, however, that it is a much steadier flow than
those through Anadyr and Bering Straits. The large variability
in the latter flows, predominantly at periods of a day to a week.

21

NUMERICAL SIMULATIONS OF BERING SHELF CIRCULATION

BRING
3 I — -y S IMIT ALASI<A y=100 km

TOPOGRAPHY

NO IMPOSED
CURRENT

Fig. 9. Numerical simulations of a rectangular Bering Sea Shelf, showing the
Anadyr Current to be a boundry current of concentrated flow resulting
from northward flow across the shoaling shelf; the current is
concentrated on the left looking up-slopc. From Kinder, Chapman &
Whitehead, 1986.

is produced by wind effects driving water against the shoreline
boundaries adjacent to the straits and thereby altering the
pressure head through them (Aagaard et ai. 1985; Coachman
& Aagaard, 1988). The Anadyr Current is much less constrained
by boundaries (also true of the downstream Chukchi Sea
portion of the ecosystem). It also seems unlikely that the large-
scale driving force due to the difference in sea levels changes
sufficiently in magnitude or rapidly enough to cause variations
like those observed in the Chirikov basin; in particular, it is
unlikely the Anadyr Current ever ceases or reverses. This is of
crucial importance to the ecosystem — it guarantees a relatively
steady, continuous, and large supply of nutrients. Furthermore,
the residence times of water parcels within the gulf, which is the
site of the first production center (cf. Fig. 3), are likely to be
much less variable than they are in the Chirikov basin; at 1 5 to
20 cm s ', water parcels will transit the gulf in about 1 month.
In contrast with the Gulf of Anadyr and Chukchi Sea, the
middle active production center of the ecosystem — the Chirikov
basin — has restrictive physical boundary conditions on its flow
field. Two straits restrict inflow of water from the south,
Shpanberg to the east of St. Lawrence and Anadyr to the west,
and there is only one outlet, Bering Strait. From the Gulf of
Anadyr, most of the Anadyr Current most of the time flows
northward through Anadyr Strait into the Chirikov basin. It is
joined by a transport of the less saline Bering Shelf water from
south of St. Lawrence Island. Bering Shelf water enters the
basin also around the eastern end of St. Lawrence through
Shpanberg Strait, while the eastern part of this strait usually

carries Alaskan Coastal water from the south; the latter water
mass forms a bouyancy boundary current along the entire
Alaskan coast. All these waters pass northward out of the
Chirikov basin through Bering Strait. Crossing Chirikov basin,
the three water masses tend to remain discretely side-by-side;
there is little lateral mixing between them (Coachman et ah
1975). The production center is in the center and western part
of the basin, associated with Anadyr and Bering Shelf water
masses, not Alaskan Coastal.

The northward flow is constricted passing through the
straits, which has important physical consequences for
ecosystem production. In transiting the straits, the currents
increase speed and greater amounts of bottom-friction-generated
turbulent energy becomes available for mixing the water
columns. Any stratification that has developed upstream from
the straits is largely broken down, and materials (in particular
nutrients) that have collected in the lower layer are redistributed
into the upper layer.

A south-to-north section through Anadyr Strait from a
3-dimensional nonlinear dynamical model (Deleersnijder &
Nihoul, 1988) shows these effects graphically (Fig. 10).
Immediately north of Anadyr Strait, there are high amounts of
turbulent kinetic energy in the upper 20 m (Fig. IOC) and
upwelling velocities as great as 5 X 10'cms'(Fig. lOA); these
together have nearly broken down strong thermal stratification
existing south of the strait (Fig. lOB). The result is a large
plume of colder, nutrient-rich water spreading from Anadyr
Strait northward along the Siberian shore and eastward across
the Chirikov basin, frequently visible in satellite imagery
(Nihoul et ai, 1990). The effect is registered in hydrographic
dataas much reduced vertical stratification; compare the plume
of small lower-upper layer salinity differences in Fig. 7.
Notice also a similar plume extending northward from Bering
Strait.

The ecological importance of the enhanced vertical mixing
in Anadyr Strait and. subsequently, in Bering Strait is enormous;
it effectively "resets" the system downstream from areas of
large production so that another production cycle can occur.
Production takes place in the waters transiting the Gulf of
Anadyr and some stratification develops from Anadyr runoff.
Nutrients become depleted in the upper layer. The "resetting"
feature mixes nutrients back into the upper layer where they
can fuel another round of high production. The Chirikov basin
production, and layering in its northern part due to Alaskan
Coastal water in the tunneling flow field (cf. Fig. 7), create a
similar situation just south of Bering Strait. These conditions
are "reset" by the Bering Strait flow leading to large production
in the southeastern Chukchi (Fig. 3).

In the tightly bounded Chirikov basin another aspect of the
flow field is important. The in- and outflows through the
bounding straits are not one hundred percent correlated; there
are periods ranging from days to weeks when the in-flow via
Anadyr and Shpanberg Straits does not equal the outflow
through Bering Strait. During these times water volume in the
basin is not conserved, which is compensated by either a rise or
fall in sea level (cf. Aagaard et ai, 1985); changes in sea level
at Nome as great as 1 m in a couple of days have been observed.

22

ANADYR STRAIT
i

ANADYR STRAIT
i

ANADYR STRAIT
i

Fig. 10. North-south section through Anadyr Strait from a .Vd numerical model ( Deleersniider& Nihoul, 1 988) showing (A) vertical velocities upward just north
of the strait; (B) breakdown of stratification just north of the strait; and (C I high concentrations of turbulent kinetic energy just north of the strait. The.se
result from physical constriction of the flow by the topography, and mix the water columns vertically, "resetting" the ecosystem.

The import to the ecosystem of nonconservative transport
through Chirikov basin is a large variation in residence times
of water parcels in the basin. This variability affects not so
much the production but the proportion of production exported
versus the proportion sequestered in the basin as sediments.

During the ISHTAR field programs, between six and ten
moorings with current meters were deployed each year in the
Chirikov basin. From these records, residence times of water
parcels entering the basin through Anadyr and Shpanberg
Straits were estimated. The data from each meter were
considered to be representative of water in an area surrounding
the mooring location extending halfway to adjacent meters.
Mean daily excursions of water parcels were calculated and
plotted sequentially, using the current data from the closest
meter. The residence time is the number of days elapsing
between the entrance of a water parcel through Anadyr Strait
until its exit through Bering Strait.

Reconstructed water parcel trajectories representative of
various length residence times are shown in Fig. 1 1 . The most
typical residence times in summer are about two weeks, when
the flow is steadily northward with little variation. Under these
flow conditions, water parcels take a relatively direct route
from Anadyr into the center of the basin, then veer left and
move directly to Bering Strait. The trajectories of minimum
residence times are much the same — nearly a direct path
between Anadyr and Bering Straits — and occur when the
current speeds in both straits are exceptionally strong. Medium
duration residences of three to four weeks occur when currents
in the straits are still generally northward, but much slower,
particularly in Bering Strait. During these times, the water
entering through Anadyr floods eastward across the basin. The
longest residence times are when flow actually reverses in the
system; water parcels spend time describing gyres in the basin
interior.

The residence times of water parcels in summer has been
quite different over the four years of intensive study. The times
for water entering through Anadyr Strait, beginning in eariy
July each year 1985-1988, estimated for alternate days, are
graphed in Fig. 1 2. The times are plotted according to the day
the water entered the basin. The measured residence times vary
by more than a factor of 5, from a very rapid transit of 9 days
(mean speed -34 cm/s) to more than 50 days. The variability

60°

174°

Fig. 11.

RECONSTRUCTED WATER PARCEL TRACKS

172°

168°

166°

Reconstructed trajectories of Anadyr Current water parceLs,
illustrating different residence times. Coding: above is residence
time in days; below is (year: Julian day of ingress through Anadyr
Strait ). Note that with longer residence times water parcel excursions
extend farther east; very long residence times involve gyre trajectories
associated with tlow reversals in the svstem.

23

is both seasonal and interannual. Early in the summer each year
water transits the basin most rapidly, typical residence times
being about two weeks. In 1985, this condition maintained
until almost the end of August, in 1987 until the middle of
August, and in 1988 the beginning of the month. Nineteen
eighty-six was different; beginning the second week in July,
residence times increased to about one month and remained so
over the summer.

RESIDENCE TIMES OF ANADYR WATER IN THE CHIRIKOV BASIN

(PLOTTED BT OflV OF INGRESS THROUGH ONADTR STRAlTl

^1988

ol I J . . . I

I 1 1

, I .... I .... I .

, I . . . . I . . .

90 195 200 205 210 215 220 225 2iO 235 240 245

JULIAN OAy

r T T

ILV e AUG 1 SEPT 1

Fig. 12. Residencetimesof Anadyr Currenl water in iheChirikov basin for the
lour yeans of ISHTAR study. Times are plotted by day of ingress
through Anadyr Strait. Notice typical residence times in summer are
about 2-weeks through July, then a switch to much longer times
somctiine during August. Nineteen eighty-si.\ was different, with
residence times of 3 to 4 weeks over the summer.

The residence times are closely related to the wind regime
and its variations. Over most of the year, the strength of north
flow through the system, and variations in this flow (e.g., from
north to south), are well correlated with the local winds; for
example, Bering Strait north transport and the north-south
wind component correlation is r > 0.7. In early summer each
year, though, the correlation breaks down. Regional winds
become light, without strong variations, the flow becomes
decoupled from the wind, and the currents are stronger and
directed more steadily to the north (Coachman & Aagaard,
1988). These are the conditions for short residence times, and
were observed to obtain at the beginning of July each year.

Over the remainder of the year, winds are both stronger
and more variable, and the flow is driven into variations that are
reasonably correlated with those of the wind. Thus the periods
of slow and reversed (southward) How become more frequent,
and residence times become markedly longer. This changeover
from "summer" to normal wind regime occured at different
timesbetween the beginning and end of August in 1985, 1987,
and 1988. Nineteen eighty-six, however, was anomolous; the
typical "suinmer" flow condition, decoupled from the wind,
never really developed. The resulting longer residence times
over the production season were undoubtedly responsible for
the greater accumulation of biomass in the Chirikov than in the
southeastern Chukchi basin in 1986, as opposed to more
"normal" years when more accuinulates in the Chukchi ( Walsh
£'/«/., 1989).

To provide more insight as to specific wind conditions
causing longer residence times. Fig. 13 was prepared. First, the
north-south component of wind at Bering Strait was examined
by itself, but no relationship with residence tiines was apparent.
The forces driving the flow field variations are obviously more
complex than just the local wind in Bering Strait. So the wind
at Anadyr Strait was added, and a qualitative picture emerges.
A primary condition for long residence times seems to be a
sustained trend of change in the winds to northerlies
(i.e., directed to the south) combined with a sustained, strong
divergence of the wind field over the Chirikov basin. The
divergence is where the winds at Anadyr are either less strong
to the north, or stronger to the south, than those at Bering Strait.
Under these conditions, the normal sea surface slope down to
the north is negated and readily reversed. Without a "push"
from the south, water parcels can hang around in the Chirikov
basin for very long times (as long as two months).

Fig. 13. North-south component of winds at Bermg Strait and Anadyr Strait
over the summers of 1985-87 (data smoothed with S-point runnning
means). Long residence times seem to be associated with changes
toward strong south-directed winds and a sustained, strong divergence
of the wind field over the Chirikov basin (hachured).

Chukchi Sea

The third, downstream production center of the northern
Bering Sea ecosystem is in the Chukchi Sea. ISHTAR has
studied the southeast comer of the region. Southwest from
Pt. Hope lies a production center where huge chlorophyll
biomass has been measured (cf. Fig. 3) and also some of the

24

highest values of prhiiary productivity ever measured in the
World Ocean. Fuel for this production center is provided by
Bering Shelf water. The water mass transits Bering Strait
(where it becomes combined with the Anadyr Current water
mass; see Coachman et al.. 1975) and circulates
counterclockwise around Kotzebue Sound following the
bathymetry (cf. Fig. 1). It still contains, in spite of high
utilization upstream, considerable nutrients (e.g., -10 |i g-at
NO,/l).

The cruise of the Akademik Korolev expanded the studies
to the west as far as Kolyuchin Bay. The most important
finding was another center of production in addition to that
southwest of Pt. Hope (Fig. 14), which was associated with an
entirely different water mass. The maximum observed salinity
of Bering Shelf/ Anadyr Current water in 1 988 was <33, while
the salinities of the water of the center off Kolyuchin were up
to 33.6 (Fig. 14. lower). At this time the Siberian Coastal
Current did not extend all the way to Bering Strait, as
demonstrated in the salinity distribution (Fig. 14, lower). The
values >32. 9 stopped about 1 00 km short ofthe strait; apparently
the current turns east and northeast, closing a gyre with the
Bering Shelf water flow to the northwest, southwest of
Pt. Hope (cf. Fig. 2). There are times, however, when the
Siberian Coastal Current does reach to Bering Strait; Ratmanov
(1937b) documented penetration of Siberian Coastal water
into the strait in 1933.

Fig. 14. Average chloroptiyll biomass (upper) and maximum S in the water
column (lower) in the southeastern Chukchi Sea, Korolev data,
August 1988. Note high chlorophyll off Kotyuchin Bay in addition
to the center southwest of Pt. Hope, associated with water with higher
salinity than any entering through Bering Strait.

Thus, the full extent ofthe production area ofthe northern
Bering Sea ecosystem in the Chukchi Sea is unknown. It is
clearly much larger than previously envisioned. It is fueled by
two different water masses — the Bering Shelf water from the
south entering directly through Bering Strait, and a Siberian

Coastal water associated with the Siberian Coastal Current.
Prime questions are the source and extent ofthe latter. Few data
are available to help search for the source; the best are from the
cruise of the USCGC Norihwliul in 1963 (US Coast Guard
Oceanographic Unit, 1965). Figure 15 plots the salinities
(upper) and nitrates (lower), averaged for the water columns
>20 ni, from these data for the Chukchi Sea and Long Strait.
The distributions in August 1963 appear to be the saine as in
1988. A water mass with salinities greater than any coming
into the system from the south follow the Siberian coast. There
is a focal point for this water near Wrangel Island; T/S analysis
( Fig. 16) shows the water mass is not extant in the East-Siberian
Sea to the west, but in fact shows the highest salinities at the
stations in Long Strait, close to Wrangel Island. High nutrient
concentrations are associated with this water; it is obviously
this water that is responsible for the second region of production
in the Chukchi Sea part ofthe ecosystem. The apparent source
of this water in the vicinity of Wrangel Island is confirmed by
sketchy data from three other cruises (Fig. 17): the Maud in
1922 (Sverdrup, 1929), Northwind in 1962 (US Coast Guard
Oceanographic Unit, \%A).imdOshoru Maru'm 1972 (Faculty
of Fisheries, 1974). It appears that the whole area east of
Wrangel Island shows evidence of this high salinity water
mass.

MAXlMUf^ S in water column
NORTHWIND 8-16 AUG 1963

180°

175°

170°

Fig. LS. Maximum S (upper) and nitrate concentration (lower) from the
Nonhwiiid. August 1963. The high S water has high nitrates, and
seems to he coming from the vicinity of Wrangel Island.

25

CHUKCHI SEA

NORTHWIND 8-16 AUG 1963

Where does this water come from? One possibiUty
hypothesized initially was that the source of the water mass
may be the pycnochne layer of the Arctic Ocean. The focal
areaeast of Wrangel Island is the head of the Herald Submarine
Canyon, which indents the Chukchi Shelf near Herald Island
(see Fig. 1). The concept was that Arctic Ocean water might
flow in-canyon along the bottom onto the shelf, as it does in
Barrow Canyon on the eastern side of the Chukchi (Mountain
et al., 1976). This hypothesis can be ruled out because the
phosphate content of the Siberian Coastal water mass is much
too low to be Arctic Ocean water.

The most likely hypothesis is that the water mass is of
Bering Sea origin. It is Bering Shelf water that enters the
Chukchi Sea during fall and winter, where its salinities are
enhanced through ice formation. Then the following summer
the water is recirculated throughout the southern Chukchi Sea
via the Siberian Coastal Current. Two observations in support
of this hypothesis are: 7. the '"O values of the water are
precisely those of Bering Shelf water (Fig. 8); and2. the focal
point of highest salinities east of Wrangel Island is an area
where the least amount of ice formation in winter is required to
enhance salinities to the requisite -33.5 (Fig. 18).

Fig. 16. T/S correlations for the Mir//iu(>(i/data. Individual lines are all stations
in the Chukchi Sea; stations from Bering Strait and the East-Siberian
Sea are enclosed in envelopes. Stations from Long Strait ( marked, see
Fig. \5) have the highest S values of all.

13V -SO'

Fig. 1 8. The amount of ice growth required to raise the salinity of water columns
to 3.^.5 "/(x) . Notice the area of minimum necessary ice growth
coincides with the area of highest salinities near Wrangel Island and
Herald Shoal (from Aagaard, Coachman & Carmack, 1981 ).

Fig. 17. Confirmation that the source of high salinity (and high nutrient) water
is near Wrangel Island and Herald Shoal to its east side. Data from
three cruises: (upper) Miiiid. 1922; (lower lelll Nurllmiiid. 1962;
(lower right) Osharn Maru, 1972.

With this hypothesis, the relatively high nutrient
concentrations are supplied by the rich Bering Shelf water in
winter that are not utilized or affected by freezing, so are
available to fuel the Chukchi Sea end of the ecosystem the next
summer. The circulation, insofar as it is known (Fig. 19). fits
in with this hypothesis, though there must be more southerly
components of flow in the western Chukchi, southwest of
Herald Shoal, than indicated in the schematic depiction. The
presence of the highest salinities near Herald Shoal, and
particularly to its west and southwest, is not coincidence; the
shoal water is undoubtably important in providing the most
effective environment for salinity enhancement by freezing.

26

178" 176" 174*' I72« 170" 168" 166" 164" 162" 160" 158" 156"

^ — - VARIABLE
— • — • "CORES" (vonoua posi

ifions) / V

178" 176° 174° 172° 170° 168° 166° 164° 162° 160° 158° 156°

Fig. 19. A best guess of the circulation in the Chukchi Sea (from Coachman,
Aagaard & Tripp, 1975). Notice that Herald Island and Shoal are in
the main pathway of Bering Shell water. However, there actually must
be more movement of water toward the Siberian Coast near Wrangel
Island than suggested in this schematic.

L'envoi

We have summarized the important physical oceanographic
factors of the northern Bering Sea ecosystem. A unique set of
features combine to make it one of the World Ocean's largest
and most productive ecosystems. The key feature is advection
of waterfrom a rich pool of nutrients (the Bering Sea Continental
Shelf edge), across an enormous distance in shallow water.
The nutrient supply continuously injected by the current is
sufficient that they never become depleted and limiting, even

with high production. There are two constrictions in the
advective stream, dividing the system into three basins and
three production centers. These are spaced such that the transit
time of water across each basin, two to four weeks, is the same
as a complete biological production-utilization-regeneration
cycle. Turbulent energy injected into the water columns at the
constrictions stirs them, "resetting" the system for the next
round of production.

The advection is driven northward from the Bering Sea
into the Arctic Ocean by a sea surt'ace slope (the Arctic Ocean
stands lower than the Bering). But there are important variations
in the transport related to the local winds, which drive water
against the land boundaries modifying the surface slope. Primary
variations are over a few days (storm time scale), and as these
are greatest and most frequent in winter, there is a seasonal
cycle of lower net north transport in winter and greater in
summer. Interannual variations are also significant. They
affect mostly the geographically constricted Chirikov basin;
here water parcel transit (residence) times can differ by a factor
of five. The variability seems to have only a small influence on
the actual amount of primary production in the ecosystem;
rather, its importance lies in varying the amount of production
that becomes deposited in the centers versus the amount that is
transported through into the Arctic Ocean.

The downstream (Chukchi Sea) end of the ecosystem is
virtually unknown. Nutrients supporting very large production
are supplied to this center by Bering Shelf water entering
directly via Bering Strait and from a second source presumed
to be Bering Shelf water enhanced in salt content through
freezing during the previous winter and recirculated via the
Siberian Coastal Current. But this is hypothesis; the circulation
of the Chukchi is not known, nor the amount and extent of
production, nor the amount of carbon that is exported to the
Arctic Ocean. Considering the possible significant role of
Chukchi Sea carbon export in global carbon budgets and
climate warming (Walsh el cil.. 1989), further study of the
Chukchi Sea end of the northern Bering Sea ecosystem has a
very high priority.

2.2 Water Mass Modification from the Bering
into the Chukchi Sea

ANTHONY F. AMOS' and LAWRENCE K. COACHMAN*

'Marine Science Institute. University of Texas. Port Aransas. USA
' School of Oceanography. University of Washington. Seattle. USA

Introduction

The only Northern Hemisphere connection between the
Pacific and Atlantic Oceans is across the shallow waters of the
northern Bering and Chukchi Seas connected by the Bering

Strait. The seminal work on the oceanography of the northern
Bering Sea (Barnes & Thompson, 1938) led to further
investigations on this important region that continue to this
day. Coachman et al. (1975) reviewed the regional physical
oceanography in the most comprehensive work on the Bering

27

Strait region to date. Studies since tiien. notably the Inner siielf
Transfer and Recycling (ISHTAR) program iiave expanded
our understanding of the regional oceanography yet further
(Coachman, 1986: Walsh ^/ a/., 1989).

Complete, integrated studies of the region have been
restricted by its strategic significance, national boundaries, and
Exclusive Economic Zones. The Third Joint US-USSR Bering
& Chukchi Seas Expedition on the Soviet research vessel
Akademik Korolev (Korolev) in the summer of 1988 (AK-47)
afforded an opportunity for US and Soviet scientists to study
the oceanography of the northern Bering/Chukchi Seas without
limitations imposed by territorial boundaries. The cruise took
place from 26 July to 2 September 1 988 and occupied 1 02 CTD
stations in the Gulf of Anadyr, Chirikov basin, and southern
Chukchi Sea (see Frontispiece). (An additional 1 1 stations
were occupied near the Aleutian Islands and in deep parts of the
Bering Sea, but are not discussed here.)

There are three primary water masses in the northern
Bering Sea, and the basis for their identification is salinity
(Coachman et ai, 1975). The most saline is water from the
continental slope of the eastern Bering Sea Shelf edge, which
enters the region via the Gulf of Anadyr and Anadyr Strait to
the west of St. Lawrence Island. This is the most important
water source to the extremely productive northern
Bering/Chukchi Sea ecosystem because of its high nutrient
loading. The least saline water lies in the east, the Alaskan
Coastal water, which flows parallel to the Alaskan coast
northward through Shpanberg Strait to the east of St. Lawrence
Island. The water mass of intermediate salinity, which is also
the coldest, is Bering Shelf water in residence over the extensive
shelf area south of St. Lawrence Island. It is advected northward
around both ends of St. Lawrence, through both Anadyr and
Shpanberg Straits, and northward between the other two; part
of the water mass modification occuring in the system is com-
mingling of these three water masses as they are advected
northward.

Salinity valuesof the water masses are not only space, but
time-variable, as much as 0.5 ppt seasonally and interannually.
Thus, in the absence of quasi-synoptic data from the whole
system, the precise changes of water mass properties as they
transit the various basins and straits have never been observed.
As the Korolev data provide the first-ever quasi-synoptic
picture of the regional water masses, this paper describes their
modification as they are advected north from the shelf break of
the Bering Sea through the Gulf of Anadyr, Chirikov basin, and
the southern Chukchi Sea.

Methods

Conductivity-temperature-depth (CTD) casts were made
surface-to-bottom using a Sea-Bird Electronics model SBE-9
system with a General Oceanics RMS 1 2 rosette water sampler.
The rosette held 1 2, 2.5-liter "GO-FLO" water sampling bottles.
These provided water samples for many other projects as well
as samples for salinity analysis to compare with the CTD
values. The salinity measurements were made usinga Beckman
RS7-C laboratory salinometer.

The Sea-Bird was delivered new, just two weeks before
AK-47 began. It has a rated accuracy of 0.004°C/year over the
range -5 to H-35°C, 0.0003 S/m/month over the range to
7 S/m, and 0.02% of full scale over the depth range 0-3,500 m.
The instrument was calibrated by the US Northwest Calibration
Center in Seattle before and immediately following the Korolev
cruise, with nearly no changes in output. Later, the same CTD
was used in the Antarctic, where salinities from some
1 ,000 points were compared with samples run on AGE and
Guildline salinometers — differences were less than 0.01 ppt.
Subsequent calibrations have shown this instrument to be very
stable and its accuracy is well within the tolerances acceptable
for modem physical oceanographic research.

Methods of CTD deployment and data reduction are
pertinent to data quality, so they are outlined briefly. The CTD
operator prepared the rosette and set up the computer about
15 min before each station. On station, the instrument was
lowered to the sea surface (or up to 5 m below surface,
depending on sea state) and held while the program to record
data was started. It was then lowered at a rate between 1 5 and
30 m/min until it was about 5 m above the sea floor. When the
instrument's attitude in the water column was seen to be stable,
it was then lowered another 2 or 3 m. The computer was then
reset for the uptrace, and the rosette bottles were tripped at
predetermined depths on the upcast.

Data is acquired by the Sea-Bird at a rate of 24 scans of
pressure, temperature, and conductivity per second. For
AK-47, scans were averaged in groups of six, giving four data
groups per second to be recorded. At a drop rate of 30 m/min,
CTD values were thus acquired approximately every 0. 1 25 m.
The data are averaged internally, digitized, and transmitted to
the ship via the center conductor in the sea cable through winch
slip rings into the deck laboratory. The deck unit (Sea-Bird
model 1 1) converts the data to computer-compatible signals,
which are fed into a Packard-Bell AT-type computer via an
IEEE 488 (GPIB) bus.

Using Sea-Bird supplied software, the CTD data were
displayed on the CRT monitor in real time as X-Y plots as the
instrument was being lowered. As the rosette bottles were
tripped on the upcast, the usual problems in calibrating the
CTD conductivity sensor were encountered. Because of water
disturbance on the upcast by the rosette and CTD housings,
salinity readings by the CTD are suspect. Thus, comparison of
salinity samples with the CTD output does not necessarily give
valid in situ calibration data. Also, comparison with downcast
values in shallow, highly variable shelf waters is likewise
suspect. Nevertheless, at least two samples from each station
were collected for checking the CTD calibration. An ancient
Beckman salinometer was used to run these salinities, which
presented problems with drift. In spite of all the difficulties,
the results show /. consistency in Sea-Bird CTD
output station-to-station; 2. close agreement with SEACAT
data when the two instruments were run together; and 3. close
agreement between CTD values and laboratory
determinations, providing confidence in the accuracy of the
data from AK-47.

28

Raw CTD data were recorded on the computer' s hard disk
drive and archived on Iomega Bernoulli 20- Megabyte removable
disk cartridges. One-meter average values for each station
were created using Sea-Bird supplied software. A data report
gives standard-level listings for all CTD data from the cruise
(Amos. 1990).

Results

water depths in the Gulf of Anadyr are less than 1 50 m, and
mostly less than 100 m. In the Chirikov basin and southern
Chukchi Sea, water depths are even less — almost everywhere
30 m or less. The north-south size of this shallow shelf sea is
enormous, subtending about 1,200 km from the shelfbreak in
the northern Bering Sea to the shelfbreak in the Arctic Ocean.
In this shelf sea, diverse water properties are encountered.
Based on AK-47 data, in summer temperatures range from
nearly 12°C at the surface near the Alaskan coast in the
Chirikov basin, to -1.6°C at the bottom in the central Anadyr
Gulf, southwest of St. Lawrence. Salinities range from 24 ppt
at the surface near the Chukchi coast off Kolyuchin Bay to
33.6 ppt at the bottom in the same location (Station 45).

A T/S diagram of all stations from AK-47 is shown in
Fig. 1 . Surface values of each station are marked by "T" and
bottom values by "B." and the dots are 1-m average values.
This diagram includes not only the shelf stations but the 1 1
stations taken in the deep Bering Sea. These latter form a tight
grouping: surface values are all >32 ppt up to about 33.4 ppt;
there is a temperature minimum in the S band 33.2-33.4
(forming a marked ""V" shape in the diagram); deeper, there is
a temperature maximum of 3.6<T<4.0°C, and below this, the
bottom values merge to a water type ~ 1 .8°C. 34.6 ppt.

us/USSR BERING ' BB

ALL STATIONS (in Fig 1)

a.

D

I-
<

cr

LU

a
z

LU

26 2B 30

SALINITY (ppt)

32

34

36

Fig. I . Temperature-salinity diagram of all Korolev stations, from the shallow
northern region (Frontispiece) and 1 1 stations from the deep Bering Sea
basin. Bats are 1-m average values; for each station the surface value
is marked by a "T" and deepest value by a "B".

The T/S values from shelf stations are massed, with few
exceptions almost all associated with surface layer values, in
the salinity range 31-33 ppt. There is one group with bottom
water temperatures <0"^C and another concentration of data
points between -0.5 and 3°C. Surface T's are spread mostly
between 3 and 10°C. There is a further scattering of surface
values, with T's >4°C, toward low salinities. A few stations
with bottom water temperatures ~()°C and S's >33 ppt deviate
from the mass of points. It has long been known that the main
flow in the northern Bering Sea is northward through Bering
Strait into the Arctic Ocean. Coachman and Shigaev (Subchapter
2.1, this volume) trace a primary pathway of this flow. Water
from the Bering Slope Current, which tlows northwestward
along the continental shelf edge of the eastern Bering Sea Shelf
( Kinder t'/ «/.. 1975), crosses the continental shelf southwest of
St. Lawrence Island in the Gulf of Anadyr. The How maintains
itselfas a current (transport -0.5 to 1 Sv) circumnavigating the
gulf because its dynamics are analogous with tho.se of a western
boundary current (Kinder et ciL. 1986). From the Strait of
Anadyr, the flow follows the western side of Chirikov basin,
transits Bering Strait, then curves northeastward into Kotzebue
Sound before being steered by the topography to the north and
west.

The second main regional flow is that of coastal water on
the east, entering through Shpanberg Strait east of St. Lawrence
and hugging the Alaskan coast northward through Bering
Strait, around Kotzebue Sound, and then northwest passed
Pt. Hope and Cape Lisburne. Between these flows is advected
a third water mass of shelf water; because this water mass is
made on the large Bering Sea Shelf south of St. Lawrence
through mixing of dilute coastal water with the more saline
Bering Sea continental slope water, it is identifiable as a
separate water mass by its intermediate values of salinity; it is
also the coldest of the water masses in summer south of Bering
Strait (cf. Coachman etal., 1975).

The Korolev data provide the first quasi-synoptic coverage
of all these water masses within the region, thus allowing
quantitative as.sessment of the changes in temperature and
salinity as they are advected northward from the Bering Sea
into the Chukchi Sea. We now examine the water mass
modifications basin by basin.

GiilfofAiuutyr

All CTD stations from the Gulf of Anadyr, together with
Station 6 from the continental slope south of the gulf, are
plotted in Fig. 2a. The latter is in the Bering Slope Current and
thus shows the characteristics of this source water to the gulf.
It has a water mass curve typical of the current; that is, a
temperature minimum of ~2°C at S ~ 33.2 ppt, forming a "V"
in T/S space, below which is a T maximum (T ~ 3.8°C at
S ~ 33.7 ppt) followed by a T decrease and S increase to the
deep basin bottom water type (T ~ 1.6°C; S ~ 34.7 ppt).

Surface temperatures in the gulf are typically 6 to 8°C at
this time of year, with salinities spread over the range 31.5 to
33 ppt. The spread in values reflects the nonconservative
nature of properties in the upper layer with exchange across the
sea surface, true in particular for temperature.

29

US/USSR BERING
ANADYR

■88

LU
CC
D
I-
<

cr

UJ

d

LU

31 32

SALINITY (ppt)

Fig. 2a. All CTD data (l-m average values) from the Gulf of Anadyr and
Anadyr Strait stations, and Station 6 from the Bering Slope Current.

Localized sources of dilution, the main source of freshwater
being the Anadyr River entering midway along its western
boundary , contribute to the spread in salinity values. Horizontal
mixing of waters of the surface layer is evidently small.

Bottom water values, on the other hand, are bunched much
more tightly and cluster into two groups. One grouping is of
cold water, <0°C, in the salinity range -32 to 32.7 ppt. The
second group is wanner, ~0 to 2°C, and more saline, 32.7 to
33.3 ppt. When the spatial distribution of these stations is
examined (cf . Frontispiece ), we see that the stations of the cold,
lower S group are all from the middle of the gulf, centered
around Stations 1 8 and 1 9, while the stations with warmer and
more saline deep water are from around its perimeter, including
Stations 12. 13 through 25. 26, 29, 31. and 33 to 38.

Temperatures and salinities of the waters beneath the
surface layer are conservative and are modified only through
vertical and horizontal (lateral) mixing as the water masses
transit the gulf. To expose the source water characteristics and
their modifications within the gulf. Fig. 2b plots stations
representative of each key water mass and location. The
extreme of cold, lower salinity water is represented by Stations
18 and 19, from the central gulf. The temperatures are only
about 0.1 to 0.2°C above freezing. This water is that of the
"cold center" of the Bering Sea, identified already by Barnes
and Thompson (1938). The water entering the gulf as the
Anadyr Current is represented by Stations 12 and 13 close tp
Cape Navarin. This water is from the Bering Slope Current
(Station 6), which is the source of highest salinity water to the
gulf; the source level lies in the depth range -50-200 m of the
current. When the water mass enters the gulf off Cape Navarin.
its characteristics are T ~ 1 to 2°C, S - 32.5 to 33 ppt. Thus, its
propeilies have already been significantly modified in the
1 50 km transit across the shelf from the continental slope, not
through surface exchange but through mixing with colder and
less saline shelf water — the deep layers have been cooled - 1 .5
to 2°C and freshened -0.5 ppt.

CL

1-
<

cr

UJ

-1 -

GULF OF ANADYR

CAPE NAVARIN

■18 1 BERING SHELF
19 I COLD CORE CENTER

I I L

32

33

34

SALINITY

Fig. 2b. T/S diagram of key stations from the Gulf of Anadyr; solid arrows
indicate directions of major modifications. Most surface layer values
arc not plotted. Water flowing north through Anadyr Strait is created
from Bering Slope Current water by mi.xing with cold Bering Shelf
water. The interaction is a two-stage process, first lateral layering
(cf Station 29) followed by vertical mixing.

This water mass then circumnavigates the perimeter of the
Gulf of Anadyr following the bathymetric contours and
interacting with water of the "cold center" enroute. The
interaction is in two stages. First is a horizontal layering, or
interleaving, of the less dense "cold center" water laterally
above the denser water from the Bering Slope Current ( now the
Anadyr Current). Station 29, halfway around the gulf, cleariy
illustrates this stage of the interaction. Then vertical mixing
becomes more effective, particulariy as the water masses are
required to shoal to 50 m as they enter Anadyr Strait, and the
result is homogenization into narrow ranges of T and S. When
the water exits the gulf through Anadyr Strait it has essentially
median values of T and S (Stations 39. 40). The two-stage
interaction, layering followed by effective vertical mixing,
conforms precisely with the model of water mass modification
in the gulf proposed by Coachman et al. (1975).

Chirikov basin

All CTD data from the Chirikov basin, including Stations
39^3 from Anadyr Strait and 76-86 from Bering Strait, are
shown in Fig. 3a. There is a concentration of bottom water
values with temperatures -1 to 3°C in the S range 32.2 to
32.9 ppt. From these values, the remainder trend toward

30

US/USSR BERING '88
CHIHIKOV + Anadyr S Bering Straits

tu
cr

D

I-
<

cr

D.

z
tu

10

/- 6

Fig.

30 31 32 33

SALINITY (ppt)

3a. All CTDdala{ 1-m average values) from the Chirikov basin, including
Anadyr and Bering Straits.

warmer and less saline values (to the upper left in the T/S,
plane). Likewise, surface water values lie along the same
general trend line. When the spatial distribution of stations is
examined, we see that the colder, more saline water is associated
with stations from the west side of the basin, while the warmer,
least saline water is all on the eastern side.

The Chirikov basin is a little shoaler on the east side, 30 m
grading downward to nearly 50 m off Siberia. The freshwater
sources to the water masses in the basin are essentially confined
to the eastern side — the Yukon River and other runoff from the
Alaskan coast. The freshwater generates layering in the water
masses of the eastern portion of the basin, and together with the
shorter water columns, seasonal insolation is very effective in
warming, producing temperaures up to 1 2°C in the upper layer
(in contrast with maxima of ~8°C in the Gulf of Anadyr).

The coldest, most saline water is water of the Anadyr
Current entering through the Strait of Anadyr (see above), and
also shelf water from south of St. Lawrence Island (cold,
relatively saline shelf water is probably also entering the basin
around the eastern end of St. Lawrence, through the west side
of Shpanberg Strait, but the A^o/'o/ev data do not cover Shpanberg
Strait).

To illustrate quantitatively the modifications occurring in
the basin. Fig. 3b plots key stations. There is a salinity gradient
of more than one-half ppt across Anadyr Strait. The most saline
water is from the Anadyr Current (Station 39. cf. Fig. 2b). On
the east side (Stations 42, 43), though, the waters are both less
saline and colder — this is shelfwaterfrom south of St. Lawrence
Island, which is originally Bering Slope water that has been in
residence on the huge shelf south of St. Lawrence where it has
become diluted to a small degree by a freshwater admixture
from the Alaskan Coastal water (see Coachman & Shigaev.
Subchapter2.1. this volume) and further modified in winter by
products from freezing activity in the perennial polynya south
of St. Lawrence ( Schumacher el al. . 1983). This is the origin

5-

VBERING STRAIT
(FAST)

179

CHIRIKOV BASIN

UJ 3

cr
z>
I—
<
(r

UJ
Q.

2 2

SOUTHWEST
OF NOME

BERING STRAIT

^(WEST)
76;'

31

32

33

SALINITY

Fig. 3b. T/S diagram of key stations from the Chirikov basin, illustrating the
major water mass modifications therein. No change in salinity of the
water on the western side indicates no lateral mixing; only deeper
temperatures are raised through vertical mi.xing. On the east, small
lateral as well as vertical mixing makes Alaskan Coastal water less
saline, warmer, and a little less dense.

also of the "cold center" water. The flow through the eastern
part of Anadyr Strait is of this shelf water mass, not pure
Anadyr water, giving rise to the cross-strait gradient in salinity.

The three stations across the western channel of Bering
Strait, Stations 76 on the west to 78 near large Diomede Island,
illustrate the characteristics ofthese water masses after transiting
Chirikov basin. The cross-strait salinity gradient is precisely
the same as in Anadyr Strait, only the waters have wanned —
minimum temperatures are now about 1.5°C instead of <0°C.
We can interpret that modification of the water masses flowing
northward through the middle and western part of the basin
includes no significant lateral mixing — there is no evidence of
any interaction between adjacent water masses within the flow,
nor any reduction in salinities by admixtures of Siberian
Coastal runoff on the west or fresher Alaskan Coastal water on
the east. The only significant mixing is vertically in the water
columns, which by mixing down warmer surface water has
raised bottom temperatures by ~\°C.

Alaskan Coastal water on the east side of the basin, not as
well covered by Korolev data, is illustrated by Station 102
taken about halfway between Nome and St. Lawrence Island
(see Fig. 1 ). This water is the warmest and least saline of the
water masses, and the closer to the Alaskan coast, the warmer

31

US/USSR BERING '88
CHUKCHI/BERING STRAI"

CHUKCHI

10

/- 5

30 31 32

SALINITY (ppt)

Fig. 4a. All CTDdata(l-m average values) from Bering Strait and southern
Chukchi Sea.

and fresher it becomes; this accounts for the trend of data points
in Fig. 4a from about 3°C. 32 ppt. toward 12°C, 30 ppt. The
flow is northward parallehng the coast, then through the
eastern channel of Bering Strait, where its characteristics are
illustrated by Station 79. Thus, the modification of the waters
on the eastern side of the basin involves both lateral and vertical
mixing. Salinities are reduced by about 1 ppt in transit through
admixing with fresher waters closer to shore, ultimately of
course due to substantial coastal runoff As temperatures are in
general higher in the shallower waters near shore, the lateral
mixing also gives rise to some warming. Water temperatures
are also increased through vertical mixing, as with the waters
on the western side, and undoubtably the warming is more
effective in the shallower waters of the eastern side. Between
the two effects, T increases are of the order of 3°C. We note that
the mixing processes on the eastern side are diapycnal, leading
to decreases in water densities, which is not true of the
modifications in the west. The reason for this is the difference
in effects of salinity and temperature on density, salinity is
much more important in "controlling"" density in cold water
(cf slopes of isopycnals in Fig. 2b).

Chukchi Sea

All CTD data from the Chukchi Sea are plotted in Fig. 4a.
Similarly to the Chirikov basin, there is a concentration of
bottom values in the salinity range -32.2 to 32.9 ppt, but the
temperatures of this water are slightly warmer than to the south,
ranging from ~ 1 .5 to 4°C. From this concentration, data points
extend in two directions. One trend is toward warmer and
fresher, toward ~10°C and 30 ppt, much like the trend in the
Chirikov basin data (cf. Fig. 3a). These data are from the water
masses that have entered the Chukchi Sea from the south,
through the Bering Strait; salinities have not been modified
appreciably since transiting Bering Strait, but the small warming
indicates that heat continues to be added to the bottom water
through vertical mixing.

WEST OF PT HOPE
49\-\48

SALINITY

Fig. 4b. As with Figs. 2b, .^b, but illustrating the major water mass modifications
occurring in the southern Chukchi Sea. The later and vertical mixing
processes found in the eastern part of the Chirikov basin continue to
modify the water masses How ing northward through Kotzebue Sound
and passed Pt.Hope. A colder, more saline water mass indigenous to
the Chukchi Sea is advected southeast by the Siberian Coastal
Current, then circulates cyclonically and mixes with the water flowing
north through Bering Strait.

The other trend is toward a colder and more saline water
type, -33.5 ppt and 0°C. This is water that appears nowhere
south of the Bering Strait, so must be indigenous to the Chukchi
Sea. The only water south of Bering Strait with S>33 ppt is in
the Gulf of Anadyr and was not observed north of Anadyr
Strait, which positively rules out the northern Bering
Sea as a possible source for this relatively cold, high salinity
water.

Key stations illustrating the water masses in the southern
Chukchi Sea are plotted in Fig. 4b. The current flowing
northward through Bering Strait trends eastward into Kotzebue
Sound, then tuins north and west and Hows passed Pt. Hope
into the northern Chukchi Sea (cf. Coachman ct al., 1975,
Chap. 4). The core of flow of this water, that with the highest
salinities, is water transitting the western channel of Bering
Strait (Stations 76-78; cf Fig. 3b). This water is observed west
of Pt. Hope at Stations 48 and 49. The water east of this core
tlow. between it and the Alaska coast (represented west of
Pt. Hope by Station 50), is all less saline and warmer, and
creates the data trend exposed in Fig. 4a. In traversing Kotzebue
Sound (a distance of -350 to 400 km) salinities of the core
water have been reduced a little, about 0.2 to 0.3 ppt, and
bottom temperatures have been increased a further 0.5°C.
Thus, both vertical mixing and a small amount of lateral

32

mixing, as obtained throughout the eastern part ol Chirikov
hasin, eontinues to modify these water masses from the south
as they traverse the southern Chukehi Sea.

The relatively eold. sahne water that is not eoming from
the south is found in the eentrai and western parts of the
southern Chukehi Sea; in the Korolcv data the extreme \ alues
are from Stations 44 and 45, north of Koi\ uehin Bay on the
Siberian Coast (cf. Frontispiece). Current measurements
(Coachman & Shigaev. Subchapter 2. 1 . this \c)lume) indicated
this water was (lowing southeast, parallel with the Siberian
coast, the so-called Siberian Coa,stal Current, This current is
advecting the cold, high S water into the southern Chukehi Sea
from somewhere in the northwest, perhaps near Long Strait
(between Wrangel Island and the mainland). The flow did not,
however, continue southeast as far as Bering Strait; no water
with S>32.9 ppt was observed there.

Thus, the Siberian Coastal Current separates from the
coast before reaching Bering Strait, and curves eastward into
the central part of the southern Chukchi Sea. Waters in the
middle of the region, midway between Alaska and Siberia
(Stations 47, 56). indicate considerable mixing has taken place
between this cold, saline water, and the core water of the
northward flow from Bering Strait that lies around the east and
north sides of the central region. The interaction has reduced
salinities of the Siberian Coastal water in the central region to
~.^3 ppt and warmed the mass by I to 2°C.

We note the situation in August 1988 is undoubtedly the
normal summer tlow pattern; however, under rare conditions it
appears that the Siberian Coastal Current can penetrate farther
southeast, as far as Bering Strait. Ratmanov (1937a) observed
cold, saline water near Cape Dezhneva in summer 1933. but it
was not moving southward through the strait. There is no
evidence that this water ever penetrates into the Chiriko\ basin.

Summary of Modifications

The quantitative changes in temperature and salinity
characteristics of the water masses as observed in August 1 988
are summarized in Table I . The changes are in characteristics
of the water layers below the surface layer, which are
conservative ( i.e., T and S values are altered by the processes

of advection and diffusion only). The surface layer properties
are affected also by surface exchange; in summer they are
warmer and less saline than the deeper waters and much more
variable.

Table I shows, in addition to the approximate T and S
change, the estimated distance over which the change has taken
place and the property value change per km. The latter statistic
gives an idea of the effectiveness of the mixing in that part of
the regime; comments list the major processes acting.

The greatest changes in water mass properties take place
at the beginning, where the Bering Slope Current water crosses
the outer shelf on its way into the Gulf of Anadyr. Layering of
cold, less saline shelf water with warmer, more saline slope
water, followed by vertical mixing, are effective in reducing
S"s andT'sand. ultimately, creating the quite uniform Anadyr
water mass, which is advected on northward through Bering
Strait. The energy for the mixing is from shear in the Anadyr
Current, generated both laterally as the current circumnavigates
the gulf and vertically in the shoaling water columns.

Across the Chirikov basin the major mixing is vertical;
this process is stronger on the east side in the shallower water.
Lateral mixing is small; there is essentially none in the west.
and it is small in the east, leading to small reductions in S of the
coastal water. These same processes continue to modify
Anadyr/Bering Shelf and Alaskan Coastal waters in the southern
Chukchi Sea at about the same rate.

Siberian Coastal water, indigenous to the Chukchi Sea,
enters the southern part of the sea from the northwest, and then
apparently circulates in acyclonic gyre, interacting with Anadyr
water around its east and north sides. The interaction seems
moderately active and analagous with that in the Gulf of
Anadyr; first a layering and interleaving of the water masses
(densities differ by -0.5 st). followed by vertical mixing.

We aeknowledge the helpof Margaret Lavender both in the field
and in data reduction. Captain O. A. Rostovstev and Chief Scientist.
Professor A. V. Tsyban. deserve special thanks, as does all the crew
of the Korotev. Viktor Shigaev was a great help in liaison and
interpretation, and the skill of hydrographic specialists Sergei and
Anatoly was much appreciated. The senior author is indebted to
Dr. R. S. Jones for allowing his participation in the cruise and for use
of the L'TMSl equipment aboard the Konilcv. This is Contribution
No. 777 of the Marine Science Institute. University of Texas.

33

TABLE 1

Water Mass

Property Modifications (Summer).

Change

per km (xK)')

km

AS(ppt) AT(C)

T

S

Comments

Gulf of Anadyr

Bering Slope Cur. to C. Navarin

150

-0.4

-1.5

2.7

10.0

lateral & vertical mix.
with shelf water

C. Navarin to mid-Gulf

250

-0.3

-.05

1.2

2.0

layering; small vertical mixing

mid-Gulf to Str. of Anadyr

250

-0.2

+0.5

0.8

2.0

vertical mixing (homo-

500

-1-0.6

-t-2.0

1.2

4.0

genization)
layering, then vert. mix.

"cold core" Water

in Anadyr curr.

Chirikov basin

Anadyr to Bering Strait

280

0.0

-1-1.5

0.0

5.4

vertical mixing

Alaskan Coastal

180

-0.6

-1-2.5

3.3

14.0

strong vertical mix; lateral
mix. with runoff

Chukchi Sea

Anadyr/Bering Shelf to Pt. Hope

380

-0.2

-^0.5

0.5

1.3

vertical mix.; small lateral
mix. with runoff

Siberian Coastal to mid-basin

220

-0.2

+ 1.5

0.9

6.8

lateral mix. with Anadyr;
vertical mixing

34

Chapter 2 References

Aagaard. K., Coachman, L. K. & Carmack. E. C. ( 198 1 ). On

the halochne of the Arctic Ocean. Deep-Sea Res. 28.

529-545.
Aagaard. K.. Roach. A. T. & Schumacher. J. D. ( 1 985 ). On the

wind-driven variabiHty of the flow through Bering Strait.

/ Geophys. Res. 90. 7213-7221.
Amos. A. F. AkudemikKorolev(A¥.-M-Vil)C'\D&did: Standard

level listings. Univ. Te.x. Mar. Sci. Piihl. TR/9()-00i.
Barnes. C. A. & Thompson. T. G. (1938). Physical and

chemical investigations in the Bering Sea and portions of the

North Pacific Ocean. Univ. Wasli. Pithl ()cean<>i;r. 3(2),

35-79.
Coachman. L. K. (1986). Circulation, water masses, and

fluxes on the southeastern Bering Sea Shelf Com. Shelf Re.s.

5(1/2), 23-108.
Coachman, L. K. & Aagaard, K. ( 1988). Transports through

Bering Strait: Annual and interannual variability.

J. Geophy.s. /?es. 93, 15535-15539.
Coachman, L. K., Aagaard. K. & Tripp. R. B. ( 1975). Bering^

Slrail: The Regional Physical Oceanography.

Univ. Washington Press. Seattle. 172 pp.
Deleersni jder. E. & Nihoul, J. C. J. ( 1 988). General circulation

in the northern Bering Sea. ISHTAR Annual Progress

Report, 392 pp.
Faculty of Fisheries ( 1974). Data Record of Oceanographic

Observations and Exploratory Fishing 17, Faculty of

Fisheries, Hokkaido University, Hakodate, 294 pp.
Grebmeier, J. M.. Cooper, L. W. & DeNiro, M. J. (1990).

Oxygen isotope composition of bottom seawater and tunicate

cellulose used as water mass indicators in the northern

Bering and Chukchi Seas. Lininol.Oceauogr. 35(5).

1182-1195.
Kinder. T. H.. Chapman. D. C. & Whitehead. J. A.. Jr. ( 1986).

Westward intensification of the mean circulation on the

Bering Sea Shelf. J. Phys. Oceanogr. 16. 1217-1229.
Kinder, T. H., Coachman, L. K. & Gait, J. A. ( 1975). The

Bering Slope Current system. J. Phys. Oceanogr. 5.

231-244.
Mountain. D. G.. Coachman, L. K. & Aagaard, K. (1976). On

the How through Barrow Canyon. / Phys. Oceanogr. 6,

461-470.
Muench, R. D, Tripp, R. B. & Cline, J. D. ( 198 1 ). Circulation

and hydrography of Norton Sound. In The Eastern Bering

Sea Shelf: Oceanography and Resources. Vol. 1, Chap. 6,
pp. 77-93. Office of Marine Pollution Assessment, NOAA,
US Department of the Interior. Washington, D.C.

Nihoul, J. C. J.. Deleersni jder. E. & Djenidi. S. ( 1990). Modeling
thegeneralcirculationof shelf seas by 3D- models. Earth-
Sci.Rev. 26, 163-189.

Ratmanov. G. E. (1937a). On the hydrology of the Bering and
Chukchi Seas. In Investigations of the Seas of the USSR 25,
10-118. (in Russian)

Ratmanov, G. E. ( 1937b). On the question of water exchange
through Bering Strait. In Investigations of the Seas of the
USSR 25, 119-135. (in Russian)

Schumacher, J. D.. Aagaard, K., Pease. C. H. & Tripp. R. B.
(1983). Effects of a shelf polynya on flow and water
properties in the northern Bering Sea. J. Geophys. Res. 88,
2723-2732.

Springer, A. M., McRoy, C. P. & Whitledge, T. E, (in press).
The paradox of pelagic food webs in the northern Bering Sea.
III. Patterns of primary production. Cont. Shelf Res.

Stigebrandt, A. (1984). The North Pacific: A global-scale
estuary. / Phy.^i. Oceanogr. 14, 464-470.

Sverdrup, H.U. (1929). The waters on the north Siberian shelf.
The Norwegian North Polar Expedition with the "Maud",
1918-1925. Scientific Results, l\, {2). 13\ Bergen.

US Coast Guard Oceanographic Unit ( 1964). Oceanographic
cruise USCGC Northwind Bering & Chukchi Seas July-
September 1962. US Coast Guard Oceanographic Report
1, 104 pp.

US Coast Guard Oceanographic Unit (1965). Oceanographic
cruise USCGC Mw/Zniv/K/Chukchi, East Siberian, and Laptev
Seas J uly-September 1963. US Coast Guard Oceanographic
Report 6, 69 pp.

Walsh, J. J., McRoy, C. P., Coachman. L. K.. Goering. J. J.,
Nihoul. J. C. J.. Whitledge, T. E.. Blackburn. T. H.. Parker,
P. L.. Wirick. C. D., Shuert. P. G.. Grebmeier. J. M..
Springer. A. M.. Tripp, R. B., Hansell, D. A., Djenidi. S.,
Deleersnijder, E., Henriksen, K., Lund, B. A., Andersen, P.,
MuUer-Karger. F. E. & Dean. K. (1989). Carbon and
nitrogen cycling within the Bering/Chukchi Seas: Source
regions for organic matter effecting AOU demands of the
Arctic Ocean. Prog. Oceanogr. 22(4). 277-359.

35

Chapter 3:

HYDROCHEMISTRY

Editors:

SERGEI M. CHERNYAK &
TERRY E. WHITLEDGE

3.1 Biogenic Nutrient Content

TERRY E. WHITLEDGE' , MIKHAIL 1. GORELKIN^ , and SERGEI M. CHERNYAK*
"Marine Science Institute. University of Texas at Austin. Port Aransas. Texas. USA

'Institute of Global Climate and Ecoloi;\. State Committee for Hydrometeoroloi^y and Academy of Sciences. Moscow. USSR

Introduction

The early investigation of the biogenic nutrient content of
Bering Sea waters have shown these elements that are necessary
for phytoplunkton grow ih lo often be present in surface waters
in quite high concentrations (Barnes & Thompson, 1938).
More recently, the Processes and Resources of the Bering Sea
Shelf (PROBES) program did an exhaustive study of the
physical-biological ecosystem dynamics of the southeastern
Bering Sea Shelf. Over a five-year period, the nutrient content
across the shelf was observed to be related to three frontal
systems that governed the nutrient dynamics in the open ocean,
outer shelf, middle shelf, and inner shelf (Coachman, 1986;
WhitledgC(Vu/., 1986).

The later program of Inner Shelf Transfer and Recycling
(ISHTAR) further investigated the transport of water and
nutrients through the northern Bering Sea into the Chukchi Sea
and studied the primary production/decomposition processes
that occurred in the Alaskan Coastal water, Bering Shelf water
and Anadyr water (Walsh et al.. 1990). The Third Joint US-
USSR Bermg & Chukchi Seas Expedition in 1988 was a
tremendous enhancement to the ISHTAR sampling program,
which had previously lacked a complete and quasi-synoptic
sampling of all of the above water masses.

The biogenic nutrient content is indicative of the potential
primary production that ma\ occur in seawater and therefore is
used to assess one ol the major factors controlling primary food
production in the marine environment. The concentration of
nitrogen, in the form of nitrate and ammonium, is particularly
useful because most oceanic environments contain small
concentrations of nitrogen relative to phosphorus and silicon
and is often thought lo limit rales of primary production
(Ryther & Dunstan, 1971 ). The uptake of biogenic nutrients
along with carbon dioxide and light is important as fuel for
primary production processes. The production of nutrients by
regenerative processes must also be considered because the
nutrients present in seawater are replenished on a continuous or
periodic basis. These regeneration processes maintain the
long-term primary production of an ecosystem especially on
continental shelves where benthic regeneration also contributes
nutrients to the euphotic zone. The biogenic nutrient content of
water in the Bering and Chukchi Seas in general is high,
reflecting its origin in the North Pacific Ocean. The deep
Bering Sea, where few biological measurements have been
taken, maintains high nutrient concentrations throughout the

year, and plant biomass represented by chlorophyll is small.
The continental shelf, which comprises about 45% of the area
of the Bering Sea, varies from high to low nutrient concentrations
as the annual cycle of primary production occurs (Whitledge
etui, 1986).

The primary purpose of this paper is to describe the
nutrient, oxygen, and pH variations of the south and east
regions of the deep Bering Sea, the northern Bering Sea Shelf
and the southern Chukchi Sea ( Frontispiece). All of these areas
were sampled on the Third Joint US-USSR Bering & Chukchi
Seas Expedition in 1 988 as a part of a program to investigate the
ecology and health of the Bering and Chukchi Seas.

Methods

Water samples were collected on the upcast with a Sea-
Bird CTD/rosette sampler. Water samples were immediately
collected in polyethylene scintillation vials and were analyzed
on a model 300 Alpkem segmented flow analyzer at 80 samples
per hour. The analytical techniques were adapted to small
volume glassware from previously described methods
(Whitledge et al.. 1981 ). The basic analytical methods were
described by Armstrong et al. (1967) for nitrate, phosphate,
and silicate. Ammonium was measured by the
phenohypochlorile method of Koroleff (1970) as adapted to a
continuous analyzer by Slawyk and Maclsaac (1972) and
modified by Patton and Crouch (1977). Standard Winkler
titrations were used to determine the concentration of dissolved
oxygen.

Results

Northern Shelf Regions

The physical transport of water from the North Pacific inio
the deep Bering Sea moves eastward and north in a counter-
clockwise gyre until it nears the coastline of the Soviet Union
where it bifurcates and a northern segment Hows through the
Gulf of Anadyr toward Bering Strait (Whitledge et al.. 1988).
This long-term net movement of water carries a large quantity
of biogenic nutrients from the deep Bering Sea onto the shallow
northern shelf of the Bering and Chukchi Seas where primary
production processes consume them. The northern tlow of
water varies from about 0.5 to 1.0 Sv and produces
bathymetrically induced upwelling as a result of the 30-50 m
water depths of the shelf.

39

The temperature and salinity distribution clearly define
the general circulation patterns between the Gulfof Anadyr and
the southern Chukchi Sea. The differential between surface
and bottom water was as large as 8.5°C and 1.5 "/„,, salinity in
the Gulf of Anadyr ( Fig. 1 A,B ) but decreased to less than 1 °C
and 0.5 "/,,,) in Chirikov basin after passing through Anadyr
Strait. The low salinity (Fig. 1C,D) Alaskan Coastal waters and
Bering Shelf waters maintain theireastem positions and reduced
salinities throughout northward transport (Coachman &
Shigaev, Subchapter 2.1, this volume). The relatively low
temperature bottom water denoted by the -1.5°C isotherm
delineates the cold high-salinity water formed during the
previous winter months by production of ice. The presence of
this cold water indicates the slow circulation velocities on the
eastern Bering Sea Shelf. Accumulation of benthic regeneration
products can occur in these waters.

The nitrate content of the surface water (Fig. 2A) displays
a pattern of reduced concentrations where the waters are
stratified in the Gulf of Anadyr and Chukchi Sea. The largest
surface concentrations of nitrate occur in the Chirikov basin
after upwelling and mixing in Anadyr Strait, especially on the
west side along the Soviet coastline, and extend into the
southern Chukchi Sea. These very large surface concentrations
support the high primary production rates reported in the
Bering Strait region (Sambrotto et al.. 1984). Near bottom
nitrate concentrations (Fig. 2B) originating in the deep Bering
Sea provide a substantial part of the nitrogen to feed primary
production processes. The nitrate values larger than
30 |imole/l are quite unusual for a shallow shelf region; even
coastal upwelling regions seldom have greater than
1 5-20 fimole/l inside the shelf break. Concentrations of near
bottom nitrate above 30 |imole/l disappear at Anadyr Strait

180

175

170

165

180 175 170 165 180 175 170 165

Fig. 1. The Mirlace (A) and bottom (B) distribution of temperatures (°C), surface (C) and bottom (D) distribution of salinity
("/„, ) measured in the northern Bering and Chukchi Seas.

40

probably as the result of strong vertical mixing; however,
values larger than 20 |imole/l were observed on the west side
of all three regions (Gulf of Anadyr, Chirikov basin, Chukchi
Sea). The presence of these large near-bottom nitrate
concentrations are almost certainly due to some nitrification
(ammonium conversion to nitrate by bacteria) occurring in the
Chirikov basin and Chukchi Sea.

Ammonium, the regenerated form of nitrogen, was found
to have very low concentrations (Fig. 2C) in surface waters.
The very high affinity of phytoplankton to ammonium reduces
concentrations to very low levels unless unusually large surface
ammonium regeneration rates are occurring. The bottom
ammonium concentrations (Fig. 2D ) reflect the active nature of
nutrient regeneration in the near bottom waters and sediments.
Decomposition of organic matter releases large amounts of

ammonium especially where high priinary
production/deposition is occurring. This process is best shown
in the central Chukchi Sea and to a smaller extent in the western
Chirikov basin. Remember that the east side of the Bering and
Chukchi Seas has very small organic production rates compared
to the western portions. The highest near bottom ammonium
concentrations were found in the low temperature "winter
water" in the Gulf of Anadyr and along the Soviet coast in the
Chukchi Sea. These large ammonium concentrations reflect
the accumulation that occurred over the several months since
the cold water was produced. In both cases more than
4 (iniole/1 concentrations were observed in the two regions.
The Gulf of Anadyr ammonium probably contributes to the
surface increases of ammonium that are observed downstream
after vertical mixing in Anadyr Strait.

180

175

170

165

==V

-+-

-+-

180

175

170

165

180 175 170 165

Fig. 2. The surface (A) and bottom (Bl distribution of nitrate ()i mole/1), the surface (C) and bottom (D) distribution of ammonium
((J mole/1) measured in the northern Bering and Chukchi Seas.

41

The surface silicate concentrations (Fig. 3 A) are similar to
those of nitrate, especially the strong east-west gradient in the
Chirikov basin. Silicate is mainly utilized by diatom populations
but other phytoplankton may also have a silicate requirement.
Even the areas where high silicate concentrations have been
reported in river discharge contained less than 5 |imole/l. Near-
bottom silicate concentrations (Fig. 3B) reflect the large
concentrations present in deep Bering Sea water with values
above 50 [imole/l. Vertical mixing in Anadyr Strait and
subsequent uptake by phytoplankton reduce concentrations to
the range of 10-30 |imole/l. The east side of the ecosystem all
had values less than 10 |imole/l.

The surface phosphate concentrations (Fig. 3C) were
adequate to support primary production processes throughout
the area of investigation. Areas with phosphate concentrations

less than 0.5 |imole/l also contained small amounts of nitrate
and silicate; therefore, phosphate was always in plentiful
supply compared to other nutrient forms. Near-bottom
phosphate concentrations ( Fig. 3D) reflect both the enrichment
from the deep Bering Sea into the Gulf of Anadyr and the
cumulative effects of phosphate regeneration in the Chirikov
basin and Chukchi Sea.

The Gulf of Anadyr serves as the conduit for flow of water
from the deep Bering Sea into the confined Chirikov basin. The
center of the Gulf of Anadyr is stratified with the warmer
surface waters depleted of nutrients ( Fig. 4), but near the coast,
all isopleths rise toward the surface, indicative of active coastal
upwelling. Surface concentrations of all nutrients were low
enough to reduce primary production. The highest chlorophyll
measured in this region (24-28 |ig/l) was on Station 26 at a

180

175

170

165

180

175

170

165

180

175

170

165

180 175 170 165

Fig. .^. The surface (A) and boltcim (Bl dislrihulion ol silicate (n mole/1), the surface (C) and hcitlcim (D) distribution of phosphate
(|i mole/I) measured in the northern Bering and Chukchi Seas.

42

depth of 20-25 m. which coincides with the upwelling area, but
the phytopianivton population was so great that nitrate, silicate,
ammonium, and phosphate were reduced to 10.3, 1.2. 0.1. and
1 .4 |.imole/l respectively. The outer end of this transect was
located in the near-hottom winter shelf water as indicated by
the ammonium signature (Fig. 4B).

The Chirikov basin receives water from the Gulf of Anadyr
after nearly complete vertical mixing occurs throughout the
water column in Anadyr Strait (Fig. 5). The very uniform
vertical nutrient concentrations on the western end of the
transect changes into a stratified system near the middle where
Bering Shelf waters and Alaskan Coastal waters are encountered.
The strong east-west gradients are the products of the lack of
flow from the deep Bering Sea and the little vertical mixing in
Shpanberg Strait on the east side of St. Lawrence Island.

The Chukchi Sea receives the waters that flow through
Bering Strait after passing through Chirikov basin ( Fig. 6 ). The
nutrient content of this northward (lowing water has been
reduced somewhat in the Chirikov basin, but the major portion
remains to support primary production in the Chukchi Sea. The
strong east to west gradient of nutrients remains similar to the
more southern areas. The Chukchi transect of stations shows
the large near surface concentrations of nutrients which
corresponds to observations of the largest chlorophyll
concentrations. Nitrate, ammonium, and phosphate

concentrations show enhancement near the Soviet coast, which
probably results from a southward tlowing Siberian Coastal
Current (Coachman & Shigaev, Subchapter 2. 1 . this volume).
The Alaskan Coastal water displays a low nutrient content
consistent with more southern transects except silicate, which
is enriched by about l()|imole/l. Even though past observations
have shown all nitrogen in the Yukon River was removed
quickly in the Chirikov basin, this nearshore increase in silicate
may be related to the Yukon River. This would be
consistent with the distribution of carbon isotope and C/N
ratios as reported by Scalan et al. (Subchapter 8.5.1, this
volume).

The temperature-salinity diagram for all samples collected
on the 1988 joint cruise (Fig. 7A) shows the very cold water
below 0°C that falls into the salinity range of 32-32.7 7,k, . The
low temperature water between and 0.5°C has a salinity of
33-33. 5"/|,„ so this must represent water that was formed
during ice production, which increases the salinity.

The nitrate-salinity diagram for all samples (Fig. 7B) on
the joint expedition fell predominantly in the salinity range of
32-32.5"/,,,. and the nitrate varied from about 0.1 to about
40 |ig-at/] . A few points deviated from this general distribution
in low salinity water in the Alaskan Coastal Current that was
depleted of nitrate and higher salinity samples from the deep
Bering Sea where nitrate concentrations exceeded 50 ^g-at/l.

STATION NO

STATION NO

75

A

^

Vso V

100

200

DISTANCE (Km)

300

400

100

DISTANCE (Km)

Fig. 4. The distribution of nitrate (A), ammonium (B), silicate (C) and phosphate (D) in a transect of stations across the Gulf of Anadyr. Units are
H mole/1.

43

STATION NO

STATION NO.

10

20

30

40

50

A

1

5

I

1

1 1 ^
I.I.

\

S

/

L

^^^,.^

B

1 . 1 . 1 . 1 .

1 00 1 50

DISTANCE (Km)

100 150

DISTANCE (Km)

250

Fig. S. The di.slribution ot nitrate (A), uninionium (B), silieate (C) and phosphate (D) in a transect of stations across the Chirikov basin. Units
are Jl mole/1.

3^^^^'°^^° STATION NO

C7)

o

CD

to

CM
(D

s

(D CD

^

1

\

1

l<

2

n

■>

--

\

B

1 1 I 1 1

1

1

100 150 200 250

DISTANCE (Km)

350

100 150 200 250
DISTANCE (Km)

Fig. 6.

The distribution of nitrate (A), aninionium (B). silicate (C) and phosphate (D) in a transect of stations across Chukchi Sea.
Units are |i mole/1.

44

I

SAUNfTY (o/oo)

Fig. 7. (A) Temperature ('€) and salinity ("/,„); (B) nitrate (n g-at/1) and
salinity (7(x,) plot for all stations sampled in the Bering and Chukchi
Seas.

SAijNrrr (o/oo)

Fig. 8. (A) Silicate (|i g-at/l) and salinity (7i„) plot; (B) phosphate (|i g-at/1)
and salinity ("/„,) plot for all stations sampled in the Bering and
Chukchi Seas.

The silicate-salinity diagram for all samples (Fig. 8A)
shows the range of silicate to be between 0.5 and 60 |ag-at/l for
most samples between 3 1 and 33 "/„„. The low salinity Alaskan
Coastal water had values below 20 |ag-at/l and the deep Bering
Sea contained concentrations above 230 |ag-at/l. In contrast,
the range of phosphate concentrations (Fig. 8B) was 0.23 to
about 3.5 ug-at/1. The uniform distribution of phosphate
compared to nitrate is probably due to the rapid regeneration of
phosphate in the water column.

Deep Bering Sea

The South and East Polygons in the Bering Sea had
stations with depths approaching 4,000 m. The vertical profiles
of nitrate and silicate (Fig. 9B) provide some insight into the
nutrient gradients in the deep Bering Sea. The concentrations
of nitrate and silicate were very similar in the upper 100 m
between the two polygon locations; however, the East Polygon
had larger nitrate and smaller silicate concentrations compared
to the South Polygon. The resulting plot of nitrate/silicate ratio
with depth (Fig. 9A) clearly shows the differences. The low
oxygen concentrations present in the South Polygon (Fig. 1 1 A)
are more conducive to denitrification process, so it is likely that
the nitrate has been lost from the deep water by this process.

The near-bottom waters near the South Polygon had previously
been observed to contain a layer of slightly less saline water
near the bottom (Park et ai. 1975). The very distinct vertical
distributions make further sampling in these regions a necessity.

The vertical phosphate distributions in the deep Bering
Sea (Fig. lOB) also tend to be elevated in the East Polygon
compared to the South with values greater than 3 |imole/l. The
dissolved inorganic nitrogen (DIN)/phosphate ratio showed
that most deep ocean values were at or above 16:1. especially
in near-bottom water where the ratios were >20: 1 .

The vertical distributions of pH (Fig. 1 IB) and dissolved
oxygen (Fig. 1 1 A ) in the deep Bering Sea reflect the relatively
high rates of primary production in the surface waters and the
slow rate of water circulation at depth. These distributions
result from the consumption of dissolved oxygen and the
respiratory release of carbon dioxide as particulate matter sinks
into the deep sea. Since these parameters are both closely
associated with the decomposition of organic matter it is not
unusual for their relationships with salinity to be similar
(Figs. 12A.B). The highest salinity waters in the deep Bering
Sea have increased values of both pH and dissolved oxygen and
may be related to bottom water renewal processes from the
North Pacific Ocean.

45

s

1988 US-USSR CRUISE

OOP BEWHO STATIONS

(Tliousands)
DEPTH (m)

Fig. 9. The vertical distribution of (A) nitrate and silicate (|J mole/1) and (B)
the nitrate/silicate ratio for all stations during the joint expedition.

Discussion

The biogenic nutiient content of the Bering Sea is closely
coupled to the primary production and regeneration process
occurring within its waters. The deep Bering Sea at South and
East Polygons have a continued supply of nitrate, silicate, and
phosphate to support primary production processes, but a
phytoplankton bloom with large chlorophyll concentrations
has not been observed. The high nutrients and low chlorophyll
are similar to the situation observed in the North Pacific Ocean
at Station P. The waters at depth in the deep Bering Sea hold
large quantities of nutrients compared to other parts of the
worid"s oceans, which indicates that the Bering Sea is a sink
rather than a source. This fact is also true for constituents other
than nutrients since there is no apparent ventilation of the deep
waters. Future work in the deep Bering Sea should focus on the
inputs to the deep water, its age and its level of anthropogenic
contamination.

The Gulf of Anadyr receives deep waters from the open
Bering Sea and transmits these waters to Anadyr Strait, which
separates St. Lawrence Island from the Soviet mainland. The
waters in the Gulf of Anadyr are productive, especially near the
coastline where upwelling occurs. The resulting phytoplankton

Fig. 10. The vertical distribution of (A) the dissolved inorganic nitrogen/
phosphate ratio and ( B ) phosphate ((i mole/1) for all stations dunng the
joint expedition.

probably act as a seed population for the upwelled water in
Anadyr Strait and provide organic matter to support regenerative
processes. Note that this nutrient regeneration occurs in the
deposition areas depicted by Coachman and Shigaev
( Subchapter 2. 1 . this volume). The bottom water in the central
Gulf of Anadyr has the signature of winter water with its
extremely cold temperatures of <0.5°C. These waters slowly
transit through Anadyr Strait while being mixed with open
Bering Sea waters.

The Chirikov basin acts as the "chemostat" in the ecosystem
by supplying large quantities of nutrients as inflows to ultimately
produce organic matter. The transit time through the Chirikov
basin may be so sinall that not all nutrients are utilized, similar
to a wash-out condition. The northward transport also includes
inner shelf water from the southeast Bering Sea that often
produces a separate phytoplankton bloom in the middle of
Chirikov basin (Hansell et al.. 1989). The majority of organic
matter and remaining nutrients advect northwiu'd along the
western edge into the Chukchi Sea (Hansell & Goering.
submitted).

The Chukchi Sea receives the northward tlow of nutrients
and organic matter and further primary production occurs in the
central portion where surt'ace concentrations of nitrate are

46

greater than 1 |imole/l (Fig. 2A). The organic matter then
suhstantiaily falls to the bottom to fuel further processes and
contributes to the high organic content of the sediments ( Walsh
etal.. 1989).

The e.xtended sur\ey during the 19S8 joint expedition
encountered an additional source of high-salinity, high-nutrient
water near Kolyuchin Bay. The high nitrate content of the
southward tlowing coastal water (Coachman & Shigaev,
Subchapter 2. 1 , this volume ) indicates that additional nitrogen
is added to the central Chukchi Sea as it joins the Bering Strait
water. There is some speculation about the original source of
this southward tlowing water but oxygen- 1 8 data indicates that
it may have been winter water that previously had passed
through Bering Strait (Grebmeier <'/«/.. 1990). The importance
of this additional nutrient input to the central Chukchi Sea is
great because it could supply an additional amount of nutrients
to enhance the annual primary production rates. The gains and

losses of the Chukchi Sea are very poorly known but there is
some speculation that nutrients utilized here transit to the deep
ocean arctic basin.

We would like to acknowledge D. Viedt for technical help in the
collection ot field samples and its chemical analysis. We would also
like to thank Dr. L. K. Coachman and the other US scientists aboard
the research vessel {WM ) Akademik Korolev. Finally, a special thanks
is given to all the Soviet scientists and especially Professor
A. V. Tsyban and Captain O. A. Rostovtsev of the R/V Akademik
Korolev. This project was part of the Third Joint US-USSR Bering
& Chukchi Seas Expedition aboard the Soviet R/V AA«(/em;A- AV»o/e\'.
We express appreciation to the US Fish and Wildlife Service, USA,
and the State Committee for Hydrometeorology, USSR, who made
our participation possible. This research was mainly supported by
Grant No. DPP86()56.'i9 from the Division of Polar Programs of the
National Science Foundation as part of the ISHTAR program.
Contribution No. 766 of the Marine Science Institute. University of
Texas at Austin.

500 1000 1500 2000 2500 3000 3500

Dapth (m)

12

10

E 8-

i 6
o

32

33 34

Salinity (o/oo)

35

500 1000 1500 2000 2500 3000 3500
Depth (m)

32

33 34

Salinity (o/oo)

Fig. 1 1. The vertical distribution of (A) dissolved oxygen (mg/1) and (B) pH
for the deep Bering Sea stations.

Fig. 12. (Al dissolved oxygen (mg/1) and salinity ["1^ ) plot (B) pH and
salinity ("/„,) plot for the deep Bering Sea stations.

47

48

Chapter 3 References

Armstrong. F. A. J.. Stems. C. R. & Strickland, J. D. H. ( 1 967).
The measurement of upwelling and subsequent biological
processes by means of the Technician Auto Analyzer and
associated equipment. Deep Sea Re.\. 14. .^81-389.

Barnes. C. A. & Thompson, T. G. (1938). Physical and
chemical investigations in the Bering Sea and portions of the
North Pacific Ocean. In University of Washington
Publications in Oceanography, Vol. 3, pp. 35-79.

Coachman, L. K. ( 1986). Circulation, water masses and fluxes
on the southeastern Bering Sea Shelf. Cont. Shelf Res. 5,
23-108.

Coachman, L. K, & Shigaev, V. V. ( 1992). Northern Benng-
Chukchi Sea ecosystem:The physical basis. (Subchapter
2.1, this volume).

Hansen, D. A. & Goering. J. J. (submitted). Pelagic nitrogen
flux in the northern Bering Sea. Cont. Shelf Res.

Hansen, D. A., Goering, J. J., Walsh, J. J., McRoy, C. P..
Coachman, L. K,, & Whitledge, T. E. (1989). Summer
phytoplanklon production and transport along the shelf
break in the Benng Sea. Cont. Shelf Res. 9, 1083-1 104.

Grebmeier, J. M., Cooper, L. W. & DeNiro, M. J. (1990).
Oxygen isotope composition of bottom seawater and tunicate
cellulose used as water mass indicators in the northern
Bering and Chukchi Seas. Limnol. Oceanogr. 35,
1178-1191.

Koroleff, F. (1970). Direct determination of ammonium in
natural waters as indophenol blue. Information on techniques
and methods for seawater analysis, luterlab Rep.i. 19-22.

Park, P. K., Broecker, W. S., Takahashi, T. & Reeburgh, W. S.
(1975). Geosecs Bering Sea station, a brief hydrographic
report. In Bering Sea Oceanography: An Update
(D. W. Hood & Y. Takenouti, eds. ), pp. 207-244. Institute
of Marine Science, Fairbanks, Alaska.

Patton, C. J. & Crouch. S. R. ( 1977). Spectrophotometric and
kinetic investigation of the Berthelot reaction for the
determination of ammonia. Anal. Chem. 49, 464—469.

Ryther, J. H. & Dunstan, W. M.(1971). Nitrogen, phosphorus
and eutrophication in the coastal marine environment. Science
171, 1008-1013.

Sambotto, R. M., Goering, J. J. & McRoy, C. P. (1984). Large
yearly production of phytoplankton in the western Bering
Strait. Science 225. 1 147-1 150.

Scalan, R. S., Behrens, E. W., Caughey, M. E., Anderson, R. K.
& Parker, P. L. ( 1 992). Characterization of sediment organic
matter in the Bering and Chukchi Seas. (Subchapter 8. 5. 1,
this volume.)

Slawyk, G. & Maclsaac, J. J. (1972). Comparison of two
automated ammonium methods in a region of coastal
upwelling. Deep Sea Res. 19,521-524.

Walsh, J. J., McRoy, C. P., Coachman, L. K., Goering, J. J.,
Nihoul. J. J., Whitledge, T. E., Blackburn, T. H., Parker. P.
L.. Wirick, C. D., Shuert, P. G., Grebmeier, J. M., Springer,
A. M., Tripp, R. D., Hansen, D. A., Djenidi, S., Deleersneider,
S., Hendriksen, K., Lund, B. A., Andersen, P., Muller-
Karger, F. E. & Dean, K. (1990). Carbon and nitrogen
cycling within the Bering/Chukchi Seas: Source regions for
organic matter affect AOU demands of the Arctic Ocean.
Prog. Oceanogr. 22, 279-361.

Whitledge, T. E., Bidigare, R. R., Zeeman, S. I., Sambotto, R.
N., Roscigno, P. F., Jensen, P. R., Brooks, J. M., Trees, C. &
Veidt, D. M. (1988). Biological measurements and related
chemical features in Soviet and United States regions of the
Bering Sea. Cont. Shelf Res. 12, 1299-1319.

Whitledge, T. E.. Malloy, S. C, Patton, C. J. & Wirick. C. D.
(1981 ). Automated nutrient analyses in seawater. Brookhaven
Nat. Lab. Formal Rep. 51398, 227 pp.

Whitledge, T. E.. Reeburgh, W. S. & Walsh, J. J. (1986).
Seasonal inorganic nitrogen distributions and dynamic in the
southeastern Bering Sea. Cont. Shelf Res. 5, 109-132.

.49

Chapter 4:

MICROORGANISMS AND

MICROBIOLOGICAL

PROCESSES

Editors:

ROGER B. HANSON &
GENNADIY V. PANOV

Subchapter 4.1:

General Characteristics of
Bacterial Populations

4.1.1 Total Number, Biomass, and Activity of
Bacterioplankton

ALLA V. TSYBAN, VASSILIY M. KUDRYATSEV, VLADIMIR O. MAMAEV, and NADEZHDA V. SUKHANOVA

Institute of Global Climate ami Ecology. State Committee for Hydrometeorology and Academy of Sciences, Moscow. USSR

Introduction

Until recently, marine microbiologists investigated only
general characteristics of heterotrophic microorganisms.
However, the development of new techniques (to measure
biomass, growth rates, and metabolic activity) (Vieble, 1984),
coupled with oceanographic measurements, has made it possible
to quantitatively assess the importance of microorganisms in
cycling of various organic and inorganic chemicals in the
ocean. Such methods are now applied to detennine ecotoxicity
and resident times of different anthropogenic contaminants.

Investigation of microbiocenoses and quantitative
assessment of microbiological processes in marine environment
are the most important elements in the evaluation of
anthropogenic inputs on marine ecosystem and their assimilation
capacities. Information on the assimilation capacity can be
obtained from long-term studies conducted across different
geographical zones of the World Ocean (Izrael & Tsyban,
1983, 1989).

Long-term microbiological research in the subarctic and
arctic seas was started in the eariy 1980"s. Eariy results
(Tsyban et al. 1987b; Izrael et al.. 1988) showed that the
growth and function of microbiocenoses depended on the
hydrological and hydrochemical conditions of the sea. The
increase in human population and factors, and the transport of
anthropogenic contaminants into the sea. has appreciably
affected the growth and activity of marine microflora (Izrael &
Tsyban, 1981, 1983a,b; Korsak, 1985).

Materials and Methods

Microbiological studies in the Bering and Chukchi Seas
were conducted by the Soviet-American ecological expedition
in summer 1988 (see Frontispiece). These studies paid particular
attention to specific regions in these seas. In the Bering Sea,
research efforts focused on the eastern and southern areas of the
deep Bering Sea, the relatively shallow regions of the central
area and the Gulf of Anadyr, and the shallow shelf area m the
Chirikov basin. All these regions have unique hydrological,
chemical, and biological conditions.

To assess total population and biomass of bacteria, 381
samples were assayed in the BeringSea, of which 320 samples
were assessed for dark CO, assimilation by bacteria.

Microbiological studies were conducted for the first time
in the Chukchi Sea. The study focused on the southern ice-free
area of the sea to assess total number and biomass of bacteria;
1 1 5 samples were taken. For dark CO, assimilation by bacteria,
107 samples were taken at 21 stations.

Total number of bacteria was determined directly on
membrane filters "Synpor" with pore diameter of 0.32 |im
(Razumov, 1932). A volume of 10 to 20 ml of water was
filtered, cells stained with 5% erythrosine, and counted by light
microscopy. Counts were done on 10-20 visual fields with a
total magnification of xI.OOO. The number of bacteria was
calculated by the formula:

X:

Sx lO^xa.
S, X b xc

where

X

=

number of bacteria per one ml of
water;

s

=

filter area, mm-;

10*^

=

coefficient for converting mm- to

a

=

average number of bacteria counted
in 1 visual field "c";

s,

^

area of eyepiece reticular network
in fim-;

b

=

volume of water filtered, ml;

c

^

number of visual fields, where
bacteria were counted over "S,"
area.

The biovolume of bacterial mass was estimated from the
average volume and total number of bacteria:

where

V
n

v,

V = n X v,

biovolume of bacterial mass, ^m';
number of bacteria per liter of water;
average volume of a single bacterial
cell, ;Um\

The linear dimensions of single bacterial cells were
determined (Tsyban et al., 1988) with a calibrated eyepiece
micrometer. From such measurements, the average volume of
bacterial cells was calculated and equaled to 0.30 ;^m- .

Bacterial mass was determined (Sorokin & Kadota, 1972;
Romanenko & Kusznetsov, 1974) by the formula:

Ph= nx vx 15x 10''

2x 100

55

where

15
10-*

2

100

weight of bacterial biomass, jUg C/1;
total number of bacterial per 1 of

water;
percentage of dry residue from raw

biomass;
weight of 1 ^m' of raw biomass of

bacteria (/ig) with specific weight

equal to unity;
average biovolume of bacterial

mass, jum';
carbon content from dry biomass;
raw biomass, %.

CO, dark assimilation by bacteria was assessed by
radioisotopic method (Romanenko, 1964; Romanenko &
Kuznetsov, 1974). To determine dark CO, assimilation by
bacteria, the C'^ sodium carbonate (Na, "CO,; 20.4 x 10'~) was
added to 100 ml of seawater. Water samples were incubated in
the dark for 1-3 days at sea surface temperatures. After
incubation, water samples were fixed with 40% formaldehyde
solution and filtered (pore diameter 0.45 mm). Filters were
exposed to 0. 1 N HCl vapors and radioactivity of bacteria on
filter was measured by liquid scintillation. Rates were calculated
by the formula

c = *^-" ^ '■

Rxt

where

C,

r

R

t

CO, assimilation by bacteria, ^g C/1;
carbonates concentration (mg/1),

determined by directly titration (0.1

N HCl in the presence of methyl

red indicator);
radioactivity of bacteria on filters

(dpm);
radioactivity of isotope Na,"C03

used in experiment, dpm;
incubation time.

Results and Discussion

Total Number. Bioma.^s. and Dark CO. Assimilaiion by
Bacteria in the Bering Sea

Results are shown in Table 1 . The growth, distribution,
and activity of microflora varied both in time and locality in the
Bering Sea. Bacterioplankton numbers, biomass, and activity
in 1988 was generally higher than in the summers of 1981 and
1984(Tsybant'r«/.. 1987). In 1981 and 1984 the total number
of bacteria fluctuated between 19-2,799 and
73-380 X 10' cells/ml. On average, the population and
biomass of bacteria in 1988 amounted to 671 x 10' cells/inland
15.09 mg C/m', respectively. These values were almost twice
as high as those found in 1981 and 1984.

Comparing this data to other regions of the World Ocean,
for instance, the total number of bacteria in the Barents Sea
ranged between 10 and 500 x 10' cells/ml (Baitaz & Baitaz,
1986); in the Scotia Sea, populations of bacterioplankton
reached 200-500 x 10' cells/ml (Azam et al.. 1981); in the
Arctic Ocean, concentrations of bacterial population varied

TABLE 1

Numbers, biomass and dark CO, assimilation by bacteria in the
Bering Sea water, summer 1988.

Sea area

Total bacterial Bacterial biomass

numbers (/jgC/l)

(10-' cells/ml)

Dark CO,

assimilation

by bacteria,

/igC/l/d

Bering
Sea

283-1050
639

6.37 - 23.62
14.38

0.48- 1.73
0.98

Northern part
of the Sea

276-1755
806

6.21 -39.49
18.13

0.49- 1.75
1,05

Gulf of Anadyr

381 -2391

727

8.57-53.79
16.38

0.09 - 2.02
0.38

Central part
of the Sea

.371 - 1601

722

8.35 - 36.02
16.26

0.09 - 2.69
0.53

East Polygon

147 - 3340
655

3.31-75.13
14.66

0.26-7.11
2.0

South Polygon

122- 1453
479

2.74-32.69
10.78

0.12-8.13
1.33

By and large
in the Sea

122-3340
671

2.74-75.13
15.09

0.09-8.13
1.04

from 40 to 440 x 10' cells/ml (Dahlback et al.. 1982); in the
region of Antarctic convergence, numbers varied from 200 to
350 X 10' cells/ml (Hanson et al.. 1983); and in oligotrophic
areas of the Pacific, the density of bactenal population varied
between 10' and 10"' cells/ml (Seki, 1986).

Variations in the growth, number, and distribution of
microflora in the Bering Sea with its complex mixture of water
masses are specific to various areas in the basin. The maximum
density of bacterial population was found on the shallow shelf
of the Chirikov basin (Table 1). The total number and biomass
of bacteria here were 2.7 times those in 1981. Relatively high
bacterial population (1,755 x 10' cells/ml) and biomass
(39.5 mg C/m') in this region were recorded at Station 106,
located near St. Lawrence Island. In the northern part of the
Chirikov basin, numbers and biomass of microflora were
somewhat lower. Thus, at Station 96, the concentration of
bacterioplankton was lowest, on average 583 x 10' cells/ml.
Nevertheless, even though total bacterial numbers were
comparatively low, the microflora activities were high. Daily
dark CO, assimilation reached on average 1.42/igC/l. At other
stations the bacterial activity was much lower, suggesting
some bacterial cells were dormant.

In the shallow northern part of the sea, a fairiy uniform
distribution of bacterioplankton and reasonably steady level of
acti\'ities occurred across the system. The surface microlayer
showed relatively low concentrations of bacterioplankton, but
bacterial activities were higher than in underiying waters. The
bacterial dark CO, assimilation in the surface microlayer was,
on average. I 2 1 pg C/1 daily, which corresponded to the level
of mesotrophic waters.

56

Thus, the shallow northern part of the Bering Sea exhibited
comparatively high total numbers and biomass and moderate
activities of microflora and an even distribution of bacterial
numbers across water types. From rates of bacterial activities
and numbers, the microbiocenoses corresponded to mesotrophic
modes.

In contrast to the Chirikov basin, low microbiocenoses
growth and absolutely different distribution of bacterioplankton
were observed in the south Bering Sea (South Polygon, see
Frontispiece). Total numbers and biomass of bacteria in this
region comprised, on average, 479 x 10' cells/ml and
10.78 mg C/m'. This data is similar to those obtained in 198 1
(Tsyban et al., 1987). The moderate concentration of total
bacteria and their biomass can be attributed to microorganisms
being grazed by protozoa and microzooplankton. According to
Mamae va ( 1 987 ), the evolutionary stage and metabolic activities
of these grazers in the Bering Sea may be high.

The variation in bacterioplankton distribution was clearly
seen at South Polygon. The highest density of bacterial
numbers (averaging 698 x 10' cells/ml) was found at Station
1 08; the lowest density (1 06 x 10' cells/ml ) occurred at Station

111. Three bacterial maxima were found in the water column.
The first maximum occurred in the surface microlayer. The
total number and biomass of bacteria in this layer averaged
1,027 X 10' cells/ml and 23.32 mg C/m', respectively, which
was 1 .4 times that in the mixed layer. Microflora nourished in
the surface microlayer because of various physical-chemical
factors (e.g., particulate aggregates, nutrients, fatty acids and
lipids) (Babenzien & Schwartz, 1970), from water-air
interaction and from high surface tension. Japanese researchers
(Saijo et al., 1974) have demonstrated that concentration of
dissolved and suspended organic substances in the surface
layer is 2-9 times that in the underlying layer.

The second maximum of bacteria was found in the surface
mixed layer (0.5—15 m), a zone of high phytoplankton biomass
and photosynthesis. According to Fogg ( 1 97 1 ) and Kudryatsev
( 1973), the excretion of organic matter may constitute more
than 20% of the total carbon produced by photosynthesis. The
dissolved organic substances that are released by phytoplankton
and other biota may be very important for bacterial growth.

The results showed that maximum density of bacterial
numbers (942 x 10' cells/ml) and high biomass
(21.18 mg C/m') occurred at Station 1 08, and minimum numbers
(427 X 10' cells/ml ) and low biomass (9.62 mg C/m') at Station

1 12. Below the euphotic zone, total number of bacteria and
their biomass gradually declined.

The third layer of high concentration of bacterioplankton
occurred in the near bottom layers of water column. Thus, at
Stations 110 and 111, near bottom bacterial population and
biomass ranged from 510 to 761 x 10' cells/ml and 1 1.5 to
17. 1 mg C/m', respectively.

Bacterioplankton activities also showed several maxima
in the water column. In the euphotic zone of the south Bering
Sea, bacteria appeared twice as active as those in the shallow
northern part. Daily dark CO, assimilation by bacteria at South
Polygon averaged 1.98 mg C/1. which is similar to bacterial
activities in mesotrophic waters.

Bacterioplankton activities in euphotic zone also correlated
with the distribution of bacterial numbers. The highest dark
CO, assimilation by bacteria occurred at Stations 108 and 1 10,
where daily values averaged 2.43 and 2.73 /ig C/1, respectively.
The lowest rate, 0.95 fig C/l/d, was at Station 109.
Bacterioplankton activities declined with depth below the
mixed layer in the south Bering Sea. However, between 150
and 2,000 m, relatively high activity of microflora was found,
coupled with high dark CO, assimilation by bacteria that
reached 2.0-3.0 /ig C/l/d. Thus, south Bering Sea possessed
high bacterial activity, particularly in the euphotic zone, and
low density of bacteria throughout water column. In this
region, bacterial distribution showed considerable variation.
Microbiocenoses also varied vertically across water column
boundaries.

Another studied region of the sea was the East Polygon
(see Frontispiece) located on the eastern slope. At this site,
depth of the water column ranged from 135 to 3,000 m and the
water column possessed a mixture of water types, dissolved O,
saturation, and temperature. All these factors undoubtedly
intluenced the formation and structure of microbiocenoses and
distribution of bacteria. Results showed relatively low activities,
similar to results reported earlier at this site in 1981 (Tsyban
etai. 1987).

Total number and biomass of bacteria at East Polygon
varied considerably (Table 1). Values averaged approximately
1 .4 times higher than those in the south Bering Sea. Maximum
bacterial population (1,302 x 10' cells/ml) and high bacterial
biomass (29.34 mg C/m') occurred at the shallow- water Station
5, and minimum bacterial (873 x 10' cells/ml) and low bacterial
biomass ( 19.65 mg C/m') occurred at the deep-water Station 3,
where bacterial activities were high. The highest rates of dark
CO, assimilation by bacteria occurred here, averaging
2.94 /ig C/1, approximately 5 times higher than those measured
at Stations 4 and 5.

Bacterioplankton in the eastern region declined from the
surface microlayer to the bottom. Maximum numbers
(2,174 x 10' cells/ml) occurred at Station 4 where
microbiocenoses showed a maximum stage of development in
euphotic zone. The number and biomass of bacteria at East
Polygon averaged 1,183 x 10' cells/ml and 26.62 mg C/m',
respectively. Below the euphotic zone, bacteria and their
biomass declined to their lowest values ( 103 x 10' cells/ml and
4.6 mg C/m') in near-bottom waters of 2, 700-3,000 m. Although
microflora activities showed little variation with depth, dark
assimilation of CO, by bacteria increased from surface layers
to the bottom at Stations 2, 4, and 5. At Station 1 , maximum
bacterial activity occurred in surface waters. Thus, the eastern
Bering Sea possessed relatively high numbers, biomass, and
activities of bacterioplankton in the surface microlayer and
euphotic zone, but values tended to decline with depth.

Microbiocenoses in the central basin and in the Gulf of
Anadyr exhibit a position between northern and southern
regions. The central basin is relatively shallow (45-145 m),
with a sharp thermocline (between 25 and 45 m, temperatures
ranging from 6.0 to 1 .0°C at Station 9) even though dissolved
O, saturation remained constant with depth.

57

The bacterial density and biomass varied considerably
between stations. Maximum average values of total numbers
(1,103 X 10' cells/ml) and bacterial biomass (24.83 mg C/m')
occurred at Station 6 and minimum values at Station 1 8, where
values averaged 513 x 10' cells/ml and 11.55 mg C/m\
respectively.

The distribution of bacterioplankton in the water column
also varied with depth (Figs. 1,2). Numbers increased at the
thermocline. In contrast to East and South Polygons, the
surface microlayerhere lacked high concentrations of bacteria.
Total numbers and biomass of bacteria averaged
691 X 10' cells/ml and 15.5 mg C/m', respectively. Highest
density of bacterioplankton occurred in the euphotic zone, and
cell number and bacterial biomass averaged 790 x 10' cells/ml
and 17.8 mg C/m', respectively. Bacterial numbers declined
with depth, but near the bottom, numbers reached a density of
708 X 10' cells/ml.

Vertical and honzontal distribution
86 89 100 104

, ■

05
10

E 15

t 25

a

os'

10

15

Vertical and horizontal distribution

Scale 10 /ml

05 10 15

Stall

L>n Localion^

"^

^ 86

^r

vV

! ^'

r

"96

•

^89^

"^

^ si 100
• 104

102 '

Fig. 1. Distribution of bacterial population in the northern Bering Sea,
summer 1988.

Compared to other areas, bacteria in the central basin
showed the lowest activity (Table 1 ), and rates of dark CO,
assimilation compared with those in oligotrophic waters.
Maximum activity of bacterioplankton occurred at Station 7,
where rates averaged 1 . 1 1 /ig C/l/d. At Stations 6, 1 8, and 19,
all rates varied between 0.20 and 0.30 jjg C/l/d.

In the surface microlayer and euphotic zone, microflora
showed similar rates of dark CO, assimilation, averaging about
0.50 ng C/l/d. Near the bottom, rates averaged 0.37 /Jg C/l/d.
Thus, in the central basin with shallow depths and strong
thermocline, the bacteria numbers and biomass are modest but
bacterial activity is low.

In the Gulf of Anadyr, river effluence influenced microbio-
cenoses. The Anadyr River discharges nearly 41 km' yearly
into the Gulf of Anadyr (Dobrovolski & Zalogin, 1982).

Fig. 2. Distribution of bactenal population in the southern Bering Sea,
summer 1988.

During the summer, surface salinities in the gulf waters declined,
and terrestrial microorganisms and suspended organic matter
of terrigenic origin enter the sea. Consequently, bacteria that
absorb to suspended matter may seriously influence the structure
of coastal bacterial populations.

Total numbers and biomass of bacterioplankton in the
Gulf of Anadyr are high (Table 1 ) and as high as those in the
northern basin. Maximum numbers and biomass occurred at
Stations 24 and 26 located in the gulf coastal waters, with
minimum values at Station 22 nearest the open sea. Vertical
profiles of bacterioplankton showed some increase in both
numbers and biomass with depth (Fig. 3). The bulk of
bacterioplankton concentrated in the euphotic zone where total
numbers and biomass averaged 910 x 10' cells/ml and
20.5 mg C/m', respectively. Near-bottom waters contained the
lowest density of bacteria in the water column.

Bacterioplankton in the Gulf of Anadyr showed the lowest
activity relative to other studied areas. This suggests that most
of the microflora were dormant. The highest activity of
microbiocenoses occurred at Station 26, the lowest activity at
Station 1 1 . Dark CO, assimilation by bacteria at those stations
averaged 1.11 andO. 17 ^ug C/l/d, respectively, and distributed
evenly throughout the water column. Dark CO, assimilation in
the surface microlayer, euphotic zone, and near the bottom
ranged between 0.48 and 0.50 ^ug C/l/d. Thus, high density of
bacterioplankton and low activities of microbiocenoses
characterized the shallow Gulf of Anadyr with its sharp
thermocline and low surface salinity. Generally speaking,
bacteria remained constant with depth, although at Stations 1 5
and 22, highest numbers and activities of bacterioplankton
occurred at the thermocline.

In conclusion, by studying bacteria in the Bering Sea in
summer 1988, it was possible to assess the status and variance
of total number, biomass, and activities of bacterioplankton in
relation to different hydrological and chemical conditions and

58

Venical and horizontal disinbuiion of cells.

Siaiion Locaiions

"."X

-h 4

)

y 24

1
1
I

C::

Fig. 3. Distribution of bacterial population in the Gulf of Anadyr of the
Bering Sea, summer 1988.

to compare them with the data obtained in previous years.
Relating bacterial numbers, biomass, and activities with other
oceanographic parameters, it was possible to analyze the
microbiological conditions with increasing anthropogenic load
in the Bering Sea ecosystem.

Total Number, Biomass. and Activity of Bacterioplanktim in
the Chukchi Sea

Until recently, there has been no microbiological studies
in the Chukchi Sea ecosystem. The first investigations,
conducted in suinmer 1988, focused on bacterioplankton, their
distribution, and biological status of the microbiocenoses.
Microbiological studies included variance across the region,
vertical distribution of bacterial nuinber, biomass, and activity.

The Chukchi Sea is one of many adjacent seas of the Arctic
Ocean. It freely communicates with cold waters to the north
and limitedly with the Pacific. Nevertheless, every year
30,000 km' of water flow into the Chukchi Sea from the Pacific
through the Bering Strait (Dobrovolski & Zalogin, 1982). Sea
water teinperatures depend mostly upon solar warming and
autumn-winter cooling. The space-time scales for salinity
depend on the inflow of Pacific waters and river waters from
coastal areas. The horizontal and vertical variance of dissolved
oxygen and biogenic elements affect the formation and growth
of microbiocenoses.

The analysis of results (Table 2) shows that total number
of bacteria and their biomass in the Chukchi Sea varied across
locality and depths. In coastal waters of Chukchi and Alaska,
maximum numbers and biomass of bacteria occurred. These
regions are strongly influenced by both river effluence and
Pacific Ocean waters. Deep-ocean waters from the Pacific,
which are warm and enriched with biogenic nutrients, penetrate
through the Bering Strait and mix with Chukchi Sea, resulting
in varied growth and distribution of microbiocenoses across
the Chukchi Sea. The activity of Chukchi littoral bacteria was

high and equal to that of mesotrophic waters. Bacterioplankton
showed the lowest activity in Alaskan waters. The distribution
of bacterioplankton along sections across different water types
(Fig. 4) can be attributed to water depths (0-45 m), temperature
(0. 1-5.2°C), salinity (30.6% to 33.6%), and dissolved oxygen
(from 51% to 98%).

TABLE 2

Assessments of population, biomass and dark CO, assimilation by
bacteria in Chukchi Sea Waters, summer 1988.

Sea regions Total population Bacterial

explored of bacteria bioinass

10' cells/ml (/igC/1)

Dark CO,
assimilation
by bacteria,

pg C/l/d

Sea northern
region

443 - 1987
913

9.97-44.71
20.55

0.13-2.79
1.00

Alaska coastal
region

443 - 1908
923

9.97 - 42.93

20.97

0.12- 1.23
0.66

Sea central
part

496-1718

875

11.16-38.65
19.69

0.47-4.01
1.61

Chukchi
coastal area

305- 1385
967

6.86-31.16
21.76

0.47 - 3.67
1.57

On the whole
over the Sea

305 - 1987
919

6.86-44.71
20.69

0.12-4.01
1.21

Maximum density of bacteria (averaging
997 X 10' cells/ml) occurred near the bottom in the Chukchi
Coastal waters. In the euphotic zone and surface layer bacteria
and their biomass were almost 1 .5 times lower than those near
the bottom.

In the Alaska littoral zone, bacterioplankton were most
abundant between and 25 m. In this layer, numbers and
biomass averaged 92 1 x 10' cells/ml and 17.92 mgC/m'. In the
surface microlayer and near the bottom bacterioplankton were
somewhat lower than the euphotic zone.

Due to mixing in the northern area of the sea, bacteria
remained constant with depth as did hydrological and chemical
factors. In the Chukchi Sea, the growth of bacteria equalled
that of mesotrophic waters. The highest number of
bacterioplankton occurred at Station 46. where bacteria and
their biomass averaged 1.154 x 10' cells/ml and
25.96 mg C/m'. respectively. High bacterial activity also
occurred at Station 45. The highest daily dark CO, assimilation
by bacteria was averaged (2.08 /ig C/1) at Station 50. where
bacterial numbers and biomass average 765 x 10' cells/ml and
17.01 mg C/m'. respectively. Vertically, total number, biomass,
and activity of bacterioplankton increased from the surface
microlayer to the bottom (Fig. 3).

The waters in the central basin of the Chukchi Sea showed
variable temperatures and dissolved oxygen. Waters mixing
over this area distributed bacteria within specific localities.
Maximum numbers occurred at Stations 55 and 74, and
numbers and biomass of bacteria averaged 1,028 and

59

5;

15.

<5
55J

Vertical and honznntal disuihulion ol celK

69 61 57

10 telK/m

5 10 15

SIdUur

i.ic

liur

45

47

•'

,30

(

y

•

•

57

^x

r

ba

•-

^61

-•

> 69

64
• -

65\

--• \

V^

•74

^■^

Fig. 4. Distribution ofbacterial population in the Chukchi Sea, summer 1 ?

l,108x lO'cells/ml and 23. 14and24.94mgC/m\ respectively.
Minimum numbers and their biomass occurred at Station 57.
where values averaged 446 x 10' cells/ml and 10.49 mg C/m\

In the central basin, highest bacterial activity compared
with the other study sites. Maximum dark CO, assimilation by
bacteria occurred at Station 64, where the rates equaled that of
eutrophic waters. Minimum values occurred at Station 74.
Vertically, numbers and biomass of bacterioplankton peaked
between 0.5 and 25 m thick relative to values in the microlayer
and near-bottom waters.

In conclusion, microbiological studies were made for the
first time in the Chukchi Sea. Water masses of the Chukchi Sea
showed a high level of microbiocenoses growth comparable to
mesotrophic waters. Additionally , bacterial numbers, biomass,
and activity in the waters of the Chukchi Sea exceeded those
found in the Bering Sea.

4.1.2 Thymidine Incorporation, Frequency of
Dividing Cells, and Growth Rates of
Bacterioplankton

ROGER B. HANSON and CHARLES Y. ROBERTSON

Skidaway Institute of Oceanography. Savannah. Georgia. USA

Introduction

The Third Joint US-USSR Bering & Chukchi Seas
Expedition offered a comparative regional and depth analysis
of bacterioplankton in the ice-free Chirikov basin and the south
Bering Sea during late July and early August 1 988. This study
focused primarily on the Chirikov basin, the region between
the St. Lawrence Island and the Bering Strait. Two deep-water
stations in the south Bering Sea ecosystem were also examined.

The principal objectives were to characterize the spatial
distribution and potential growth rate of bacterioplankton, to
estimate bacterioplankton productivity, and to assess their
importance relative to primary production in the western and
eastern Chirikov basin. The results from this study provided
some essential, first time estimates of bacterioplankton
production, growth rate, and biomass in the shallow ecosystem
of the northern Bering Sea and in deep waters of the south
Bering Sea.

60

Materials and Methods

Study Area and Slalion Locations

The second leg of ihe 1988 US-USSR cruise aboard the
research vessel Akademik Korolev focused pri manly on the
shallow Chirikov basin (<50 meters), the region between
St. Lawrence Island and the Bering Strait (see Frontispiece). In
the Chirikov basin, three major water types occur and are
bathymetrically steered northward across this northern Bering
Shelf.

Anadyr water (AW) is located in Soviet waters along the
western boundary of the system. The Bering Shelf water
( BSHW) is restricted to the central basin; and Alaskan Coastal
water ( ACW) is located near the Alaskan coast and forms the
eastern boundary of the northern shelf ecosystem. These
waters are identified by temperature/salinity profiles and bottom
water properties. In the summer, AW is characterized with
salinities >32.5"/(ki and temperatures <I.5°C, BSHW with
salinities of 31.8 to 32.5"/iki and temperatures of 0-1.5°C. and
ACW with salinities of <31.8"A«i and temperatures of >4°C
(Walsh f/«/., 1989).

Two additional areas were also made in deep water of the
south Bering Sea basin near the Aleutians (see Frontispiece).
Bacterioplankton dynamics were measured at Station 1 10 in
the South Polygon (53°9'N. 175°9'W) and at Station 113, the
old GEOSECS station in the eastern Bering Sea basin (53°2'N,
177°3'W).

Physical Measurements

Salinity, temperature, and depth data were collected using
a Sea-Bird SBE9 CTD/General Oceanic Rosette System. This
information was used to select water depths for bacterioplankton
samples.

TCA and were dissolved in Aquasol. Radioactivity, corrected
for counting efficiency using an internal 'H standard, was
detennined by liquid scintillation.

Bacteria in 10-ml water samples were preserved with
0.2 |im filtered formaldehyde (2% final concentration) and
stored at 5°C. One to 3 weeks following the cruise, bacteria
were stained with Acridine Orange and filter on 0.2 |im
Nuclepore filters for counting total bacteria in 10 microscopic
fields filter ' (Hobbie etal.. 1977), along with dividing cells in
20 microscopic fields filter ' (Hagstrom el al., 1979). The
frequency of dividing cells were calculated relative to the total
number of single plus dividing cells. Bacterial numbers and
dividing cells were determined by epifluorescence microscopy .

Estimates of cell production and growth rates in natural
populations of bacteria were calculated using two different
techniques: thymidine incorporation into DNA material using
the theoretical conversion factor of 2 x 10'* cells mole '
thymidine incorporated (Fuhrman & Azam, 1982) and the
frequency of dividing cells using the empirical relationship
between FDC and specific growth rate (u) of In u = 0.81
(FDC) -3,73 for southern ocean bacterioplankton (Hanson
etal., 1983).

Growth rates were calculated from estimates of cell
production divided by standing stocks of bacteria. To convert
cell production and standing stocks to carbon, an estimate of
cell carbon was assumed to be 10 fentogram C cell ' based on
estimates from Antarctica and British Columbia (Fuhrman &
Azam, 1980; Fuhrman, 1981).

Statistics Analysis

Data transformation and statistics analysis (i.e.,
correlations, slope analysis, t-test, ANOVA) were computed
with SAS, Inc., software.

Bacterioplankton Measurements

On the shallow Bering Sea Shelf, water samples for
bacterioplankton measurements were collected from ? depths
at 12 stations using 1.7-1 Niskins bottles on the rosette. Sample
depths were chosen to represent surface mixed waters,
hydrographic conditions within the region (i.e.. themiohalocline
or midwater column), and near-bottom waters. In the deep
Bering Sea at Stations 110 and 113, water samples were
collected from 1 2 depths: 6 depths in the upper 250 m of the
water column and 6 depths over the remaining water column
down to the bottom.

Bacterioplankton measurements included

l"H-methyl|thymidine incorporation, bacterial numbers and
frequency of dividing cells, and empirical growth experiments.
For thymidine incorporation (Fuhrman & Azam. 1982).
unaltered ?0-ml water samples were transferred to an 8-oz
sterile Whiri Pak bag. | 'H-methyl|thymidine (84.8 Ci mmol ' )
was added to obtain a final concentration of 20 nmoles 1 '.
Water samples were incubated in the dark at in situ surface
temperatures. After 3 h. samples were chilled in an ice bath and
ice-cold trichloroacetic acid (TCA) was added to a final
concentration of S'/f TCA. After30minonice, 25-ml replicate
samples were filtered on 25-min Millipore cellulose acetate
filters of 0.45 |i pore size. The filters were rinsed with cold 57c

Results and Discussion

Bacterioplankton. Thymidine Incorporatum. and Frequency
of Dividing Cells

Anadyr water ( AW) : Rates of thymidine incorporation by
bacterioplankton along the western boundary of the Chirikov
basin remained constant with depth, except at Station 86 where
rates refiected the themiohalocline in the Bering Strait
(Frontispiece, Figs. Ia,b). Ratesaveraged 1.37 pmolesl' h ' in
AW (Table I ). Salinity profile at Station 86 characterized low-
salinity ACW in the upper 15 m and high-salinity AW below
30 m. Rates of thymidine incorporation correlated strongly
with temperature but not with the index of the population
growth rate (i.e., specific activity of thymidine incorporation)
(Fig. 2, Table 2).

Bacterial populations were generally more abundant in
surface waters in AW and averaged 3.7 x 10" cells 1 '. Highest
numbers occurred in the surface waters of the Bering Strait
(Station 86, Fig. la). Bacteria in these waters correlated with
the narrow range in water temperatures (Fig. 3. Table 2). This
relationship to the index of population growth rate was similar
to that found for ACW (Fig. 2, Table 2).

The frequency of dividing cells, an index of cellular
growth rate, ranged from 4 to 8% dividing cells in surface

61

waters at all stations. Below the minimum frequency of
dividing cells (<4%), dividing cells again increased with depth
to5.1%nearthebottom(Figs. la,b). The frequency of dividing
cells averaged 4.4% dividing cells over the water column. The
specific activity of thymidine uptake, population growth rate,
averaged 4.04 x 10 -' moles cell ' h ' (Table 2) and showed no
relation to the frequency of dividing cells, cellular growth rate,
except at Station 86. Both indices of growth rates showed no
relation to temperature (data not shown).

Alaskan Coastal water : With the exception of Station 9 1
where the water column was isothermal ( 10°C), ACW showed
a strong thermocline near 10 m (Figs. 4a,b; 5a,b). Rates of
thymidine incorporation along the eastern boundary of the
Chirikov basin averaged 1 .55 pmoles 1 ' h ' but not significantly
different (P = 0.05) from the rates measured along the western
boundary (Table 1 ). At Station 84 in the Bering Strait and
Station 91, thymidine incorporation varied little with depth,
whereas at Station 92, the highest rates occurred within the
thermocline. At Station 102 northeast of St. Lawrence Island,
thymidine incorporation increased in the high salinity bottom
waters (Fig. 4b).

Rates of thymidine incorporation were related inversely
with temperature and positively with the index of the population
growth rate (Fig. 2, Table 2). Rates measured in the bottom
waters of the eastern Bering Straits clustered with rates measured
in the waters of the western boundary of the Chirikov basin
(AW, see Fig. 2), suggesting similar bottom waters flowing
through the eastern and western sides of the Bering Strait.

Bacterial populations averaged 3.6 X 10* cells 1' (Table 1)
and were also similar to population densities in AW. Highest
densities occurred above the thermocline at Stations 92 and
102 and were approximately constant with depth at Stations 84
and 91 (Figs. 4a,b; 5a,b). Bacterial populations in ACW
showed no relation to temperature.

The frequency of dividing cells in ACW averaged 0.037
(3.7% dividing cells) (Table 1). The highest frequency of
dividing cells (5.0%) occurred near the themiocline and declined
towards the bottom, except at Station 91 where dividing cells
remained constant over the water column. The specific activity
of the population averaged 4.85 x 10^' moles cell ' h '
(Table 1 ) and was similar to the specific activity measured in
AW. The specific activity showed no relationship to dividing
cells except at Station 84 in the Bering Strait. Similar observation
was seen at Station 86 in the western Bering Strait.

Bering Shelf water : Waters at Stations 89, 100, 104, and
1 06 characterized BSH W ( Figs. 2,3 ). Waters at Stations 89 and
106 nearest to the western boundary of the system typify AW
with bottom temperatures <2°C, whereas low-salinity ACW
dominates surface waters near the eastern boundary at Stations
100 and 104. Rates of thymidine incorporation averaged
1 .70 pmoles 1' h ' (Table 1 ). Highest rates in BSHW occurred
at Station 104, northeastof St. Lawrence Island (Fig. 3). Rates
were highly variable with temperature (P > 0.05) but correlated
significantly with the specific activity (Fig. 2, Table 2).

Bacterioplankton populations averaged 5.2 x 10" cells 1 '
(Table 1 ) and were significantly higher than the Anadyr and
ACWs ( ANOVA, P < 0.05). The highest densities occurred

TABLE 1

Vertical distribution of averaged bacterioplankton parameters from

the three water types measured in the Chirikov basin. Units:

N = number of samples averaged at each depth, depth = meters.

Thymidine Incorporation = pmoles 1 ' h ',

Bacteria = 10" cells 1 ', Specific Activity of

thymidine incorporation = 10-' moles cell ' h '.

Anadyr Waters

Thymidine

Freq.

Specific

N Depth

Incorp.

Bacteria

Dividing

Activity

4 05

1.66

4.2

0.035

4.02

4 10

1.46

4.7

0.056

3.01

3 15

1.31

3.3

0.038

3.95

3 20

1.07

1.9

0.032

6.04

2 25

1.26

44

0.053

2,92

4 40

1.31

3.6

0.051

4.23

average

1.37 + -0.11

3.7 + -0.3

0.044 -1- -0.004

4.04 -1- -0.36

Alaskan Coastal Waters

Thymidine

Freq.

Specific

N Depth

Incorp.

Bacteria

Dividing

Activity

05
10
15
20
25
30-35

1.39
1.53
1.55
1.81
1.58
1.54

3.1
4.4
3.5
3.9
3.9
2.3

0.036
0.050
0.038
0.033
0.026
0.035

4.66
3.48
4.69
4.96
4.82
6.55

average

1.55-0.09 3.6-0.2 0.037-0.003 4.85-0.54

Bering Shelf Waters

Thymidine
N Depth Incorp,

Bacteria

Freq.

Dividing

Specific

Activity

3 05

1.89

5,1

0.051

3.94

3 10

1.87

4,7

0.044

3.71

4 15

1.97

5,7

0,044

3,52

4 20

1.58

6,1

0,034

2,96

3 25

1.57

5,0

0,029

3,33

3 30-40

1.30

3,8

0.027

3,41

average

1.70-0,19

5,2-0,5

0.038-0,003

3,45-0,28

overall

mean

1,54-0,08

4,1-0.2

0,040-0.002

4,11-0,24

above or within the thermocline. Bacteria numbers were also
highly variable with temperature and specific activity
(Fig. 3, Table 2).

The frequency of dividing cells averaged 0.038 (3.8%
dividing cells) (Table 1 ), In general, frequency of dividing cells
decreased from 5.1% in the surface to 2.9% below the
thermocline. The specific activity averaged
3.45 X 10^' moles cell ' h ' (Table 1 ), which was significantly

62

THYMIDINE INCORPORPATION

12 3 4

I — » — I — I — ' — I — r-

THYMIDINE INCORPORPATION

12 3 4

I — T~i — r — I — I — I — I — I — I — r — ' — ' — ' — ' — I — ' — ' — ' — ' — I

J

BACTERIA

) 2 4 6 8 10

5

A oAnadyr
\ ^^ Waters

10

IS

CTA

^ Stc. 86

^20

\

\

L

30

/ 1

/ 1

35

/ 1

40

K 6

45

.

BACTERIA

2 3 4 5 6

7 8 9

Anadyr

5

Q 4

Waters

10

6^^

Sto. 95

15

Js-'O

X
1—

Q.20

LiJ
Q

23

- <^ /

30

y^^^

35

;\.

40

O \k

FREQUENCY OF DIVIDING

12 3 4 5 6 7 8

I t I I I [ I I I I I I I I I 1 I I I 1 I 1 I I I I I I I I I I I I I I

§

18

15 -

15 -

^ 20 -

a. 20

UJ,5|.
Q

25 -

30

48 1-

SPECIFIC ACTIVITY

4 6 8

10
— 1

TEMPERATURE

123456789 10
I ' ' ■ ' 1 ' ' ' ■ I ' ■ ■ ' I ' ' ' ' I ' ' I I I I I I I I I I ■ ■ I

SALINITY

31 32 33 34 35

—I — T — I — T — 1 — f—T — I— I— I — I — I — I — I — r— I — I — I — I — I — I

5

10

15

X
I—

Q.20
UJ
Q
25

35
40

FREQUENCY OF DIVIDING

12 3 4 5 6 7 8

ftTIT]llll|IIT1ITTI(I>1ll|ITI)Illlt)

SPECIFIC ACTIVITY

2 3 4 5 6 7 8

I I I I I I I I '' I I I ' I ' I I ' I ' I I I I I I I I ' I I

TEMPERATURE

3456789 10

■ I ■ ' I ' I ' 1 1 1 1 I I I 1 1 I I ■ I I I I I ' I I ' ' ' 1 1 1 1 1 1

SALINITY

31 32 33

5 -

iiTT|tiii|ii — I r' \' 1

34
-" — 1

9

15

-e

X

1

1-
a.

20

- 6

UJ

Q

25

.

30

1

35

J

40

. 6

to.

Figure la. The vertical distribution of thymidine incorporation (pmoles 1
specific acliviiy of thymidine incorporation (10'-' moles cell

' h '), bacteria (10' cells 1 'l, frequency of dividing cells ("5 of total bacteria),
h '), temperature (°C). and salinity ("A.O at Stations 86 and 95 (AW).

63

THYMIDINE INCORPORPATION

12 3 +

THYMIDINE INCORPORPATION

—I — r--r — f ' ■ r

-T 1 1 1 1 1

BACTERIA

2 3 4 5 6

7 8 9

s

10

: ,7

Anadyr
Waters
Sta. 96

15

X
h-

Q.20
LJ
Q
25

■ i

30

I
1

35

1

40

L i 6

2

— 1 1 r-

3 4

—I r— T r— t — 1

BACTERIA

23456789

-T — r — 1 — I — I — I — > — 1

Anadyr
Waters
Sta. 98

5

10

15

I
I—

a. 20

UJ
Q
25

40

FREQUENCY OF DIVIDING

2 3 4 5 6 7 8

I I ' I ' ' r ' ' ■ ' I ' ■ ' I I ' ' ' ' I ' ' I ' I ■ ' ■ ' I

SPECIFIC ACTMTT

m-i-P-r-i-r-T-n

.X)

1

2

TEMPERATURE

3 4 5 6 7 8 9

10

0^°

SALINITY

31 32 33

34

5

- Q

1

t

I

10

- 6

I

L

15

-

i

\

X
1—

Q. 20
UJ
Q
25

- 6

I

i

30

- '

35

- 1

40

-A

I

k

FREQUENCY OF DIVIDING

2 3 4 5 6 7 8

r T r r 1 r n

r ^ T y y ii i - ^ t i i t t " ^ i " t~t |~t~t i t t

SPECIFIC ACTIVITY

5

2

3 4

5 6

7 8

-

10

-

i<^0

15

I
1—

Q. 20
Ld
Q
25

-

\

1
1

^

s

ii!i

30

\

\

\
\

35

"

\

\

40

L

X

iD

TEMPERATURE

1 23456789 10

1 ■ ■ ■ I I ' ' ' ■ I ' ' ' ' I ■ ' ' ' I ' ■ ' ■ I ' ' ' ' I ' ■ ■ ■ I ' ' ' ' I ' I I ' t

SALINITY

15

I
h-

Q.20
LjJ
Q
25

30
35

40

31 32 33 34

— 1 — r — ) — I — r— I — I — I — I — I — I — I — I — I — I — I

Q

I
O

6

Figure lb. The vertical distribution of thymidine incorporation, bactena, frequency of dividing cells, specific activity, temperature and salinity at
Stations % and 9X(AWs).

64

THYMIDINE INCORPORPATION

12 3 4

r-

T-

~r~

BACTERIA

1 2 3 4 5 6 7 B 9 10 11 12 13 14

1 ' 1 ' r ■ I ' 1 ' 1 ' 1 ' I ' I ' I ' I ' I ' I ' I '

-iSr-

-T«e — A- —

Bering Sea

sta. no

THYMIDINE INCORPORPATION

12 3 4

I — I 1 — 1 1 1 1 ( 1 — f — I r — I 1 1 1 1 1 1 1 1

BACTERIA

1 2 3 4 5 6 7 S 9 10 1112 13 14

1 ■ r ' r ' 1 ' I ■ r ' I ' 1 ■ [ ' [ ' I 1 I I I ' I ' I

^&—

Qffl > > &

Bering Sea
Sta. 113

FREQUENCY OF DIVIDING

12 3 4 5 6 7 8

1 ' I ' ' I ' ' ' I t ' ' ' ' I I ' ' ' I ' ■ ' ■ [ ' ■ ' ' I ' ' ' ' I

SPECIFIC ACTIVITY

12 3 4

-1 — 1 — I — I-

r~

OcO--A=-=^

-1 — r-

500
1000
1500

CL2000

u
a

2500

3000
3500
4000

^-

-©

(X

FREQUENCY OF DIVIDING

1 2 3 4 5 6 7 8

1 ■ ■ ' ' I I I I I 1 I I I 1 r ' ' I ' I I I ' I I ' I I I I I I I ' I

SPECIFIC ACTIVITY

1 2 3

-] — I — I — 1 — I — r—

1

TEMPERATURE

4 5 6 7 8

' ' I ' ■ ■ ' I ' ' ■ ■ I ■ I I ■ I ■ ' ' ' I '

SALINITY

1 2

I ■ ' ' I I '

32

1 1-

35

TEMPERATURE

3 4 5 6 7 8 9

SALINitV

33 34

500

: ^0

/

1000

: f^

: ®

DEPTH

sis

: /
: /
- /
'- 0)

c '

I '

3000

■ 1
- CD

• 1

3500

■ 1
' 1

; 6

4000

-OD

4000

Figure 2. The venical distribution of thymidine incorporation ( pmoies 1 ' h ' ), bacteria (1 0' cells I ' ), frequency of dividing cells (% of total bacteria),
specificactivity of thymidine incorporation (10 -' moles cell ' h'). temperature {°C), and salinity ("A.,) al Stations 110 and 1 13 in the south
Bering Sea.

65

§4.

O

o
u

_c

c

'-0 -I

I-

a)

"T 1 <-

5

—1 r-

10

Specific Activity

— 1

13

a

i_

o

B-^

o
u

c

c

s:

1 -

c)

I I ' I
1 2

I ' I
3 4

I I I I I
5 6 7

Temperature

I I I I I I I

9 10 11 12

-" — I — r-
10

—I
15

Specific Activity

4-

o -

o
u

_c

c

1'^

d)

A

^

■'A

^

a/

/o

/

A
A

/

/

I I I I I I I I I ' I I I I I ■ I

4 5 6 7 8 9 10 11 12

Temperature

Figure 3. Linear regression of thymidine incorporation plotted against specific activity (a.b)and temperature (c.d). Figs, 3a and 3c show data from ACW's
(circles) and AWs (squares), and Figs. 3b and 3d show data from BSHW's (triangle) and BSW's (diamond). Statistics for linear regressions are
given in Table 2.

66

THYMIDINE INCORPORPATION

12 3 4

THYMIDINE INCORPORPATION

12 3 4

BACTERIA

2 3 4 5 6

1 1 — ' — r — I — T — ' — r—

BACTERIA

4 5 6

Alaskan Coastal

Water

Sta. 84

5
10

15

X
I—

0.20
UJ
Q
25

30

35

40

Alaskan Coastal

Water

Sta. 91

FREQUENCY OF DIVIDING

5 6

' I ' ' ■ ' I ■

SPECIFIC ACTIVITY

TEMPERATURE

5 -

10 -

15

CL 20 -

bJ

Q

25 -

1

2

3

4 5 6 7 8

9

10

?

D

r— 1 — 1 — r

31

SALINITY

32 33

1 1 1 1 1 1 1 1 1 1 T—

34

30

40

FREQUENCY OF DIVIDING

2 3 4 5 6 7 8

' I ' ■ ' ' I ■ ' ' ' 1 ' ' ' ' I ' ' ' ' I ' ' ' ' I ' ' ' ' I

SPECIFIC ACTIVITY

2 3 4 5 6 7 8

TEMPERATURE

23456789

30

31

SALINITY

32

10
IS

Q.20

UJ

Q

25|-A

30
3S

40

-1 — I 1 1 1 T"

10

1 ' ' ' M ' ' ' ' 1 ■ ' ' ' 1 ' ■ ' ' 1 ' ' ■ ■ I ' ■ ' ■ I ■ ■ ' ' I

34

9
I

6

I

1

I
6

Figure 4a. The vertical distribution of thymidine incorporation (pmoles 1 ' h '). bacteria (10" cells 1'), frequency ofdividing cells (% of total bacteria),
specific activity of thymidine incorporalion (K)-' moles cell ' h '), temperature (°C), and salinity ("/m) at Stations 84 and 91 (ACW's).

67

THYMIDINE INCORPORPATION

12 3 4

I — I — I — I — I — 1 — I — I — 1 — I — I — I — I — 1 — I — I — t — I — 1 — I — 1

BACTERIA

123456789

Q. 20
UJ
Q
25

30

35
40

— 1 — 1 — <-
A

-I — 1 — r — <— I'll
"^-^ ©^

1 ■ ' I 1 1

-

d

^

Alas

kan Coastal

Water

L Sta.

92

THYMIDINE INCORPORPATION

12 3 4
r — 1 — 1 1 1 — I — r — 1 1 1 — 1 — 1 — 1 1 — 1 — I — 1 — 1 — 1 — 1 — I

BACTERIA

1 23456789

5

10

15

X
I—

Q. 20
UJ
Q
25

30

35

40

-~t--l - 1- T r r

1 , 1 I 1

•^

X

>

®

i

b

Alaskan
. Sta. 102

Coastal

Water

FREQUENCY OP DIVIDING

2 3 4 5 6 7 8

1

SPECIFIC ACTIVITY

2 3 4 5 6 7

S
10
15 -

Q_20
UJ
Q
25

30
35

40

1 ' ' ' ' I '

- o'

TEMPERATURE

1 23456789 10

1 I I I ' I ' I I ' I ' ' ' ' I ' ' ' ■ I ' ' ' ' I ' ' ' ' r ' ' ' ■ 1 ■ ■ ' ' I ' ' ' ' I

SALINITY

30 31

32

33 34

5

-

10

"^^"^^

. - ' ' ®^

IS

©^

— ^

T

/

1—

/

0.20

Cp A

UJ

n

25

6 h

30

■

35

-

FREQUENCY OF DIVIDING

12 3 4 5 6 7 8

5 -
10

15

0,20
UJ
Q
25

30
35

I ' ' ' ' I ' ' ' ■ I

' I ' ' ' '"i

SPECIFIC ACTIVITY

12 3 4 5 6 7 8

.30

40

5
10
15 -

Ql20
UJ
Q
25

30 -
35 -
40 -

I ' ' ' ' 1 '

TEMPERATURE

3 4 5 6 7 8

9 10

I ' I I ' I I ' ' I I ' ' ' ■ r ' ' ■ ■ I ' ' ■ ■ I ' ' ' ' I ■ ' ' ' I ■ ■ ■ ' I '

SALINITY

31 32

33

34

— I — I — I — I — I — \ — 1 — I — I — 1 — 1 — r-

©■

o

I

6

Figure 4b. The vertical dislribulioii ol ihyniidine incorporation (pinoles 1 ' h '). bacteria ( 11/ col Is I '), trcqiiency ol dividing cells (% of total bacteria),
specific activity ol thymidine incorporation (I0-' moles cell ' h '). temperature ( C), and salinity ("/.) at Stations ^1 and 102 (ACW's).

68

THYMIDINE INCORPORPATION

12 3 4

I — I — I — I — I — r — ' — « — I — • — 1 — ' — r

"T — T — I — 1 r-

BACTERIA

123456789

15

1—

Q. 20
UJ
Q
25

-1 — 1 — I 1 — I 1 \ — 1 — I — I — I — 1 — I — 1 1

Berinql Shelf Waters
Sta.

10

15

I
f-

0.20
LiJ
Q
25

30

35

40

THYMIDINE INCORPORPATION

12 3 4

— I — r— 1 1 — 1 1 — I— I 1 1 — I 1 — I 1 — I 1 1 1 — 1

BACTERIA

234567B9
1 — 1 — I — t — I — I — • — T — ' — r — I — I — ' — I — ' — 1

Bering Shelf Waters
Sta. 106

FREQUENCY OF DIVIDING

12 3 4 5 6 7 8

I I I I I I I I I 1

SPECIFIC ACTIVITY

.12345678

5

-

till

I » ' '

1 T 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 r r 1 1

10

r

-^^

15

-

>^ :o

I
1-

0.20
bJ
Q
25

-

^

-

/

30

-

/
/

\

/

\

35

-

/

/
/

/

\

40

L

O

A

TEMPERATURE

1 23456789 10

ri 1^1 I r I I ^'7 T T I r [T-i TT T r t- r r I T ^ ^' I ' ' ' ' I ' ' ' ' I t -f-t-i

SALINITY

30 31 32 33 34

Q. 20
LiJ
Q
25

30 -

— I 1 1 1 1 1 1 1 1 < \

9^

I
I

FREQUENCY OF DIVIDING

12 3 4 5 6 7 8

I I ' ■ I I ' I ' ■ [ ■ ' ' M ' ' ' ' r ' ' I ■ I ■ ' ■ ' I ' ■ ■ ' I

SPECIFIC ACTIVITY

12345678

5 -

15

Q. 20
bJ
Q
25

30
35

I ' ' ' ■ I ■ ' ' ' I t ■ I I 1 I I I I 1

/^t)

TEMPERATURE

123456789 10

I I r I I I I I I I [ I I I I I I ri 1 I * T I rt

T ITT'T T riT

rf-T-TTT- mn

SALINITY

10

15

0.2<B

Ul I

Q I

2^

I

3d)

35 -

-T 1 1 1 1 1 1 — 1 1 1 1

.©'

9

Figure 5a. The vertical distribution of thymidine incorporation (pmoles I ' h '), bacteria ( 1 0* cells 1'), frequency of dividing cells (% of total bacteria),
specific activity of thymidine incorporation ( 10 '' moles cell ' h 'I, temperature (°C), and salinity ("A.;) at Stations 89 and 106 (BSHW's).

69

THYMIDINE INCORPORPATION

THYMIDINE INCORPORPATION

12 3 4

BACTERIA

1

5 -

10

15 -

I
h-
D. 20 -
LxJ
Q
25 h

35

B^ing ^helf Waters
Sta. 100

1

5 -

10

15

I
h-

Q.20
LJ
Q
25

30

35

40

BACTERIA

23456789

"I — ' — 1 — I — r-

Bering Shelf Waters
Sto. 104

FREQUENCY OF DIVIDING

12 3 4 5 6 7 8

I I I I I I I I I I I I I I I

I ' ' ' ' I

SPECIFIC ACTIVITY

TEMPERATURE

1 23456789 10

r»TTTTT>TTTTI t T'TT-rT I f TTTT-f 1'1 t 1 |Tr-rT T ^' Tl | t T r I 1

-^0

SALINITY

31 32 33

34

5
10

15

X
(—

Q. 20
UJ
Q
25

30

35

40

P^

o

FREQUENCY OF DIVIDING

2 3 4 5 6 7

' I ■ ' ' ■ I ' ' ' ' I ' ■ ' ' I ' ■ ' ' I ■ ' ' ■ t ' ■

SPECIFIC ACTIVITY

5

2 3 4 5 6

7 8

-

\ -"^

10

-

15

I
1—

Q. 20
UJ
Q

25

-O

30

-

35

4n

-

TEMPERATURE

123456789 10
I ' ' ' ' I ' ' ' ' I ' ' ' ' 1 ' ' ' ' 1 ' ■ ■ ■ I ■ ' I ' I ' ' ' M ' ' ' ' I ■ ' ' ■ I

30

10

15

I
h-

0.20
UJ
Q
25

30

33

40

SALINITY

31 32

— I — ^-~y — ' — ' — r —

33

34

I

Figure 5b. The vertical distribution of thymidine incorporation (pmoles 1 ' h'),bacleria(10''cellsl'), frequency of dividing cells {% of total bacteria),
specific activity of thymidine incorporation (10-' moles cell ' h '), temperature (°C). and salinity CVm) at Stations 1 00 and 104 (BSHW's).

70

15-1

10-

-t-i
O
D

m

a)

-1 1 1 1 1 1 1 r-

— I 1 r-

10

^5-,

Specific Activity

IS

. c)

10

■*->
U

o

m

O/'

a CO

-e-

■8

-> I I I I I — I — I — I — I — 1 — I — r — I — I — I — 1 — I — I — I — I — f— ' — I
1 2 3 4 5 6 7 8 9 10 11 12

Temperature

15

10

o
u

D

b)

/

/

/.

0/

0/ ^-

ii. £i

-^A

A
A

.iP

^

15

10

-t->

o

D

m

-T — r-
10

I
15

Specific Activity

d)

A

/

/

^ir

^ /
/

'^aO

/

aO

A

A

A
A

-\ — r—1 — I — I — I — I — I — I — I — I — I — I — I — I — I — I — 1 — I — I — I — I — I
1 2 3 4 5 6 7 8 9 10 11 12

Temperature

Figure 6. Linear regression of bacteria plotted against specific activity (a.b) and temperature (c,d ), Fig. 6c shows data from ACWs (circles) and AWs
(squares), and Figs. 6b and 6d show data from BSHW's (triangle) and BSW's (diamond). Statistics for linear regressions are given in
Table 2.

71

TABLE 2

Statistical analysis for linear regressions of plots in Figs. 5 and 6.

Variable abbreviations: Thy (thymidine incorporation), Bac

(bacteria), T (temperature), and Spa (specific activity of thymidine

incorporation) are the parameters for the regression analysis.

Statistics Abbreviations: F-value (value for data variance), r-

(correlation coefficient), C.V. (coefficient of variation). Intercept

(y-intercept). Slope (slope of the best linear regression), T-test (test

of null hypothesis (Ho), Slope >0).

Anadyr Waters

Regres. F value r- C.V. Intercept Slope T-test

Thy*T

5.6

0.23

22.7

1.94

-0.058

0.03

Thy*Spa

8.8

0.33

21.3

1.09

0.092

0.008

Bac*T

0.1

<0.01

29.3

3.44

0.015

NS

Bac*SPA

26.2

0.59

18.7

5.11

-0.322

0.0001

Alaskan Coastal Waters

Reeres.

F value

C.V. Intercept Slope T-test

Thy*T

33.4

0.64

22.7

-0.56

0.887

0.0001

Thy*Spa

0.5

0.03

37.9

1.14

0.056

NS

Bac*T

6.5

0.26

34.7

0.17

1.625

0.02

Bac*Spa

10.7

0.37

32.2

6.00

-0.564

0.004

Bering Shelf Waters

Regres

F value

C.V. Intercept Slope T-test

Thy*T

3.2

0.15

47.3

1.04

0.169

NS

Thy*Spa

6.2

0.25

44.2

0.50

0.347

0.02

Bac*T

1.6

0.09

40.1

3.93

0.315

NS

Bac*Spa

1.8

0.09

39.9

6.91

-0.507

NS

Bering Sea water

Regres.

F value

r-

C.V.

Intercept

Slope

T-test

Thy*T

98.2

0.82

70.1

-0.92

0.418

0.0001

Thy*Spa

23.4

0.51

114.1

-0.21

0.797

0.0001

Bac*T

79.2

0.78

46.4

-1.37

1.433

0.0001

Bac*Spa

8.4

0.27

84.5

1.87

2.038

0.008

lower than Anadyr and ACW" s (T-test. P < 0.05 ). The specific
activity again was unrelated to frequency of dividing cells
(T-test, P> 0.05).

Bering Sea water : The highest rates of thymidine
incorporation and numbers of bacterioplankton were measured
in the surface mixed layer of the south Bering Sea (Fig. 6).
Incorporation rates ranged from 5 pmole 1 ' h ' above the
thermocline to less than 1 pmole 1' h ' below the thermodine
and less than 0.2 pmoles 1 ' h ' below 100 m. Rates were
strongly correlated with temperature and specific activity
(Fig. 2, Table 2). However, this strong relation could be
attributed to any number of factors (e.g., phytoplankton
productivity or biomass in the upper mi.\ed layer).

Surface mixed layer processed the highest number of
bacterioplankton (1 x 10" cells 1 '), and numbers decreased to
less than l-2x 10'*cellsl' below l()()m(Figs. 5a,b). Likewise,
bacteria correlated strongly with temperature and specific
activity (Fig. 3, Table 2).

Surface waters also had the highest frequency of dividing
cells (4 to 7% dividing), but frequency of dividing cells
decreased with depth to less than 2% dividing below 500 m
(Fig. 6). At Station 1 10, bacterioplankton showed a secondary
peak in dividing cells at 1 ,500 m, and below 2,000 m dividing
cells increased with depth to nearly 12% dividing cells. Specific
activity showed a similar distribution to frequency of dividing
cells in the water column. In the mixed layer, specific rates
averaged 2.5 x 10-' mole cell ' h ' (Table 1) and decreased to
0.1 1 X 10 -' mole cell ' h ' below 500 m. At Station 1 10, both
specific activity and the frequency of dividing cells increased
with depth below 1,500-2,000 m. At Station 113, specific
activity, but not frequency of dividing cells, increased with
depth below 1,500 m (the old GEOSECS Station).

Spatial Distribution of Bacterioplankton

In the Chirikov basin, bacterioplankton dynamics showed
considerable variability through the water column and across
the water types. The regional depth distribution of
bacterioplankton parameters are summarized in Table 1 . In
nutrient-rich AW, the highest rates of thymidine incorporation
occurred in the surface and near bottom waters.
Bacterioplankton, frequency of dividing cells, and specific
activity, generally covaried with the rates of thymidine
incorporation, even though the water column was isothermal.

In nutrient-poor ACW, the thermocline was generally a
dynamic region in the water column for bacterioplankton
activity. Bacterioplankton, thymidine incorporation, frequency
of dividing cells, and specific activity peaked within the region
of the thermocline at water depths of 10-20 m, whereas in
BSHW, the upper mixed layer contained highest
bacterioplankton activity.

Like BSHW, the highest bacterioplankton activity occurred
in the upper mixed layer in the deep waters of the south Bering
Sea. Below the thermocline, bacterioplankton uptake of
thymidine diminished greatly even though measures of
population growth rate increased with depth in bottom waters.
In these deep waters, bacterioplankton populations were an
order of magnitude or two lower than upper mixed layer.

Comparison to other Marine Ecosystems

Thymidine incorporation data reported here for Chirikov
basin and south Bering Sea (0.0 to 4.7 pmoles 1' h') fell within
the range of values reported for other coastal-shelf waters and
adjacent and marginal seas in both high and low latitudes of the
Northern and Southern Hemispheres. In polar waters of
McMurdo Sound and the ice edge zone of the Ross Sea,
Antarctica, where temperatures range from -1.8 to 5°C year
round, Fuhrman and Azam (1980) found similar rates of
thymidine incorporation of 0.2 to 1 1 .3 pmoles 1 ' h"' (calculated
from values in Table 1, Fuhrman & Azam, 1980).

Within the Antarctic Polar Front (2.5°C) of the Drake
Passage, rates were also on the order of 0.1 to
10 pmoles 1 ' h ' over the upper mixed layer, but within the
productive marginal ice edge zone (-1 to 2°C) off the Palmer
Peninsula, rates as high as 200 pmoles 1' h ' were measured
(Hanson & Lowery, 1983). In northern latitudes off Nova
Scotia, Canada, Douglas et al. (1987) found thymidine

72

incorptiration rates ranging from 1 .4 pinoles 1 ' h ' in coastal
waters with temperatures of 6.5°C to rates of 4.7pmoles 1 ' h '
at the shelf break with temperatures of 7.5-1 0°C. In the Celtic
Sea where water-column temperatures varied from 8 to 15°C.
thymidine rates ranged from 0.24 to 0.81 pmoles (values
converted from data given in Table 3 in Joint & Pomroy. 1983).
In coastal shelf waters off NW Spain with temperatures of
I0-I8°C, rates of 0.1 to 10.1 pmoles 1' h' were reported
(Hanson ei al., 1986a; Hanson et al.. accepted). In other
temperate waters, rates ranged from 0. 1 to 20 pmoles I ' h ' for
California Coastal waters (calculated from data in Table 1 in
Fuhrman ct al.. 1980) and for southeastern US shelf waters
(Hanson t-i al., 1988). Therefore, results from the Chirikov
basin and surface waters of the south Bering Sea show that
bacterioplankton during this late summer period appeared as
productive as bacterioplankton on many continental shelves
and oceanic ecosystems in northern temperate and southern
polar regions.

Bacterioplankton are the most abundant group of marine
organisms in pelagic communities, yet the least understood in
regard to population structure, function, and interaction with
other pelagic communities in marine food webs. Total
bacterioplankton counts varied little with water type on the
north Bering Sea Shelf (overall 4.2 x 10"! 0.2 [S.E.J cells 1 ' ).
The highest density of bacterioplankton occurred in the surface
waters ofthe south Bering Sea (about 1.3x 10''cells I ')■ These
densities are quite similar to values reported for other polar or
subpolar regions (Fuhrman & Azam, 1980, 1982;
Hanson et al., 1983; Garrison et al.. 1986; Pomeroy &
Deibel, 1986; Douglas et al.. 1987; Kottnieier & Sullivan,
1987).

Estimate of Bacterioplankton Productivity and Growth Rate.s
Because of the uncertainty in the proportion of
bacterioplankton that use thymidine for DN A synthesis relative
to total metabolically active cells ( Douglas c/t//., 1987), we can
only estimate the productivity of the bacterioplankton in the
Bering Sea ecosystem. Our estimates are based on a theoretical
conversion factor of 2 X 10"* cells produced (mole of thymidine
incorporated) ' (Fuhrman & Azam, 1982), the accuracy of
which depends on a number of assumptions that have been
discussed previously (Fuhrman & Azam, 1982; Ducklow &
Hill. 1985; Douglas e/rt/., 1987).

Empirically derivedCF'sgenerally range 1 to5x lO'^cells
produced (mole of thymidine incorporated) ' (Kirchman «'?«/.,
1982; Riemann et al., 1984, 1987; Ducklow & Hill, 1985).
Acknowledging the relative accuracy ofthe theoretical CF. we
applied the theoretical CF and report the productivity of the
bacterioplankton in the Chirikov on the order of 1 -5 x I O*" cells
produced 1 ' h ', average 3 x 10" cells 1 ' h ' (Table 3). These
rates of cell productivity in the Chirikov basin are on the same
order as rates measured in other high and low latitude
ecosystems. In McMurdo Sound and the Ross Sea. Antarctica,
Fuhrman and Azam ( 1980) estimated cell productivity rangmg
from<(). 1 to 21 X 10" cells 1' h' (rates adjusted 1.54 times; a
theoretical CF of 1.3 x 10"* cells (mole of thymidine
incorporated] ' was originally applied to thymidine
incorporation for cell productivity estimates).

TABLK 3

Bacterioplankton production (mg carbon m - d '), bioinass

(g carbon m -), growth rate (u, d '). and doubling time

(Ln 2/u,days) in the Chiriko\ basin and south Bering Sea.

August 1 988. Bacterioplankton production based on estimates

from thymidine (Thy) incorporation and frequency of

dividing cells (FDC).

N Production

Biomass

Growth

Doubling

Thy FDC

Rate

Time

Anadvr Waters

2(J 263 835

1.48

0.18

3.8

Alaskan Coastal Waters

20 223 623

1.08

0.21

3.3

Bering Shelf Waters

20 245 1050

1.82

0.14

4.9

Bering Sea Waters (upper

mixed laver)

6 387 1770

3.00

0.13

5.3

Dividing-cell productivity by the total number of
bacterioplankton, an estimate of the specific growth rate of
bacterioplankton population can be calculated. Specific growth
rates in the three water types in the Chirikov basin are given in
Table 3. Growth rates were not significantly different across
the basin. Rates averaged 0. 1 8 day ' ( or a population doubling
time of roughly 5 days). The doubling time of 5 days is similar
to the doubling times reported for temperate coastal and shelf
waters ( 1 to 4 days, Fuhrman & Azam, 1982; 4 days.
Joint & Pomroy. 1983; 0.8 to 10 days, Hanson et al., 1986b,
1988).

Assuming a thymidine-active subpopulation of 50% ofthe
total number of bacterioplankton in the Chirikov basin, the
doubling time of this subpopulation is 2.5 days. The doubling
time of the thymidine-active bacterioplankton in Canadian
Shelf waters off Nova Scotia ranged from 0.5 to 1.2 days
(Douglas et al., 1987). Thus, mean growth rate for
bacterioplankton of high latitude ecosystems are in general
comparable to rates calculated for bacterioplankton in low
latitude environments.

Hagstrom et al. ( 1979) proposed a frequency of di\'iding
cells (FDC) method to estimate bacterioplankton growth rates
without incubation and radioactive organic substrates.
Theoretical consideration and empirical evidence have shown
that the frequency of cells in the dividing state is proportional
to the growth rate ofthe population ( Newell & Christian, 1981;
Larsson & Hagstrom, 1982; Hanson ('/«/., 1983). Tocalculate
growth rates by the FDC technique, a basic assumption is that
all cells are metabolically active. But because of inactive cells
in the population. FDC values underestimate the growth state
of the active population. Thus, estimates of bacterioplankton
growth rates using FDC error conservatively.

73

The FDC values in this study ranged from 1 to 1 2% of the
ceils dividing (averaged 4%). not much different from values
reported elsewhere. Using the empirical relationship between
FDC and specific growth rate, u (In u = 0.81[FDC]-3.73),
(Hanson ef «/., 1983), for southern ocean bacterioplankton. we
calculated a specific growth rate of 0.58 day ', a doubling time
of 1.7 days. Growth rates estimated from the FDC method in
the Chirikov basin were generally lower than those made from
thymidine incorporation. A similar conclusion was made by
Riemann ('/ al. (1984), although Newell and Fallon (1982)
found lower results for thymidine incorporation compared
with FDC. The results shown here for thymidine incorporation
and FDC procedures indicate doubling times between 2 and 5
days. Correcting for inactive cells, bacterioplankton growth
rates probably range on the order of 1 to 3 days during the late
summer period in the Chirikov and south Bering Seas.

In summary, bacterioplankton carbon production in the
Chirikov basin and the surface waters of the south Bering Sea
was estimated based on an average carbon content of
10 fentograms carbon per cell (Fuhrman & Azam, 1980).
From thymidine-based cell productivity estimates,
bacterioplankton production averaged 245 mg C m - d ' in the
Chirikov basin and 387 mg C m - d ' in the upper mixed layer
of the south Bering Sea (Table 3 ). Frequency of dividing cells-
based production was 2 to 5 times the thymidine-based estimates
(Table 3). The large difference between both estimates is
attributed to the relative accuracy of the theoretical conversion
factor and the empirically derived FDC equation. Thus, a
comparison of bacterioplankton production and phytopiankton
production in the Chirikov and south Bering Seas suggests that
bacterioplankton production ranges between 5 and 33% of the
phytopiankton production (Table 4). If we assume that the
average growth yield of marine bacteria is about 50% of the
organic matterconsumed, then bacterioplankton in these waters
may consume upwards to 70% of the total phytopiankton
production, but it is probably much less. Future bacterial
studies need to evaluate the incorporation of thymidine into
cellular components, growth kinetics, active cells, and empirical
relationships of thymidine incorporation and frequency of
dividing cells.

The uiithors ihank the US Fish ,ind Wildlife .Service (USFWS)
and Division of Polar Programs (NSF) for traveUi lid shipping assistance
and Mr. Steven Kohl (USFWS) for logistical arrangements that

TABLE 4

Comparison of bacterioplankton and phytopiankton production

(mg carbon m - h ') in the Chirikov basin and south Bering Sea.

August 1988. Bacterioplankton production estimated from

thymidine incorporation and frequency of dividing cells (see

Table 3).

Bacterioplankton Phytopiankton
Production Production

Anadyr Waters
(0-40 meters)

10.9-35.6

Alaskan Coastal
Waters
(0-35 meters)

9.3-25.9

Bering Shelf
Waters
(0-40 meters)

10,2-43.8

Bering Sea
Waters
(0-30 meters)

16.1-73.8

175

Percent
Bacterioplankton

6-20

209

221

5-21

7-33

9-74

175-221

5-^^

allowed the authors to participate in the Third Joint US-USSR Bering
& Chukchi Seas Expedition. Mr. Harold J. O'Connor (USFWS), the
US Project Leader, and Dr. Alia Tsyban, the USSR Project Leader,
represented the bilateral US-USSR Environmental Agreement under
Activity 02.07-2 1 1 . Dr. Terry Whitledge and Dr. Alia Tsyban acted
as chief scientists for the Americans and Soviets on the Soviet's RA'
Akadcmik Korolcv. The authors acknowledge the cooperation and
assistance of the captain, crew, and Soviet scientists during the
research cruise aboard the RA' Akademik Korolev.

74

4.1.3 Bacterial Production and Destruction of
Organic Matter

VASSILIY M, KUDRYATSEV, VLADIMIR O. MAMAEV*. and TAMARA F. STRIGUNKOVA*

^Institute of Global Climate and Ecoloi;y. Stale Committee for Hydrometeorology and Academy of Sciences, Moscow. USSR

'Bach Biochemistrs- Institute and the Academy of Sciences, Moscow, USSR

Introduction

Bacteria play an important role in mineralization and
detoxication of anthropogenic materials (e.g., oil hydrocarbons,
pesticides, anionic surfactants, and heavy metal compounds)
(Larsson & Lemkemeier, 1981; Tsyban, 1981; Bernard &
George, 1986;Braginsky, 1986; Sahasrabudhe& Modi, 1987;
Tsyban f/«/., 1987d; Kirsof/«/., 1988; O'Connor & Huggett,
1988). While considerable data have been published on the
processes and mechanisms of organic matter destruction, the
extent of biological self-purification have not been studied
thoroughly enough, especially in subarctic and arctic areas of
the World Ocean. In these regions, characterized by low
temperatures and increasing anthropogenic load, the role of
microbial transtomiationofcontaminants becomes considerably
more important. In this regard, the assessment of bacterial
production, destruction of organic matter, and the transfonnation
of toxic organic compounds of anthropogenic origin is very
important to determine the assimilation capacity, self-
purification of organic contaminants, and prognosis of marine
ecosystems.

Materials and Methods

The production-destruction process affected by bacteria
in the Bering and Chukchi Seas was studied in July-August
1988 during the third Soviet-American ecological expedition.
Bacterial production and the rate of organic matter (OM)
destruction was measured in the Gulf of Anadyr, Bering and
Chukchi Seas (Fig. 1 ).

Dark CO, assimilation was measured by the Romanenko
and Kuznetsov ( 1 974) method. Details are given in Methodical
Foundationsof Integrated Ecological Monitoring of the Ocean
( Tsyban ef«/., 1988) and Kuznetsov and Dubinina( 1989). To
determine dark CO, assimilation, water samples were taken
from standard hydroiogical depths with Niskin bottles and
added to 100-ml stoppered bottles. The bottles were tilled in
the same way as samples taken for soluble oxygen (i.e.. Hushed
with 3 water volumes). The bottles, filled with water, were
placed in dark sacks and 0.5 ml of NaV CO,(specific activity
about 20 X Kfcounts/min) were added. Bottles were stoppered
without air bubbles under the stopper. Duplicate samples were
taken from each depth. Two reference bottles were included at
each station and, apart from radioactive sodium carbonate, 1 ml
of 40% fomialdehyde solution was added. Bottles inside the
sack were tightly closed to light and incubated at surface
seawater temperature.

BactenjI Decomposition

produclion 1 of organic matter

0.5g CIm- BJ per l.Og Clttt

• Station number

36 S^^
^35

d1 .19

Fig. 1 . Bacterial prttductitin and dcctMiipttsitnin olarganic matter in the 0.5 to
4,'^ m layer in the Gulf of Anadyr, and central Bering Sea. summer,
1988.

After suitable exposure, depending on temperatures,
formalin ( I ml ) was added to each bottle. Water samples were
filtered through a "Sinpor" membrane filter having pore diameter
0.35 or 0.45 |Jm and immediately treated with 1 '7c hydrochloric
acid to remove residues of radioactive carbonate. Radioactivity
was measured by means of liquid scintillation. Dark COj
assimilation was calculated by the following formula:

c = Cffe ■

Rxt

where

r =

^catl, ~

R =

dark CO, assimilation, |ig C/l/d;

radioactivity on filters, dpm/min;

carbonate contents in the water, mg C/1
(determined by direct titration with 0.1
HCl in the presence of methyl red tracer);

isotope added to each bottle, dpm/min;

incubation time. 24 hours

75

Bacterial production was calculated by the fomiula

Pb =:Q.x16.6,

where

Pg = bacterial production, |ag C/l/d;

Q, = quantity of 14 CO, assimilated, |ig C/l/d;

16.6= relationship of total biomass carbon and

biomass synthesized from carbon dioxide

(100:6).

To assess mineralization processes of organic matter,
biochemical oxygen demand ( BOD) is usually used. In practice,
BOD is more often determined after 24 hours of exposure
under in situ conditions. Presently, there is no single and
reliable technique for BOD determination. "Bottle" technique
over-estimates the oxygen demand of bacteria and is labor
intensive. Apart from that, the effectiveness of the oxygen
technique in eutrophic waters to determine destruction of
organic matter in waters with low temperature and primary
production is difficult. In mesotrophic and oligotrophic waters,
the radioisotope technique is extensively used to measure
destruction of organic matter which is more sensitive and less
labor intensive. The application of this technique is due to the
relationship between oxygen demand and heterotrophic
assimilation of CO, by bacteria (Romanenko, 1965), where
7 mg C/CO, is assimilated per mg of oxygen used for bacterial
respiration. Hence, there is a coefficient to determine the
quantity of oxygen consumed by bacteria relative to
heterotrophic assimilation of CO,.

Oxygen used by bacterial respiration was calculated by the
formula

where

O, =

Ct =

7 =

O, = Cj/l.

oxygen deinand for organic matter

destruction, mg 0,/l/d;
dark CO, assimilation, |ag/l/d;
Coefficient between oxygen demand and

CO, assimilation.

Results and Discussion

Bacterial Production and Organic Matter Destruction in the
Bering Sea

The change in bacterial numbers and biomass does not
determine their biological state and role in marine ecosystems.
These questions can be assessed by means of a sensitive
radiocarbon technique to measure the bacterioplankton
respiration.

The data obtained in summer 1988 (Table 1) show
considerable variance in the rate of bacterial production
(1.5-135 |ig C/l/d) and destruction of organic matter
(4.8^35.0 |ig C/l/d). Production in the Bering Sea averaged
17.3 ng C/l/d or 28.4 fig C/m'. The destruction of organic

TABLE 1

The rates of bacterial production and destruction of
oraanic matter in the Berins Sea in summer 1988.

Investigated
sea areas

Bacterial
production

Organic matter
destruction

P/B

Hg C/l/d gC/m- ngC/yd g C/m-

Benna
Strait

8.0-28.9 0.7 25.7-92.7

16.4 52.7

2.4

1.1

Northern

8.2-29.2

0.8

26.2-97.7

Bering Sea

17.6

56.5

(Chirikov

basin)

2.5

1.0

Anadyr Bay

1.5-33.7
6.4

0.9

4.8-108.2
20.7

2.9

0.4

Central
Bering Sea

1.5-44.8
8.9

1.3

4.8-144.1

28.5

4.1

0.5

East Polygon

4.3-118.5
33.4

100.2

13.8-380.9

107.3

321.9

2.3

South Polygon

2.0-135.5

22 2

66.6

6.4-435.5
71.2

213.6

2.1

Total for
the Sea

1.5-135.5
17.3

28.4

4.8-435.5
55.7

91.2

1.2

matter averaged 55.7 |ig C/l/d or 9 1 .2 fig C/m-. These rates are
20 times higher than similar estimates obtained in summer
1981 and 1984 (Tsyban et al., 1987a). These rates also
equalled production and destruction processes in mesotrophic
marine ecosystems (Sorokin, 1980).

High rates of bacterial production and destruction of
organic matter occurred in eastern and south Bering Sea
(e.g.. East and South Polygons). Maximum rates, found at
Stations 3 and 108, averaged 47.8 and 153.7 |ag C/l/d,
respectively.

Low rates of bacterial production occurred between
0.5—15 m at Stations 5 and 109, where rates averaged 8.3 and
1 5.8 ng C/l/d, respectively. Rates of organic matter destruction
at these stations averaged 26.8 and 50.9 |ig C/l/d. These rate
processes in 1988 are 10 times higher than those measured in
1981. The rates of bacterial production and organic matter
destruction varied considerably across the eastern and south
Bering Sea areas (Table 1). Thus, southern and eastern Bering
Sea were characterized by high but variable rates of bacterial
production and organic matter destruction across the basin. A
high production/biomass (P/B) coefficient was also obser\'ed
in eastern Bering Sea (Table 1 ).

In the central basin and in the Gulf of Anadyr, low rates of
production and destruction occurred even though the total
numbers of bacterioplankton in these areas were higher than in
the southern and eastern Bering Sea (Tsyban et a!. , Section 4. 1 ,
this volume). The rate of bacterial production and organic

76

matter destruction in euphotic zone averaged 8.4 |ig C/l/d, and
26.9 )ig C/l/d, respectively. Lower rates occurred in the Gulf
of Anadyr.

Maximum activity of microflora and high rates of bacterial
production of 25.5 and 18.7 |ag C/l/d and organic matter
destruction of 8 1 .9 and 60.0 |.ig C/l/d were found at Stations 7
and26(Fig. I; Subchapter4. 2.1, this volume). The lowest rates
of bacterial production of 4.2 and 2.8 |ig C/l/d and organic
matter destruction of 13.4 and 9.1 |ig C/l/d were found at
Station 6 in the deep central part of the Bering Sea, and at
Station 1 1 in the Gulf of Anadyr. These results are similar to
those obtained for stratified waters in the vicinity of frontal
zone of the Irish Sea (Turley & Lochte, 1985).

The results showed that the highest rates of bacterial
production and organic matter destruction occurred in the
surface microlayer and near-bottom waters in the deep central
basin of the Bering Sea, higher than rates measured in the zone
of phytoplankton photosynthesis. In Gulf of Anadyr, rates
gradually decreased with depth, and in bottom waters, rates of
bacterial production and organic matter destruction were two
times lower than in the surface microlayer.

In general, the central part of the Bering Sea and Gulf of
Anadyr were characterized by the low bacterioplankton activity,
the low rates of bacterial production and organic matter
destruction, as well as by low production/biomass coefficient.

Because of its distinct hydrological and hydrochemical
characteristics, the northern part of the Bering Sea is much
different in other areas in the sea. Shallow depths, intensive
water exchange and unstratified water column produced a
uniform distribution ofbacterioplankton and microflora activity.
The rates of bacterial production and organic matterdestruction
were high (Table 1 ) in this part of the sea. The average daily
rate was about 18|igC/l. Organic matterdestruction amounted
to about 56.6 |ig C/1, which is about 3 times higher than in the
Gulf of Anadyr. Integrated over the water column, the rate of
bacterial production was 0.8 g C/m- and destruction of
2.5 g C/m-.

The highest microflora activities and diurnal rates of
bacterial production of 12.1 |ag C/l/d or 0.85 g C/m- were found
at Station 96 and the lowest rates at Station 92. The rate of
organic matter destruction at Station 96 was 68.0 |ig C/l/d or
2.7 g C/m-, whereas at Station 92 destruction was two times
lower (Fig. 2; Subchapter 4.2.1, this volume).

The distribution of microflora activity in the Chirikov
basin was independent of the uniform distribution of
bacterioplankton. The rates of bacterial production and organic
matter destruction in the surface microlayer decreased with
depth. The daily rate averaged about 20 fig C/1 of bacterial
biomass in the surface microlayer while organic matter
destruction averaged to 65. 1 |ig C/l/d.

Thus, the shallow waters of the northern Bering Sea was
characterized by high rates of bacterial production and organic
matter destruction, the integrated rates being much lower than
in deep water areas of the sea. In addition, microflora activity
varied horizontally and vertically, and P/B coefficient averaged
0.97 in the northern Bering Sea.

Bacterial r— i Decomposition

production H of organic master

0.5g C/m 2 ■-I per l.Og C/nT

• Station number

CHUKCHI

PENINSULA

I ^'°° n

M I. 104

Fig. 2, Bacterial production and decomposition of organic matter in the 0.5
to 45 m layer in the northern Bering Sea, summer 1988.

In summary, this investigation of microbiological processes
in the Bering Sea allowed us to assess the scales of some links
in production and transformation of organic matter. It was
shown that CO, assimilation by heterotrophic microorganisms
contributes to the production of organic carbon in the system.
Microflora contribution to the total production via CO, fixation
is sufficiently high and can amount to about 30% of the primary
production. In addition, microflora contributes to the destruction
of organic matter. The rate of destruction processes was
determined based on the activity of bacterial population, trophic
ability level, and hydrological and chemical conditions in the

Bacterial Production and Organic Matter Destruction in the
Chukchi Sea

The rates of bacterial production and organic matter
destruction were measured in the Chukchi Sea for the first time.
The results (Table 2) show that a relatively high rate of
production and destruction occurs in the water column. The
average rate of bacterial production was about 20 \ig C/l/d, or
0.8 g C/m-. The rate of organic matter destruction was about
64.9 ng C/l/d, or 2.5 g C/m-. These rates are slightly higher than
those in the Bering Sea. They agree with the rates of production
and respiration in mesotrophic waters, such as temperate seas,
regions of equatorial divergence, upwelling areas where daily
production of bacterioplankton biomass varied from 5 to
20 |ig C/1 and respiration from 10 to 60.0 |ig C/1 (Sorokin,
1985).

Based on microflora activity, rates of bacterial production,
organic matter destruction, and bacterial respiration, some
areas in the sea differed from other areas. The highest microflora

77

TABLE 2

The rates of bacterial production and organic matter
destruction in the water column of the Chukchi Sea. summer 1988.

Investigated
sea areas

Bacterial

production

Organic matter
destruction

^gC/l/d

gC/m^

|ig C/l/d

gC/m=

Northern part
of the Sea

2.2-46.5
16.7

0.7

6.9-149.5

53.6

2.4

Coastal Alaska
Area

2.0-20.6
11.0

0.3

6.4-65.9

3.54

1.0

Central part
of the Sea

7.9-66.9
26.8

1.1

25.2-214.8
86.4

3.4

Coastal
Chukotka Area

7.9-61.3
26.2

1.0

25.2-196.6
84.3

3.2

Total for
the Sea

2.0-66.9
20.2

0.8

6.4-214.8
64.9

2.5

activity was found in the central basin of the Chukchi Sea
( Fig. 3; Subchapter 4.2.1. this volume ). In coastal waters of the
Chukchi, rates of bacterioplankton production and organic
matter destmction averaged 2-3 times higher than the rates of
production and organic matter destruction in Alaskan Coastal
waters.

The daily rate of bacterial production averaged
26.8 ng C/1 or 1.1 g C/m-; bacteria respiration rate was
86.4 ]Xg C/i or 1.3 g C/m-; P/B coefficient was 1.3. A low
microflora activity was observed in coastal areas of Alaska.
Diurnal rates of bacterial production averaged 0.3 g C/m-,
respiration rate 1 .0 g C/m', and P/B coefficient was the lowest,
0.5," measured in the region.

Although the rates of bacterial production and organic
matter destruction varied in the water column, microflora
activity and organic matter destruction gradually increased
from surface layers towards the bottom of the water column.

Bactenal
production
(I5g C/m-

i\

DcLomposition
of organic matter
per l.Og C/rrr
Station number

P

Jl:^

iCIU

{?

CHUKCHI \

PENINSULA

Fig. 3, Bacterial production and decomposition of organic matter in ttie 0.5
to 45 m layer of the Chukchi Sea, summer 1988.

In the northern Chukchi Sea, rates of bacterial production in
layer 25^5 m were 1.7 times higher than rates measured in
water layer 0.5-25 m. Total production of bacterial biomassin
bottom waters averaged 27.8 |ig C/l/d, while in euphotic waters
production was 20 |ig C/l/d.

In conclusion, the study of microflora and microbiological
processes in the Chukchi Sea allowed us to identify specific
features of formation and function of microbiocenoses in this
Arctic Sea. In addition, the activity of microflora and rates of
bacterial production was determined and the role of
bacterioplankton assessed in the transformation of organic
matter. The results showed that the rates of bacterial production
and organic matter destruction in the Chukchi Sea equaled rates
in mesotrophic waters.

78

Subchapter 4.2:

Heterotrophic Saprophytic Microflora

4.2.1 Distribution of Indicator Groups of Marine
Heterotrophic Microorganisms

ALLA V. TSYBAN, GENNADIY V. PANOV, and SVETLANA P. BARINOVA

Natural Environment and Climate Monitoring Laboratory and Academy of Sciences, Moscow. USSR

Introduction

Over the last few decades, the attention over ocean pollution
has become one of the most urgent problems in applied
oceanography and is drawing great attention by world scientific
communities (Goldberg, 1970; Bemhard & Zattera, 1975;
Izrael & Tsyban, 1981, 1985a, 1989; Pravdic, 1981; Gesamp,
1982; Kullenberg, 1984). Today's anthropogenic impact on
the World Ocean creates a tense ecological situation. Pollutants
are becoming not only a continuously active ecological factor
(Izrael & Tsyban, 1985), but also an evolution factor by
affecting sea organisms (Izrael & Tsyban, 1989). Pollutants
getting into the sea environment, including xenobiotics, cause
rapid change in sea organisms and, due to directional selection,
result in active growth of certain hydrobionts and disappearance
of others that are not able to tolerate the action of foreign
substances. Organisms, which have adapted to new chemical
compounds that pollute the sea environment and then take a
dominant position in the biocenosis structure, are named after
the chemical substance. There are grounds to suggest that the
development of these hydrobionts is a function biological
response to the chemical pollutants of the world's oceans
(Izrael & Tsyban, 1981, 1985a, 1989). Biological significance
of indicator types is determined by their special designation.
Some fill a critical gap in biocenoses, others help to restore the
natural backgrounds while still others determine the immunity
of the sea ecosystem (Izrael & Tsyban, 1989). The latter
include sea microorganisms.

Microorganisms have high rates of reproduction and
extensive range of constitutive and inductive enzymatic activity.
The latter characteristic stipulates their ability to transform and
utilize practically all naturally occurring organic compounds.
For this reason, these organisms are distinguished for their
unique ability to rapidly adapt to changing environmental
conditions. For example, an accidental oil spill in the world's
oceans would result in rapid and abrupt increase of hydrocarbon
oxidizing bacteria by 3-5 orders of magnitude (Gunkel, 1968;
Atlas el ai, 1976; Le Petet et ai. \911: Oppenheimer et ai.
1977; Atlas, 1981).

The possibility of using microorganisms that are capable
of oxidizing oil as indices of the degree of hydrocarbon
oxidation under natural conditions and indicators of oil pollution
was shown in the 1950's (Izjurova, 1950; Voroshilova &
Dianova, 1950. 1952). According to Voroshilova and Dianova
(1950, 1952), the number of oil-oxidizing bacteria in clean
pools did not exceed 1 00 cells/ml, and in 50% of the cases, less
than 10 cells/ml. Another parameter used as an index of the
degree of water pollution with oil products is the ratio of the

numbers of oil-oxidizing to heterotrophic bacteria (Voroshilova
& Dianova, 1950; Gavrishova, 1969; Mironov, 1970). Atlas
(1981) used the ratio between oil oxidizing microorganisms
and total bacterial number as an index of oil pollution.

The concept of using microbes as indicative of organic
pollutants in the World Ocean has been most actively developed
during the last 20 years. Itwas shown (Tsyban ef a/., 1985)that,
depending on the phenomena under consideration, microbial
cenoses may act not only as indicators of physicochemical and
biological processes but also as a powerful biotic factor,
facilitating pollutants' elimination from the sea environment.

At present, physiological and biochemical potential of
microbial populations is at the stage of active developments.
However, these important fields of marine microbiology have
not investigated the distribution in different parts of the World
Ocean or with depth of heterotrophic bacteria using or
transforming various organic substances. Bacteria using high-
molecular toxic compounds (e.g., benzo(a)pyrene [BaP] and
polychlorinated biphenyls [PCB's]), are an important
characteristic of the world ecosystems state under the conditions
of increasing anthropogenic influence.

Materials & Methods

Investigations of indicator microflora in the Bering Sea
began in 1981 (Izrael et al., 1987) and continued during the
period of the Second Joint US-USSR Expedition on board the
research vessel (WW ) Akademik Korolev in 1984 (Izrael etai,
1988; 1989; 1990). These investigations were continued in
1 988 during the Third Joint US-USSR Bering & Chukchi Seas
Expedition on the Akademik Korolev. It should be noted that
in 1 988 observations were carried out not only in the same areas
of the Bering Sea as in 1981 and 1984 but also covered some
new areas: the Gulf of Anadyr, the Chirikov basin, the Bering
Strait, and the southern part of the Chukchi Sea. All together,
82 stations were studied in the Bering Sea and 3 1 stations in the
Chukchi Sea.

Water samples from the near-surface microlayer 0-2 cm
thick were taken with sterile water microsamplers, with sterile
bottles, or with plastic Niskin Water samplers, presterilized
with 96% ethanol. These samples were immediately analyzed
to reveal indicator bacteria, including the following forms:
saprophytic bacteria (SB), hexadecane oxidizers (HDB),
benzo( a)pyrene transformers ( BaPB ), and polychlorobiphenyl
transformers ( PCB B ). The detennination of bacterial indicator
groups is viewed as a study of physiological activity of
indigenous sea microflora prior to their isolation from the
habitat.

81

Numbers were determined by the method of ultimate
dilutions, described as early as 1927 by Razumov (1927),
which is widely used in similar works (Gunkel, 1967; Atlas,
1981; Platpira, 1982, 1985; Shtukova, 1990). The method
consists of adding into two to three rows of test tubes, containing
a liquid medium or "sea potassium-yeast medium" (SPY).
These media were supplemented with hexadecane, BaP, or
PCB as the only source of carbon. Dilutions were made in
measured volumes of analyzed seawater so that the initial
sample in the first test tubes was diluted 1:10, and followed by
1:100, 1:1,000, 1:10,000 (etc.) times accordingly. After
incubation, test tubes were checked for maximum dilution of
the sample that showed growth of the bacterial physiological
group understudy. Growth was determined visually by change
in transparency and color of the medium. A special statistical
McCredy table was used to determine the numbers of bacterial
cells per milliliter. When using the method of ultimate dilutions,
we assumed that the observed bacterial growth occurred when
at least one actively dividing bacterial cell was transferred
during inoculation.

To study SB. fish broth made with seawater from
investigated areas was used as a liquid medium, prepared from
0.5 kg of fish cooked in 1 liter of water, and diluted 10 times
with the same seawater. The medium was poured into test
tubes and sterilized in an autoclave with pressure 1 atm
(1.01 X 10' Pa) for 20 minutes. To determine the number of
other indicator bacteria groups, a liquid SPY medium was used
(Tsyban, 1970; Seki, 1986) containing K.HPO^ (1 g),
NHjCl ( 1 g), yeast extract (0.5 mg), and seawater ( 1 ,000 ml).
These media were poured into test tubes and autoclaved.
Sterile substrate, hexadecane, BaP, PCB, or Aroclor 1232
(0.01-1%) was added into test tubes after inoculation.

The SPY medium, as an elective media, has found extensive
application in the practice of marine microbiology ( Seki, 1 982;
Tsyban etai, 1985; Izrael & Tsyban, 1989).

The statistical method of prismatic ecograms was used to
analyze the results (Tsyban, 1970).

Results and Discussion

Saprophytic Bacteria in the Bering and Chukchi Seas

In the central Bering Sea (East Polygon), the MPN of SB
varied within the range of 0-1.8 x 10' cells/ml,
222^40 cells/ml for the investigated stations. These bacteria
varied with depth at Stations 1, 2, and 3 of about
3,000 m deep. Maximum concentrations of more than
1,000 cells/ml occurred at depths 10-25 m (thermoline), 150,
500, and 2,500 m. The above bacterial groups were not
discovered at Station 1, 15 m and 3,000 m; at Station 2.
2,000 m; Station 3, surface microlayer; or Station 4, 25 m. At
shallow-water stations ( Stations 4 and 5 ), SB increased only in
deep-water and near-bottom layers of waters deeper than
100 m. Such distribution of microflora reflected water masses
heterogeneity in this sea area. Compared to 1984 (Izrael c? a/.,
1988; Tsyban el al., 1990), the number of SB at East Polygon
remained constant (0-10'' cells/ml), but their vertical distribution
varied with depth.

In the northwest Bering Sea at the sections near
St. Lawrence Island, SB distribution was also variable.
Maximum concentrations ( 10' cells/ml) occurred at depth and
in the near bottom layers of Stations 7, 18, and 19. Overall, the
vertical distribution of this group of microorganisms showed
an increase in numbers with increase in depth. At Station 36,
not far from the St. Lawrence Island, the SB (10- cells/ml)
remained constant over the entire water column from 1 5 m to
the bottom. At other stations SB in the upper layers of water (0,
5, and 10 m) ranged from 10' to 10' cells/ml.

Distribution analysis of mean SB number showed that
maximum mean MPN values were typical for Station 7
(2.4 X 10' cells/ml). At other stations of the section (with the
exception of Station 35), mean values for saprophytes varied
between 105 and 360 cells/ml. At Station 35, the SB mean was
about 96 cells/ml.

First studies of microflora of the Gulf of Anadyr were
made during this cruise. Numbers varied across a very wide
range from zero to 1.8 x 10^ cells/ml. Maximum values
occurred at Stations 24 and 27. At Station 1 1, SB did not range
greatly — 0-300 cells/ml. mean 56 cells/ml. At Station 41,
situated between the Gulf of Anadyr and Chirikov basin, SB
averaged 7.1 x 10' cells/ml. Vertical distribution of saprophytes
was variable, with a trend towards increasing concentration
with depth (Fig. 1 ).

In the Chirikov basin and Bering Strait, SB varied vertically
and horizontally. Overall, concentrations ranged between
and 1.8 x 10' cells/ml. At Stations 96, 100, 102. and 104. cell

?f

27 Sialion No

MPN, tcll5/ml
1 . 11-100
2-101-1000

CHUKCHI 'i^^

peninsula!

'l

•..

I

• ''

•32 •

36 •l^

\

• 22

•35

•l3

•,5

• 19
• 10

• /

b)

C>7

T?f

MPN. <:cllf,/ml
1 ■ 1-10

CHUKCHI T"-^
PENINSULA L

3- 101-1000

•3^#^'

^

•

27

<

•24

3e.t

\

•22

•55

•13

•,5

•,9

•
7

d)

Fig. I. Vertical distribution of mean values of the most probable number
(MPN) of heterotrophic-saprophytic (a), hexadecane oxidizing (b),
benzo(a)pyrenc transforming (c) and PCB-transforming (d) bacteria
at stations in the northwestern Bering Sea and the Gulf of Anadyr in
summer 1988.

82

numbers averaged 10- cells/ml, and at Stations 89, 92, and 104,
numbers averaged 10' cells/ml. At Station 102, in the
southeastern part of the basin, SB averaged only 1 70 cells/ml,
but near the Alaskan shore (Station 92) we found the largest
concentrations (4.4 x 10' cells/ml) in the Bering Sea.

In the deep Bering Sea (South Polygon), SB ranged from
to 1.8 X 10' cells/ml, but mean values (per station) were
higher, 1.3-2. 6 X 10' cells/ml. Compared to 1984(Izraelc/^j/.,
1988; Tsyban er ai. 1990), the numbers of SB increased
slightly. In 1984, they were within the range of
0-3. Ox lO'cells/ml. Themean values were also higher in 1988
than in 1984. Distribution of these bacteria varied over water
column depth. Saprophytic microflora in the near-surface
microhorizon (0-2 cm thick) were absent or in extremely low
numbers at Stations 108, 1 10, and 1 12.

In summer 1988, the first microbiological survey in the
southeastern Chukchi Sea was made. The area was characterized
by two large sources of biogenous elements. Here, inorganic
nitrogen compounds were being advected through the Bering
Strait and along the coastal Siberian Current. Biogenous
elements also originated from the Chukchi and Alaska Rivers.
Through the combination of these flows, a wide area with high
rates of primary production of organic matter by phytoplankton,
was fonned in the southeastern Chukchi Sea. In the process of
photosynthesis, phytoplankton excrete newly synthesized
organic matterthat is substrate forbacterioplankton. Extensive
growth of phytoplankton is usually accompanied by increased
numbers of SB (Gocke, 1977; Rheinheimer, 1977, 1985).

Indeed, our results show that the numbers of SB were
higher in the Chukchi Sea than in the northwestern and northern
parts of the Bering Sea. The number of SB varied between
1.8 and 2.0 x 10^ cells/ml, with averages between 0.4 and
16.6 X 10' cells/ml. Highest mean numbers of SB occurred in
the coastal zone of Alaska (Station 66, 1 1.2 x 10' cells/ml;
Station67, 16. 6x 10' cells/ml). High mean numbers of SB also
occurred at Station 55, 10.3 x 10' cells/ml. At other stations in
the Chukchi Sea, mean values varied between
0.4 X 10' cells/ml (Station 74) and 9.6 x 10' cells/ml (Station
57; Fig. 2). Vertical distribution of bacteria varied little over
depth. At Stations 50, 55, 61, 67, and 69, SB distribution
remained constant with depth and varied by no more than one
order of magnitude at Stations 50, 61, and 69
( 10--10' cells/ml). At other stations, SB varied by 2-3 orders
of magnitude. The largest variation was observed at Station 49
(3-1.8 X 10-* cells/ml).

Analysis of SB in the Bering and Chukchi Seas Relative to
Temperature and Salinity

During the time of expedition in the Bering Sea, water
temperatures varied from - 1 .6°C to + 1 0. 1 °C and salinity ranged
from 29.73% to 34.64%. For analysis, we grouped samples to
both temperature and salinity (Fig. 3a). In the Bering Sea, 27%
of the water samples fell in the temperature range between -2
and +2°C; 40% between +2 and +6°C; and 33% between +6
and + 10°C. The waters of the Chukchi Sea, in comparison with
the Bering Sea, was colder. The majority of samples (65% ) fell
within the temperature range between +2 and -i-6°C, and only
10% of samples had temperatures exceeding +6°C.

• •

dj y

n-100 '01 1000 MF'N ^eWilmi

/" ALASKA

.^

• ^' •

W52k

>3 •e,

•"•\

p.,^

69*

67© #66

CHUKCHI

PE.N1NSULA

\*72 •74 •75,^

■f

K *(

ALASKA

r^

e

Fig. 2. Vertical distribution of mean values of saprophytic (a), hexadecane
oxidizing (b),BaP-transforming(c), and PCB-transforming(d) bacteria
at stations in the Chukchi Sea in summer 1 988. Numbers near symbols
are station numbers.

N«IO cells/ml
6 — I

Fig. 3. Occurrence rate (%) of samples with various combinations of
temperature and salinity in pairs in the Bering (a) and the Chukchi (b)
Seas in summer 1988. and mean values of heterotrophic saprophytic
bacteria number in the above samples from the Bering (c) and Chukchi
(d)Seas. Number of bacteria are 10' cells/ml.

83

In the Chukchi Sea, waters appeared less saline (24.04 to
33.66%) than the Bering Sea, and only 5% of the stations had
salinities greater than 33%. Salinities less than 29.70% were
included in the 29.70-31.35% for analysis (Fig. 3b).

In the Bering Sea, the highest mean number of SB
(3.7 X 10' cells/ml) occurred in warm waters, with temperatures
+6°C and salinity between 33.00 and 34.65%, which represented
a small percentage (3%) of the total number of analyzed
samples. These samples dominated the surface 25 m in the
southern Bering Sea (South Polygon and Station 1 13).

Water samples from the Bering Sea with temperatures
higher than 6°C and salinity 3 1 .3 1-33.00% represented 25% of
samples. These samples were usually taken from the surface
25 m in the central, northwestern, and northern areas of the sea
and contained about 8.0 x 1 0- SB cells/ml ( Fig. 3 ). Mean values
of SB number with other pair combinations of temperature and
salinity grouped close to each other, 1.0 to 3.7 x 10' cells/ml
(Fig. 4).

In the Chukchi Sea, the highest mean number of SB
(1.15 x 10^ cells/ml) also grouped in relatively warm waters
(> + 6°C), but in contrast to the Bering Sea, less saline waters
(>31.35%). The lowestmeannumberofSB(5.7x 10- cells/ml)
was similar to other pair combinations of temperature and
salinity, 4.7 to 6.0 x 10' cells/ml (Fig. 3).

Ecogram analysis showed that during the cruise in the
Chukchi Sea, the saprophytic microflora grew rapidly as
maximal mean SB in the Chukchi Sea (1.15 x 10^ cells/ml)
occurred in warm, low salinity waters, typical of southeastern
water (Stations 65 and 66). An area affected by river flow from
the Alaska coast (Fig. 2).

Hexadecane-oxidizing Bacteria in the Bering and Chukchi
Seas

The most probable number of HDB in the central Bering
Sea, East Polygon, in summer 1988, varied between and
1.8 X 10' cells/ml. Maximum numbers occurred only at Station
3', at depths of 45 and 150 m. At other stations, HDB varied
less— 0-30, 0-180, and 0-300 cells/ml.

In the South Polygon, HDB ranged between and
180 cells/ml at Station 1 12 (average 90 cells/ml). At the other
stations, HDB ranged from 0-1.8 x 10' cells/ml (averaged
between 180 and 700 cells/ml). Samples with maximum HDB
represented >10% of the total number of samples in this deep-
sea area (Fig. 4).

This bacterial group varied vertically. The greatest vertical
variation occurred at a station nearest the St. Lawrence Island,
where HDB increased with depth, with practically no
hexadecane-oxidizing microflora in the near surface microlayer.

Mean numbers of HDB in the section ranged between 10
and 100 cells/ml. Only at two stations. 7 and 19, did DB
numbers exceed 10- cells/ml. Generally, in the southeastern
Bering Sea, including the Gulf of Anadyr, HDB varied between
and 1.8 x 10' cells/ml. Hexadecane-oxidizing microflora
occurred in 72% of the samples.

Fig. 4. Occurrence rale ['~i ) of various value.s of the mosl probable number
(MPN, cells/ml ) of heterolrophic saprophytic and other functions of
groups in the Bering and Chukchi Seas in summer 1988:

(a) southern Chukchi Sea;

(b) northern Bering Sea (Chinkov basin) and the Bering Strait;

(c) the Gulf of Anadyr; and

(d) central and southern Bering Sea.

In the Chirikov Basin, HDB also varied between and
1.8 X 10' cells/ml, averaging between 10 and 100 cells/ml.
HDB increased at Station 83 in the Bering Strait and at Station
89 (Fig. 5). In general, the HDB distribution in the Chirikov
basin resembled the distribution in the open sea (Fig. 4).

In the Chukchi Sea, HDB varied between and
1.8 X 10"* cells/ml. Their distribution appeared extremely
variable. Thus, at Station 66, only a few cells/ml occurred,
while at Station 49, they ranged up to 3.4 x 10' cells/ml
(Fig. 2). Generally, HDB occurred in 62% of the samples, but
at only 1 cells/ml ; waters that are characteristic of nonpolluted
seas (Fig. 4). A relatively high number ( 10- cells/ml) of HDB
occurred in 2 1 % of the samples. This may be explained by the
fact that microorganisms of this group also use aliphatic
hydrocarbon as a source of carbon and energy. The source may
be anthropogenic, but aliphatics also seep into the sea from
underwater oil fields, and are synthesized and subsequently
released by some seaweed.

Prismatic ecogram analysis (Figs. 6,7) showed that the
largest mean numbers of HDB (7.1 x 10- cells/ml)in the Bering
Sea occurred in waters with high concentration of SB; that is,
waters with relatively high temperatures (>6°C) and salinities
(>33%) (Fig. 6). Such combinations of temperature and
salinity occurred in only 3% of the total number of analyzed
samples (Fig. 6). However, the numbers of hexadecane-

84

Fig. 5. Vertical distribulion of mean values of saprophytic (a), hexadecane
oxidizing { b), BaP-transfomiing (c ). and PCB-transforming ( d) bacteria
at stations in the northern Bering Sea (Chirikov basin) in summer
1988.

oxidizing microflora were also high in waters with temperatures
<6°C, but with relatively high salinity (>33%) (Fig. 6). In the
Chukchi Sea, the highest mean number of DB
(6.6 X 10- cells/ml) (Fig. 7) were found in waters with
temperatures between +2°C and +6°C and salinity between
31.35% and 33.00%. Such conditions occurred in 60% of all
the samples (Fig. 7).

This analysis of hexadecane-oxidizing microtlora in the
waters of the Bering and the Chukchi Seas confirms that these
waters remain relatively unpolluted. The waters of the northern,
central, and especially southern areas of the Bering Sea have
experienced aliphatic hydrocarbon inputs of natural or
anthropogenous origin.

Benzo(a)pyrene Transforming Bacteria in the Bering and
Chukchi Seas

Mean numbers of BaPB in the northwestern Bering Sea,
includingtheGulfof Anadyr, averaged about lO'ceils/ml. The
highest concentration of BaPB occurred at Stations 24 and 27
near the coastal zone and at Station 41 between the Gulf of
Anadyr and the Chirikov basin (Fig. 1).

The vertical distribution of BaP-transforming microflora
followed a similar distribution for hexadecane-oxidizing
microflora. However, in the Chirikov basin, high mean numbers
of BaPB were not only found at Stations 83 and 89. but also at
Stations 86 and 104 (Fig. 5). Similar numbers occurred in the
Chukchi Sea (Fig. 2).

In the central and southern Bering Sea, BaPB varied
between 0-3.0 x 10"" cells/ml, but most often values fell
between 10 and 100 cells/ml (28%^ of all the samples) and
100-1,000 cells/ml (29% of all the samples), respectively

N. celli/ml
500—1

Fig. 6.

Occurrence rate (R,%) of samples with various pair combinations of
temperature and salinity in Bering Sea in summer 1988 (a), and mean
numbers of hexadecane oxidizing (b). BaP-transforming (c). and
PCB-transforming (d) bacteria (cells/ml) in the above samples.

(Fig. 4). As for BaPB distribution, the open waters in the
central and southern Bering Sea differed from other areas.
Here, 40% of samples possessed low BaPB numbers, whereas
only 11% of samples contained more than 1,000 cells/ml
(Fig. 4). Water samples with relatively high temperatures
(>6°C) and salinity (>33%) in the southern Bering Sea again
contained the highest mean numbers of BaP transforming
microorganisms, 8.9 x 10- cells/ml (Fig. 6).

In the Chukchi Sea, highest mean numbers of BaPB
(6.0 x 10- cells/ml) occurred in water samples with relatively
low salinity (<31.35%) and temperatures between 2°C and
6°C. Such conditions exist in the surface waters at Stations 45
and 59, a coastal area affected by the Siberian rivers outflow,
and at Station 53 in Alaska Coastal waters ( Figs. 2,7). Compared
to 1 984 and, as far back as 1 98 1 , the number of BaP-transforming
microflora in the Bering Sea in 1988 has increased at a number
of stations, and their distribution has become more extensive.

Polychlorinated Biphenyls-transfonning Bacteria in the Bering
and Chukchi Seas

In 1981, research in the Bering Sea began on the number
and distribution of heterotrophic bacteria that transform PCB's
and has continued in summers 1984 and 1988.

At the East Polygon, in the central Bering Sea, the PCBB

varied between and 180 cells/ml. Maximal concentration,

3.0 X 10' cells/ml, was measured at only 150 m at Station 1.

The distribution of this bacterial group varied with depth, but

85

peaked at 0.5- 1 m, i 50-200 m, and 1 ,500 m at the deep-water
stations. At shallow-water Stations 4 and 5. highest
concentrations occurred at 0.5, 15, and 45 m. Compared to
1984, the numbers of PCB-transforming bacteria had not
increased and their vertical distribution remained constant
(Fig. 8).

Vertical variations of PCBB in the northwestern Bering
Sea resembled the distribution of both hexadecane and especially
BaP-transforming bacteria. Maximum numbers of PCBB
(10- cells/ml) occurred in near-bottom waters. At Station 7,
which is the farthest from St. Lawrence Island, only
10 cells/ml were measured. At Station 35, the density of
PCB-transforming bacteria increased to 180 cells/ml at 25 m.

Fig. 7. Occurrence rate {9c) of samples with various pair comhinations of
temperature and salinity in the Chukchi Sea in summer 1988 (a) and
mean valuesof numbers (cells/ml ) of hexadecane oxidi/mg (b), BaP-
transformmg (c). and PCB-transformina (d) bacteria.

The horizontal distribution of PCBB in the northwestern
Bering Sea, including the Gulf of Anadyr, was highly variable.
Mean numbers ranged between 1 and 10 cells/ml at Stations 32
and 36; 1 1-100 cells/ml at Stations 7, 9, 10, 13, 19, 27, and 35;
and 101-1,000 cells/ml at Stations 24 and 41 (Fig. 1). The
variation of PCBB was generally greater than for HDB, but
similar to the BaP-transfonning microflora (Fig. 1 ).

Compared to 1981, the numbers of PCBB in 1988 increased
2-3 times, from 100 cells/m in 1 98 1 to 1 80 and 300 cells/ml in
1988. The distribution of PCBB also became more extensive
in 1988 (Fig. 9).

Stations

16(B)

Fig. 8 Vertical distribution of PCB-transforming bacteria in the central
Bering SeatEast Polygontsummer 1984 and I98X. The insert shows
location of stations.

1 10 100 1000

Fig. 9 Vertical distribution of PCB-transforming bacteria at three stations of
North Polygon in the northern Bering Sea near St. Lawrence Island in
summer 1981. 1984, and 1988.
X - axis = station numbers and indices of stations; and
Y - axis = depth (m).

In the Chirikov basin and the Bering Strait, PCBB varied
between and 180 cells/ml. with 39% of all the samples
containing 180 cells/ml (Figs. 4,5). Due to significant vertical
variability, mean numbers for the various stations never
exceeded 100 cells/ml. Only at Station 83 in the Bering Strait,
the mean number of PCBB averaged more than 100 cells/ml,
ranging from 180 to 690 cells/ml. Distribution of PCBB
showed high numbers at 0.5, 45, 250, and 2,500 m.

In the southern Chukchi Sea, PCBB also varied between
and 3.0 x 10' cells/ml (Fig. 2), but concentrations most often
fell within the range of 10-100 cells/ml in 29% of all the
samples (Fig. 4a).

Although the mean numbers of PCB-transforming
microflora ranged between 10 and 1,000 cells/ml (Figs. 2,6),
PCBB at 6 out of 1 8 stations under investigation rarely exceeded
100 cells/ml. At the remaining 12 stations, PCBB fell within
range of 10 and 100 cells/ml (Fig. 2). In the Chukchi Sea, 10%
of samples contained PCB-transforming microflora with more
than 10' cells/ml (Fig. 4a). These bacteria were absent in 16%
of all those analyzed whereas, in the Bering Sea, as much as
30% of the samples had no PCBB (Fig. 4).

PCB-transforming bacteria showed similar distribution
ecograms as other indicator groups in the Bering Sea. Maximum
mean numbers of PCB-transforming bacteria
(7.4x 10- cells/ml) occurred at stations with high temperatures.

86

6-10°C, and salinities >33% in surface water. In the Chukchi
Sea, the ecograms differed between Stations (Fig. 7). The
largest mean number of PCBB (8.8x1 0' cells/ml ) again found
in the waters with salinities of 3 1 .35-33.009; and temperatures
>6°C (Fig. 7).

The resemblance of ecograms between the Chukchi and
Bering Seas (Fig. 6) indicates the variety of functional groups
that exist in these seas and that these groups are widely
distributed and comprise an integral part of the ecosystem.
These ecograms illustrate again the variability and patchiness
of these groups in these seas.

In summary, from the results on the number and distribution
of saprophytic, hexadecane-oxidizing. BaP- and PCB-
transforming bacteria in the Bering and Chukchi Seas, and
comparison with investigations conducted in 1981 and 1984,
we found:

/. In the summer of 1988, SB were ubiquitous, albeit
highly variable, in the Bering and Chukchi Seas. In the Bering
Sea, these bacteria occurred most frequently at hundreds of
cells/ml, whereas in the Chukchi Sea, they exceeded
10' cells/ml. Based on boreal concentrations of SB. the Bering
Sea can be characterized as oligomesotrophic and the Chukchi
Sea as mesotrophic.

2. Hexadecane bacteria were also highly variable in the
Bering and Chukchi Seas. In the Bering Sea, maximum
numbers changed little since 1984 and were most abundant in

the Bering Sea (South Polygon) where significant concentrations
of anthropogenic hydrocarbons occurred.

3. Benzo(a)pyrene-transforming bacteria were also variable
in the Bering and Chukchi Seas. These bacteria were widely
dispersed in the Chukchi Sea, generally at lOcells/ml. Although
the distribution of BaP-transforming bacteria was also patchy
in the Bering Sea (the Chirikov basin, the Bering Strait, South
and East Polygons), BaPB were most abundant at 1 00 cells/ml.

4. PCB-transforming bacteria covaried with the distribution
of BaP-transfomiing bacteria.

5. Relative to 1981 and 1984, numbers in each functional
group and their distribution increased significantly in summer
1988. suggesting that the Bering Sea ecosystem is experiencing
anthropogenic inputs.

6. From characterizing the number and distribution of
each functional bacterial group ( in particular. PCB-transforming
bacteria) in the Bering and Chukchi Seas, we conclude that
there exists an anthropogenous effect on the ecosystems. The
degrees of entrophication varies with each region. In the
central Bering Sea, as well as in the Gulf of Anadyr,
anthropogenic impact is minimal. However, in the northern
Bering Sea and in the southern Chukchi Sea, anthropogenic
influences are evident. Because of the remoteness of the area
from big industrialized centers, the presence and distribution of
PCB- and BaP-transforming bacteria indicates the global
propagation of organic pollutants via atmospheric processes.

4.2.2 Taxonomic Composition of Heterotrophic
Bacteria

ALLA V. TSYBAN\ GENNADIY V. PANOV\ SVETLANA P. BARINOVA, VLADIMIR I. IVANITSA', and
GALINA V. KHUDCHENCO=

'Institute of Global Climate and Ecology. State Committee for Hydrometeorology and Academy of Sciences. Moscow, USSR
^Odessa State University. Odessa, USSR

Introduction

Methods and Materials

The study of the morphologic characteristics and taxonomic
composition of microorganisms of the Bering Sea was started
in 1 98 1 and 1 984, and continued in 1 988 during the Third Joint
US-USSR Bering & Chukchi Seas Expedition. In 1988,
investigations included microbial structure (microbial
population including taxonomic diversity ) of the Chukchi Sea.
It is noteworthy that these microbiological investigations were
conducted over extensive areas of the Bering and Chukchi Seas
and that they included the taxonomic determination of
heterotrophic bacteria that were isolated from different sites of
the marine environment.

The taxonomic investigation included 829 strains of
bacteria isolated from different sites of the marine environment
(the water column, bottom sediments, and biota): 432 strains
isolated from the Bering Sea in summer 1981; 320 strains
isolated from the Bering Sea in summer 1984; and 77 strains
isolated from the Chukchi Sea in 1988. In addition, the results
are compared to bacterial cultures isolated from the Baltic Sea
impact region of the World Ocean.

Bacteria from the marine environment and their culture
were isolated using fish broth and fish peptone agar prepared
with fresh seawater(Tsyban. 1980). The inocula were incubated
at 28°C.

87

To characterize the cultures according to morphologic and
phenotypic traits, generally accepted methods were used
(Gerhardt, 1983; Yegerov, 1983). Taxonomic position of the
strains was investigated using the schemes of marine Gram-
negative bacteria and the 8th edition of Bergey's determinant
(Shewanc/fl/., 1960;Pallroni, 1975; Sieburth, 1979;Buchanan
& Gibbons, 1982; Oliner, 1982).

Results and Discussion

The morphology of 432 isolates of heterotrophic
microorganisms from the Bering Sea environment in 1981
showed that rods accounted for 81.4% of the bacterial
representatives. The cocci accounted for 18.6% of the isolates
(Table 1 ). The length and width of the rods ranged from 0.7 to
2.0 and from 0.3 to 1. 5 |im, respectively. Their diameter varied
from 0.5 to 1.5 |im.

Most bacterial isolates (87.4%) possessed mobility (see
Table 1 ). Peritrichs and monotrichs accounted for 74.5% and
25.5%, respectively. The presence of spores was found in 82
of 297 isolates, which accounted for 27.6% (see Table 1 ).

For comparison, among 66 isolates from the Baltic Sea in
1982, the cocci were far less than in the Bering Sea, only 4.5%
of the investigated isolates. The rest, 95.5%, were motive

peritrich rods (see Table 1). The number of spores formed
(13.6%) in the composition of Baltic microflora were also
lower than in Bering Sea fiora (see Table 1 ).

One of the most important morphologic and systematic
traits of microorganisms is affinity to the Gram Stain. The test
of 297 isolates from the Bering Sea bacteria showed that most
isolates (70.8%) were Gram-positive; the remaining 29.2%
were Gram-negative. It is interesting to note that among 66
isolates from the Baltic Sea, 60.5% of microorganisms were
Gram-negative, and only 39.5% were Gram-positive (see
Table 1 ).

Visual pigments occurred in 59.2% of 432 bacterial isolates
from the Bering Sea. Pigmentation of Bering Sea isolates
ranged from white to red: 16.9% pink; 1 1.8% creamy; 9.3%
yellow; 5.6% beige; 3.7% grey; and 14% red. One isolate
formed brown colonies.

Investigations of Baltic cultures showed that, unlike Bering
Sea cultures, most isolates (60.6%) formed colorless colonies.
Among these colonies, only 4 isolates were distinguished:
25.7% white, 9.1% beige.

Most of Bering Sea isolates (67.2%) dissolved gelatine,
decomposed peptone (9%), and formed ammonia. Others
(12.64^) induced a change in protein molecules and formed
hydrogen sulphide. Indole was also formed by 36.6% of the

TABLE 1

Morphologic traits of the isolates of heterotrophic bacteria from the Bering and Baltic Seas in 1981 & 1982, respectively.

Morphologic
trail

BermgSea. 1981

Baltic Sea, 1982

Number

Number

%

Number

Number

%

of

of

of

of

isolates

isolates

with

determined

morphologic

traits

isolates

isolates

with

determined

morphologic

traits

432

81

18.6

66

3

4.5

432

351

81.4

66

63

95.5

297

82

27.6

66

9

13.6

432

377

87.4

66

63

95.5

432

55

12.6

66

3

4.5

297

210

70.8

66

26

39.5

297

87

29.2

66

40

60.5

Cocci
Rods
Presence of

sporification
Motile forms
Immotile

forms
Gram-positive
Gram-negative

Pigmentation of colonies

Absence of

pigment
Pigments:

pink

creamy

yellow

white

beige

brown

black

432

176

40.8

66

40

60.6

432

73

16.9

66

-

-

432

51

11.8

66

4

6.1

432

41

9.4

66

3

4.5

432

39

9.0

66

17

25.7

432

24

5.6

66

6

9.1

432

1

0.2

66

-

-

432

-

-

66

2

3.1

88

1 97 isolates studied. Nitrates were reduced to nitrites by 37.9%
of cultures. Half of the isolates fermented glucose, and 13.5
and 23.2% of the isolates produced acid and gas. respectively.
Only 3% of the isolates produced a significant amount of gas.

In addition, of all the strains studied in the Bering Sea,
80.7% possessed catalase activity, 54.8% oxidase, and 29%
lecithinase activity. The presence of lipase was found in 40.9%
of 332 isolates (see Tables 2,3).

It is noteworthy that while studying the physiological
properties of bacteria isolated from an impact region of the
World Ocean — the Baltic Sea — significant distinctions were
found as compared with the bacterial populations of the Bering
Sea, a background region of the World Ocean.

For example, unlike Bering Sea isolates, 25.7% of Baltic
microorganisms formed ammonia in the decomposition of
peptone (see Table 2). In addition, Baltic isolates (on a
percentage basis) possessed a greater ability to ferment glucose.

lactose, and mannitol than that of Bering Sea isolates, and to
produce gases (15.0%).

Specific enzyme assays show that 80.7% of Bering Sea
isolates possess the catalase activity (80.7%) slightly more
than Baltic isolates (59.0%). On the other hand, oxidase(83%)
and lecithinase (42.3%) activity proved to be typical of a
greater percentage of Baltic isolates as compared to the Bering
Sea.

Similar results were found in 1984 for bacteria isolates
from different localities in the Bering Sea.

Taxonomic characteristics of 200 isolates from 1981, and
320 isolates from different sites of the Bering Sea were also
determined on the basis of morphology and physiology. The
results are presented in Table 4. The genera most prevalent
were Bacillus (27.5%), Bacterium (22.5%), Pseudomonas
(18%) and Platwcoccus ( 1 3.5%). These genera accounted for
81.5% of the number isolated from the sea.

TABLE 2

Physiological properties of the isolates of heterotrophic bacteria from the Bering and Baltic Seas in 1981 & 1982, respectively.

Physiological
properties

Bering Sea.1981

Baltic Sea, 1982

Number

Number

%

Number

Number

%

of

of

of

of

isolates

isolates

with

determined

traits

isolates

isolates

with

determined

traits

Break down

of gelatine

332

224

67.2

Formation of

ammonia

glucose

432

225

52.2

66

54

81.5

lactose

432

58

13.5

66

21

31.7

mannitol

432

100

23.2

66

35

53.0

Formation of

catalase

432

348

80.7

66

39

59.0

oxidase

432

236

54.8

66

55

83.0

lecithinase

432

125

29.0

66

28

42.3

lipase

332

136

40.9

-

-

-

TABLE 3

TABLE 4

Distribution isolates from the Bering and Baltic Seas in 1981 and
1982 according to the basic enzymatic traits.

Groups of bacteria

Isolates possessing the above traits, %

BerinaSea. 1981

Baltic Sea. 1982

Lactose positive
Oxidase positive
Catalase active

13.5
54.8
80.7

31.7
83.0
59.0

Taxonomic position of the isolates from the Bering Sea
in 1981 and 1984.

Isolated strains

Genus

in

1981

in 1984

Number

't

Number

%

Pseudomonas

36

18

86

26.8

Xantomonas

-

5

1.7

Bacillus

55

27.5

75

23.4

Bacterium

45

22.5

54

16.9

Planococcus

27

13.5

57

17.8

Aerococcus

2

1

3

0.9

Alcaligenes

T

1

7

2.2

Halohaclerium

-

2

0.6

89

These genera also dominated in 1984, accounting for
84.9% of the total number. However, the relative number of the
genera Bacillus and Bacterium was somewhat less, while the
numbers of the genera Planococcus and especially
Pseudomonas increased. Generally, pigmented forms
dominated (93.3%) of all isolates.

For the Chukchi Sea, isolates fell between bacterial
populations of the Bering and Baltic Seas (Table 5). Here,
isolates from the Chukchi Sea occurred over 1 1 genera:
Pseudomonas. Xantomonas. Alcaligenes. Klebsiella.
Aeromonas, and others (Fig.l). Taxonomic diversity of the
dominating genera in the Chukchi Sea was somewhat less than
in the Bering Sea ( 1 3 genera) but greater than in the Baltic Sea
(9 genera).

TABLE 5

Some morphological traits of Lsolates of heterotrophic bacteria

from the Bering. Chukchi and Baltic Seas in % of the total number

of the investigated strains.

Morphologic traits Bering Sea Chukchi Sea Baltic Sea

Cocci

Gram-positive

Gram-neaative

18.6
70.8
29.2

L\0
29.9
70.1

4.5
39.5
60.5

Thus, this comparative analysis suggests that a distinction
occurs between the morphological, physiological, and
taxonomic characteristics of bacterial isolates from the Chukchi
Sea realtive to the Baltic (an impact region) and Bering (a
background region) Seas. Only the index of relation between
pigmented and nonpigmented forms does not comply with this
assessment. Based on this analysis ( i.e., the number of bacillary
and Gram-negative bacteria, taxonomic diversity, and number
of Pseudomomis sp. ) the Chukchi Sea is specified as a region
with a higher level of anthropogenic pollution.

Pseudomonas
Xantomonas
Alcaligenes
Halobactenum
Aefomonas
Flavobactenum'
Staphylococcus
Micrococcus
Planococcus
Aerococcus
Bacillus
Ailhrobacter

Another

Benng Sea

Fig. I. Taxonomic positin of the strains of heterotrophic microorganisms of
the Chukchi. Bering, and Baltic Seas.

90

Subchapter 4.3:

Microbiological Transformation
of Organic Matter

4.3.1 Transformation of Benzo(a)pyrene

YURIY L. VOLODKOVICH and OLGA L. BELYAEVA

Institute of Global Climate and Ecology. State Committee for Hydrometeorology and Academy of Sciences, Moscow. USSR

Introduction

Microorganisms, distributed in the World Ocean, play a
leading role in the functioning of these ecological systems and
in biogeochemical cycles. Microflora is the most active
component in these ecological systems (Izrael & Tsyban,
1982). Its biomass in the upper 1 00 m layer of the World Ocean
reaches 25 x 10''GC/m-, which is similarto plankton biomass.
While possessing functional enzyme systems and high
biochemical activity, the microbial communities influence
oceanic biogeochemical cycles of carbon. Many polycyclic
aromatic hydrocarbons (PAH's) that are distributed in sea and
ocean ecological systems possess toxic, mutagenic, and
carcinogenic properties, which can manifest a clear threat to
biotic components and possibly to human health.

Microbial transformation of aromatic hydrocarbons and
heterocyclic compounds has been well studied (Rodoff, 1961 ;
Treccan, 1963; Bumpus, 1989). However, the rates of
benzo(a)pyrene (BaP) transformation in seawateras well as the
significance of this process in local and regional systems have
not yet been studied. This paper reports on BaP transformation
as a process that eliminates this dangerous compound from the
sea. The investigations were conducted in the Bering and
Chukchi Seas as part of an all-round investigation of PAH's
that started in 1981 (Tsyban et ai. 1987d).

Methods and Materials

Studies on the transformation of PAH's were conducted at
nine stations in the Bering Sea and in the southern part of the
Chukchi Sea in August 1988. This cruise was the Third Joint
US-USSR Bering & Chukchi Seas Expedition on board the
research vessel Academik Korolev.

Seawater was collected in sterile samplers. Surface
microlayers was sampled with metal screens (0.02 mm). Water
column was sampled with Niskin (depths: 0.5, 2 and, 10 m).
Water samples with natural microbial communities were
transferred in sterile glass bottles for microbiological studies
on board ship.

The rates of BaP transformation by natural bacterioplankton
was conducted under //; situ conditions. Water samples of
250- ml volume was transferred into 500 ml dark glass bottles
along with BaP dissolved in acetone. Four BaP concentrations
were used: 100 and 20 |ig/l (10 days) and, 1.0 and 10 ng/1
(21 days). Abiotic factors were followed in sterile water from
each depth with respective BaP concentrations. These
experiments and controls were repeated 2-3 times.

To simulate in situ conditions, samples were incubated on
the ship's deck in running water for 10-21 days. To temiinate
the microflora activity, a few milliliters of concentrated HCl
were used. Residual concentrations of BaP were extracted in
250 ml of benzol and stored until analyzed.

The BaP benzol extracts were olated and evaporated. The
evaporated part of the benzol extract was eluted by 2 ml of
solution of 1,12 benzapareline in octane (concentration
0. 1 mg/ml) and also used as an inner standard.

The concentration of BaP in non-octane solution was
determined by spectral and fluorescent analysis with the use of
Shpolsky at 196°C on spectrographer C-12 (Shpolsky et al..
1952; Fedoseevaera/., 1986). Sensitivity of the method was
determined at 1 x lO'" g/ml + 10%. The rate was determined
as the difference between the initial (artificially introduced)
and final mass of BaP. Rates are expressed in percent of BaP
transformed.

Results and Discussion

One consequence of PAH's circulation in the sea is its
distribution relative to specific microflora that are adapted to
new hydrochemical conditions and capable of transforming
these dangerous compounds. Our results show that BaP
transformation occurs in Bering Sea waters (Tsyban et al.,
1987c ). During the 1988 cruise in the subarctic region of the
Chukchi Sea, BaP transformation was again confirmed. The
distribution of BaP transformers was patchy with numbers in
the 0.5 m surface layer ranging from 10 to 1,000 cells/ml. The
maximum density occurred in the Chirikov basin at Station 89
where more than 10' cells/ml were found.

The potential activity of the microflora to transform BaP
was studied in 10 //; situ simulation experiments. The results
show that bacterioplankton from the Bering and Chukchi Seas
possess the ability to transform BaP (Fig. 1). Microbial
transformation of BaP varied from 8 to 5 1 % (Table 1 ) with little
variation between replicates. The lowest transformation
(2-3%), which is within experimental error, was found in the
central part of the Chirikov basin.

Comparison of 1984 and 1988 data (Fig. 1; Tsyban et al..
1986; Izrael et al., 1987) shows that BaP transformation is
relatively stable in the Bering Sea. At North Polygon, BaP
transformations ( 1 0-day incubation ) were about 45-55% during
these years. Considering the differences in experimental
conditions, the results show that maximum biodegradation
occurred in the 0.5 m level of the Gulf of Anadyr waters. The
rate was 39 mg of BaP/1 over a period of 10 days. In the

93

BaP transfiirmalion in perceni
fnim the onginal tonteniralion

urtacc liiver 1984
.urfafc layer 1*^88
1988

Fig. 1 . BaP microbial transformation m experiments iii ,v;7h in the Bering and
Cliuckchi Seas water (August, 1988).

Chukchi Sea, maximum activity of microbial populations was
found at Stations 45 and 50, where 25—45% of the BaP was
transformed.

The e.xperiments showed little differences in the amount
of PAH's degraded by bacterioplankton in the surface
microlayer and 0.5 m level (Table 1 ). In certain areas of the
World Ocean, these processes are more pronounced in the
surface microlayer. the zone of air-sea interaction (Tsyban,
1985). However, there is no direct correlation between the BaP
content in sea waters and amount transformed. For example,
low rates of BaP transfomiation occurred in waters with the
highest concentration of BaP, 63 |lg/l at Station 29.

To study the degradation of PAH' s at in situ concentrations
( 1 and 10 |ig/l), long in situ experiments were conducted up to
2 1 days. The results show that 54-57% of the initial BaP mass
was transformed with the first 5-7 days (Table 2 ); after 2 1 days
the process declined considerably. Maximum degradation was
67-85% of the initial concentrations. Similar results were
found for concentrations of 1 and 10 |ig/l. The results from
Stations 36 and 50 showed that despite local features of the BaP
transfomiation (Table 1 ), bacterioplankton of the Bering and
Chukchi Seas possess similar biodegradation potential.
Transformation and removal of BaP in the surface layer occurred
at a rate of 7 |ag/l over a period of 3 weeks.

In summary, from the investigations performed in 1981.
1984, and 1988 in the Bering and Chukchi Seas, heterotrophic
microflora exist in the waters, and the heterotrophic microflora
show a pronounced biodegradation potential in relation to

TABLE 1

Microflora transformation of BaP in the Bering and Chukchi Seas
Water in in situ experiments of 10 days. August 1988.

Region of

Station

Level of

BaPc

ancentration.

BaP

the works

No.,

sampling

Hg/1

Microbial

date

nitial

Final

transfor-

C, Control Exper.

mation.

%C,

East

3,

0.5

100

99.8

14.7

Polygon

28.07

0.5

100
100

85.3
91.5

8.5

The Gulf

7,

Surtace

100

99.7

of Anadyr

01.08

microlayer
Surface

100

81.5

18.5

microlayer

0.5

100

76.0

24.0

0.5

100

80.5

19.5

The Gulf

18,

Surface

100

99.7

of Anadyr

03.08

microlayer
Surface

100

93.9

6.1

microlayer
0,5

100

60.7

39.3

The Chukchi

45

Surtace

20

19.9

Sea

microlayer

09.08

Surface

20

17.9

10.5

microlayer
0.5

20

9.7

51.5

(1.5

20

15.8

21.0

The Chukchi

50

Surtace

20

20.0

Sea

microlaver

10.08

Surface
microlaver

20

15.1

24.5

0.5

20

10.9

45.5

The Chinkov 89

0.5

20

20.0

basin

11.08

0.5

20

19.2

3.8

0.5

20

19,5

2.6

The Bering
Sea

110
10.08

0.5

0.5

20
20

20.0

17.8

11.0

0.5

20

13.8

31.0

0.5

20

12,1

39,5

PAH's (Izrael ct a!., 1987). In addition, the rate of BaP
transformation in the Bering Sea microflora is sufficiently high
and similar to rates measured in the Baltic Sea (Tsyban et ai,
1985). Thus, the metabolism of PAH's by microflora should
be considered as an essentially important process in the
detoxication and remov al of pollutants from the ecosystems of
the World Ocean.

94

TABLE 2

Dynamics of BaP transformation catised by the Bering and

Chukchi Sea waters microtlora in long in situ experiments

(Auaiist 1488).

Region,

Length of

Original

On

ginal

Station No.

j,\position.

concentration

concentration

days

BaP = 1 .0

BaP

= 10.0

|4

g/l/C,

Hg/

i/c,„

BP transformation

ng

% from C|

mg

9c from C|,i

The Bering

Sea. North

7

0.31

31

4.21

42.1

Polygon.

10

0.59

40

5.47

54.7

Station No.

36

14

0.85

85

6.68

66.8

South-East

part of the

3

1.53

15.3

Chukchi Sea,

5

0.29

29

3.91

39.1

Station No.

53

7

0.52

52

5.70

57.0

10

0.80

80

7.12

71.2

14

0.81

81

7.64

76.4

:i

0.83

83

7.81

79.1

4.3.2 Transformation of Poly chlorinated

Biphenyls by Marine Bacterioplankton

ALLA V. TSYBAN, SERGEI M. CHERNYAK, and GENNADIY V. PANOV

Institute of Global Climate and Ecology. State Committee for Hydrometeorology and Academy of Sciences. Moscow. USSR

Introduction

Pollution of biosphere, the World Ocean, by xenobiotics
has become not only an ecological problem but a social
problem. In the postwar years, production of synthetic organic
compounds increased worldwide. In 1950, 7 million tons were
produced — by 1970,63 million tons, and by 1983. 230 million
tons(Geiss&Bourdeaux, 1986). At present, 5 million different
xenobiotics are produced by chemical manufacturers, with
fifty thousand being sold on the world market every year. No
iTiore than 10% of synthetic compounds (of the total amount
produced) are reportedly toxic and only twenty thousand
xenobiotics have been studied for genotoxic activity (Loprieno,
1981; Tanabe, 1983).

Most investigated chlorinated hydrocarbons are PCB's
(Tanabe, 1983). This is due to wide application in industrial
and domestic materials, resistance to biodegradation and
bioaccumulation capability, acute toxicity, and unfavorable
effect upon reproductive processes in pelagic organisms. Also,
analytical techniques allow for reliable PCB determination in
most environmental samples.

Current predictions (Bletchly. 1984) on the dynamics of
chlorinated hydrocarbons in the marine environment indicate
that chlorinated hydrocarbon concentration in the World Ocean
will increase 1.3-1.7 times by the year 2000. Because of the
production of new synthetic substances and accumulation in
the environment, scientists are interested in knowing the sources
and fates of xenobiotics. At present, the elimination of PCB's
from the environment occurs through photochemical oxidation
and microbial degradation.

Aspects of PCB biotransfortiiation need further study. In
recent years, a great body of information has been ctiilected,
transformation of PCB's by individual strains of
microorganisms, relating to different systematic groups (Ahmed
& Focht, 1973; Sayler et cd.. \911: Furukawa et ai. 1978;
Furukawa et ai. 1979, 1983; Liu, 1980; Furukawa &
Chakrabarty, 1982; Furukawa, 1982; Brunner ef «/., 1985;
Unterman et ai. 1983; Bedard el ai, 1986; Bopp, 1986;
Bedard et ai. 1987a, 1987b; Kohler et ai. 1988). Many
bacteria have been shown toutilize PCB's as a source of carbon
and energy (Karasevich, 1982;Shieldst7a/., 1985). However,
not all PCB congeners are subject to microbial attack, which is

95

associated with the structure of PCB components. Thus,
results from laboratory assays indicate that different PCB
congeners are subject to different degrees of microbial attack
and that each strain is capable of transforming a different
spectrum of congeners ( Kohler et ai . 1 988 ).

Because the World Ocean can be regarded as a reservoir of
anthropogenic compounds, the assessment of PCB
transformation in the marine environment is important. Our
investigations of PCB microbial transformation under natural
marine conditions were conducted during the Third Joint
US-USSR Bering & Chukchi Seas Expedition. This work
assesses biodegradation potential of PCB " s by isolated bacterial
strains and natural marine bacterioplankton communities.

Materials & Methods

Experimental assessment of marine microflora
biodegradation potential of PCB's was made on board the
research vessel Akademik Korolev in July-August 1988.
Overall, 12 assays (Table 1) were conducted in the eastern,
northern, and southern parts of the Bering Sea, including the
Gulf of Anadyr, the Chirikov basin, and the southern Chukchi
Sea.

TABLE 1

Characteristics of the regions of sampling when conducting
experiments (see Frontispiece for location of Stations).

Sea. Sampling Stations Experiment Water Salinity
Region Number Temperature (%)

°C

Bering Sea,

3

1

8.8

32.60

East Polygon

Bering Sea,

7

2

7.2

32.60

Gulf of Anadyr

18

3

7.3

31.16

22

4

6.5

31.46

Bering Sea,

35

5

7.4

30.91

North Polygon

Chukchi Sea

45

6

2.3

24.04

50

7

6.1

31.66

53

8

4.4

31.09

55

9

5.3

31.56

69

10

-> 2

32.26

Bering Sea,

89

11

6.1

31.70

Chirikov basin

Bering Sea,

110

12

9.6

32.94

South Polygon

Niskin bottles (5-10 1) sterilized with 96° ethanol were
used to collect samples from the upper ().5-m surface layer.
Subsamples (200 ml) were drained into .500 ml dark glass
bottles. These bottles were washed thoroughly, rinsed with
acetone and hexane, and sterilized with dry heat at 200°C for

2 hours. For assay control, seawater from the same samples
were sterilized by autoclaving at 1 atm (1.01 x 10^ Pa) for 30
minutes.

Gas-liquidchromatography (Tuistra&Traag, 1983; Kohler
et ai. 1988) was used to determine background PCB
concentrations in 200-ml samples, which were always below
detection. To determine the most probable number (MPN) of
saprophytic (SB) and PCB-transforming (PCBB) bacteria, a
dilution method was used (Tsyban et al., 1988).

To determine the MPN of SB, a broth based on seawater
from the various regions was used as the culture medium (see
Subchapter 4.3). The medium was distributed into test tubes
and sterilized by autoclaving. After inoculation, PCB solution
was added into each test tube.

Considering the distribution of PCB in the Bering Sea
conducted in 1984 (Izrael & Tsyban, 1990), experiments were
based on the use of PCB Aroclor 1 232 mixture, a composition
similar to the PCB mixture found in the region. Each experiment
was conducted with two series of test bottles: the first series
with PCB concentration of 100 ng/1 and the second series of
lOng/1. Each test was duplicated.

Polychlorinated biphenyls solution in ethanol was added
to control and test bottles and thoroughly shaken for 1-2 min
and then incubated in the dark to prevent photochemical
processes. The experiment was incubated under //; situ
conditions (range 2-10°C) over the period of investigations.

At 1,3,5, 10, 14, and 21 days, water (1 ml ) was taken from
each test and control bottle to determine the MPN of SB and
PCBB. Concentrated H,S04 ( 1 ml ) was added into each bottle
to stop microbial metabolism. The amount of PCB remaining
was determined by gas-liquid chromatography.

Results and Discussion

From the Aroclor 1232 experiment. 1 9 out of 70 congeners
were transformed and those (Table 2) became the focus of the
study.

In the East Polygon in the Bering Sea, the percentage of
individual Aroclor 1232 consumption, with an initial
concentration of 100 ng/1, varied from 7% for
hexachlorobiphenyls (Table 2) to 95-100% for
dichlorobiphenyls (Figs. 1,2). Trichlorobiphenyls were also
transformed, ranging from 64 to 90%. Degradation of
pentachlorobiphenyls varied little, ranging 36-44% (Fig. 1,
Table 3). Fortetrachlorobiphenyls, this group of Aroclor 1232
congeners can be divided into those that were readily labile
over the 10-21 days, a biotransformation rate of 49-58% of the
initial content, and those that were relatively stable, a rate of
10-18% of the initial content.

Similar observations were revealed with an initial PCB
concentration of 10 ng/1. Transformation of congeners, however,
was more rapid, especially during the first 3 days (Table 3).

Figure 1 a shows the change in number of saprophytic and
PCB-transforming microorganisms with an initial PCB
concentration of 100 ng/1. After the first day. the MPN of the
bacteria did not increase over the initial numbers, but bacterial
break down of PCB's continued. For dichlorobiphenyls, 40to
52% of these congeners (nos. 5,8, 15; Fig. lb) were transformed

96

TABLE 2

Systematic numbering of Aroclor 1232 congeners (Ballschmitter

and Zell, mSO), and congeners subjected to transformation by

bacterioplankton of the Bering and the Chukchi Seas.

PCB-

100

Congeners

Numbers

Structure

5
8

15

Dichlorobiphenyls
2,3
2,4/

4,4/

18
22
28
31

Trichlorobiphenyls

2,2/,5
2,3.4/
2.4,4/
2.4/.3

40
44
47
52
60
66
70
77

Tetrachlorobiphenyls
2.3/3.3/
2.2/.3.5/
2,2/.4,4/
2,2/5,5/
2,3/.4,4/
2,3/.4,4/
2.3/.4/.5
3.3/.4.4/

87
97
101

Pentachlorobiphenyls

2.2/.3.4.5/
2.2/.3/,4,5
2.2/.4.3.5/

153

Hexachlorobiphenyls
2.2/.4.4/5.5/

21 days

Fig. la. Most probable number of sapropliy tic bacteria (.SB, cells/ml) and PCB
transforming bacteria (PCBB, cells/ml)

in the first day. The same trend also occurred with an initial
PCB concentration of 10 ng/l. In the first day, 70-73% of
dichlorobiphenyls were transfomied (Table 3).

Over the next 10 days bacterial numbers increased
exponentially with both bacterial groups of SB and PCB
reaching 1.8 x 10^ cells/ml (confidence interval, 2.7 x 10' to
1.2 X 10^ cells/ml). The percentage of transformation of PCB

days

Fig. lb. Microbial transtormalion of individual Aroclor 1232 congeners (%)
in the experiments. In Experiment No. I. PCB initial concentration
was at lOOng/l. Numbers are coherent numbers, see Table 2. Samples
collected from the Bering Sea. East Polygon (Station 3).

tV-ww»iv.5Ji.«

Control, initial
composition of PCB

1 SI day

t

18

A \

8

10

15

-^wV

A

A

jm K

3rd day

1

8

5 7

AX

8

K

10 15 ,

V

5th day

1

18

7

8

A

\° J

1

-"VA,

J\Ml^ V

Fig. 2. Microbial transformation of Aroclor 1232 (congeners numbers 5, 8,
15; see Table 2 ) in the central Bering Sea, Station 3 (East Polygon) in
July 1988.

97

also followed the increase in all numbers (Fig. la.b). However,
after 10 days biotransformation decreased as most of PCB
congeners remained practically unchanged.

Figure 2 shows Aroclor 1232 chromatograms that reflect
the change in concentrations of individual PCB congeners over
the experiment period. The concentration of congeners varied
from to 10%.

Experimental data (Table 3; Figs. 3,4.5) indicate a great
similarity in the rates of PCB transfomiation in various regions
of the Bering and the Chukchi Seas. In the Chukchi Sea. with
a thawing ice flow and a low salinity of 24.04%. the change in
the MPN of bacteria under study and the rate of Aroclor 1232
transformation were similar to those found in the Bering Sea
(Figs. 1,5; Table 3). Controlbottles with sterile water and PCB
concentrations at 100 ng/l or 10 ng/1 remained unchanged.

cells/ml

10

10

10

1

10

14

€ PCBB

I
21

days

Fig. .^a. Most probable number (MPN) of saprophytic bacteria (SB,
cells/ml) and PCB transforming bacteria (PCBB, cells/ml).

TABLE 3

Transformation rate (degradation percentage) of individual
Aroclor 1232 congeners by bacterioplankton of the Bering and the Chukchi Seas.

Experiment
Numbers

Congeners
Numbers

Initial concentration of PCB
100 ng/1

1 ?• 5 10 14 21

day days days days days days

Initial concentration of PCB
10 ng/1

I 3 5 10 14 21

day days days days days days

^

s

10

II

13

14

5
8

15
18

22

28

31

40

44

47

52

60

66

70

77

87

97

101

153

5
8

15
18
22
28
31
40
44
47
52
60
66

52

71

87

94

100

100

70

86

92

98

100

100

46

72

86

95

100

100

73

87

95

100

100

100

40

67

84

95

95

95

70

81

94

100

100

100

14

34

50

57

61

64

33

57

58

61

63

63

14

44

61

61

65

65

31

54

57

62

62

62

29

58

78

90

90

90

54

82

89

90

90

90

12

38

59

66

66

66

30

52

55

59

61

67

10

10

40

45

45

50

30

50

52

55

55

55

18

40

54

58

58

58

38

48

55

58

58

60

5

12

15

15

15

18

6

13

17

20

20

20

5

10

12

15

15

15

10

12

13

14

15

15

13

38

44

50

50

50

32

48

54

56

58

58

5

II

18

18

18

18

6

13

17

19

20

20

12

19

45

48

48

49

32

44

51

52

52

52

5

7

10

10

10

10

6

8

10

10

10

10

10

33

40

42

42

42

20

40

43

45

45

45

g

29

35

36

36

36

20

28

36

37

38

38

8

")T

33

44

44

44

21

25

36

47

48

48

3

5

7

7

7

7

■)

6

8

8

8

8

53

72

88

95

100

100

71

87

93

99

100

100

46

72

87

94

100

100

72

86

95

100

100

100

41

66

85

96

96

96

69

82

95

100

100

100

13

35

51

57

61

65

32

56

57

62

64

65

14

43

62

64

67

67

30

55

58

62

62

62

30

57

77

90

90

90

50

80

86

90

90

90

12

40

60

66

66

66

31

52

54

60

60

65

10

10

39

44

44

49

29

51

53

54

56

56

17

41

55

57

58

58

37

49

54

59

60

60

6

12

15

15

17

18

7

14

18

21

21

22

5

10

12

15

15

15

10

12

13

14

15

15

12

40

44

50

50

50

27

51

55

59

59

59

6

12

19

19

19

19

6

13

17

19

20

20

98

TABLE 3 - continued

Transformation rate (degradation percentage) of individual
Aroclor 1232 congeners by bactenoplantvton of the Bering and the Chul^chi Seas.

Experiment
Numbers

Congeners
Numbers

day

Initial concentration of PCB
lOOng/l

3 5 10 14 21

days days days days days

dav

Initial concentration of PCB
Klniz/l

5 10 14 21

days days days days day''

8

10

I 1

i;

13

11

70

77

87

97

101

153

5

8

15

18

22

28

31

44

47

52

60

66

70

77

87

97

101

153

5

8

15

18

22

28

31

10

20

44

48

48

4S

.^3

46

52

52

52

52

5

7

10

10

10

10

6

8

10

10

10

10

9

32

41

42

42

42

21

41

43

45

45

45

21

29

36

37

38

39

20

28

36

37

38

38

8

•>2

33

44

44

44

20

26

38

48

48

48

3

5

7

7

7

7

2

6

8

8

8

8

52

72

88

95

100

100

72

86

92

100

100

100

47

71

85

95

100

100

70

87

94

100

100

100

40

65

84

95

100

100

72

85

94

100

100

100

14

35

52

55

62

64

31

57

59

61

65

65

13

44

61

64

68

68

29

54

59

63

63

63

30

57

77

90

90

90

51

81

87

90

90

92

12

39

59

66

66

66

31

55

55

59

64

66

17

41

55

58

58

58

36

50

56

60

61

61

6

12

15

15

17

18

6

14

19

22

-)-)

11

4

1 1

12

14

15

15

10

12

13

14

15

15

40

41

45

51

51

51

33

50

55

57

59

62

5

12

18

18

18

18

6

13

17

19

20

20

11

19

45

48

48

49

27

47

55

56

56

56

3

7

10

10

10

10

6

8

10

10

10

10

10

32

41

42

42

43

20

42

44

46

47

48

10

28

37

38

38

38

20

23

36

37

38

38

8

22

33

44

44

44

20

25

37

47

48

50

T

5

7

7

7

7

2

6

8

8

8

8

50

72

86

94

100

100

70

88

95

98

100

100

45

72

85

96

100

100

71

87

92

100

100

100

40

65

86

95

95

95

69

87

92

100

100

100

14

35

55

55

63

65

28

55

62

64

65

65

14

44

61

66

68

68

24

56

68

64

64

64

29

59

77

89

90

90

53

81

87

90

92

92

11

39

59

66

66

66

30

52

54

58

62

66

40

10

10

39

45

45

50

22

50

53

58

58

58

44
47
52

16

41

55

58

58

58

5

12

15

15

15

18

5

11

15

15

16

16

33

55

59

62

62

63

6

18

21

ii

22

23

10

12

13

14

15

15

60

44

50

50

50

23

55

60

65

69

70

66

70

77

87

97

101

153

5

12

18

18

18

18

6

13

17

19

20

20

12

19

47

48

48

48

29

47

50

59

59

60

5

7

10

10

10

10

6

8

10

10

10

10

10

32

42

42

42

42

20

40

45

45

45

45

9

29

3H

38

38

39

20

28

36

37

38

38

8

22

33

44

44

44

20

25

42

50

50

50

3

5

7

7

7

7

2

6

8

8

8

8

99

100

Fig. 3b. Microbial transformation of individual Aroclor 1232 congeners C/c)
in E.xperiment No. 2, PCB initial concentration was at 100 ng/1.
Samples collected from the Gulf of Anadyr of the Bering Sea. Station
7. Numbers are coherent numbers, sec Table 2

MPN. cells/ml
10^

10

10

PCBB

a)

days

13 5 10 14

Fig. 4a. Most probable numbers of SB and PCBB.

21

PCB'

davs

Fig. 4b. Microbial transformation of individual Aroclor 1232 congeners in
Experiment No. 6. PCB initial concentration at 100 ng/1. water from
the Chukchi Sea. Station 45. Numbers are coherent numbers, see
Table 2.

Lm^w

Control, initial
composition ot PCB

Initial 8

f

V

3rd dav

^Jy}^jj-M

5th day

1

7
5 11
A. A ^

Jv^

[

Fig. 5. Microbial transformation of low chlorinated Aroclor 1232 congeners
(coherent numbers 5. 8. 15) at Station 4 in the southern Chukchi Sea
in August 1988.

Analysis of PCB congeners, after biological degradation,
showed that the decomposition of the chlorinated hydrocarbon
is primarily affected by stearic configurations and halogen
atom substitutions. The stability of PCB congeners is probably
influenced by intermolecular bonds. The decomposition of
PCB occurs through the production of arene-oxides, which are
substituted with biphenyl molecules in positions 2, 2', 5, 5'.

Thus, the results show that only low chlorinated biphenyls
are subject to rapid microbial decomposition in the arctic and
subarctic waters. Many such compounds, however, are only
partially transformed, which in turn may be more toxic to
marine biota. Highly chlorinated biphenyls. in contrast, are
extremely resistant to degradations. Consequently, these
compounds may accumulate in the ecosystem and circulate in
the marine environment for many decades ( Izrael & Tsyban,
1989).

In summary, the results clearly show the ecological toxicity
of chlorinated hydrocarbon pollution in the arctic regions.
Because of low arctic temperatures, chemical degradation of
xenobiotics is practically absent due to slow rates of microbial
transformation.

100

Subchapter 4.4:

Biologic Characteristics of
Marine Microorganisms

4.4.1 Biological Features and Genotoxic
Properties of Microorganisms

ALLA V. TSYBAN*. GENNADIY V. PANOV, VLADIMIR A. IVANITSA*. and GALINA V. KHUDCHENKO'

Institute of Global Climate and Ecology. State Committee for Hydrometeorology and Academy of Sciences. Moscow, USSR
'Odessa State University', Odessa, USSR

Introduction

Local or regional increase in the concentration of some
natural components, such as heavy metals, oil, and nonnatural
components up to toxic levels, is a characteristic feature of the
present ecological situation in the World Ocean (Izrael et al.,
1987). Therefore, a serious problem has arisen, concerning a
change in the metabolism of microorganisms as well as their
adaptation to new chemical conditions of the environment.

It has been determined that adaptation of microorganisms
plays an important role in biodegradation of toxic organic
compounds. Adaptation can be defined as a change in the
microbial population which increases the rate of transformation
of toxic substances as a result of the preliminary contact with
these compounds. It is quite obvious that to predict the
biodegradation rate of organic pollutants in the marine
environment, it is necessary to gain an understanding of the
mechanisms of microbial transformation, such as genetic
transfer or mutation, enzyme induction, and changes in the
level of populations. It is also obvious that these mechanisms
play an important role in the process of adaptation of microbial
populations to new substances.

Although mechanisms of microbial degradation may differ,
the process is under the genetic control of chromosome or extra
chromosomal (plasmid) material. Numerous forms of genetic
transmission with plasmids can occur and can offer strong
possibilities for genetic engineering in nature, including the
World Ocean. Evidence in support of this can be seen in the
distribution of benzo(a)pyrene- and PCB-transforming bacteria
in estuaries, the Baltic, Bering, and Chukchi Seas (see preceding
Subchapters).

While studying the mechanisms of biodegradation.
controlled by plasmids, the traits providing selective advantages
to marine organisms become of primary importance. Such
traits are the resistance to bactericidal toxic compounds (for
instance, heavy metals) and the ability to utilize a number of
substances of a biogenic origin (Karasevich, 1 982; Izrael ei al. ,
1987). Thus, protective functions determined by plasmid
genes can be acquired by a microbial cell under changing
environmental conditions. Although other traits should not be
disregarded, they are not related to direct selection. These traits
provide a cell with some advantages in the habitat and possibility
of transferring traits inside a bacterial population (Izrael &
Tsyban, 1989).

The above account outlines the importance of studying the
signs of plasmid transmission in marine microorganisms. The
purpose was to assess and forecast the ecological state of the
environment, including protective properties of marine

ecosystems. In addition, change in the genotypes of marine
microorganisms can be determined (Izrael & Tsyban, 1990).
New data on the biological properties of heterotrophic
microorganisms of the Bering Sea were recently obtained.
Investigations of the physiological, biochemical, and genetic
features of strains isolated from various components of marine
ecosystems were conducted by microbiologists of the Natural
Environment and Climate Monitoring Laboratory (Institute for
Global Climate and Ecology from 1991) of the USSR State
Committee for Hydrometeorology and USSR Academy of
Sciences. These materials have already been published in part
by Izrael f/(;/. (1987) and Izrael &T,syban( 1989, 1990). The
present paper describes research on the biological, biochemical,
and genetic features of strains isolated from the Bering and
Chukchi Seas in 1984 and 1988.

Methods and Materials

Investigations were conducted on 320 strains of
heterotrophic bacteria isolated from the Bering Sea in 1984,
and on 77 strains of bacteria isolated from the Chukchi Sea
water in summer 1 988. Selection of traits was determined by
plasmids, and methods of data processing were determined by
experimental procedures.

The specific character of genetic investigations of a large
collection of microorganisms isolated from the marine
environment has necessitated the choice of the mass screening
method. The collection of the cultures was subdivided into
homogeneous groups based on traits that are easily identified
in mass screening (Izrael & Tsyban, 1990). Resistance of
cultures to antibiotics, organic pollutants, and heavy metals
(Hg, Cd, Co, Cu, Pb. and Ni) were investigated as signs of the
presence of plasmids.

Ability to degrade petroleum hydrocarbons and paraffin
was determined from the presence of the zone where bacteria
grew on the compact nutritious medium prepared on seawater
(Tsyban, 1980) around sterile disks soaked with relevant
hydrocarbons. Minimum inhibiting concentrations (MIC)
were serially diluted in a solid medium. Eleven antibiotics of
the basic groups: ampicillin (Amp), benzylpenicillin (Ben),
and mcthicillin (Mtt) from the penicillin group: gentamicin
( Gen ), kanamycin ( Kan ). monomycin ( Mon ), and streptomycin
(Str) from the group of aminoglycosides; chloramphenicol
(Clm) and tetracycline (Tet), broad-spectrum antibiotics;
polymicin (Pol) from the group of polypeptide antibiotics: and
nalidixic acid (Nal) in the range of concentrations from 0.06 to
4,000 |ig/ml. Due to high sensitivity of microorganisms to
gentamicin. the range of its concentration was 0.06 to 8 Hg/ml.

103

Resistance of the strains to each antibiotic taken separately,
frequency of mono-, di-, and polyresistant strains, as well as
resistance spectra (R-spectra) were recorded.

To determine the resistance of heavy metals, the following
salts were used: Hg(NO,), 2H,0, Pb(NO,),. CdCl,. CuSO,
(waterless), and NiSOj in the range of 0.5 to 1,024 ng/ml. In
terms of the number of ions, this amounted to 0.4-882 for
Hg2=*; 0.35-670 for Pb-^ 0.3-627 for Cd-*; 0.2-464 for Co-^
and 0.15-331 forCu^

Choice of the concentrations of antibiotics and heavy
metals and assessment of the bioresistance level of marine
microorganisms were based on literature data. Kulskyi er al.
(1986), working on the problems of natural sensitivity of
different representatives of microflora from aquatic and soil
biocenoses, published information on maximum permissible
concentrations (MFC) of these pollutants.

The genotoxic effects of cultured microorganisms were
studied using a biological model including three indicator
strains of Escherichia coli: E. coli WP-2 (a wild strain that
retains its unchanged complete gene pool). E. coli Pol A- (a
strain that is unable to synthesize one of the enzymes responsible
for DNA reparation [DNA polymerase 1 ] ), and E. coli Rec- (a
strain that lacks a recombination system, specified by
conjugation [Slater e? a/., 1971]).

Growth suppression of genetically altered strains E. coli
Pol A- and E. coli Rec- to a genotoxic effect of the substrate
under study was accepted as proof of its carcinogenic activity.

The pathogenic properties of bacteria strains were assessed
using white mice as well the cultures of human embryo kidney
cells (RH) and fish skin cells (EPC) (Tsyban, 1988).

Results and Discussion

In the process of experimental investigations, data were
obtained that characterize the following biological properties
pf marine microorganisms: the relation to organic pollutants
(e.g.. resistance and degradation ability), resistance to heavy
metals, genotoxic and DNA-damaging properties, and
pathogenicity.

Growth of cultures on media containing organic pollutants
is defined not only by the cultures' ability to degrade these
compounds, but also by their resistance to high concentrations
of pollutants. The screening test made it possible to divide the
strains of the dominant taxons into three groups: /. resistant to
a pollutant and capable of degradation; 2. resistant but not
capableofdegradation;andi. sensitive to a pollutant (Table 1 ).
The results show that microorganisms isolated from the Bering
Sea are rather resistant to the impact of oil and paraffin*. The
greatest activity for oil degradation was exhibited by bacteria
of the genus Pseudomonas; 72.6% of active cultures occurred
among them, and only 6.0% of the strains proved sensitive to
oil. In the study of effects of paraffin on the tested strains, it was
observed that Bering Sea microorganisms were sensitive and
that 28.7% of the investigated strains failed to grow in the
presence of paraffin.

TABLE 1

Decomposition of petroleum hydrocarbons and paraffin by

microorganisms of different taxonomic groups isolated from the

Berina Sea.

Genus Number

Percent of

positively tested strains

of

strains

Oil

Paraffin

DR

R

S

DR

R

S

Pseiidoinonas 84

72.6

21.4

6.0

65.5

10.7

23.8

Bacterium 52

69.2

25.0

5.8

67.3

17.3

15.4

Pkmococcus 58

65.5

27.6

6.9

62.1

5.2

32.7

Bacillus 76

69.7

23.7

6.6

53.9

7.9

38.2

Other genera 47

66.0

23.4

10.6

46.8

21.3

31.9

TOTAL 317

69.1

24.0

6.9

59.6

11.7

28.7

Note: D = decomposition; R

= resistance; S

= sensitivity.

One of the processes occurring in natural microbial
populations is microevolution of bacteria, proceeding under
the selective pressure of anthropogenic factors. Thus, a variety
of microorganisms may develop in their bioresistance to a
number of pollutants.

The mechanism of acquired poly resistance to unfavorable
environmental factors is based on the intensive intra- and
interspecific exchange of extrachromosomic elements of nuclear
material (i.e.. plasmids). The level of this exchange is highest
in sewage and may be the same in water bodies having high
pollution levels (Baya er al., 1986; Kulskyi ef al.. 1986; Day
et al.. 1987; Boominathan el al.. 1988; Gealt, 1988; Lmton,
1988; Schmidt & Schlegel, 1989).

The character and level of antibiotic resistance were
studied in representatives of the genera Pseudomo)uis and
Bacillus that dominate in the microbial communities of the
Bering and Chukchi Seas. MIC of antibiotics, the proportion
of sensitive and stable strains, the number of resistance
determinants, and the most widespread R-spectra were
determined. In the study of R-strain distribution, the strains for
which the MIC of an antibiotic exceeded 31.2 |ag/ml (2 |ig/ml
for gentamicin), were considered R-strains.

A common feature of all represented taxonomic groups of
Bering Sea microorganisms was the small percentage of strains
sensitive to all the antibiotics (0 to 6.3% in different taxonomic
groups). The percentage of strains resistant to one antibiotic
averaged 24.6%, with a maximum value for the representatives
of Bacillus genus (37.5%). Strains resistant to two antibiotics
occurred on average 12.0%, with small variations among
different taxonomic groups, a range of 8.3-15.6%. Strains
resistant to methicillin were most frequent and dominated
among the representatives of the genera Pseudomonas and
Planococcus (54.2 and 46.5%, respectively). They averaged
43.5% (Table 2).

104

TABLE 2

Resistance of Bering Sea microorganisms of different taxonomic groups to antibiotics
(the proportion of resistant strains - R-strains, %).

Total

Genus of

number
of the
strains

Antibiot

cs

micro-

Penicillins

.■\minoglvcoside

s

organisms

Amp

Ben

Krh

Mtt

0\c

Gen

Kail

Mon

Ris

Str

Pseudomonas

48

45.8

37.5

20.8

54.2

56.3

16.7

14.6

16.7

37.5

12.5

Planococcus

43

27.9

23.3

9.3

46.5

39.5

2.3

32.6

27.9

20.9

23.3

Bacillus

64

21.9

18.8

9.4

32.8

25.0

6.3

4.7

1.6

10.9

7.8

Other genera

36

38.9

3 1 .0

8.3

44.4

52.8

11.1

8.3

13.9

TT ~l

16.7

TOTAL

191

32.3

26.7

12.0

43.5

41.4

8.9

14.1

13.6

22.0

14.1

Multiple resistance to antibiotics was typical of the majoiity
of the heterotrophic microorganisms, isolated in the Bering Sea
basin, irrespective of their taxonomic position. The percentage
of such strains was 60.8%. The highest percentage found in the
genera Pseudomonas and Planococcus was 70.8 and 67.5%.
respectively (Table 3).

TABLE 3

Number of determinants of resistance to antibiotics with
microorganisms of different taxonomic groups.

Total

Percent

number

Genus

of the

Sensi-

Monore-

Diresis-

Polyre-

strains

tive

sistant

tant

sistant

PseiuUnmmas

48

2.1

14.6

12.5

70.8

Planococcus

43

2.3

18.6

11.6

67.5

Bacillus

64

6.3

37.5

15.6

40.6

Other 10 genera

36

27.8

8.3

63.9

TOTAL

191

2.6

24.6

12.0

60.8

The percentage of microorganisms resistant to natural and
semisynthetic penicillins ranged from 12.0% for carbenicillin
to 26.7-41.4% forbenzylpenicillin, ampicillin, and oxacillin.
The tendency was typical of all taxonomic groups. However,
most strains were among the genus Pseudonumas (above 50%
in some cases). Resistance to antibiotics is characteristic of
Pseudomonades (Palleroni, 1975).

Resistance of Bering Sea heterotrophic microorganisms to
aminoglycosides occurred much less frequently. Maximum
resistance to hentamycin, kanamycin. monomycin, and
streptomycin varied from 8.9 to 1 4. 17f. Resistance to ristomycin
was somewhat higher (22.2%). Among the different taxonomic
groups, the greatest number of strains resistant to
aminoglycosides occurred in the genus Planococcus.

Analysis of resistance spectra of Bering Sea strains of the
main taxonomic groups revealed great diversity (42. 37, and 33
spectra in the genera Pseudomonas. Planococcus. and Bacillus.
respectively) as well as the absence of the dominating

R-spectra. Diversity of R-spectra can probably be considered
as an indication of an extraordinary genetic plasticity of the
studied Bering Sea microorganisms.

The study of antibiotic resistance of the strains isolated
from Chukchi Sea water was conducted and compared with
antibiotic resistance of the strains isolated from the Baltic Sea
— an impact region of the World Ocean (Table 4).

TABLE 4

Resistance of the microorganisms of the Chukchi and Baltic Seas
(the proportion of R-strains, %).

Genera of

microorganisms

Antibiotics

Pseudom
Chukchi Sea

modes
Baltic Sea

Others

Chukchi Sea B

altic Sea

Amp

14.8

77.8

8.8

68.2

Ben

70.3

93.3

64.7

90.9

Mtt

100.0

86.7

79.4

95.5

Gen

11.1

6.7

14.7

13.6

Kan

im

17.8

58.8

50.0

Mon

92.6

28.9

67.6

68.2

Str

33.3

35.6

23.5

36.4

Clni

33.3

86.7

17.6

86.4

Nal

63.0

95.6

61.8

95.5

In Table 2, Pseudomonades of the Chukchi Sea were
characterized by resistance to benzylpenicillin and methicillin,
kanamycin and monomycin (77.7 and 92.6%, respectively),
and nevigramon-nalidixic acid (63.0%). The majority of the
Chukchi Sea strains showed a low resistance to gentamicin
(11.1%) like those of the Baltic Sea. Only one-third of the
strains proved resistant to streptomycin (33.3 %).

Pseudomonades from the Chukchi and Baltic Seas were
distinguished by the number of strains resistant to ampicillin,
levomycetin, kanamycin, and monomycin. The proportion of
the strains from the Chukchi Sea, which were resistant to the
first two antibiotics, were considerably less than of Baltic
Pseudomonades (14.8 and 33.3% versus 77.8 and 86.7%,
respectively). As far as resistance to kanamycin is concerned.

105

the contrary situation was observed. The percentage of the
strains resistant to kanamycin and other aminoglycosides in the
Chukchi Sea were considerably higher (77.7 and 92.6% versus
17.9 and 28.9% in the Baltic Sea).

The similar irregularities were found for other genera,
isolated from the Chukchi Sea (Table 4). It should be noted that
the modal values of MIC of antibiotics for Pseitdomanades
from the Chukchi Sea did not exceed (except for methicillin)
1 25 |ig/ml. while in similar repre.sentatives of Baltic microflora,
the modal MIC values of all antibiotics of the groups of
penicillins, chloramphenicol, polymyxin, and nevigramon were
1,000 |ag/ml (Table 5).

TABLE 5

Modal values of the MIC of antibiotics for murine bacteria,
percent.

TABLE 6

Antibioticogram of strains of marine Pseudomonades from the
Chukchi Sea.

Genera of microorganisms

Antibiotics Pseudomonades

Others

Chukchi Sea

Baltic Sea

Chukchi Sea

Baltic Sea

Amp

7.8/40.7

> 1.000.0/60.0

7.8/32.4

> 1.000.0/36.4

Ben

31-125.0/18.5

> 1,000.0/73.3

250.0/26.5

> 1,000.0/77.3

Mtt

> 1,000.0/62.9

> 1,000.0/84.4

> 1,000.0/50.0

> 1,000.0/90.9

Gen

0.5/55.6

0.3/31.1

0.5/38.2

1.0/36.4

Kail

62.5/37.0

15.6/31.1

31.2/20.6

125.0/27.3

Mon

125.0/40.7

15.6/37.7

250.0/23.5

62.5/27.3

Str

31.2/33.3

7.8/31.1

15.6/38.2

> 1,000.0/27. 3

Clm

15.6/29.6

>l,000.(J/46.6

7.8/47.1

> 1,000.0/3 1.8

Nal

250.0/25.9

> 1,000.0/40.0

15.6/23.5

> 1,000.0/68.2

Note: Modal values of the MIC (jjg/ml) are in the numerator; the
proportion of strains with the given modal values (%) in the
denominator.

A similar situation was revealed in the analysis of the
modal MIC values for other heterotrophic microorganisms of
the. Chukchi Sea. Among the Pseudomonades of both the
Chukchi and Baltic Seas, the percentage of those that are shown
to be polyresistant to antibiotics is high (92.5%).

Combination of resistance determinants are presented by
18 R-spectra. In contrast to Baltic strains, no dominating
R-speclrum was revealed in Chukchi strains (Table 6).

To determine if it is appropriate to relate the diversity of
R-spectra and polyresistance to the antibiotics of the dominating
taxonomic groups of heterotrophic microorganisms as criteria
of the pollution level of the region under investigation, a
comparison of data was obtained for Pseudomonas bacteria,
isolated from the Bering, Chukchi, and Baltic Seas (Fig. 1,
Table 4).

In Fig. I, antibiotics were grouped according to the
resistance to them by marine microorganisms. Resistance to
the first group, comprising ampicillin, kanamycin, and
streptomycin, is determined by plasmid genes. Resistance to
the second group, comprising benzylpenicillin, methicillin,
and monomycin, is determined by chromosomic genes. Figure
1 shows that in the Baltic and Chukchi Seas, among bacteria in
the genus Pseiidoimmas. the number of strains resistant to the
antibiotics is much higher than that in the Bering Sea. In the
Baltic Sea, microorganisms of other taxonomic groups were

Distribution among

the spectra

Abs.

R-spectra

number

percent

Amp Ben Mtt

Kan

Mon

Str

Clm

Nal

2

7.4

Amp Ben Mtt

Mon

Str

Clm

Nal

1

3.7

Ben Mtt

Kan

Mon

Str

Clm

Nal

2

7.4

Ben Mtt

Ger

1 Kan

Mon

Str

Clm

1

3.7

Ben Mtt

Kan

Mon

Clm

Nal

1

3.7

Ben Mtt

Ger

1 Kan

Mon

Str

1

3.7

Amp Ben Mtt

Kan

Nal

1

3.7

Ben Mtt

Kan

Mon

Nal

3

11. 1

Mtt

Kan

Mon

Str

Nal

1

3.7

Mtt

Ger

1 Kan

Mon

Str

1

3.7

Ben Mtt

Kan

Mon

4

14.8

Ben Mtt

Mon

Nal

~>

7.4

Ben Mtt

Kan

Nal

1

3.7

Mtt

Kan

Mon

Nal

->

7.4

Mtt

Mon

Clm

1

3.7

Mtt

Mon

Nal

1

3.7

Mtt

Mon

1

3.7

Mtt

1

3.7

more resistant to antibiotics than those in the Chukchi Sea. In
the Bering Sea, they were the most sensitive to antibiotics. Of
special interest, in the Chukchi Sea, the Pseudomonades and
other microorganisms showed more resistance to those
antibiotics, which was determined by chromosomic genes.

Bacteria of the genus Pseudomonas from the impact
region of the Baltic Sea possessed a rather high sensitivity to
aminoglycosides, especially to gentamicin and kanamycin.
Resistance to penicillins was also found in 77.8-93.3% of the
cases. In this case, the number of polyresistant strains, having
three and more determinants of polyresistance, accounted for
95.6%. However, the Baltic strains also possessed the
dominating R-spectrum in 42.2% of the strains.

This information suggests that among the dominant
heterotrophic microtlora in the Chukchi and Bering Seas, the
formation of strains resistant to antibiotics exists. However,
their abundance as a whole is less than in the impact region of
the World Ocean, such as the Baltic Sea. Thus, it is possible to
state that the percentage of resistance spectra and the level of
polyresistant strains in bacterial cenoses reflect the level of
pollution in the region.

Based on toxicological estimates of "stress indices," heavy
metals ranks second among pollutants behind pesticides ( Izrael
& Tsyban, 1989). Therefore, the abundance of dominant
marine bacteria that are resistant to heavy metals, may also
characterize the degree of marine pollution. To examine this
hypothesis the resistance of Chukchi Sea microflora to Cd, Co,
Cu, Ni, Hg, and Ph ions was investigated. Similar responses of
the strains from the Baltic Sea were studied for comparison
(Tables 7,8).

106

R. % - proponion of resistant strains of microorganisi
100 -

AmpicitlfitAmp)
Genlamvcin fGeni
Kunttmycin iKanf
Slrepu>m\cin fSlr)

AmpitillintAmp)
Genfamycin (Gent
Karuinyctn (Kant
Slrepiomycin iSlr)

BenzilpeniiHlintBfn)

MeuaUin tMii)
Monomycin iMon)

Fig. I . Resistance of marine microorganisms to antibiotics.

Thirty-three strains of Pseiidomonades, 1 7 strains of other
bacillary bacteria (including 7 strains from the group
Flavobacterium-Cytophaga. 5 from the ^Qnu^Arthrohacter, 2
from the genus Bacillus), and 12 strains of coccal forms
(including 8 strains from the genus Siaphylococcus, 2 from the
genus PUmococcus, and 2 from the genus Micrococcus) were
studied for resistance to heavy metals. Results show that
strains from the Chukchi Sea respond to heavy metals as those
from the Baltic Sea; that is. a wide MIC range and high modal
MIC values were found.

These results suggest that bacteria from the Chukchi Sea
have adapted to high concentrations of heavy metals. Because
all groups of bacteria did not differ in the mode and MIC range
of cadmium and lead, natural stability of the strains is one
explanation. However, modal values for Co, Cu, Hg. and.
partially. Ni. are substantially lower in Chukchi Sea strains
relative to those from the Baltic Sea. For instance, the mode of
cobalt MIC was 1.024 mg/1 for Chukchi Sea strains and
128 mg/1 for Baltic strains, while that for Cu was 256 and
128 mg/l and Hg was 32 and 16 mg/1. respectively.

However, for Chukchi Sea strains, the lower and upper values
of the MIC range were somewhat lower for most metals.
Although specific strains from the Chukchi Sea are resistant to
heavy metals, their resistance was considerably lower than in
strains from the Baltic Sea.

Anthropogenic pollution of marine waters with chemical
substances produces a considerable negative effect on the
genetic apparatus of microbes. This effect is due to mutagenic
and genotoxic material of certain pollutants. Microorganisms
are not only targets for the genotoxicants or mutagenes, but in
some cases they themselves enhance the effect and strengthen
it. Thus, microorganisms can, in the process of decomposition,
activate transforming pollutants into more toxic forms.
Similarly, it is acknowledged that microorganisms produce
different biologically active substances that elicit a broad
antibiotic effect. The chemical composition and structure of
these compounds suggest that they can also possess mutagenic
and genotoxic effects and, under environmental pressures, the
mutagenic and genotoxic activity of microorganisms themselves
can be strengthened. Thus, the development of marine
microorganisms, conditioned by chemical pollution, can serve
as an extra factor that strengthens the mutagenic stress upon
microbial communities. If ecological conditions continue to
deteriorate as in some regions of the World Ocean, the frequency
of induced mutations may increase, resulting in an artificial
evolution of bacterial strains.

The problem of mutagenic, genotoxic, and carcinogenic
effect of marine pollution, and the role of the microorganisms
are not yet investigated.

To detect genotoxic and DNA-damaging effects of
chemical compounds, bacteria that are most sensitive are
widely used. The disturbance of bacteria genotype is
immediately expressed in its phenotype because of the gaploid
chromosomes. In addition, a high level of correlation is
observed between mutagenic activity found in microorganisms
and their carcinogenic properties in animals.

Therefore, three strains of Escherichia coli were used for
the genetic screening: E. coli WP-2, E. coli Rec-, and E. coli
Pol A-. Sixty-two strains of bacteria capable of decomposing
hydrocarbons and cyclic organic compounds of the Bering Sea
were studied. This work involved: I. heat-killed marine
bacteria; 2. exometabolites — metabolic products released by
bacteria into the culture medium; and J. endometabolites —
metabolites contained in bacterial cells and released by
ultrasound disintegration.

The investigations showed that the ability to synthesize
metabolites with general toxic activity and DNA-damaging
effect was common to the different taxonomic groups of
Pseudomonas. Bacterium. Alcaligenes. Planococcus.
Flavobacterium-Cytophaga. Xantomonas, Arthrobacter. and
Bacillus. The general toxic effect of Pseudomonades was
noted for exo- and endometabolites and killed cells at 75, 50,
and eO'/f of the 32 strains, respectively (Table 9). The DNA-
damaging effect was found in 83% of all Bering Sea strains.
The results suggest that the genotoxic effect of the genus
Pseudomonas is not a specific feature of this genus. On E. coli
Pol A- model this effect was typical of exometabolites found in
69% of the strains, endometabolites in 54% of the strains, heat-

107

TABLE 7

Range of heavy metal MIC values for microorganisms of the Chukchi and Baltic Seas

Range of heavy metal MIC values, mg/1

Other non-

Metallions

Seas

Pseudoincmades

spore forming
rods

Bacilli

Micrococci

Cd-'

Chukchi

136.7

19.6-313.4

19.6-156.7

39.2-156.7

'

Baltic

78.3-313.4

78.3-313.4

39.2-156.7

not investigated

Co-*

Chukchi

14.5-116.2

29.0-116.2

29.0-116.2

29.0-116.2

Baltic

29.0-464.7

232.3-464.7

29.2-4

not investigated

Cu-*

Chukchi

10.0-39.9

10.0-39.9

2.5-39.9

10.0-39.9

Baltic

20.0-39.9

20.0-39.9

20.0-39.9

not investigated

Ni-*

Chukchi

96.5-386.0

96.5-386.0

96.5-386.0

96.5-386.0

Baltic

48.0-386.0

96.5-386.0

96.5-386.0

not investigated

Hg^*

ChukThi

2.4-19.3

4.8-19.3

4.8-19.3

4.8-19.3

Baltic

4.8-38.5

4,8-38.5

4.8-19.3

not investigated

Pb=*

Chukchi

160.1-640.4

80.0-320.2

40.0-320.2

160.1-320.2

Baltic

80.0-320.2

160.1-320.2

160.1-640.1

not investigated

TABLE 8

Modal MIC values of heavy metal salts for marine bacteria from the Chukchi and Baltic Seas.

Mode of MIC of strains ( n-

ig/l)/percent

Other non-

Metallions

Seas

Pseiidomonades

spore fomiing
rods

Bacilli

Micrococci

CdCl,

Chukchi

256/90.9

256/76.4

256/50.0

256/58.3

Baltic

256/40.6

128-256/35.7

256/42.9

not investigated

CoCl,

Chukchi

128/48.5

128/58.8

128/58.4

128/58.4

Baltic

1,024/59.5

512-1,024/42.9

1,024/42.9

not investigated

CUSO4

Chukchi

128/45.4

128/58.8

64/41.7

128/58.4

Baltic

256/67.6

256/71.4

256/64.3

not investigated

NiS04

Chukchi

1.024/42.4

256-512/35.3

256/50.0

512/50.0

Baltic

1,024/62.2

512-1,024/35.7

512/50.0

not investigated

Hg(N0,),2H,0

Chukchi

16/51.5

16/58.8

16/41.716/50.0

Baltic

32/35.1

32/35.7

32/42.9

not investigated

Pb(NO,)2

Chukchi

256/51.5

256/82.3

256/66.7

256/75.0

Baltic

256/8 1 . 1

256/85.8

256/85.8

not investigated

Note: Modal values (mode) of MIC is in the numerator; propoilion of the strains resistant to the given concentration of the
metal ions is in the denominator.

108

killed cells in 38% of the strains. On the E. coli Rec- niodel.
the above figures were 50, 50. and 67'7f , respectively ( Table 9 ).
Twenty-eight percent of the strains of Bering Sea
Pseudomonades produce compounds possessing DNA-
damaging effect upon both mutant strains. This suggests
carcinogenic activity.

TABLE 9

Toxic and DNA-damaging effects of metabolites of
Psfuddimmadi's from the Bering Sea.

Number of strains (%)
with positive effect
Test-object Exometa- Endometa- Killed

bolites bolites cells

E. coli WP-2
E. coli Pol A-
E. coli Rec-

75 50 60

69 54 38

50 50 67

In representatives of the F/(n'()/«(rr('/7H/;;-Cv/( '/'/;«,!,'(/ group,
DNA-damaging effect appears considerably lower than the
Pseudomonas. Only one of the seven strains gave a positive
effect in the model E. coli Pol A-.

From the comparison of the results on toxic and genotoxic
properties of the metabolites of the genus Pseudomonas isolated
from the Bering and Chukchi Seas, it was found that the
Chukchi Sea occupies an intermediate position between the
Baltic and Bering Seas. With respect to an increase in the
number of strains possessing the genotoxic activity, the seas
are listed in the order of the Bering Sea, the Chukchi Sea, and
the Baltic Sea.

Thus, investigations showed that an ability to produce
metabolites with a genotoxic effect is a marginal characteristic
of marine bacteria, such as Pseudomonas, Alcaligenes,
Xaiitomoiias. Arthrohaclcr, Bacillus, and Flavnhactehum-
Cytopliaga. However, the ability of marine bacteria to produce
substances possessing genotoxic activity, which was determined
under laboratory conditions, does not affirm if these properties
are dangerous under natural conditions. It remains unknown
whether bacteria produce a genotoxic effect in the marine
environment.

To determine the minimum concentrations of bacteria,
sufficient to elicit DNA-damaging effect, three strains of the
Elavi)hacterium-Cytf>pha,i>a group, which manifested a
genotoxic effect, were used. It was detennined that the maximum
dilution of exometabolites, at which the DNA-damaging action
was preserved, was 1:125. This corresponds to a bacterial
density in seawater on the order of 1 x 10' cells/ml under
experimental conditions. The active dilution for two other
strains ranged from 1 :25 to 1 :5. This corresponds to a bacterial
density to 1 x 10' to 1 x 10'' cells/ml.

Exo- and endometabolites of four strains (including the
above strains) with genotoxic and DNA-damaging effects
were analyzed by means of the standard Ames test. The
purpose is to elucidate questions about mutagenic activity.

As test strains, the specialized strains Salmonella typhimurium
TA-98 and TA- 100. when used, revert to prototrophicity with
respect to histidine due to mutation of a reading frame shift and
replacement of base pairs.

The results from this test suggest that one of the four strains
produced metabolites with mutagenic activity. Exometabolites
of this strain, in a volume of 0. 1 ml per Petri cap, induced
genetic mutations of the frame shift type. The frequency of
occurrence was more than 40 times higher than spontaneous
mutation (82.6 x 10*% as compared to the control value of
2.0 X 10"%).

Of great importance seems to be the DNA-damaging
effect clearly marked in the genus Pseudomonas. This genus
has gained an advantage in conditions of marine pollution and
develop in waters subjected to heavy anthropogenic inputs. So
we speculate that the development of indicator microfiora,
which includes bacterial decomposers in impact regions of the
World Ocean, is secondary pollution of the marine environment
(i.e., intensifying the potential response of chemical pollution
and threatening the genotype of marine ecosystems).

The ability of certain forms of microorganisms to change
under the effect of chemical pollution can be far from safe for
other marine organisms and man. There is a risk of possible
genetic transformation of harmless bacteria under the pressure
of the environmental mutagens and selection towards aggressive
pathogenic forms of microorganisms. The risk increases if the
protective mechanisms of animals and man have not yet
adapted. In this case, transformation of the microorganisms
can mutate from the nonpathogenic to quasi-pathogenic group
and from the latter into the pathogenic group.

Two main models are used to determine pathogenicity of
microorganisms. One is classical and is based on the
reproduction of an infection process in laboratory animals. The
other examines the effect of bacteria on man and animal cell
cultures as a model. Cell cultures provide a less expensive,
rapid answer, with a more stable assay with higher sensitivity
and reliability than results with experimental animals.

Pathogenic properties of 1 4 strains from the Bering Sea, 1 8
strains from the Chukchi Sea, and 27 strains from the Baltic Sea
were studied with the use of white mice and the reinoculated
kidney cells of a human embryo (RH) and fish skin cells (EPC)
(Tsybanf/«/.. 1988).

The study included 26 strains of two groups of bacterial
populations. These groups were Pseudomonas and
Flavobacterium-Cytophaga, isolated from the Bering Sea and
other regions of the World Ocean. With the use of the model
of intraperitoneal infection, white mice did not reveal pathogenic
properties. However, the use of cell cultures revealed a
differentiation of strains by the level of potential pathogenic
activity of bacteria cells.

The cytopathic effects cause morphological changes of
cells and disruption of the monolayer. For pathogenic strains,
cytopathic response occurred in 50-100% of the tests, quasi-
pathogenic (potentially pathogenic) strains — 25-50%, and
nonpathogenic strains — less than 25%. Changes observed
included vacuolization of cytoplasm, rounding-off of some
cells, and acidification of the medium. For controls, two
species were used: Pseudomonas fluorescence BKM-894(H)

109

as nonpathogenic, and Pseudomonas aeruginosa 2-9 as
pathogenic. Cytopathic effect of these strains on RH ceils
suggested that P. fluorescence BKM-894(H) did not produce
an appreciable effect on the cell culture, while the aggressive
strain P. aeruginosa 2-9 killed laboratory animals, destroyed
the cell culture monolayer by 75-100% after 48 hours and
completely suppressed the mitotic activity of the cells.

Analysis of cytopathic data (Table 10) showed that 44.5,
44.4, and 11.1% of the bacterial strains of the genus
Pseudomonas, isolated from the Baltic Sea, were pathogenic,
quasi-pathogenic (potentially pathogenic), and nonpathogenic
strains, respectively. Thus, both the quantitative and qualitative
assessment of cytopathic data suggests a high pathogenicity of
Baltic strains, and much higher than those of Bering strains.
These results support the related level of anthropogenic pollution
in the Baltic Sea (an impact region) and the Bering Sea (a
background region). In the Chukchi Sea, the proportions of
pathogenic, quasi-pathogenic, and nonpathogenic strains made
up 66.7, 1 1 .2. and 22.2% of the total number of the investigated
strains, respectively.

TABLE 10

Cytopathic effect of the strains of Pseudoinonades on the culture of
RH cells from the Bering, Chukchi and Baltic Seas.

The proportion of strains with
cytopathic effecl, %

Region

Nonpathogenic

Potentially
pathogenic

Pathogenic

BerinaSea 1984

Chukchi Sea 1988

Baltic Sea 1987

42.9

11.1

50.0

1.1

44.4

7.1

66.7

44.5

The discovery of pathogenic microorganisms in the
Chukchi Sea is of much interest and requires a thorough study.
The limited information available restricts an interpretation
about the cause of this phenomenon. The results of parallel
investigations of the cytopathic effect and invasive properties
of 1 8 strains oi Pseudomonas and Flavobacterium-Cytophaga
using the culture of kidney cells of a human embryo ( RH ) and
fish skin cells (EPC) are shown in Table 1 1. The study of Baltic
and Chukchi Seas strains, using the model of fish skin cells

(EPC) made it possible to determine their pathogenic properties
against fish. The comparison showed that 64. 2% of the studied
strains possessed cytopathic action. The results also showed
that a number of strains that did not manifest pathogenic
properties on human cells produced cytopathic effects on fish
cells. This confirms the different degree of pathogenicity of the
same strains of marine bacteria for man and fish.

TABLE 11

Cytopathic effect of the strains of Pseudomonades from the
Chukchi and Baltic Seas on the culture of RH and EPC cells.

Proportion of strains, %
Number of the Pathogenic Potentially Nonpathogenic

Region investigated pathogenic

slrains RH EPC RH EPC RH EPC

Chukchi
Sea, 1988

18 66.7 77.8

22 2 22.2

Baltic

Sea, 1987 14 50.0 71.4 50.0 28.6

Thus, these investigations suggest that under the pressure
ofchemical pollutants, pathogenic properties of microorganisms
can change as a result of transfomiation and selection. Besides
an ability to decompose complex organic compounds and resist
the action of antibiotics, heavy metals, and xenobiotics. marine
microflora can acquire pathogenic properties.

The discovered tendencies for increasing the aggressiveness
of marine bacteria are based on the adaptation of the bacterial
community to new chemical substrates, conditioned by transfer
of genetic determinants. The process is accompanied by the
selection and accumulation of strains in the polluted
environment. These strains contain plasmids for decomposition
of and resistance to xenobiotics. Based on the premise (Rochelle
etal. 1 989 iofconjugation in one plasmid of genes responsible
for decomposition and resistance to xenobiotics, with genes of
antibiotics resistance and pathogenic properties, we hypothesize
that the processes of adaptation of microorganisms to chemical
pollution are accompanied by selection and accumulation of
strains pathogenic for fish and man. This transition of
microorganisms from saprophytes to quasi-pathogenic
(potentially pathogenic ) and eventually pathogenic poses serious
concerns for marine mammals and man.

110

Chapter 4 References

Ahmed, M. & Focht. D. D. (1973). Degradation of
polychlorinaled biphenyls by two species of Achromobacter.
Can. J. MIcrohlnl. 19, 47-52.

Atlas, R.M.( 1984). Microbiological degradation of petroleum
hydrocarbons: An environmental perspective. MIcrohiol.
Rev. 45. 180-209.

Atlas, R. M.. Schofield. E. A., Morelli, F. A. and Cameron.
R. E. (1976). Effects of petroleum pollutants on arctic
microbial populations. Environ. PoUia. 10( 1 ), 35—43.

Azam, F., Ammerman, J. W. & Cooper. N. (1981).
Bacterioplankton distributional patterns and metabolic
activities in the Scotia Sea. Antarctic J. U.S. 16, 164-165.

Babenzien, H. B. & Schwartz, W. (1970). Studies of the
microbiology of neuston. Limnologica 7, 247-171.
(in Russian)

Baitaz, O. N. & Baitaz, V. A. (1986). Some data about spatial
distribution of bacterioplankton in the Bering Sea. Complex
oceanological studies of the Barents and White Seas. Apatites,
pp. 84-89. (in Russian)

Ballschmitter,K.&Zell,M.(1980). Analysisofpolychlorinated
biphenyls (PCB) by glass capillary gas chromatography.
Freseniiis Z. Anal. Chem. 302, 20-3 1 .

Baya, A. M., Brayton, P. R., Broun, V. L., Grimes, D. J.,
Russek-Cohen, E. & Colwell, R. R. (1986). Coincident
plasmids and antimicrobial resistance in marine bacteria
isolated from polluted and nonpolluted Atlantic Ocean
samples. Appl. Environ. Microbiol. 51(6), 1285-1292.

Bedard, D. L., Haberl, M. L., May, R. & Brennan, M. J.
(1987a). Evidence for novel mechanisms of polychlorinated
biphenyl metabolism in Alcalii>ene.\ ciitropus H850. Appl.
Environ. Microbiol. 53, 1 103-1 112.

Bedard, D. L., Untemian, R., Bopp, L. H., Brennan, M. J.,
Haberl M. L. & Johnson, C. (1986). Rapid assay for
screening and characterizing microorganisms for the ability
to degrade polychlorinated biphenyls. Appl. Environ.
Microbiol. 51,61-768.

Bedard, D. L., Wagner, R. E., Brennan. J. J., Haber, M. L. &
Brown, J. F. ( 1987b). Extensive degradation of Aroclor and
environmentally transfomied polychlorinated biphenyls by
Alcaligenes eutrophus H850. Appl. Environ. Microbiol. 53,
1094-1102.

Bemhard. M. & George. S. G. ( 1986). Importance of chemical
species in uptake loss and toxicity of elements for marine
organisms. Importance Chem. Speciat. Environ. Proce.s.s.
Kept. Dahlem. Workshop. Berlin. 2-7 September. 1987.
pp. 385-422.

Bemhard. M. & Zattera. A. (1975). Major pollutants in marine
en\ironment. In Marine Pollution and Marine Waste
Disposal. Pergamon Press, Oxford and New York,
pp. 195-300.

Bidleman, T. F. & Olney, C. E. (1974). Chlorinated
hydrocarbons in the Sargasso Sea atmosphere and surface
water. 5r;>/(r£' 183, 516-518.

Bidleman, T. F., Olney, C. E. & Rice, C. P. (1976). High
molecular weight chlorinated hydrocarbons in the air and
sea; rates and mechanisms ofair sea transfer. In Mar.Pollut.
Transfer 10, 346.

Birger. M. O. (ed. ) ( 1 973 ). Reference Book forMicrobioloi-ical
and Virusological Methods of Investigation. Medicina
Publishers, Mo.scow. pp. 177-180. (in Russian)

Bletchly.J.D. (1984). Polychlorinated biphenyls: Production,
current use, and possible rates of future disposal of OECD
member countries. In Proceedings of PCB Seminar
(M. C. Barvos, ed. ). pp. 343-372. Ministry of Housing,
Physical Planning and Environment, The Netherlands.

Boominathan, K., Gurujeyakshmi, G„ Balajee, S. & Mahadevan
(1988). Xeno-disimilatory plasmids. Curr. Sci. (India)
57(21). 1182.

Bopp, L. N. (1986). Degradation of highly chlorinated PCB"s
by Pseiidomonas sp. strain LB400. J. hid. Microbiol. 1,
23-29.

Braginsky, L. P. (1986). Certain regularities and reaction
mechanism of freshwater ecosystems to pesticides and
surfactants. E.\p. Aqiiat.To.xicol. 11, 7-22. (in Russian)

Brunner. W., Suthedad, F. N. & Focht. D. D. (1985). Enhanced
biodegradation of polychlorinated biphenyls in soil by analog
enrichment and bacterial inoculation. J. Environ.
Qiial. 14, 324-328.

Buchanan & Gibbons (eds. ) (1982). Bergey's Manual of
Determinative Bacteriology (8th ed.), pp. 196-207. The
Williams and Wilkins Co., Baltimore, Maryland.

Bullion. V. V. (1988). Extracellular production of
phytoplankton and research methodology. J. Hydrobiol. 24,
64-73. (in Russian)

Bumpus. J. (1989). Biodegradation of polycyclic aromatic
hydrocarbons by Phaiierochaete chnsosporiiim. Applied
Environ. Sci.. pp. 154-158.

Cadee, G. C. ( 1988). Organic carbon in the upper 100 m and
downward tlux in the Banda sea; monsoonal difference.
Neth. J. Sea Res. 22, 109-121.

Chemyak. S. M. & Mikhaleva. J. M. (1985). Chlorinated
hydrocarbons in the Baltic Sea biota. In Study of the Baltic
Sea Eco.system. 2. 82-84. Gidrometeoizdat Publishers.
Leningrad, (in Russian)

Dahlback, B., Gunnarson, L. A. H., Hermansson, M. &
Kielleberg, S. (1982). Microbial investigation of suri'ace
microlayers, waters column, ice and sediment in the Arctic
Ocean. Mar. Ecol. Progr. Ser. 9. 101-109.

Day, M. J., Bale. M. J. & Fry. J. C. (1988). Plasmid transfer in
the freshwater environment. Safety Assur. Environ. Intro.
Genet. Eng. Organ. : Proc. NATO Adv. Res. Workshop,
Rome. 6-10 June, 1987. Beriin, pp. 181-197.

Dean-Ross, D. (1987). Biodegradation of toxic waste in soil.
A^A/A-fH-.v 53, 490-492.

ill

Dobrovolski, A. D. & Zalogin. B. S. (1982). The seas of the

USSR. M. P. H. of Moscow State University, (in Russian)
Douglas, D. J., Novitsky, J. A., & Foumier, R. O. (1987).

Microautoradiography-based enumeration of bacteria with

estimates of thy midine-specific growth and production rates.

Mar. Ecol. Prog. Sen 36, 91-99.
Ducklow. H. W. & Hill, S. M. (1985). Tritiated thymidine

incorporation and the growth heterotrophic bacteria in warm

core rings. Limnol. Oceanogr. 30. 260-272.
Erickson, M. D. (1986). Analytical chemistry of PCB's.

Butterworth Publishers, Boston. Massachusetts, pp. 5-53.
Fedoseyeva, G. E. & Khessina, A. la. ( 1968). Application of

quasilinear spectra of luminescence for quantitative

detemiination of polycyclic hydrocarbons series. J. Appl.

Spectr. 9(2), 282-288.
Fogg, G. E. ( 1 97 1 ). Extracellularproducts of algae in freshwater.

Arch. Hydrobiol. Beeh. 5, 1-25.
Fuhrman, J. A. (1981). Influence of method on the apparent

size distribution of bacterioplankton cells: epifluorescence

microscopy compared to scanning electron microscopy.

Mar. Ecol. Prog. Sen 5, 103-106.
Fuhrman, J. A., Ammerman, J. W. & Azam, F. (1980).

Bacterioplankton in the coastal eutrophic zone: distribution,

activity and possible relationships with phytoplankton. Mar.

Biol. 60, 201-207.
Fuhrman, J. A. & Azam, F. (1980). Bacterioplankton secondary

production estimates for coastal waters of British Columbia,

Antarctica, and California. Appl. Environ. Microbiol. 39,

1085-1095.
Fuhrman, J. A. & Azam, F. ( 1982). Thymidine incorporation

as a measure of heterotrophic bacterioplankton production in

marine surface waters: Evaluation and field results. Mar.

Biol. 66, 109-120.
Furukawa, K. (1982). Microbial degradation of polychlorinated

biphenyls (PCB's). In Biodegradation and Deto.xication of

•Environmental Pollutants (A. M. Chakrabarty, ed.),

pp. 33-57. CRC Press, Boca Raton, Florida.
Furukawa, K. & Chakrabarty, A. M. ( 1982). Involvement of

plasmids in total degradation of polychlorinated biphenyls.

Appl. Environ. Microbiol. 44, 619-626.
Furukawa, K., Matsumura, F. & Tonomura, K. (1978).

Alcaligenes and Acinetobacter strains capable of degrading

polychlorinated biphenyls. Agric. Biol. C/)e;?!. 42,543-548.
Furukawa, K.. Tomizuka, N. & Kamibayashi, A. (1979).

Effect of chlorine substitution on bacterial metabolism of

various polychlorinated biphenyls. Appl. Environ. Microbiol.

38,308-310.
Furukawa, K., Tomizuka, N. & Kamibayashi, A. (1083).

Metabolic breakdown of Kaneclors (polychlorophenyls)

and their products by Acinetobacter sp. Environ. Microbiol.

46, 140-145.
Garrison, D. L., Sullivan, C. W., & Ackley, S. F. (1986). Sea

ice microbial communities in Antarctica. Bioscience 36,

243-250.
Gavrilova, M. A. (1969). Microbial oxidation of some oil

products in the water of the Danube. Gidrobiologiya. 5(3),

24-31. (in Russian)

Gealt, M. A. ( 1988). Recombinant DNA plasmid transmission

to indigenous organisms during waste treatment. Water Sci.

Technol. 20{ll/\2}, 179-184.
Geiss, A. & Bourdeaux, J. (1986). Analytical Cheniistty of

PCB's. Butterworth Stoneham, Massachusetts.
Gerhardt, F. (ed. ). (1984). Methods of General Bacteriology

in 3 volumes. Mir Publishers, Moscow, (in Russian)
Gocke,K. (1977). Heterotrophic activity. In Microbial Ecology

of a Brackish Water Environment (G. Rheinheimer. ed. ).

Springer Verlag, Berlin, Heidelberg, New York,

(Ecol. Studies 25), pp. 198-222.
Goldberg, E. D. ( 1970). Chemical invasion of ocean by man.

McCraw-Hill Yearbook, Science and Technology, 280.
Goldberg, E. D. ( 1975). Synthetic organohaloides in the seas.

Proc. R. Soc. London. 189, 277-279.
Gomes, H. R. & Pant, A. (1987). Extracellular products of

photosynthesis in a tropical environment. Proc. Indian Nat.

Sci. Acad. 53, 4S\^^5.
Gorlenko, V. M., Dubinina, G. A. & Kuznetsov, S. I. ( 1977).

Ecology of Aquatic Microorganisms. Nauka Publishers,

Moscow, 289 pp. (in Russian)
Gunkel, W. (1967a). Experimental-oecologische

Untersuchungen ueber die limitierenden Faktoren des

mikrobiellen Oelabbaues im marinen Mileue. Helgolaender

Wiss. Meeresunterr., Bd. 15. (in German)
Gunkel, W. (1967b). Arbeitssitzung ueber

Gewaesserveroelung. Oelbekaempfung und Oelabbau.

Helgolaender Wiss. Meeresunterr., Bd. 16, 285-384.

(in German).
Gunkel, W. (1968). Bacteriological investigations of

oil-polluted sediments from the Cornish coast following the

Torrey Canyon disaster. In Biological Effects of Oil Pollutant

on Littoral Communities. Field Stud. 2, 96-102.
Hagstrom, A., Larsson, U., Horstedt, P. & Normark, S. ( 1979).

Frequency of dividing cells, a new approach to the

determination of bacterial growth rates in aquatic

environments. Appl. Environ. Microbiol. 37, 805-812.
Hanson, R. B., Alvarez-Ossorio, M. R., Cal, M. R., Roman,

M., Santiago, G., Varela, M. & Yoder, J. ( 1 986a). Planktonic

response following a spring upwelling event in the Ria de

Arosa, Spain. Man Ecol. Prog. Ser. 32, 101-1 13.
Hanson, R. B. & Lowery, H. K. ( 1983). Nucleic acid synthesis

in oceanic microplankton from the Drake Passage. Antarctica:

evaluation of steady-state growth. Mar. Biol. 73, 79-89.
Hanson, R. B., Pomeroy, L. R., Blanton, J. O., Biddanda, B. A.,

Wainwright, S., Bishop, S. S., Yoder. J. A. & Atkinson. L. P.

(1987). Climatological and hydrographic influences on

nearshore food webs off southeastern US: Bacterioplankton

dynamics. Cont. Shelf Res. 8, 1321-1344.
Hanson. R. B., Pomeroy, L. R. & Murray, R. E. (1986b).

Microbial growth rates in a cold Gulf Stream eddy of the

northwestern Sargasso Sea. Deep-Sea Res. 33, 427-446.
Hanson, R. B., Santiago, G. & Cal, M. R. (accepted).

Bacterioplankton productivity in an upwelling area off

northwest Spain. Mar. Biol.

112

Hanson. R. B., Shefer, D., Ryan, T. H. .. Pope, D. H. & Lowery,
K. H. ( 1983). Bacterioplankton in Antarctic ocean waters
during late winter; abundance, frequency of dividing cells
and estimates of production. Appl. Environ. Microbiol. 45,
1622-1632.

Hobble, J. E., Daley. R. J. & Jasper. S. ( 1977). A method for
counting bacteria on Nuclepore filters. Appl. Environ.
Microbiol. 33. 1225-1228.

Ivanov. M. V, ( 1 988 ). Microbiological components of sulphur-
carbon cycle in ocean. In Comprehensive Analysisof Natural
Environment, pp. 112-116. Transactions of the Soviet-
American Symposium. Gidrometeoizdat Publishers,
Leningrad, (in Russian)

Izrael, Yu. A., Simonov. A. 1. & Tsyban, A. V. (1980).
Scientific aspects of complex investigation of Pacific Ocean
waters with the purpose of preventing its pollution. Natural
resources of the Pacific Ocean for the welfare of mankind.
Moscow, pp. 101-1 16. (in Russian)

Izrael. Yu. A. & Tsyban, A. V. ( 1981 ). Monitoring problems
and ecological after-effects of ocean pollution.
Gidrometeoizdat Publishers, Leningrad, (in Russian)

Izrael. Yu. A. & Tsyban, A. V. (1982). Ecological principles
for monitoring state of World Ocean. In All-Round Global
Monitoring of Natural Environment Pollutiim. pp. 44-61.
Gidrometeoizdat Publishers, Leningrad, (in Russian)

Izrael, Yu. A. & Tsyban, A. V. (1983). About assimilation
capacity of the World Ocean. Proceedings of the USSR
Academy of Scieiues 252, 702-704. (in Russian)

Izrael, Yu. A. & Tsyban, A. V. ( 1985a). Ecology and problems
of complex global monitoring of the World Ocean.
Transactions of the 1st International Symposium.
Gidrometeoizdat Publishers. Leningrad, 1, 19-49. (in
Russian)

Izrael. Yu. A. & Tsyban. A. V. ( 1 985b ). Atmospheric pollutants
transfers and their influence upon ocean-atmospheric
interactions. In Ecological After-Effects of Ocean Pollution,
pp. 7-27. Gidrometeoizdat Publishers, Leningrad, (in
Russian)

Izrael. Yu. A. & Tsyban, A. V. (eds. ) (1987). All-round
analysis of the ecological system of the Bering Sea.
Gidrometeoizdat Publishers, Leningrad, (in Russian)

Izrael, Yu. A. & Tsyban. A. V. (1988). Methodic Principles of
Ocean Complex Ecological Monitoring. Gidrometeoizdat
Publishers, Moscow, (in Russian)

Izrael, Yu. A. & Tsyban, A. V. ( 1989). Anthropogenic Ecology
of Ocean. Gidrometeoizdat Publishers. Leningrad, (in
Russian)

Izrael, Yu. A. & Tsyban. A. V. (eds. ) (1990). Study of the
Bering Sea Ecosystem. Number 2. Gidrometeoizdat
Publishers, Leningrad, (in Russian)

Izrael. Yu. A., Tsyban, A. V., Panov, G. V. & Korsak. S. V.
(1986). Comprehensive analysis of the Bering Sea
ecosystem-monitoring and managing environmental impact.
American and Soviet perspectives. Proceedings of the Fifth
US-USSR Symposium on Comprehensive Analysis of the
Environment, pp. 58-88. (in Russian)

Izrael. Yu. A.. Tsyban, A. V.. Panov. G. A.. Korsak. M. N.,
Kudryatsev. V. M.. Volodkovich. Yu. L. & Chemyak. S. M.
( 1987). Comprehensive Analysis of the Bering Ecosystem.

Monitoring and Managing Environmental Impact: American

and Soviet Perspectives. National Academy Press, USA,

pp. 58-88.
Izrael, Yu. A., Tsyban, A. V. & Panov G. V., Korsak, M. N.,

Kudryatsev, V. M., Volodkovich, Yu. L. & Chemyak, S. M.

( 1 988). Comprehensive analysis of the Bering Sea ecosystem.

In Transactions of the Soviet-American Symposium, pp. 77-

111. Gidrometeoizdat Publishers, Leningrad, (in Russian)
Izrael. Yu. A.. Tsyban. A. V., Panov, G. V. & Chemyak, S. M.

(1990). Microbial transformation of polychlorinated

biphenyls in polar sea regions. DAN USSR (Reports of the

USSR Academy of Sciences) 310. 502-506. (in Russian)
Izyurova, A. 1. (1950). Rate ofdisintegration of oil products in

water and soil. Gigiena i sanitaria 5, 23-28. (in Russian)
Joint, I. H. & Pomroy, A. J. ( 1 983). Production of picoplankton

and small nanoplankton in the Celtic Sea. Mar. Biol. 77,

19-27.
Karasevich, Yu. N. (1982). Fundamentals of Selecting

Microorganisms Utilizing Synthetic Organic Compounds.

Nauka Publishers, Moscow, (in Russian)
Kirchman, D. K.. Ducklow, H. W. & Mitchell. R. (1982).

Estimates of bacterial growth from changes in uptake rates

and biomass. Appl. Environ. Microbiol. 44, 1296-1307.
Kirso, U. E., Stom, D. 1., Belykh, K. I. & Irkha. N. I. (1988).

Transformation of Carcinogenic and Toxic Sidistances in

the Hydrosphere. 271 pp. Tallinn Publishers, (in Russian)
Kohler, H. E., Kohler-Staub, D. & Focht, D. D. (1988).

Cometabolism of polychlorinated biphenyls: Enhanced

transformation of Aroclor 1 254 by growing bacterial cells.

Appl. Environ. Microbiol. 54. 1940-1945.
Korsak. M. N. ( 1 985 ). The results of investigations of plankton

community in the Bering Sea. In Ecological After-Effects of

Ocean Pollution, pp. 56-66. Gidrometeoizdat Publishers.

Leningrad, (in Russian)
Kottmeier, S. T. & Sullivan, C. W. ( 1987). Late winter primary

and secondary production in seawater westof the Antarctica

Peninsula. Mar. Ecol. Prog. Ser. 36, 287-298.
Kudryatsev, V. M. (1973). Freshly synthesized organic

substances discharged by the cells of plankton algae. //;/;

Bidl. Biol. Inner Waters 18, 20-24. (in Russian)
Kullenberg.G. (1984). The vital seas. Questions and answers

about the health of the oceans. UNEP, 28.
Kulskyi, L. A.. Savluk, O. S. & Potapchenko, O. G. (1986).

Resistance of microorganisms to heavy metals. Water

Chem. and Tech. 8(2). 38-43. (in Russian)
Kuznetsov, S. J. & Dubinina, G. A. (1989). Methods of

Investigating Aquatic Microorganisms. 288 pp. Nauka

Publishers, Moscow, (in Russian)
Larsson. P. & Hagstrom, A. ( 1 982). Fractionated phytoplankton

primary production, exudate release and bacterial production

in a Baltic eutrophication gradient. Mar. Biol. 67. 57-70.
Larsson, P. & Lemkemeier, K. ( 1 98 1 ). Microbial mineralization

of chlorinated phenols and biphenyls in sediment-water

system from humic and clear-water lakes. Water Res. 23,

1081-1085.
Le Petet, I., N'Guyen. M. H. & Tagger, S. (1977). Quelques

donnees sur I'ecologie d'une zone marine littorale les relets

d'une raffinerie de petrole. Environ. Pollut., 13.

(in French)

113

Linton, A. H.( 1988). Plasmids in the environment. Schriftens.

Ver. Wasser, Boden and Lufthyg, No. 78, pp. 197-224.
Liu, D. (1980). Enhancement of PCB's biodegradation by

sodium linginsulfonate. Water Res. 14, 1467-1475.
Loprieno, N. ( 198 1 ). Short term tests to assess the mutagenic

and carcinogenic hazards of new chemicals. Biol. Int. 3,

2-14.
Mameava, N. V. (1987). Compositions and quantitative

distribution of infusoria in the Pacific pelagic area. In

Comprehensive Analysis of the Bering Sea Ecosystem.

pp. 174-192. Gidrometeoizdat Publishers, Leningrad.

(in Russian)
McMans, G. G. & Peterson, W. P. ( 1988). Bacterioplankton

production in the nearshore zone during upwelling of central

Chile. Mar. Ecol. Prog. Ser. 43, 11-17.
Mironov,O.G.( 1970a). Effect ofpollution on marine organisms

and the process of selfpurification of the marine environment.

In The Study of the Baltic Sea. Thesis report, Riga, 29 pp.

(in Russian)
Mironov, O. G. (1970b). On the role of microorganisms

growing on oil, in self-purification and indication of oil

pollution in the sea. Oceanology 10(5), 820-827. (in Russian)
Mironov, O. G. (1985). The Interaction of Marine Organisms

with Petroleum Hydrocarbons. Gidrometeoizdat Publishers.

Leningrad, 127 pp. (in Russian)
Newell, S. Y. & Christian, R. R. ( 1981). Frequency of dividing

cells as an estimator ofbacterial productivity. A/?/)/. Environ.

Microbiol. 42, 23-3 1 .
Newell, S. Y. & Fallon, R. D. ( 1982 ). Bacterial productivity in

the water column and sediments of the Georgia (USA)

coastal zone: Estimates via direct counting and parallel

measurement of thymidine incorporation. Microb. Ecol. 8,

33-46.
O'Connor, J. M. & Huggett, R. (1988). Aquatic pollution

problems North Atlantic coast, including Chesapeake Bay.
. Aqiiat. To.xicol. 11, 163-190.
OilintheSea(1985). Inputs, fates and effects. MARPOLMON

Report. Nat. Acad. Press, Washington, D.C.
Oliver. J. D. (1982). Taxonomic scheme for the identification

of marine bacteria. Deep Sea Research 29(6A), 795-798.
Oppenheimer, G. H., Gunkel, W. & Gassman. G. (1977).

Microorganisms and hydrocarbons in the North Sea during

July-August 1975. In Proceedings Oil Spill Conference.

American Petroleum Institute. Washington D.C,

pp. 593-610.
Overbeck,J.( 1974). Microbiology and biochemistry. Mitt Int.

Limnol. 20, 198-228.
Pearson.C. R.(1983). Halogenated aromatic. In Environmental

Handbook Part B, pp. 89-1 16.
Pelleroni. N. Y. ( 1975). General properties and ta.xonomy of

the genus Pseudonumas — genetic and biochemistry of

Pseudomonas. pp. 1-36. New York.
Platpira, V. P. ( 1982). Results of microbiological monitoring

in the Gulf of Riga. In Environment and Hydrobiocenoses

of the Gulf of Riga. Riga: Zmantne. pp. 76-92. (in Russian)
Platpira V. P. (1985). Microflora and transformation of

petroleum hydrocarbons in the marine environment. Riga:

Zinantne, 162 pp. (in Russian)

Piatt, J. (1984). Primary productivity in the central North

Pacific comparison of oxygen and carbon fluxes. Deep-Sea

Re.'i. 31. 1311-1319.
Pomeroy, L. R. & Deibel, D. ( 1986). Temperature regulation

and bacterial activity during the spring bloom in

Newfoundland coastal waters. Science 233, 359-361 .
Pravdic, V.(1981). GESAMP. The first dozen years. UNEP,

93.
Razumov, A. S. ( 1932). Methodics for direct calculation of

bacteria in water. Its comparison with the method of Koch.

Microbiology 1, 131-136.
Rheinheimer, G. (ed. ) (1977). Regional and seasonal

distribution ofbrackish water environment. Springer Verlag,

Berlin, Heidelberg, New York. (Ecol. Stud. 25),

121-137.
Rheinheimer, G. H. (1986). Influence of eutrophication on

bacterial abundance and activity in the Baltic Sea. In

Integrated Global Ocean Monitoring. Proceedings of the

First International Symposium. Gidrometeoizdat Publishers,

Leningrad, 2, 280-286.
Riemann, B., Nielsen, P., Jeppcsen, M., Marcussen, B. &

Fuhrman, J. A. ( 1984). Diel changes in bacterial biomass

and growth rates in coastal environments, determined by

means of thymidine incorporation into DNA, frequency of

dividing cells (FDC), and microautoradiography. Mar.

Ecol. Prog. Ser. 17, 227-235.
Riemann, B., Bjomsen, P. K., Newell, S. & Fallon, R. (1987).

Calculation of cell production of coastal marine bacteria

based on measured incorporation of ['H]thymidine. Limnol.

Oceanogr. 32, 471-476.
Rochelle. P., Fry, J. C. & Day. M. J. (1989). Factors affecting

conjugal transfer of plasmids encoding mercury

resistance from pure cultures and mixed natural suspensions

of epilithic bacteria. J. Gen. Microbiol. 135(2),

409-424.
Rodoff, M. (1961). Oxidation of aromatic compounds by

bacterial. Appl. Microb. 3, 193-221.
Romanenko, V. J. (1964). Heterotrophic assimilation of CO,

by bacterial flora in water. Microbiology 33, 679-683.

(in Russian)
Romanenko, V. J. ( 1965). Ratio of oxygen and carbonic acid

uptake in heterotrophic bacteria with peptone culturing.

Microbiology 35, 397-402. (in Russian)
Romanenko, V. J. (1985). Microbiological Processes and

Decomposition of Organic Matter in Internal Waters. Nauka

Publishers, Leningrad, (in Russian)
Romanenko, V. J. & Kuznetsov. S. J. (1974). Freshwater

Microorganisms Ecology. A Laboratory Hatulbook. Nauka

Publishers. Leningrad, 194 pp. (in Russian)
Sahasrabudhe, S. R. & Modi, V. V. (1987). Microbial

degradation of chlorinated aromatic compounds. Microbiol.

Set. 4, 300.
Saijo, Y., Mitamura, O. & Ogiyama. K. (1974). Chemical

composition of surface film in the coastal sea area and in

freshwater lakes. Jpn. J. Limnol. 35. 110-116.
Sayler, G. S.. Shon, M. & Colwell. R. R. ( 1977). Growth of an

estuarine Pseudomonas sp. on polychlorinated biphenyl.

M/c7-<;/;.£fo/. 3. 241-255.

114

Schmidt, T. & Schlegal, G. ( 1 989 ). Nickel and cobalt resistance

of various bacteria isolated from soil and highly polluted

domestic and industrial waters. FEMS Microbiol. Ecol.

62(3), 315-328.
Seki, H. (1982). Organic materials in aquatic ecosystems.

CRC Press, Inc., Boca Raton, Florida.
Seki, H. (1986). Thresholds in eutrophication of natural

waters. Environ. Monit. A.wt'.v.v. 7, 39-46.
Shields, M.S., Hooper. S. W. & Sayler, G. S. ( 1 985 ). Plasmid-

mediated mineralization of 4-chlorobiphenyls. J. Bacteriol.

163. 882-889.
Shewan, Y. M., Hobbs, Y. & Hodkiss, W. A. (1960). A

determinative scheme for the identification of certain genera

of gramnegative bacteria with special reference to the

Pseudomonadaceae. J. Appl. Bacteriol. 23, 379-390.
Shpolski, E. v., Ilyin, A. A. & Klimov. L. A. (1952).

Fluorescence spectra of coronene in frozen solutions.

Transiictiou.^ of USSR Academy of Sciences 87, 935-939.

(in Russian)
Shtukova, Z. A. ( 1990). Bacterioplankton of the Baltic Sea in

1987. In Ecosysiem Investigation of the Baltic Sea, Issue 3.

pp. 58-68. Gidrometeoizdat Publishers, Leningrad.

(in Russian)
Sieburth, Y. ( 1979). Sea Microbes. Oxford University Press,

New York.
Slater, E. E., Anderson, M. D. & Rosenkranz, H. J. (1971).

Rapid detection of mutagens and cancerogens. Cancer Res.

31,907-973.
Sorokin, Yu. J. (1971 ). Quantitative assessment of the role

played by bacterioplankton in biological productivity of the

Pacific tropical waters. In Functional Activities of Pelagic

Communities in Trophic Regions of the Ocean, pp. 92-1 22.

Nauka Publishers, Leningrad, (in Russian)
Sorokin, Yu. J. ( 1980). Bacterioplankton. Bacterial production

and degradation of organic matter. In Ecosystetn of the

Pelagial of the Peruvian Region, pp. 104-115. Nauka

Publishers, Moscow, (in Russian)
Sorokin, Yu. J. ( 1982). The Black Sea. Nature and Resources.

Nauka Publishers, Moscow, 216 pp. (in Russian)
Sorokin. Yu. J. (1984). Bacterioplankton and primary

production in the central part of the Indian Ocean. Biology

of the Sea 2, 3-19. (in Russian)
Sorokin, Yu. J. (1985). Bacteria and microzooplankton

production. In Biological Resources of the Ocean.

pp. 71-86. Agropromizdat Publishers. Moscow. (in Russian)
Sorokin, Yu. J. & Kadota. H. (1972). Microbial production and

decomposition in freshwaters. p. 1 12. Blackwell Publishers.

London.
Subramanian. B. R., Tanabe, S., Hidaka, N. & Tatsukawa. R.

( 1983). DDT and PCB isomers and congeners in Antarctic

fish. Arch. Environ. Contain. Toxicol. 12,621-626.
Tanabe, S. (1984). PCB in the western North Pacific. Arch.

Environ. Contain. Toxicol. 13.731-738.
Tanabe, S. (1985). Distribution, behavior, and fate of PCB in

the marine environment. J. Occanogr. Soc. Jpn.. 41(5),

358-370.
Treccan, V. ( 1963). Microbial degradation of hydrocarbons.

Prog. Ind. Microbiol A, 1-33. (in Russian)

Tsyban, A. V. ( 1970). Bacterioneuston and bacterioplankton
of the Black Sea shelf zone. Naukova Dumka, Kiev 276. (in
Russian)

Tsyban, A. V. (ed. ) ( 1980). Manual for Methods of Sea Water
and Bottom Sedimentations Biological Analysis.
Gidrometeoizdat Publishers, Leningrad pp. 8-79. (in Russian)

Tsyban, A. V. (1981). Methods of calculating microbial
degradation of petroleum hydrocarbons. In Study of the
Baltic Sea Eco.system 1. 61-68.

Tsyban, A. V., Abalikhin, T. A. & Barinova, S. P. (1973).
Microorganisms as a factor of pollution and self-purification
processes in coastal water areas. Sanitaryprotection of seas
and sea coasts. Transactions of Scientific and Practical
Conference. Sukhumi, (in Russian)

Tsyban, A. V., Korsak. M. N., Kudryatsev, V, M., Panov, G. V.
& Azhipa, O. Ya. (1987a). Bacterial production and
decomposition of organic matter. In Comprehensive Analysis
of the Bering Sea Ecosystem, pp. 89-97. Gidrometeoizdat
Publishers, Leningrad, (in Russian)

Tsyban, A. v., Kudryatsev, V.M.,Mamaev,V.O. &Sukhanova,
N. V. (1992). Total number, biomass and activity of
bacterioplankton of the Bering and Chukchi Seas (Subchapter
4. 1. 1, this volume).

Tsyban, A. V., Kudryatsev, V. M, & Panov, G. V. (1987b).
Total amount and biomass of bacterial population. In
Comprehensive Analysis of the Bering Sea Ecosy.stein. pp.
81-89. Gidrometeoizdat Publishers, Leningrad,
(in Russian)

Tsyban, A. V.. Panov. G. V. & Kudryatsev. V. M. (1987c).
Distribution and quantitative composition of heterotrophic
microorganisms, oxidizing organic polluting substance. In
Comprehensive Analysis of Ecological System of the Bering
Sea. pp. 97-1 1 1. Gidrometeoizdat Publishers. Leningrad.
(in Russian)

Tsyban, A. V.. Panov. G. V.. Kudryatsev. V. M.. Mikhailov, V.
v., Lycheva.T. A. & Azhipa,0. Ya. (1990). Microorganisms
and microbiological processes. In Ecosystem Investigation
of the Bering Sea. issue 2, pp. 198-252. Gidrometeoizdat
Publishers, Leningrad, (in Russian)

Tsyban, A. V., Panov, G. V., Subbotin, V. G., Timoshenkova,
N. P. & Chemyak, S. M. (eds. ) (1988). Methodological
Foundations of Integrated Ecological Monitoring of the
Ocean. Gidrometeoizdat Publishers, Moscow, 288 pp.
(in Russian)

Tsyban, A. V., Panov, G. V., Ventzel. M. V., Volodkovich. Yu.
L. & Korsak, M. N. (1986). Long-term period ecological
investigations in impact and background regions of the
World Ocean. In Complex Global Monitoring of State of
Biosphere, Vol. 3, pp. 45-60. Gidrometeoizdat Publishers,
Leningrad, (in Russian)

Tsyban. A. V., Volodkovich, Yu. L. & Belyaeva, O. L. ( 1 987d).
Studying of benzo(a)pyrene circulation in the Bering Sea. In
Comprehensive Analysis of the Ecological System of the
Bering Sea, pp. 218-232. Gidrometeoizdat Publishers,
Leningrad, (in Russian)

Tsyban, A. V.. Volodkovich, Yu. L., Panov, G. V., Khessina,
A. Ya. & Yermakov, Ye. A. (1985). Distribution and
microbial degradation of carcinogenic hydrocarbons in some

U5

regions of the World Ocean. In Ecological Consequences of
Ocean Pollution, pp. 88-1 12. Gidrometeoizdat Publishers.
Leningrad, (in Russian)

Tsyban, A. V., Volodkovich, Yu. L. & Pfeiffere. M. Yu.
(1985). Circulation of the contaminants in the Baltic Sea
ecosystem. Investigation of the Baltic Sea
ecosystem. Gidrometeoizdat Publishers, Leningrad, pp.
244-257.

Tuistra, L. G, M. T. & Traag, W. A. (1983). Capillary gas
chromatographic-mass spectrometric determination of
individual chlorobiphenyls in technical Aroclors. / Assoc.
Off. Anal. Chem. 66. 708-717.

Turley, C. M. & Klochte, K. (1985). Direct measurement of
bacterial productivity in stratified waters close to a
front in the Grish sea. Mar. Ecol. Progr. Ser. 23,
209-219.

Unterman, R., Bodard, D. L., Bopp, L. H., Johnson, C. &
Haberl, M. L. (1985). Microbial degradation of PCB. In
Proceedings: International Conference on New Frontiers
for Hazardous Waste Management, pp. 481-488.
U. S. Environmental Protection Agency, Cincinnati, Ohio.

Vieble, W. J. ( 1984). Aquatic microbial ecology - research
questions and opportunities. Trans., Ecol. Res. 1980. Proc.
NATO ARW and INTECOL Workshop Future and Use Ecol.
Decade Environ. New York. London, pp. 35^9.

Vinogradov, M. E. & Shushkina, E. A. (1989). Macroscale
distribution of quantitative characteristics of plankton in the
Pacific. Oceanology 19. 121-125. (in Russian)

Volodkovich, Yu. L. & Belyaeva, O. L. ( 1987 ). Biogeochemical
cycles of benzo(a)pyrene in the Bering Sea ecosystem. In
Proceedings of the Third Congress of Soviet Oceanologists,
Vol. 1, pp. 91-93. Gidrometeoizdat Publishers, Leningrad,
(in Russian)

Voroshilova, A. A. & Dianova, E. V. (1950). On bacterial
oxidation of oil and its migration in natural water bodies.
Microbiology 19(3), 38-45. (in Russian)

Voroshilova, A. A. & Dianova, E. V. (1952). Petroleum-
oxidizing bacteria - indicators of the intensity of biochemical
oxidation of petroleum under natural conditions.
Microbiology 2\(A). 14-22. (in Russian)

Yegerov, N. S. (ed. ). ( 1983). Manual for Practical Studies in
Microbiology. Moscow State University, USSR, pp. 5-146.

116

Chapter 5:

PLANKTON

Editors:

MIKHAIL N. KORSAK &
C. PETER McROY

Subchapter 5.1:

Phytoplankton

5.1.1 Certain Characteristics of Phytoplankton

MIKHAIL V. VENTSEL and NATALIA P. VASJUTINA

Institute of Global Cliimite and Ecology, State Committee for Hydrometeorology and Academy of Sciences, Moscow, USSR

Introduction

This report presents results of the preliminary analysis of
phytoplankton samples collected during the Third Joint
US-USSR Bering & Chukchi Seas Expedition. The specimens
were observed by the "living droplet" method using a light
microscope. We determined the species composition of the
microalgae, their size, and the number of cells. As a result, we
have quantitative estimates of the total number and biomass of
phytoplankton per unit volume. In addition, dominant species
have been identified, since their development in the plant
community strongly influences the value of the quantitative
indices mentioned before. These results are shown in Table 1 .

Distribution of phytoplankton was determined in the
following regions: the Chirikov basin (Stations 87-107), the
Gulf of Anadyr ( Stations 9^ 1 ). the central Bering Sea region
(Stations 1-7), and the southern Bering Sea region (Stations
108-113).

An intensive development of phytoplankton was observed
in the Chirikov basin. The number and biomass of microalgae
were high at all stations. The total number in the surface layer
varied in the range of 500-1,700 x 10' cells/1, and the highest
value was observed at Station 86. Total numbers of
phytoplankton were dominated by diatoms: Leptocylindrus
daniciis, Chaetoceros socialis. Chaetoceros debilis, and
Rhizosolenia alata. Biomass at the surface varied in the range
of 300-3,000 mg/1. The largest contribution to the total
biomass was also due to diatoms: Leptocylindrus danicus,
Rhizosolenia alata. and Chaetoceros concavicornis. At all
stations in the Chirikov basin, the quantitative indices decreased
with the depth. The only exception was Station 1 06. where the
number and biomass were high at a depth of 45 m as well. In
general at 40—45 m, the numbers varied in the range of
80-1,000 X 10' cells/1, and biomass — 120-850 mg/1.

Thus, in the Chirikov basin an intensive development of
phytoplankton was observed, with diatoms occupying a leading
position in the plant community.

In the Gulf of Anadyr, phytoplankton were not as abundant
as in the Chirikov basin and their numbers varied in a smaller
range, from 100 to 700 x 10' cells/1. At many stations, the
number of phytoplankton increased with the depth
(Stations 15, 19,32,36). This was probably connected with the
presence of the pycnocline at these depths. The most numerous
species in the plant community of the Gulf of Anadyr were
algae of various classes:

Class Bacillariophyceae — Fragilaria oceanica,

Fragilaria striatula,
Chaetoceros compressus,
Chaetoceros socialis,
Leptocylindrus danicus.

Class Dinophyceae
Class Chrysophyceae

Gymnodinium wulffii,
Goniaulax orientalis.
Chromulina sp.

Biomass of phytoplankton in this region varied over a wide
range from 6 to 3,600 mg/1. High values of biomass were
caused by the presence of large diatoms like Rhizosolenia
alata. Amphiprora hyperborea, and Coscinodiscus oculus
iridis in the plant community.

In general, it may be noted that during the period of the
expedition, the phytoplankton composition of the Gulf of
Anadyr was very diverse. While the number of microalgae was
evenly distributed throughout area, there was a wide range in
the biomass values. This was connected with the presence of
large forms of phytoplankton in the samples.

There was an uneven distribution of phytoplankton in the
central area of the Bering Sea. The phytoplankton numbers in
the surface waters varied in the range of
100-2,400 X 10' cells/1 and biomass in the range of
40-1,800 mg/1. Quantitative indices decreased with depth,
which was characteristic for all the central area stations, except
for Station 7. At this station, the number and biomass of
phytoplankton were roughly uniform with depth.

Most abundant vegetation in this region consisted of small
forms. The taxonomic composition of phytoplankton is
characteristically depauperate in diatoms as compared with the
northern part of the sea. The following species were numerically
dominant:

Class Chrysophyceae — Chromulina sp.

Class Haptophyceae — Calyptrosphaera insignis.

Class Xanthophyceae — Meringosphaeramediterranea.

Class Cyanophyceae — Synechococcus sp.

Class Loxophyceae — Pedimonas mikron.

Class Bacillariophyceae — Fragilaria striatula,

Chaetoceros debilis,
Nitzschia delicatissima.

In the southern part of the Bering Sea, phytoplankton was
characterized by the following: their numbers at the sea
surface varying in the range of 700-1, 700 X 10' cells/1. Among
numerically dominant species there were no diatoms or
peridinians. Instead, representatives of the following classes of
algae were most abundant in this region:
Class Cyanophyceae — Synechococcus sp.

Class Loxophyceae — Pedimonas mikron.

Their biomass ranged from 3 to 1,300 mg/1.

As for biomass, the following species of microalgae were
dominant:
Class Bacillariophyceae — Fragilaria striatula.

Chaetoceros concavicornis.

121

TABLE

The number, biomass. and dominant species of phytoplankton.

Sta.

Depth

Number

Biomass

No.

cells/1

mg/1

1

1 84.600

264.6

10

87.414

5.3

20

132.600

266.3

25

60.452

6.2

45

51.435

4.0

2

2,440,800

1.824.8

45

39.000

19.9

3

106.600

208.3

10

648.960

130.6

45

23.400

5.1

4

590.200

1.458.3

15

477.100

484.7

45

68.900

127.7

5

285.243

333.5

15

38.592

14.2

45

146.523

102.6

6

15

469.300

215.5

7

183.300

43.5

45

104,907

45.5

128

267,800

71.7

9

678,000

106.4

32

610,200

54.6

88

16,250

5.8

11

135

71,961

23.4

13

3,651,596

26.3

130

119,646

73.8

15

96,030

7.4

42

185,600

47.1

19

153.600

211.9

55

374.400

56.3

24

363.200

32.1

45

214.400

13.6

27

316.800

3.640.1

45

374.400

334.8

32

463.078

56.6

45

610.324

71,3

35

224,070

23.9

45

277,420

171.0

36

126.973

18.7

45

313.698

151.2

41

742.632

2.584.5

45

83.226

123.5

83

496.000

269.0

86

1.740.800

3.158.0

89

912.000

2.654.x

45

281.600

521.3

96

953.600

937.8

40

1 .046.400

850.2

ino

1,148.800

2.934.2

102

486.400

3.109.7

lOX

651.600

2.7

45

1 .248.000

54.1

110

1.667.200

1,3.^9.2

112

1.420.800

131.5

45

358,40(1

82.2

113

1,324,80(1

121.5

45

1,244.800

73.2

Dominant Species

Numerically

Biomass

Fragilaria striatula
Chromitlinales sp.
Synechococcus sp.
Meringosphaera meditenanea
Synechococcus sp.
Chaetoceros debilis
Synechococcus sp.
Fragilaria striatula
Synechococcus sp.
Synechococcus sp.
Chaetoceros debilis
Nitzschia delicatissima
Chaetoceros debilis
Fragilaria striatula
Chromulina sp.
Fragilaria striatula
Fragilaria striatula
Fragilaria striatula
Fragilaria striatula
Fragilaria striatula
Chromulinales sp.
Chromulincdes sp.
Chromulinales sp,
Chroomonas sp.
Chromulinales sp.
Chroomonas sp,
Synechococcus sp.
Chroomonas sp.
Pnmnesiides sp.
Svnechoccus sp.
Thalassiosira nordenskioeldii
Phaeocystis pouchettii
Phaeocystis pouchettii
Fragilaria oceanica
Phaeocystis pouchettii
Phaeocystis pinichetiii
Prvmnesiales sp.
Chaetoceros compressus
Phaeocystis pouchettii
Chaetoceros socialis
Leptocylindrus danicus
Phaeocystis pouchettii
Chroomonas sp.
Chaetoceros socialis
Chaefoceros subsecundus
Leptocylindrus danicus
Chaetoceros socialis
Chaetoceros socialis
Chaetoceros debilis
Leptocylindrus danicus
Pedimonas tnikron
Synechococcus sp.
Synechococcus sp.
Synechococcus sp.
Synechococcus sp.
Synechococcus sp.
Synechococcus sp.

Amphiprora hyperborea
Chromulinales sp.
Amphyprora hyperborea
Meringosphaera mediterranea
Meringosphaera mediterranea
Chaetoceros debilis
Chaetoceros debilis
Amphiprora hyperborea
Calyptrosphaera insignis
Chaetoceros debilis
Chaetoceros concavicornis
Chaetoceros concavicornis
Rhizosolenia alata
Coretron criophyllum
Calyptrosphaera insignis
Leptocylindrus danicus
Fragilaria striatula
Fragilaria striatula
Denticulopsis seminea
Fragilaria striatula
Goniaulux orientalis
Gymnodmium sp.
Eucampia zoodiacus
Distephanus speculum
Chromulinales sp.
Amph i roroa hype rbo rea
Gymnodinium nuljfi
Leptocylindrus danicus
Rhizosolenia alata
Leptocylindrus danicus
Thalassiosira nordenskioeldii
Gymnodinium wulffi\
Coscinodiscus oculus-iridis
Fragilarai oceanica
Dinohryon balticum
Gymnodinium wulffii
Goniaulax orientalis
Chaetoceros compressus
Gymnodinium wuljfii
Chaetoceros socialis
Leptocylindrus danicus
Leptocylindrus danicus
Rhizosolenia alata
Chaetoceros concavicornis
Leptocylindrus danicus
Leptocylindrus danicus
Leptocylindrus danicus
Leptocylindrus danicus
Leptocylindrus danicus
Leptocylindrus danicus
Hemiselmis sp.
Distephanus speculum
Chaetoceros concavicornis
Fragilaria striatula
Fragilaria striatula
Gymnodinium wulffii
Distephanus speculum

ill

Class Dinophyceae — Gyiuncdiniuni wiiljfii.

Class Cryptophyceae — Hemiselmis sp.

Class Chrysophyceae — Disteplunuis speculum.

Thus, due to large ceil sizes, representatives (it both
diatoms and peridinians dominated the biomass.

In general, the following relationships in distribution of
qualitative and quantitative characteristics of phytoplankton in
the Bering Sea, in 1988, were noted:

/. Depletion of the diatom and peridinian flora from north
to south, which can be attributed to the seasonal succession of
phytoplankton.

2. As for quantitative indices, they were subject to sharp
variations both from station to station and at different depths,
which was characteristic for the region under investigation,
being hydrologically complex.

5.1.2 Phytoplankton Biomass Distribution in the
Northern Bering Sea and Southern
Chukchi Sea

WILLIAM S. ROBIE. C. PETER MCROY. and ALAN M. SPRINGER
liisiiiulf of Marine Science, University af Alaska. Fairbanks. Alaska. USA

Introduction

The ecosystem of the northern Bering Sea and southern
Chukchi Sea Shelf region is strongly influenced by the advection
of cold, nutrient-rich seawater from the edge of the deep Bering
Sea basin ( Springer. 1988). This conclusion resulted from data
collected by Inner Shelf Transfer and Recycling (ISHTAR)
Project investigators between 1983 and 1989 (Walsh et ai,
1989). The project was the first large-scale scientific study
attempting to elucidate the ecological processes of these northern
shelf waters, aregion of extremely high primary and secondary
productivity (McRoy et ai, 1972: Motoda & Minoda. 1974:
Sambrotto et ai.. 1984: Springer. 1988) leading to high upper
trophic level productivity (Hood & Kelley, 1974). The Third
Joint US-LISSR Bering & Chukchi Seas Expedition, aboard
iheAkadeinik Korolev. provided the first opportunity to extend
the ISHTAR experimental design across the whole northern
shelf area to examine the areal and vertical distribution of
phytoplankton biomass.

Historical studies of the Bering Sea region show high
productivity associated with the continental shelf area in the
southeastern Bering Sea ( Banahan & Goering. 1 986: Sambrotto

et ai. 1986: Schneider et al.. 1986: Smith & Vidal. 1986;
Walsh & McRoy. 1986) and in Bering Strait (McRoy et al.,

1972;Motoda& Minoda. 1974:Iverson<'/«/.. 1979). Zenkevitch
( 1 963 ), working with many years of Soviet data, proposed that
cold oceanic water from the North Pacific Ocean and warm
shelf water from the southeastern Bering Sea create an east-
west biogeographical division in the northern shelf region. A
Japanese study by Motoda and Minoda ( 1974) also described
zoogeographic associations in the pelagic fauna with cold and
warm water masses. Kinder ef a/. (1 975) described the Bering
Slope Current system as a northwest, subsurface flow of North

Pacific Ocean water entering through the Aleutian Islands and
continuing along the continental shelf slope bisecting at Cape
Navarin to form the Anadyr Stream.

Takenouti and Ohtani (1974) and Coachman et al. (1975)
described the northern Bering Sea as consisting of three distinct
water masses: Alaskan Coastal, Bering Shelf, and Anadyr
water. Productivity and chlorophyll data from McRoy et al.
(I972),Sambrottoe?fl/.( 1984). Springer( 1988). and Whitledge
etal. ( 1988) showedextremely high phytoplankton production
in the northern Bering Sea and southern Chukchi Sea. Benthic
studies (Zenkevitch. 1963; Alton. 1974; Grebmeier et al..
1988; Grebmeier & McRoy, 1989) revealed rich benthic fauna
in this region, also indicating a persistent system of intense
primary production in the overlying water. These studies led
to the hypothesis that advection of cold, nutrient-rich, oceanic
water (Anadyr water) onto the continental shelf of the northern
Bering and southern Chukchi Seas fueled the high primary
productivity (Walsh t'/fl/.. 1989). This production regime has
been described as a "continuous culture" system analogous to
an upwelling regime (Sambrotto et al., 1984).

Prior to 1988, the data set describing the production
associated with this flow was confined to the waters east of the
US-USSR convention line. The joint US-USSR expedition
allowed expansion of the data set across the entire shelf (see
Frontispiece) to include the core of the Anadyr Stream.

Study Area

The study area extended from the South Polygon (53°N,
175°E) in the southern Bering Sea to the southeastern Chukchi
Sea near Cape Lisburne (69°N, 167°W: Frontispiece).
Ecological investigations began at the East Polygon (58°N,
1 75° W; Stations 1-5) and continued in the Gulf of Anadyr and

123

the Bering Shelf area southwest of St. Lawrence Island
(Stations 6-43). After investigation of Anadyr Strait, the
expedition proceeded north into the Chukchi Sea
(Stations 44-75). After completing the studies in the Chukchi
Sea, Bering Strait was surveyed twice (Stations 76-86).
Proceeding south from the Bering Strait, studies were undertaken
in the Chirikov basin (Stations 87-107) and the southern
Bering Sea (Stations 108-1 13). including the South Polygon.

Materials and Methods

Phytoplankton biomass was assessed at each station in the
Bering and Chukchi Seas as chlorophyll a fluorescence ( Parsons
etai, 1984).

Briefly, water samples (250 ml) were collected at 11
depths from each station using Niskin bottles attached to a
rosette sampling apparatus. Samples were filtered through
25 mm Gelman glass fiber filters (pore size: 0.3 \im) in a
multiple-sample filtration apparatus using a vacuum pump.
Each filter was suctioned dry and then placed in a 20-ml glass
test tube with 1 ml of 90% acetone to extract the photosy nthetic
pigments. To facilitate extraction of all pigments, a tissue
grinder was used to homogenize the filter in acetone. The
sample was then transferred to a 15-ml centrifuge tube and
centrifuged for 10 min. After centrifugation, the supernatant
was transferred to a cuvette, where its fluorescence was measured
using a Turner Designs fluorometer before and after acidification
with two drops of 5% HCl.

For analysis, chlorophyll data from stations on the shelf
south of St. Lawrence Island, in the Gulf of Anadyr, and in the
polygon stations were integrated from the surface to 50 m to
give areal chlorophyll values. In the Chirikov basin and
Chukchi Sea where the bottom is less than 50 m deep, chlorophyll
values were integrated from surface to bottom.

Results

Chlorophyll concentrations were measured at each of the
113 stations studied during the cruise from 27 July to

2 September 1988. Samples for chlorophyll analysis were
obtained at approximately 10 discrete depths at each station.
Over 1,000 samples were collected and analyzed in this
comprehensive study of the Bering and Chukchi Seas.

Central Bering Sea Polygons

The East and South Polygons each consist of five stations
in the deep Bering Sea. The polygon stations are part of a
continuing study and were included in the Second Joint LTS-
USSR Bering Sea Expedition in 1984.

East Polygon. Stations 1 to 5 were located in the East
Polygon ( 58°N, 1 75° W) over the shelf slope area in the eastern
Bering Sea (Frontispiece). Bottom depth at these stations
ranged from 140 m at Station 5 to 3,190 m at Station 3.
Integrated chlorophyll values ranged from 22 mg/m- at Station
5 to 121 mg/m- at Station 2. The average for all stations was
66 mg/m-. Deep-water (2,689 m and 3,190 m) Stations 2 and

3 had the highest values, 1 2 1 and 90 mg/m-, respectively, with

the lowest values 22 and 48 mg/m-, being found at the shallower
( 140 m and 150 m) shelf-slope Stations 5 and 4, respectively.
South Polygon. Stations 108 to 1 13 were located in the
South Polygon (53°N, 175°W) in the deep basin of the Bering
Sea over Bowers Ridge ( Frontispiece). The minimum depth at
these stations is 220 m. Integrated chlorophyll values were less
than 30 mg/m- at each station with the exception of Station 1 1 2
(67 mg/m-). The average for all stations was 35 mg/m-.

Gulf of Anadyr and Western Bering Shelf

Stations 7 to 43 were located in the Gulf of Anadyr and on
the adjacent shelf southwest of St. Lawrence Island
(Frontispiece). Integrated chlorophyll ranged from 13 mg/nr
at Station 1 2, east of Cape Navarin outside the Gulf of Anadyr,
to 797 mg/m- at Station 24 in the central region of the gulf
(Fig. 1). Relatively low values (13 to 45 mg/m-) characterized
the southern half of the study area, particularly the shelf area
south of St. Lawrence Island. High values were measured near
the northern coast of the Gulf of Anadyr. Stations 24 and 26 had
exceptionally high concentrations of 797 mg/m- and
430 mg/m-, respectively. These were some of the highest
values measured during the cruise. Station 26 had chlorophyll
concentrations greater than 50.0 mg/m' in the top 10 meters,
decreasing to less than 1.0 mg/m' below 20 meters (Fig. 2b).

Fig. 1 . Depth integrated ((l-?0 m) chlorophyll (mg chl ii/nr ) lor Akademik
Korolev stations.

The highest chlorophyll values were found in the north and
central Gulf of Anadyr with concentrations decreasing to the
south and east (Fig. 1 ). A cross section, from Station 26 in the
northwest comer of the gulf to Station 35 on the adjacent shelf
area south of Anadyr Strait, shows a subsurtace chlorophyll
maximum (>15.0 mg/m') located along the northern coast of

124

e)

b)

a)

87 88

STATIONS
89 90

91

30 60 90
97 98 99 100 101

20
02

15
26 27 28

30 45 60
29 32 33 34 35

325 430
38 39 107

100 200 300
DISTANCE

400
(km)

490

Fig.

Vertical c
10 North (

ross-sections of chlorophyll (mg/m') arranged from South
a to e). Transect location given on Frontispiece.

the gulf at a depth of 20 to 30 m (Fig. 2b). A cross section from
Station 1 3 to .Station 39, from the outer shelf ( 1 50 m) to Anadyr
Strait (30 m), reveals high phytoplankton biomass strictly
limited to the strait area providing evidence of the influence of
nutrient-rich Anadyr water (Fig. 2a).

Anadyr Sirail

Data from Anadyr Strait indicate that high integrated
chlorophyll values were associated with waters near the
Siberian coast at Station 39 ( 193 mg/m-). Values decreased to
the east to 23 mg/m- at Station 43 next to St. Lawrence Island
(Fig. 1). A cross-section of Anadyr Strait provides another
view of the association between phytoplankton stocks and
Anadyr water. Chlorophyll concentrations decrease to less
than 1.0 mg/m' across the eastern half of the strait (Fig. 2c).

Chihkov basin

Stations 87 to 1 07 were in the Chirikov basin (Frontispiece).
Data from this area revealed high chlorophyll values on the
western side of the basin, suggesting the presence of higher
nutrient water (Fig. 1 ). Integrated chlorophyll values as high
as 593 mg/m-, at Station 87, were observed close to the Soviet
coast. The western side of the basin is characterized by values
over 100 mg/m-. Chlorophyll values decrease to the east across
the basin. Phytoplankton biomass of less than 50 mg/m- was
characteristic of the eastern side of the basin in Alaska Coastal
water. The maximum eastward extent of high chlorophyll
values was observed in the central part of the basin at Station
94 (307 mg/m-). Data from a transect across the central basin,
from stations 97 to 102, shows distinct areas of high biomass,
one next to the Soviet coast and one in the central part of the
basin (Fig. 2d). The western concentration has a subsurface
chlorophyll maximum (>3.0 mg/m') at 10 to 15 m while the
eastern area has a maximum (>8.0 mg/m') at 20 to 25 m. These
two areas of high biomass lose their identity and converge with
the water masses flowing toward Bering Strait (Fig. 2e). The
highest concentration of chlorophyll in the Chirikov basin was
measured at Station 87 the closest station to the Soviet coast.

Bering Strait

Bering Strait was surveyed twice. The first transect
occupied six stations (76-8 1 ) across the strait while the second
transect occupied five of the same stations (82-86), omitting
only the westernmost station. Integrated values of chlorophyll
indicate the same pattern for both transects (Fig. 1 ). Highest
values, up to 619 mg/m- at Station 76, were observed adjacent
to the Soviet coast west of Ratmanov Island and the lowest
value ( 27 mg/m- at Station 8 1 ) occurred east of Diomede Island
near the Alaskan coast.

During the first passage, the chlorophyll maximum on the
western side of the strait (>25 mg/m') was at the surface at
Station 76 (Fig. 3a). On the eastern side of the strait there were
noconcentrationshigherthan 1.7mg/m'. Although the western
side of the strait showed high integrated values throughout the
water column, most phytoplankton were close to the Soviet
coast. In the second transect a similar pattern existed as in the
first with the exception of a subsurface maximum (8.0 mg/m')
on the western side at 30 m. Bottom concentrations on the
eastern side near Diomede Island appear to match bottom

125

d)

c)

concentrations next to the islands on the western side indicating
that some of the phytoplankton associated with Bering Shelf-
Anadyr water flowed through the eastern portion of the strait.

Chukchi Sea

Stations 44 to 75 were in the southern Chukchi Sea
(Frontispiece). The highest values of integrated chlorophyll
(625, 696, and 1,167 mg/m-) found during the cruise were ^/

observed at stations 54, 56, and 55, respectively. Values in
excess of 300 mg chl/m- characterized the majority of these
stations with the highest values found in the center of the region
(Fig. 1). Thirteen of the 31 stations, all in the center of the
region or near the Soviet coast, had integrated chlorophyll
values greater than 300 mg/m-. Only the outer regions of the
study area to the north and east had values less than 1 00 mg/m-.
In the Chukchi, as with the Bering Sea components of the
cruise, high chlorophyll values were observed off the Soviet
coast at Stations 44. 59, 7 1 , and 72. The lowest values in the
area, less than 50 mg/m-, were found closer to the Alaskan
coast. Cross sections from Stations 72-75 and Stations 7 1-66
show high phytoplankton biomass on the western side of the
basin, presumably as a result of the flow of Bering Shelf-
Anadyr water carrying its load of phytoplankton and nutrients
(Figs. 3b,c).

Cross sections from Stations 59-65, and Stations 44-50,
indicate that the characteristic water masses of this system are
no longer recognizable from chlorophyll distribution
measurements ( Figs. 3d,e). North ofapproximately 67° latitude,
the Bering Shelf-Anadyr water masses appear to spread out as
current speed decreases and the flow becomes bathymetrically
steered (Coachman & Shigaev, Subchapter 2.1, this volume).
High chlorophyll concentrations occurred all across the transect
even close to the Ala.skan coast at Station 48 (Fig. 3e). High
integrated chlorophyll (>,W0 mg/m- )ischaracteristic of Stations
54 and 64 near the eastern side of the study area ( Fig. I ). Cross
sections from the northern Chukchi Sea (Figs. 3d,e) exhibit a
pronounced subsurface chlorophyll maximum similar to those
observed in the Chirikov basin and Benng Strait. Concentrations
greater than 70.0 mg/m' were measured at 15 m at Station 54. b)

Discussion and Conclusion

Our data support the general model that the advection of
the Anadyr water mass over the continental shelf of the
northern Bering Sea and into the Chukchi Sea strongly influences
the biological regune. In its wake (Coachman et al.. 1975) is
left a bounty of biological production resulting from its nutrient
load and the morphology of the shelf.

Chlorophyll measurements from the Gulf of Anadyr 3)
indicate a northward flow of nutrient-rich water around the
gulfs perimeter, originating from the bifurcation of the Bering
Slope Current in the vicinity of Cape Navarin. The influence
of Anadyr water (created by slight modification of Bering
Slope water in the Gulf of Anadyr) is not evident until it reaches
the euphotic zone as it flows around the Gulf of Anadyr and
through Anadyr Strait. The flrst biological indications of this
water mass are present at shallow-water stations in the northwest ^'g -"*
Gulf of Anadyr where the nutrient-rich water is exposed to the

CL
UJ
Q

STATIONS
44 45 46 47 48 49 50

65 130 195 260

59 60 61 62 63 64 65

60 150 230 310

71 70 69 68 67 66

10
20
30
40
50
60

50 100 150 200
72 73 74 75

#=-^

(

3
1

\^

4

^^.-^

^^^~~

i^-

-"""^^

1 1 1

25 50 75 100 130
76 77 78 ,— , n 79 80 81

25 50

DISTANCE (km)

Vertical cross-sections of chlorophyll (mg/m') arranged from South
to North (a to e). Transect location given on Frontispiece.

126

euphotic zone. High phytoplankton biomass at Stations 24 and
26 with lower biomass at surrounding stations indicate that
there may be a more complex production system operating in
the Gulf of Anadyr than our sampling regime was able to
adequately evaluate.

Chlorophyll data indicate that the tlow of Anadyr water as
the Anadyr Stream is entrained along the Soviet coast as it
flows north. High chlorophyll measurements consistently
occur near the Soviet coastline in the northern Bering Sea.
However, the influence of the Anadyr Stream on phytoplankton
biomass further from the coast was evident in a large loop of
chlorophyll isoplelhs in the central Chirikov basin (Fig. 1).
This pattern of phytoplankton distribution could result from the
flow of Anadyr water through the western end of Shpanberg
Strait into Chirikov basin or it could result from eastward
advection of high nutrient water flowing through Anadyr
Strait. Analysis of cross-sections from Chirikov basin indicate
that the loop of phytoplankton biomass, shown as a distinct
subsurface chlorophyll maximum, may be a separate entity
from the phytoplankton stock closer to the Soviet coast
( Fig. 2d ). Both phytoplankton concentrations merge as Anadyr
and Bering Shelf waters merge and flow through the western
side of Bering Strait. The highest phytoplankton biomass in the
Chirikov basin can be found near the Soviet coast. Future
expeditions should examine the Soviet coastal areas more
intensely.

Water masses in the Chirikov basin (Anadyr, Bering
Shelf, and Alaska Coastal) appeared well-defined with respect
to phytoplankton biomass distribution. An explanation for the
"loop" of phytoplankton in the central Chirikov basin is difficult
from chlorophyll data alone. The flow of Anadyr and Bering
Shelf water into the Chukchi Sea carries not only nutrients but
phytoplankton from the productive regions upstream in the
Chirikov basin. As opposed to the areas south of Bering Strait,
identification of individual water masses by chlorophyll
distribution is difficult. The absence of high chlorophyll values

near the Alaskan coast reflects the passage of nutrient-poor
Alaska Coastal water. The high nutrient Anadyr and Bering
Shelf water masses and their associated phytoplankton stocks
mix in Bering Strait and flow into the Chukchi Sea creating the
large chlorophyll pool in the center of the basin (Fig. I ).

Chlorophyll distribution in the Chukchi Sea supports the
presence of a southeast flowing current, from the north on the
Soviet coast (Zenkevitch, 1963; Coachman & Shigaev,
Subchapter 2.1, this volume). Areal distribution and depth-
sections of data indicate that the high chlorophyll values found
in this region have a distinct source near the Soviet coast
(Figs. l,3c-e). Depth-sections from the northernmost (Stations
59-65 and 44-50) transects suggest the existence of two
separate chlorophyll stocks, one over Hope Sea Valley in the
central Chukchi basin and one along the Soviet coast northeast
of Kolyuchin Bay (Figs. 3d,e). Data from the southernmost
transects in the Chukchi Sea, below 67° latitude, do not clearly
show these stocks (Fig. 3b). It is difficult to distinguish the
potential influence of high nutrient Siberian Coastal water
from that of Anadyr Stream flowing north through Bering
Strait.

The data from the Akculewik Korolev expedition fill several
gaps in the growing data base for the Bering/Chukchi Seas.
Since 1983, the ISHTAR Project has studied the ecology of the
northern Bering and southern Chukchi Shelf. But it was not
until the results of the expedition aboard XheAkadeinik Korolev
that hypotheses concerning the functioning of this productive
marine ecosystem could be confirmed (see Walsh et ciL, 1 989).

This project was part of the Third Joint US-USSR Bering &
Chukchi Seas Expedition aboard the Soviet research vessel Akademik
Korolev. We express appreciation to the US Fish and Wildlife Service
and the USSR State Committee for Hydrometeorology . who made our
participation possible. Our participation was funded in part by the
National Science Foundation. Grant DPP-8405286. Contribution
No. 627. Institute of Marine Science. University of Alaska. Fairbanks,
AK 99775-1080, USA.

5.1.3 Distributions of Algal Pigments in Near-
surface Waters

ROBERT R. BIDIGARE, MICHAEL E. ONDRUSEK, and JAMES M. BROOKS

Geochemicul and Environmental Research Group. Departmenl of Oceanography. Te.xas A&M Universitx. College Station.
Texas. USA

Introduction

The Bering Sea is a productive, high-latitude oceanic
environment whose expanse shelf supports large standing
stocks of zooplankton and marine vertebrates. In contrast to
most oceanic regions, the Bering Sea has high levels of
phytoplankton biomass and production associated with waters

overlying its shelf domain, as well as its open-ocean domain
(Holmes, 1958; Kawamura, 1963; Taniguchi, 1969; McRoy
etai, 1972; Koike ('/«/., 1982; Sambrotto <>/«/., 1984, 1986;
Hansen et al., 1989). Wal.sh et al. (1985) proposed that a
significant proportion of the shelf-based production is
transported to the Bering Sea Slope, which serves as a major
storage site for atmospheric carbon dioxide. The fact that the

127

zooplankton-to-phy toplankton biomass ratio calculated for the
Bering Sea is higher than most oceanic areas (Motoda &
Minoda, 1974) suggests that there is an efficient transfer of
phytoplankton carbon to higher trophic levels. However,
recent work by Springer et cil. ( 1 989 ) indicates that on average
the zooplankton of the northern Bering Sea are unable to
control the large blooms of diatoms that occur during springtime
in this region.

Sambrotto etal. ( 1 986 ) have shown that there is a significant
degree of seasonal variability in both phytoplankton biomass
and production on the southeastern Bering Sea Shelf. The
shallowing of the mixed layer was the most important process
responsible for bloom initiation, which occurs annually during
early May. The investigators also concluded that vertical
mixing forced by atmospheric events is important in controlling
the magnitude of the spring bloom. Innerannual variations in
zooplankton biomass have also been documented for the Bering
Sea, which may reflect variations in meteorological conditions
(Motoda & Minoda, 1974).

During early to midsummer, boreal-oceanic diatoms
dominate the phytoplankton community of the open
western/central Bering Sea and the eastern Bering Sea Shelf,
while temperate-neritic diatoms are characteristically found in
the vicinity of the Aleutian Island chain (Motoda & Minoda.
1974: Whitledgeeffl/., 1988). The dominant offshore diatoms
include representatives from the following genera:
Chaetoceros sp., Rhizosolenia sp., Denticula sp.,
Thalassiosira sp., Nilzschia sp., Fragilaria sp., and
Thalassiothrix sp. On the southeastern Bering Sea Shelf,
diatoms are dominated by Thalassiosira aestivalis and
T. nordenskioldii during prebloom conditions (April) and
Chaetoceros spp. (especially C. debilis) during bloom
conditions that occur during May (Sambrotto
et al.. 1986). Kisselev (1937) also reported the presence of
dinoflagellates and green algae in the northern Bering Sea.

' To further investigate the distributions of phytoplankton
in the Bering and Chuckchi Seas, near-surface water samples
were analyzed for pigment content by high-performance liquid
chromatography (HPLC). This study was part of the Third
Joint US-USSR Bering & Chukchi Seas Expedition, designed
to examine biological-chemical-physical interactions in the
Bering Sea.

Materials and Methods

A series of stations were occupied during July-August
1988 aboard the R/V Akademik Korolev in the Bering and
Chukchi Seas. Near-surface samples were collected at 1 12 of
these stations for the determination of photosynthetic pigment
concentrations (Figs. 1-12). One-liler water samples were
filtered through 47 mm GF/F glass fiber filters and transported
to Texas A&M University for HPLC pigment analysis. Filters
were extracted in 6 ml lOO'/f acetone (final acetone concentration
- -90%) for 24-48 h (-20 "C). Following extraction, pigment
samples were centrifuged for 5 min to remove cellular debris.
Pigment extracts were analyzed for pigment content by HPLC

(Bidigare, 1989). Briefly, chlorophylls and carotenoids were
separated using a Spectra-Physics Model SP8700 liquid
chromatograph equipped with a Radial-PAK C.s column
(0.8 X 10 cm, 5 |i particle size; Waters Chrom. Div.) at a flow
rate of 6 ml/min '. Prior to injection, 1 ml aliquots of the
standards and algal extracts were mixed separately with
300 |i 1 of ion pairing solution (Mantoura& Llewellyn, 1983).
A two-step solvent program was used to separate the algal
pigments. After injection (500 \i\ sample), mobile phase A
(80: 1 5:5; methanol:water:ion-pairing solution) was ramped to
mobile phase B (methanol) over a 12-min period. Mobile
phase B was then pumped for 18 min for a total analysis time
of 30 min. Individual peaks were detected and quantified (by
area) with a Waters Model 440 Fixed Wavelength Detector
(436 nm) and a Spectra-Physics Model SP4400 integrator,
respectively. The identities of the peaks were determined by
comparing their retention times with those of pure standards
and extracts prepared from "standard" plant materials of known
pigment composition. On-line diode array spectroscopy
(HPLC/DAS; 350-550 nm for carotenoids and 400-700 nm for
chlorophylls) using a Hewlett-Packard Model HP8451 Diode
Array Spectrophotometer was performed to confirm the
identities of the major chlorophylls and carotenoids. The
HPLC system was calibrated with pure standards whose
concentrations were determined spectrophotometrically in
1-cm cuvettes (Bidigare, 1989). Known pigment quantities
were injected and resultant peak areas were used to calculate
individual standard response factors (ng area'). Pigment
concentrations (ng pigment 1 ' ) of the samples were calculated
with these response factors and knowledge of the extraction
and sample volumes. The HPLC method employed is not
capable of separating chlorophyll c, from chlorophyll r,, nor
zeaxanthin from lutein.

Results

The quantitatively important algal pigments measured in
suspended particulate samples collected from near-surface
waters of the Bering and Chukchi Seas were chlorophyll a;
chlorophyllide a; chlorophyll b\ chlorophylls c, -i- c,;
chlorophyll c,; 19'-hexanoyloxyfucoxanthin:

19- butanoyloxyfucoxanthin; fucoxanthin; peridinin;
diadinoxanthin; diatoxanthin: and p,p-carotene (Table 2).
Concentrations of zeaxanthin plus lutein, prasinoxanthin, and
alloxanthin were near or below the limit of HPLC quantification.
Phytoplankton pigments in the study area were not uniformly
distributed. Chlorophyll a concentrations ranged from
1 2 to 26,6 1 8 ng 1 ' , wi th highest concentrations measured in the
Gulf of Anadyr and the Chukchi Sea (Fig. 1). Distributions of
chlorophyllide a, chlorophyll c, fucoxanthin, diadinoxanthin,
diatoxanthin, and |3,P-carotene all displayed patterns similar to
that of chlorophyll rt (Figs. 2,4,7,10,1 1,12). In contrast,
elevated concentrations of chlorophyll /' and peridinin were
measured in a narrow zone extending from the Chirikov basin
to just north of the Bering Strait (Figs. 3,6). Chlorophyll c„
19'-hexanoyloxyfucoxanthin.and 1 9 -butanoyloxyfucoxanthin

128

levels were highest at stations occupied in the Chirikov basin
and the south-central Bering Sea (Figs. 5,8,9). A tabular listing
of stations, positions, and algal pigment concentrations is given
in the Table 1.

Discussion

The concentrations of photosynthetic pigments in the
marine environment are primarily dependent on the quantity,
species composition, and photoadaptative state of the
phytoplankton present. For these reasons, accessory chlorophyll
and carotenoid pigments have been used as diagnostic "tags"
for investigating algal distributions and their physiological
processes. In coastal waters off Australia, Jeffrey (1974)
documented the usefulness of acces.sory pigments for examining
phytoplankton distributions in the water column. The thin-
layer chromatographic method employed identified the major
pigments as chlorophylls a. h, and c: carotene; astaxanthin;
fucoxanthin; peridinin; diadinoxanthin; and neoxanthin.
Chromatographic data were used to "fingerprint" vertical and
temporal variations in the phytoplankton community structure.

Several recent investigations have demonstrated the utility
of HPLC as a "chemotaxonomical" tool for identifying marine
algal groups. For example, high concentrations of zeaxanthin
were used to infer the presence of cyanobacteria in the North
Sea and tropical Atlantic Ocean (Gieskes& Kraay, 1983a). In
another study, the dominance of a symbiotic cryptomonad was
established for a spring bloom in the central North Sea by
HPLC identification ofalloxanthin, a carotenoid characteristic
of this marine algal group (Gieskes & Kraay, 1983b). HPLC
pigment analysis has also been shown to be useful for
characterizing phytoplankton biomass and compositional
changes across frontal systems located at the northern wall of

the Gulf Stream (Amone et ai, 1986; Trees el al, 1986) and
in the Santa Barbara Channel (Smith et al, 1987).

In this study, the criteria presented in Table 3 were used to
infer distributions for the major algal groups (diatoms, green
algae, dinoflagellates, chrysophytes, and prymnesiophytes).
The most abundant accessory pigments detected in this study
were chlorophyll c, diadinoxanthin, and fucoxanthin (Table 2),
which reflect the dominance of diatoms in the Gulf of Anadyr
and the Chukchi Sea during midsummer. In addition, the suite
of pigments also common to the diatoms (chlorophyllide «,
diatoxanthin, and p,P-carotene) all displayed elevated
concentrations in these regions. Distributions of chlorophyll b
and peridinin indicate that green algae and dinofiagellate
abundances were highest in a band extending from just north of
St. Lawrence Island, through the Bering Strait, and into the
Chukchi Sea. These distributional patterns are consistent with
those described by Kisselev ( 1937 ), who found that these algal
groups were abundant in the northern Bering Sea.
1 9'-Hexanoyloxyfucoxanthin and 1 9'-butanoyloxyfucoxanthin
concentrations were highest in waters overlying the Chirikov
basin (located just north of St. Lawrence Island)and the central
and southern regions of the Bering Sea, reflecting the presence
of prymnesiophytes and chrysophytes, respectively;
concentrations of these pigments were near the limit of HPLC
detection at stations occupied in the Chukchi Sea.

In summary, pigment concentrations in the Bering and
Chukchi Seas were complex and variable and suggest that
phytoplankton are not uniformly distributed with respect to
both biomass and composition. A comparison of these
distribution patterns with concurrently measured physico-
chemical parameters (i.e., nutrients and currents) will provide
insight into the factors affecting phytoplankton abundance in
the Bering and Chukchi Seas.

Fig. 1 . Contours of chlorophyll (J ( ng'l ' ) measured in Ihe Bering and Chukchi
Seas during July-August 1988, aboard the R/V Akculemik Korulev.

Fig. 2. Contours of chlorophyllide a (ng-1 ') measured in the Bering and
Chukchi Seas during July-August 1988. aboard the RA' Akademik
Korolev.

129

Fig. 3. Contours of chlorophyll /)(ng'l ') measured in the Bering and Chukchi Fig, 4. ContoursolchlorophyllttngM 'Jmeasuredinthe BeringandChukchi
Seas during July-August 1988, aboard the RA' Akademik Korolev. Seas during July-August 1988, aboard the IW Akademik Korolev.

Fig. 5. Contours of chlorophyll c, (ng-1') measured m the Bermg and Fig. 6. Contours of pendmm (ng'l ') measured in the Bering and Chukchi
Chukchi Sea.s during July-August 1988, aboard the RA' Akademik Seas during July-August 1988, aboard the R/V Akademik Korolev.

Korolev.

130

Fig. 7. Contoursoffucoxanthin ( ng'l') measured in the Benng and Chukchi
Seas during July-August 1988, aboard the RA" Akademik Korolev.

Fig. 8. Contours of 1 9'-butanoloxyfucoxanthin (ng'l ' ) measured in the Bering
and Chukchi Seas during July-August 1 988, aboard the KN Akademik
Korolev.

Fig. 9. Contours of 19'-hexanoyloxyfucoxanthin (ng'l') measured in the Fig. 10. Contours of diadinoxanthin (ng-1 ') measured in the Bering and
Bering and Chukchi Seas during July-August 1988, aboard the IW Chukchi Seas during July-August 1988, aboard the RA' Akademik

Akademik Korolev. Korolev.

131

Fig. 1 1. Contoursofdiatoxanthin(ng»r') measured in the Bering and Chukchi Fig. 12. Contoursofp.p-carotene(ng»l"')measured in the Beringand Chukchi
Seas during July-August 1988, aboard the R/V Akademik Korolev. Seas during July-August 1988, aboard the RA' Akcidemik Korolev.

TABLE 1

Near-surface pigment concentrations (ng 1 ') measured in the
Bering and Chukchi Seas during July-August 1988.

Station Lat(N) Lon(W) Chlr, Chida Chk Per Bfuc Fuco Hfuco Diad Diat Chi/; Ch\a Car

AKA-I

.S7..'S4

174.48

35

42

125

95

35

272

140

60

13

120

717

AKA-2

57.50

175.52

26

116

183

66

51

733

181

63

112

869

AKA-3

57.93

175.08

45

44

186

116

60

476

218

115

9

153

1061

AKA-4

58.52

174.49

46

54

171

46

65

466

181

107

29

62

878

AKA-5

58.50

175.50

44

T)

14

194

AKA-6

59.50

179.50

38

20

37

235

124

33

74

658

AKA-7

60.47

177.83

46

14

57

105

6

228

AKA-8

60.94

176.93

8

17

29

175

AKA-9

61.34

176.10

35

40

9

7

TTT

AKA-10

61.25

176.76

42

42

70

151

43

9

351

AKA-ll

61.58

178.65

2

76

71

21

51

130

42

280

AKA-12

61.88

179.42

.0

16

27

41

14

208

AKA-13

62.18

179.85

14

47

44

14

203

AKA-14

62.84

179.51

13

1

24

->-)

10

1

292

AKA-15

62.58

178.51

6

10

66

AKA-16

62.34

177.33

24

16

172

AKA-17

62.17

176.34

12

39

44

23

190

AKA-18

62.01

175.04

7

21

7

1

14

150

AKA-19

62.44

174.01

17

17

9

9

142

AKA-20

62.58

175.06

24

24

24

13

68

195

AKA-2 1

62.75

176.17

44

10

18

148

AKA-22

63.00

177.03

(J

10

81

AKA-23

63.35

177.84

3

TT

12

12

162

132

TABLE 1 - continued

Station

Lat(N)

Lon(W) Chlr,

Chida

Chl(

Per

Bfuc

Fuco

Hfuco

Diad

Diat

Chi/;

Chla

Car

AKA-24

63.68

178.47

186

4,290

11,666

1,074

155

203

26.618

318

AKA-25

64.00

179.33

55

19

215

AKA-26

65.00

178.67

35

4

89

AKA-27

64.74

177.78

43

12

225

42

50

760

AKA-28

64.25

177.50

61

11

278

13

45

692

AKA-29

63.83

176.97

2

7

13

4

16

99

AKA-30

64.17

175.97

21

30

44

10

122

AKA-31

64.34

175.01

15

86

12

155

33

90

53

645

AKA-32

64.00

180.00

26

14

38

13

8

143

AKA-33

63.49

175.03

10

1

61

AKA-34

63.18

174.14

18

84

AKA-35

63.02

173.00

44

5

119

AKA-36

63.45

172.18

15

21

13

11

3

34

98

AKA-37

63.66

173.82

6

12

75

AKA-38

63.90

173.53

28

21

17

52

392

AKA-39

64.23

172.70

51

381

997

109

3,227

AKA-40

64.13

172.50

37

151

371

69

16

697

AKA-41

64.03

172.21

6

65

213

52

285

AKA-42

63.92

172.07

12

38

17

17

43

221

AKA-43

64.10

171.20

9

14

9

14

164

AKA-44

67.37

173.33

15

61

11

102

AKA-45

67.74

172.80

39

9

163

AKA-46

67.92

171.75

18

8

104

AKA-47

68.10

170.88

68

28

133

AKA-48

68.27

170.00

21

158

33

368

AKA-49

68.47

169.13

3

49

5

250

AKA-50

68.66

168.33

57

9

3

113

332

AKA-51

68.16

168.74

75

15

137

AKA-52

68.08

167.00

31

71

6

266

AKA-53

67.70

165.72

13

83

4

67

539

AKA-54

67.76

167.32

69

419

44

952

AKA-55

67.74

168.44

193

1,894

6,723

468

45

75

13,198

170

AKA-56

67.74

169.93

4

12

AKA-57

67.71

171.35

78

29

154

AKA-58

67.50

172.14

77

26

165

AKA-59

67.15

171.99

47

6

154

AKA-60

67.26

170.83

13

89

20

265

AKA-61

67.33

169.75

17

123

426

44

938

AKA-62

67.34

168.72

41

449

32

1,361

108

13

62

3,265

36

AKA-63

67.34

167.73

93

355

1,517

101

3,135

AKA-64

67.30

166.71

4

119

540

41

1,199

AKA-65

67.34

164.98

39

49

91

37

17

137

485

AKA-66

66.93

165.92

40

290

17

512

AKA-67

66.93

165.83

(1

89

18

324

AKA-68

66.92

167.83

19

102

475

45

834

AKA-69

66.91

168.91

8

284

1,283

118

23

3147

5

AKA-70

66.91

169.92

194

1,329

4,846

257

20

133

10,426

180

AKA-71

66.91

171.01

9

118

21

275

AKA-72

66.55

170.17

11

401

1,801

179

7

4,098

21

AKA-73

66.55

169.32

16

84

273

1,090

6

98

31

119

2,488

12

AKA-74

66.56

168.60

38

131

52

677

67

22

162

1,559

AKA-75

66.55

167.29

20

242

24

742

AKA-76

65.98

169.60

184

1,607

16

4,521

344

28

77

10,713

119

AKA-77

65.93

169.35

91

10

338

8

58

14

67

981

AKA-78

65.85

169.22

140

422

1,110

80

2.765

AKA-79

65.70

168.68

55

399

12

40

742

AKA-80

65.67

168.50

6

257

7

485

AKA-81

65.63

168.35

14

7

271

16

539

AKA-83

65.67

168.50

73

182

196

29

341

11

29

370

1,039

AKA-84

65.71

168.69

63

95

19

354

48

42

190

1,215

133

TABLE 1 - continued

Station Lat(N) Lon(W) Chic, Chida Chk Per Bfuc Fuco Hfuco Diad Diat Ch\b Ch\a Car

AKA-85

65.83

169.17

16

104

288

27

19

887

25

98

23

181

2,357

27

AKA-86

65.94

169.38

27

31

326

1,577

131

21

3,835

24

AKA-87

65.41

170.36

41

163

955

21

3,231

243

31

7.813

155

AKA-88

65.36

169.99

18

194

58

907

79

65

1.889

14

AKA-89

65.24

169.36

47

171

586

53

825

AKA-90

65.18

168.66

24

144

54

479

15

83

12

53

962

AKA-91

65.24

167.98

30

64

38

360

5

44

34

691

AKA-92

64.67

167.69

1

16

124

27

329

AKA-93

64.75

168.43

125

29

185

AKA-94

64.86

169.19

370

794

906

93

1.729

AKA-95

64.97

169.98

15

107

19

470

70

1.091

AKA-96

65.09

170.71

1->

32

369

1.301

136

23

43

2,851

65

AKA-97

64.75

171.50

70

445

21

68

8

944

AKA-98

64.72

170.87

13

25

17

175

15

45

62

488

AKA-99

64.54

1 70.04

12

32

39

158

16

54

426

AKA-100

64.38

169.16

T)

93

320

42

421

AKA-101

64.23

168.32

40

213

55

311

AKA-102

64.09

167.39

21

273

42

15

226

AKA-103

63.66

168.36

144

39

251

AKA-104

63.85

169.21

21

211

65

836

165

773

9

AKA-105

64.03

170.09

T

112

38

239

583

83

197

7

77

1,315

3

AKA-106

64.22

170.98

1

67

114

246

122

112

6

127

874

AKA-107

64.40

171.62

36

295

14

476

AKA-108

54.42

176.74

26

66

126

104

59

483

AKA-109

54.5 1

175.47

15

63

118

104

46

10

412

AKA-110

53.93

176.01

64

75

114

40

267

199

147

14

369

AKA-111

53.53

175.54

54

16

61

120

133

85

14

47

396

AKA-112

53.43

1 76.59

99

129

234

30

72

623

308

124

75

801

AKA-113

53.17

177.22

103

30

47

108

214

45

111

533

TABLE 2

Average and range of photosynthetic pigment concentrations (ng 1 ' )

measured in near-surface waters of the Bering and Chukchi Seas

durins Julv-Aucust 1988 (n = 112).

Parameter Chic,

Chida

Chli

Per

BFuco Fuco

HFuco Diad

Diat

Chi/)

Chl(/ Car

Average 5

26

167

10

13 567

30 64

5

31

1,301 10

Minimum ND*

ND

ND

ND

ND ND

ND ND

ND

ND

12 ND

Maximum 99

370

4.290

116

239 11,666

.308 1.074

155

370

26.618 318

*ND = not detectable

1.34

Pigment

TABLE 3

List of the important phytoplankton pigments used

as diagnostic source marlcers for interpretation

of HPLC-derived pigment data.

Significance

Golden-brown Algae

Fucoxanthm
Chlorophyll c.+c.

19'-Hexanoyloxy fucoxanthm

Fucuxanthin

Chlorophyll r,+f,

19'-Butanoyloxyfucoxanthin
Fucoxanthin
Chlorophyll c,+Cj

Peridmin
Chlorophyll c.

Chlorophyll b-containing Algae

Lutem

Prasinoxanthin

Zeaxanthin

Divinyl chlorophyll a

Phycobilin-containing Algae

Zeaxanthin
Alloxanthin

*Also contam minor amounts of zeaxanthin.

Diatoms (and some
Chrysophytes and
Prymnesiophytes

Prymnesiophytes

Chrysophytes

Dinoflagellates

Chlorophytes*

Prasinophytes*
Prochlorophytes

Coccoid Cyanobacteria
Cryptophytes

5.1.4 Complex Hydrooptic Researches

ALEXANDER A. KUMEISHA' . SERGEI N. DRAKOV, and ALEXANDER E. LUKIN'

'Institute of Physics and Academy of Sciences. Minsk. BSSR

* Institute of Global Climate and Ecology. State Committee for Hydrometeorology and Academy of Sciences, Moscow, USSR

Introduction

In the ocean ecological researches of today, the optical
methods find practical application alongside of traditional
biochemical methods. These new methods have undoubtedly
some advantages over the conventional ones. It is possible to
make measurements without disturbing the environment; there
is high spatial and time resolution and wide diversification of
the information received. The interaction of biological and
hy drophy sical factors gives rise to the formation of conservative
optical structures, dependent primarily on phytoplankton and

their metabolites. As waters are carried by currents from
regions of formation, the biocenoses living therein undergo
gradual transformation, which is reflected in the optical
properties. Thus, if we identify those optical features that are
typical of water masses of different origin (or characteristic of
water mass in one or another stage of transformation), we shall
be able to identify ocean waters in terms of productivity and
other biological properties. The properties of light scattering
are dependent upon phytoplankton, which are extremely
susceptible to pollution. By determining the deviation of water
optical properties from natural level (in the regions that

135

potentially can be affected anthropogenically), we can draw
conclusions about the extent of pollution and to monitor its
dynamics.

The paper presents the results of complex hydrooptical
studies in the waters of the Bering and Chukchi Seas, The main
objective pursued was to study spatial and time variability of
hydrooptical characteristics and their correlation with biological
and microphysical parameters of particulates.

Hydrooptical Quantities — Definitions

Distribution of light in the ocean water is a function of its
absorption and scattering. These phenomena can (neglecting
polarization) be fully described by three primary hydrooptical
quantities; 1. indices of absorption k; 2. scattering cr, and
3. the angular dependence of scattering, x(Y) indicatrix.

If a collimated monochromatic beam of light is incident
along an axis (1) traveling through a small volume dV=dSdl in
the medium, this beam passes in solid angle, dw and creates
illumination E„(dS ) on an area normal to the beam. The amount
of flux absorbed by the volume will be proportional to

dF=KE„dSdl

(1)

Proportionally factor k is known as the coefficient of absorption,
its dimension is M ' ". The scattering index cr.

dF =aE„dSdl .

(2)

so that the full value of flux, scattered and absorbed on its path
dl, will equal equations ( 1 ) and (2):

dF=dF,+dF =(K+o)E„dSdl^E„dSdl .

(3)

The sum of absorption k and scattering o indices is known as
attenuation index 8 , and the relationship A=5/e is the probability
01 photon survival. The dimension of attenuation index is
e[M ']. T=e' defines the transmissivity of a water layer 1-m
thick, also referred to as transparency of water.

Expression (3) is a differential fonn of Bouguer's Law,
according to which any flux that has travelled in a scattering
and absorbing medium, is attenuated (hereinafter we shall
consider the values of relevant indices determined to the In
base):

F(l)=F(o)exp(£l).

(4)

Scattering of light varies with direction. A flux of light,
scattered in a single solid angle (or intensity of light dl) in a
direction, making up angle y with axis 1, will be proportional to
the value of volume dV of flux;

dI(Y)-C(Y)E„dV.

(5)

Proportionality factor cs(y ) is ternied as the index of directed
scattering and has the direction [ M ' ster ' ] ■ Scattered ( radiation
diffused) is known as the indicatrix of scattering:

X(Y)= 0(Y) ■ <6)

o
SinceJ /(y) dw= I, it can be treated as three-dimensional density
of probability of photon scattering at some angle (y ) with
respect to the direction of light propagation.

Often used in hydrooptics are the so-called integral
quantities — indices of scattering in front (6) and back ((i)
hemispheres:

5=27tl C3(7)sinYdY,

P = 2rtj cXyJsiuYdY

kI2

(7)

(8)

and their ratio K=5/p, called the asymmetry factor. The extent
of isotropy of scattering is defined by the mean cosine of
scattering:

c5sY = 2jrI x(Y)sinYCOSYdY

(9)

Parameters K and cosy characterize indicatrix "stretching,"
which increases with the increase of particle sizes. The
anisotropy of scattering will also be characterized by

R(YJ = 27i1 x(Y)sin(Y)dY.

(10)

determining a part of radiation scattered into solid angle with
angular opening from to y,,- Let us take 2° for Yo-

Hydrooptic Instruments

Critical for making complex hydrooptical measurements
//( situ is their synchronism. The apparatus complex, used by
us, made it possible to realize this principle with the help of
rather simple technical means. The complex included an
immersible transmittance meter with a bathometer and a board
meter of angular light scattering indicatrix-meter. First, a
vertical profile attenuation index e of water was measured, and
second, the angular characteristics of light scattering (C5( y ) ) of
samples were taken from different horizons.

The photometer/transmittance meter used was a
'■Kvant-3." The optical-mechanical and electronic units of the
instrument are accommodated inside a hermetic case, which,
via traction and electric connectors, is connected with a double
cable-line, type KF 7-90-180. The meter measures and
compares the intensity of light flux before and after its passing
through a layer of certain thicknesses 1 ( defined by the instrument
measurement base). This principle of measurement is realized
as follows: formed by corresponding elements of the optical-
mechanical unit, a probing beam of light is emitted through a

136

porthole into the seawater; then, after having been reflected
from an outboard spherical mirror, it returns. Such a returning
beam, attenuated by the seawater, is directed to a
photomultiplier where it is compared with a reference beam,
passing inside the instrument. Originally, this reference beam
has the intensity equal to that of the probing beam. The
required spectral range is discriminated with the aid of a
suitable light filter, which is installed in front of the
photomultiplier. A different signal is transmitted over the
cable-line to the board block and registered there as a function
of the depth probed. The instrument measurement base is 0.5
m; maximum depth of immersion, 250 ni (Kumeisha &
Vinokurov, 1984).

The assessment of measurement errors is a very difficult
problem because of the lack of "clear water" reference. Usually
verification is carried out with the aid of samples that are
standardized neutral filters and thin glasses and whose
coefficients of transmissivity (orrellection) are measured on a
standard spectrophotometric equipment or can readily be
calculated. Modeling has shown that the absolute error of
measurements made to detemiine the attenuation index of clear
{£ < 0.15 m ') waters is not in excess of 0.01%; in less clear
waters the relative error is nearly 5%.

A bathometer is an attachment to the "Kvant-3""
transmittance meter which allows an assessment, on the basis
of visual analysis, of a profile of the attenuation index. The
bathometer valves are tested for reliable functioning by
measuring the transmittance of an assay selected, making use
of a special cell in the "Kvant-3" instrument (intended for
onboard analysis), and then comparing transmittance values
with those measured //( situ on the horizons of probing. All tests
showed satisfactory results.

A board indicatrix meter is constructed as a cylindrical cell
with an attached illuminator and scanning device with a
photodetector. The illuminator emits a collimated beam of
light, which, via portholes in the cell, transilluminates water
samples (cell volume is 3 ml). The scanning device receives
radiation scattered from the zone at angles from 0.5° to 165°
relative to the direction of its propagation. The illuminator and
receiver embody aperture and field diaphragms pemiitting
alteration of angular divergence of light fiuxes and their cross-
sections. The volume, subjected to photometry analysis, is
5- 10 ml. Hence, one can safely neglect the contribution of this
factor to the scattering of zooplankton.

Received light is directed to the photomultiplier through a
glass light filter; an electric signal, proportional to the light
flux, is then amplified, filtered, and applied to a digital
recorder.

In order to obtain absolute values of scattering indices, the
intensity of light that has passed through the instrument is
measured (Gabrilovich, 1976). The instrument was verified
with the aid of monodisperse polystyrene latex solution.
Comparing the results of measurements and calculations, the
relative error of angular measurements of light scattering has
been found to be 10%.

Results

All primary hydrooptic characteristics were measured at
wavelength X = 530 mm. The obtained vertical profiles of
attenuation index were tabulated through 1 m in shallow parts
of the seas and through 5 m at depth H = 100-250 m. Since, in
biology, they often operate with average characteristics ( related
to water layer or water column), we also calculated average
index of attenuation in layer 0-H:

j e(H')dH'

<e>H =

H

Absolute values o{y) within 0.5-165°, full index of
scattering and integral characteristics of indices (k, cos y and
R [ Y„ = 2° 1 ) were calculated from angular relationships of light
scattering. Volume concentrations V^ and V, (in cmVm') of
coarse (particles having radii in excess of 1 urn) biological and
fine mineral (less than 1 |im) fractions of suspended matter
were assessed following Kopelevich (1981). Such calculations
are possible using a physical model of scattering. Ocean water
particulates is divided into two independent fractions in terms
of size and index of refraction. Angles of y < 2° for coarse
particles, and y> 45° for fine, can be calculated; however, the
numbers are weakly correlated.

This is, of course, an idealized model of ocean water
particulates; yet, on the whole, it allows interpretation of
material that has been collected earlier. Its advantage lies in the
fact that it permits assessing the content of fine fraction
particulates (including submicron particles), which is beyond
the capacities of conventional geological methods. It should be
noted, however, that the model has not been tried by the author
( Kopelevich, 1 98 1 ) to describe indicatrices of highly productive
waters where variation of content of coarse and fine particulates
differs from that in open ocean. Fine suspended particles may
predominantly be of organic matter. Applicability of generally
accepted concepts becomes doubtful when suspended minerals
dominate in coarse fraction. This is why the assessments of
particulates content, presented in this report, should be regarded
only as preliminary, subject to verification through direct
biological observations and through appropriate model-based
calculations.

Volume content of fine and coarse fractions (V, and VJ
was inferred from the following relations:

V, = 10.2o,4, ,-1-4x1 0-*o,,., -0.002,
V, = 2.2xl0^o„.,-1.2a,45.„

(11)
(12)

where o,, ,and 0,43, are indices ofdirected scattering at l°and
45° angles.

The optical type of water, assessed from measured values
of 0,4;; I and o, , ,, will also be helpful when added to the above-
mentioned parameters. Since according to ( 1 1 ) and (12) such

137

values show the content of fine and coarse fractions in
particulates, the typification will differentiate waters by their
contents of possible volumes of coarse and fine particles. High
concentration of a certain fraction will be denoted by the letter
"H,"" medium by "M,"" low by "L." Combinations of these will
be denoted by two-letter codes, of which the first letter specifies
volumetric content of fine particles and the second letter that of
coarse particles. The numerical equivalent of the letters used
has been given in Table 1 .

This typification is very helpful. Comparisons of waters
in the areas explored by us with typical ocean waters in
different stages of development can be made quickly. For
instance, from data of the same paper, type MM is typical of
open ocean waters; types LM (particularly, LL and ML) are
typical of deep-water horizons and types MH, HM, and HH
only of higher productivity regions.

Fraction

TABLE 1

Volumetric content. cmVm'
L M

H

Coarse
Fine

<0.1
<0.015

0. 1 -0.45
0.015-0.055

>0.45
>0.055

Chukchi Sea

Investigation of Spatial-Temporal Variability of
Transmittance Field

Fig. I,

Zonal dislnhution of attenuation index {£ ) average for a certain layer
of water.

It would probably be most reasonable to begin analyzing
the hydrooptic characteristics of spatial-temporal variability
by considering zonal distribution transmittance in northern
waters. The frontispiece shows that route of expedition with
numbers of stations. Numeration relates to the period of joint
Soviet-American research.

Water transmittance T is dependent upon the attenuation
index (e ) according to the relation T = e*. In the literature, data
is presented for the attenuation index field. In order to make it
possible to compare our results with the data of other researchers,
we shall keep to this tradition (i.e., we shall imply, when
speaking of "transmittance" and "transmittance field,"
corresponding values of distribution e) .

Figure 1 shows zonal distribution of attenuation index ( e)
average for a certain layer of water. When interpreting the
results, it is useful to bear in mind that, according to Kopelevich
( 1981 ), the suspended coarse fraction contributes 40-45*7^ to
light attenuation in the green portion of spectruin in oligotropHic
and mesotrophic waters and nearly 80% in littoral waters. It
seems quite justifiable to apply the latter assessment to
productive littoral waters of high latitudes. In this case, the
vertical structure e ,„, will depend mainly on the distribution of
suspended coarse fraction, while attenuation index (average
for the layer) will be dependent on average content of coarse
fraction.

Maximum amounts of suspended matter are contained in
the Chukchi Sea waters (with absolute maximum found at the
area of Stations 55 and 60) and a minimum in the Gulf of

Anadyr waters (with minimum found in its southeastern
periphery ) ( Fig. 1 ). When assessed in this way, the Bering Sea
waters will be in somewhat medium position.

This zonal distribution reflects the main qualitative
transfomiation that the Pacific waters undergo as they are
transported to the Chukchi Sea, with an increase of suspended
matter with increasing latitude.

Another parameter that is closely associated with average
attenuation, with wide application in oceanology, is
transmittancy, or maximum depth at which a reference white
disk (Secchi disk) is still seen. Such a depth is determined as
follows: the disk is gradually immersed deeper and deeper into
water, and the depth is noted at which the disk vanishes from
sight and then appears in sight again when being raised. The
average value H,, found froin the above-mentioned values is
termed as Secchi transmittance of water or transmittancy.

These measurements are important because transmittancy
(associated with all primary hydrooptic characteristics and
illumination conditions), in practice, may accurately be
expressed in the form of a single uniparametric relationship
derived from average value of attenuation ( e ) „,, index in layer
O-H:

- -A . (13)

H.,

( f>

Proportionality factor A depends on the rest of primary
optic properties of water (and, hence, on ocean region) and on
illumination conditions. This allows with known a priori

138

valuesof Atoassess( e) |,,Jn those regions where no hydrooptic
apparatus-assisted measurements have been carried out but a
lot of material on white disk obsei^ation exists.

The value of A for waters of the World Ocean varies from
3 to 8 (Ivanov, 1975). However, the calculations made by the
author (Levin, 1983) show that under certain "standard"
conditions of observation, the range of A depends on the actual
variability of optical properties so the range should be narrower.
Thus, if the Sun's altitude is more than 60°, and if the disk is
observed from the solar board side, the coefficient A for waters
having transmitlancy within 5-20 m and oblong indicatrix of
scatting (1/k < 0.02). will change almost linearly with the
change of probability of photon survival A from 5.1 (with
A = 0.06) up to 6.6 (with A == 0.9). Calculations show that the
most scattered ocean indicatrices known lower the A value by
10%. When the Sun's altitude is 30° and Ais within the same
range, the A value must vary from 4 to 5.5 (if observed from the
solar side of board) and from 5 to 8.5, when observed from the
shadow side. Slight heaving of the sun will lower the A value
to 3-5.

From our apparatus-assisted and visual observations, we
can assess the value of the proportionality factor for the waters
of northern latitudes.

Figure 2 shows an experimentally determined function of
H,^ in the waters of the Chukchi Sea (triangles), northern area of
the Bering Sea (clear circles), and Gulf of Anadyr (solid
circles).

It is obvious that most turbid waters are in the Chukchi Sea
(Hf,= 4-10 m), moderately cloudy waters are in the northern
area of the Bering Sea ( H^ = 6- 1 6 m), and relatively clear waters
are in the Gulf of Anadyr (H^ = 10-24 m).

Figure 2 illustrates two approximating curves plotted
according tot 13) fortwo values of factor A (4.3 and 4.8). It is
obvious that clear waters of the Bering Sea are more accurately
described by (13) when A = 4.3 and turbid waters of the
Chukchi Sea at A = 4.8. Discrimination, as manifested by the
above-given assessments from the paper (Levin, 1983), may
possibly be an evidence of different correlation between
absorbing and scattering abilities of suspended matter in different
areas. However, this fact can more reliably be borne out by
numerous apparatus-assisted and visual observations.

Eh-I'^ 1

Fig.

E,\penmentally found function of H^^ in the waters of the Chukchi Se
(A), northern area of the Benng Sea ( O) and Gulf of Anadyr (•).

At this stage, the average value of A for northern areas is
equal to 4.5.

As mentioned earlier, the transmittance of water in the
blue-green field of spectrum will depend mostly on the amount
of particles present in the water. In productive areas of the
ocean, the bulk mass of suspended matter is made up of
phytoplankton. Optically, the type of algae can be defined by
size, shape, and index of refraction. These characteristics
directly affect the angular structure scattered radiation. The
bigger size of biological particles and the higher their content
in the total composition of suspended matter, the more forward-
extended is the water scattering indicatrix and the higher the
values of its integral characteristics — asymmetry factor K,
mean cosine of scattering angle c"os"y, and portion of light R,
scattered in the minor "forward" angle.

As waters are carried over by currents from the regions
where they formed, the conditions of suspended matter alter,
due to the content changes and composition transformers. It is
clear that since the latter of the two processes is more inertial,
the angular characteristics of light scattering are inore
conservative as compared with water transmittance. In this
connection, it seems reasonable to determine the totality of
angular and integral characteristics that are typical of water in
which some species of algae prevail (some peculiar features of
such algae being quite typical) and then to employ these
characteristics as an indicator for identifying this type of water
in the process of its propagation. The transmittance field
correlates over lesser areas and can be used to give details in the
processes of synoptic nature.

Bearing in mind the aforesaid, let us now turn directly to
analyzing the experimental data. We shall begin our review
with considering the cross sections of transmittance field in the
northern waters moving from to lower to higher latitudes.

Gulf of Anadyr

The crosscurrent Hows northwardly through this region
(Sukhovey. 1986). We shall assume that waters at the starting
points ofthe area underconsideration are of Pacific origin. The
upper layer of water between 60° and 62° north latitude
showed clear water in all quasi-latitudinal sections. Such water
followed bottom relief and gradually ascended from 100 to
60 m. Beginning approximately from 62°N, the clear water
mass was split by a subsurface maximum of cloudiness,
propagating northward, to the Gulf of Anadyr.

As proved by the analysisof angular and integral

characteristics of light scattering, the waters in the area under

investigations have high values of asymmetry factor

(K = 80- 1 20) and mean cosine (0.95-0.96), an indication ofthe

presence of coarse biological particles. Theirrelative volumetric

content amounts to 88-92%. A cross section at nearly 63°N

(Station 24) has an unusual transmittance structure of water

(Fig. 3). In this and other figures, the solid circles show the

horizons from which water assays were taken to assess light

scattering data. Station numbers and depths from which assays

have been taken are given in the figures. In the left-hand

column are the asymmetry factor K , relative to volumetric

content of suspended matter fine fraction:

P= '^f ; R {Yo=2),
V, + V,.

139

and small angle value of indicatrix x(y= 1°)- Given as fractions
in the right-hand column are volumetric contents V^ and V, in
(cmVin') of coarse and fine fractions and also the type of water
(Kopelevich, 1983). Here, in the surface 10-m layer of water,
there is intense development of diatomic particulates (ocean
water was brown). At this station (Station 24), the white disk
could be discerned at the depth as small as 3 m. The integral
characteristics of light scattering here were also high ( K > 90,
cos Y - 0.943 ); as for the coarse fraction, its relative content was
somewhat lower (84%). For the purpose of comparison.
Fig. 4 shows how chlorophyll a is distributed throughout that
quasi-latitudinal section (data from Robie et al., subchapter
5.1.2, this volume). Obviously, there is certain correlation
between the two presented structures.

It is possible that conditions prevailing at the area of
Station 24 were more beneficial for particulates development
and that it was just those factors that caused a sharp rise of
productivity in originally bioactive Pacific waters. It is
noteworthy, however, that these waters give higher values of K
and cos y • This can be explained as follows: All light-
scattering indicatrices measured in northern waters (all in all
about 100 angular relationships had been obtained) were
analyzed statistically. The analysis showed the volumetric

content of fine fraction increasing with the rise of productivity
at a higher rate than that of coarse fraction. In other words, the
relative content of the latter drops (which, by the way, was the
case at Station 24). Accordingly, the indicatrix becomes less
extended and its integral characteristics decrease. Since the
water at Station 24 belongs to a very definite type, we shall
consider the diatom particulates as having the following
characteristics:

K = 80-120,
cos Y = 0.945-0.960,
X,„ = 50-70,
R„_,., = 0.1