NOAA Technical Memorandum NMFS-AFSC-130


A Comparison of the Eastern Bering and


Western Bering Sea Shelf and


Slope Ecosystems Through the


Use of Mass-Balance Food Web Models


by


K. Y. Aydin, V. V. Lapko, V. I. Radchenko, and P. A. Livingston


U.S. DEPARTMENT OF COMMERCE 

National Oceanic and Atmospheric Administration 

National Marine Fisheries Service 

Alaska Fisheries Science Center 

July 2002 
NOAA Technical Memorandum NMFS 

The National Marine Fisheries Service's Alaska Fisheries Science Center 

uses the NOAA Technical Memorandum series to issue informal scientific 

and technical publications when complete formal review and editorial 

processing are not appropriate or feasible. Documents within this series 

reflect sound professional work and may be referenced in the formal scientific 

and technical literature. 

The NMFS-AFSC Technical Memorandum series of the Alaska Fisheries 

Science Center continues the NMFS-F/NWC series established in 1970 by 

the Northwest Fisheries Center. The new NMFS-NWFSC series will be used 

by the Northwest Fisheries Science Center. 

This document should be cited as follows: 

Aydin, K. Y., V. V. Lapko, V. I. Radchenko, and P. A. Livingston. 

2002. A comparison of the eastern and western Bering Sea shelf and 

slope ecosystems through the use of mass-balance food web models. 

U.S. Dep. Commer., NOAA Tech. Memo. NMFS-AFSC-130, 78 p. 

Reference in this document to trade names does not imply endorsement by 

the National Marine Fisheries Service, NOAA. 
NOAA Technical Memorandum NMFS-AFSC-130


A Comparison of the Eastern Bering and


Western Bering Sea Shelf and


Slope Ecosystems Through the


Use of Mass-Balance Food Web Models


by 1 2 2 1

K. Y. Aydin, V. V. Lapko, V. I. Radchenko, and P. A. Livingston 

1 Alaska Fisheries Science Center 

7600 Sand Point Way N.E. 

Seattle, WA 98115 

www.afsc.noaa.gov 

2 Pacific Research Institute of


Fisheries and Oceanography (TINRO)


4 Shevchenko Alley


Vladivostok Russia 690600


U.S. DEPARTMENT OF COMMERCE 

Donald L. Evans, Secretary 

National Oceanic and Atmospheric Administration 

Vice Admiral Conrad C. Lautenbacher, Jr., U.S.Navy (ret.), Under Secretary and Administrator 

National Marine Fisheries Service 

William T. Hogarth, Assistant Administrator for Fisheries 

July 2002 
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copy format. 
ABSTRACT 

A comparison of the food webs of the eastern and western Bering Sea continental 

shelf large marine ecosystems (EBS and WBS LMEs) is presented, with a literature 

review of Russian and English sources for the western Bering Sea food web. A model is 

constructed using Ecopath, a tool for performing quantitative mass-balance calculations 

to synthesize food web data. The model focuses on the earliest period for which detailed 

diet data was available in both systems, 1980-85. 

The results show that the broad EBS shelf supports a benthic community of 

considerable diversity, while the narrower WBS shelf contains an ecosystem with a 

higher per-unit-area production in the pelagic layers and a more productive pelagic 

phytoplankton and zooplankton community. Keystone species in both systems are 

walleye pollock (Theragra chalcogramma) and Pacific cod (Gadus macrocephalus). In 

the eastern Bering Sea, small flatfish and crab species have a large impact on the energy 

flow from the benthic web to upper trophic levels. On the other hand, in the WBS, a 

large proportion of detritus entering the benthic food web is consumed by epifaunal 

species such as urchins and brittlestars. This may be due to the larger percentage of WBS 

shelf area close to shore. Additional measures of ecosystem structure, maturity, and 

sensitivity are presented. 

Future steps in pursuing ecosystem modeling efforts through the food webs in 

these two systems should lie in determining the importance and role of deep Bering Sea 

Basin processes, especially through mesopelagic forage fish, and in further 

subpartitioning each model into fine scale biophysical domains. 

iii 
iv 
CONTENTS 

Introduction......................................................................................................................... 1 

Methods............................................................................................................................... 3 

The Ecopath Model..................................................................................................... 3 

Model Setting.............................................................................................................. 4 

Results and Discussion ..................................................................................................... 10 

Outline....................................................................................................................... 10 

Overall Biomass and Flow Between Trophic Levels ............................................... 10 

Biomass and Trophic Level of Individual Components ........................................... 12 

Production and Consumption of Individual Components......................................... 16 

Primary Production Required ................................................................................... 17 

Fishing, Predation, and Unexplained ("Other") Mortality........................................ 20 

Food Web Network Structure ................................................................................... 23 

Keystone Species, Top-down and Bottom-up Control ............................................. 32 

Conclusions....................................................................................................................... 45 

Appendix A: Western Bering Sea Model ......................................................................... 49 

Marine Mammals and Seabirds ................................................................................ 50 

Fish and Cephalopods............................................................................................... 51 

Benthic Invertebrates ................................................................................................ 53 

Zooplankton .............................................................................................................. 55 

Protozoa .................................................................................................................... 57

Phytoplankton ........................................................................................................... 57 

Appendix B: All Model Input Tables ............................................................................... 60 

Appendix C: Western Bering Sea Shelf/Basin Partitioning ............................................. 70 

Citations ............................................................................................................................ 71 

v 
INTRODUCTION 

In order to develop meaningful measures of large marine ecosystem (LME) 

function and health, a comparative study of ecosystems is required. Unfortunately, the 

unique nature of each separate LME makes drawing comparisons between systems 

difficult. Furthermore, such comparisons may require a synthesis of large bodies of 

literature that exist in different locations and contain results in different contextual 

formats that are not readily adaptable for comparison. 

The Bering Sea (Fig. 1) covers more than 2.3 million km2

, and as a whole 

supports high biological production and multiple fisheries (NRC 1996). In a 

management context, its waters lie in both Russian and U.S. Exclusive Economic Zones 

(EEZs), with international waters in a section of the central basin (the “donut hole”). 

Chirikov 

Basin 

Inner 

Domain 

Outer 

Domain 

Middle 

Domain 

Aleutian 

Basin (east) 

Aleutian 

Basin (west) Commander 

Basin 

Anadyr 

Cape Navarin Basin

Figure 1. The Bering Sea, with boundaries of the EBS shelf model (eastern solid line), the WBS shelf 

model (western solid line), and the WBS shelf+basin model (dotted line). Isobaths shown are 50m 

(between inner and middle domains), 100m (between middle and outer domains) and 200m (between outer 

domain and slope/basin). 

Sherman and Alexander (1986) define LMEs as ocean spaces of at least 

200,000 km2, characterized by distinct hydrographic regimes, submarine topography, 

1 
productivity, and trophically dependent populations. With respect to the biophysical 

setting of the Bering Sea, three ecosystems have been defined as relevant LMEs 

(Sherman 1993): the eastern Bering Sea (EBS), the western Bering Sea (WBS), and the 

adjacent Gulf of Alaska (GOA). A unified framework for concurrently exploring the 

food webs of each of these regions has not been presented in the past, and such a 

framework is useful for examining large scale climate and human-induced changes as 

they occur in these systems. 

The Alaska Fisheries Science Center (AFSC) and the Russian Pacific Institute of 

Fisheries and Ocean Research (TINRO) have each been conducting ecosystem studies in 

their respective sides of the Bering Sea. It is evident from the published Russian literature 

and data listings provided to the National Marine Fisheries Service (NMFS) that Russian 

researchers have data on the abundance and trophic links of marine ecosystem 

components in the western Bering Sea. Similarly, scientists on the eastern side of the 

Pacific have been updating energy flow models of the eastern Bering Sea shelf. 

Unfortunately, there have never been any joint integrative studies looking at the 

food webs of the Bering Sea as a whole. The difference in physical and biological 

conditions between the eastern and western areas may result in fundamentally different 

responses to ecosystem change. On the other hand, the presence of similar important fish 

species such as walleye pollock (Theragra chalcogramma) and Pacific cod (Gadus 

macrocephalus) targeted by fisheries may result in profound similarities. 

The goal of this project is to elucidate ecosystem production and energy pathways 

in the eastern and western Bering Sea shelf and slope regions by developing and 

comparing quantitative food web models of these areas. The third LME mentioned 

above, the Gulf of Alaska, is a target for future modeling work. By using a common 

modeling framework, Ecopath, we hope that this effort shall serve two primary purposes: 

1. It shall synthesize the predator and prey data from the western Bering Sea into a 

quantitative food web, while providing a substantial literature review similar to that 

provided for the eastern Bering Sea in Trites et al. (1999). 

2. It will allow the examination of the resulting food web models as a preliminary 

exploration and comparison of the ecosystem interactions which occur in both 

ecosystems, and also of the independent data analysis methodologies used to derive 

the predator/prey quantitative interactions used in each model. 

The primary results of the western Bering Sea data review and initial model 

building are contained in Appendix A of this report, as provided by the Russian 

participants in this project; this Appendix serves as a companion piece to the eastern 

Bering Sea data review contained in Appendix 2 of Trites et al. (1999). The results of the 

comparison and synthesis of the eastern Bering Sea shelf and Western Bering Sea models 

(hereafter referred to as the EBS and WBS models) are contained in the Results section 

of this report, and represent a joint effort of all of the current authors. 

2 
 

METHODS 

The Ecopath Model 

Ecopath is a food web analysis tool that has gained broad recognition as a sound 

methodology for assembling and exploring data on marine food webs (Polovina 1985, 

Christensen and Pauly 1992, Pauly et al. 2000; see the website www.ecopath.org for the 

latest available software, manuals, and list of published models). The methodology’s 

strength lies in its emphasis on using data collected and analyzed in many common types 

of fisheries analyses, especially stock assessment and food habits studies; and its ability 

to combine the data into a single coherent picture. A resulting model both highlights the 

dominant predator/prey processes as they can be gleaned from the data, and helps focus 

attention on major data gaps relative to their importance in the functioning of the 

ecosystem as a whole. 

Ecopath is a mass-balance model, built by solving a simple set of linear equations 

which quantify the amount of material (measured in biomass, energy, or tracer elements) 

moving in and out of each compartment in a modeled food web. The master Ecopath 

equation is, for each functional group (i) with predators (j): 

Bi 





P 

 * EEi + IMi = ∑



Bj * 



Q 

 * DCij 



+ EMi + Ci .  B i j   B j 

For each compartment, a subset of the parameters: 

1. B (biomass); 

2. P/B (production/biomass); 

3. Q/B (consumption/biomass); 

4. DC (full proportional diet matrix); 

5. IM (Immigration) and EM (emmigration); 

6. C (Fisheries catch + discards); 

may be provided as data inputs and the model will estimate a seventh parameter, 

“Ecotrophic Efficiency” (EE), the fraction of input production which is utilized by other 

compartments. The estimation of EE is the primary tool for data calibration in Ecopath: 

independent estimates of consumption and production of different species often lead to 

initial conclusions that species are being preyed upon more than they are produced (EE > 

1.0), which is impossible under the mass-balance assumption. 

Therefore, by using an EE greater than 1.0 as a diagnostic tool for error, it is then 

possible to assess the relative quality of each piece of input data to adjust inputs to a selfconsistent whole. This process is known as “balancing” the model: it does not imply that 

the true ecosystem is in equilibrium but rather quantifies the uncertainty contained in the 

estimates of supply and demand present in the system. 

For the EBS and WBS models, data for Parameters 1-6 listed above were gathered 

from numerous sources. In cases where reasonable estimates of biomass were not 

available, the EE for the compartment was set to a constant, to estimate the minimum 

biomass required to supply the rest of the food web’s consumption of that compartment. 

The compartments for which this approach was taken are discussed below. 

3 
Model Setting 

Geographic setting 

A simple “box-type” food-web model contains no explicit differentiation of 

biogeography. The ideal ecosystem box model is both closed in terms of migration and 

uniform in terms of spatial processes. Unfortunately, in selecting the size of the region to 

be modeled, the goals of closure and uniformity are mutually exclusive, especially when 

examining higher trophic level fish stocks. Furthermore, the offshore boundaries of 

marine ecosystems are flexible, and may differ for different marine plant and animal 

communities and may shift with time as environmental changes occur. 

Pacific waters flow into the Bering Sea from the Alaskan Stream and by the 

Western Subarctic Gyre currents (Ohtani 1973). Intensive water exchange makes the 

Bering Sea a relatively open gulf of the Pacific Ocean (Shuntov and Dulepova 1991). 

The counterclockwise circulation of water along the shelf creates several regions of 

differing biological productivity; for example, the inner, middle and outer fronts 

described below, and the “Green Belt”, a region of intense primary productivity 

associated with the shelf break (Springer et al. 1996). 

Each of these regions possesses distinct communities of lower trophic level 

species with differing process rates (McRoy et al. 1986). However, many fish and 

mammal species are part of single stocks which are distributed throughout these zones. 

The model’s capability to partition stocks by subregion is limited: therefore, all of the 

zones were included in a single model and lower trophic level processes were weighted 

by subarea to calculate averages over the system as a whole. 

The eastern Bering Sea shelf consists of inner, middle, and outer shelf ecological 

zones separated by oceanographic fronts associated with the 50, 100, and 200 m isobaths, 

respectively, each of which possesses fundamentally different physical processes and 

species compositions (Fig. 1; Table 1). The EBS model was limited entirely to the area 

of the EBS south of 61°N and 20 km or more offshore as representing the extent of the 

NMFS trawl survey area. 

The wide shelf of the EBS was considered self-contained, with no major input of 

diet items from the Bering Sea basin. The only exception to this was for Pacific salmon 

(Oncorhynchus spp.), for which 75% of their diet was considered to come from outside 

the eastern Bering Sea. Marine mammals’ migration and off-the-shelf foraging was 

handled by lowering the average biomass of seasonal migrants. However, since some 

species were resident on the shelf while taking short foraging trips over the basin, some 

of the diet of these animals necessarily reflected basin species. 

The shelf/basin split was more difficult to model in the western Bering Sea. The 

total area of the Bering Sea in the Russian EEZ is dominated by the Bering Sea Basin: the 

western Bering Sea shelf is narrow and covers less than 10% of the total western area 

(Fig. 1; Table 1). Moreover, the cyclonic circulation of the main basin contributes 

strongly to the Kamchatka Current south of Cape Navarin (Stabeno et al. 1999). 

South of Cape Navarin, the shelf (0-200 m) varies from less than 5 km to 50 km 

in width, but in general this whole shelf area is closer to shore than the inshore border of 

the EBS study area (Fig. 1). While temperature and salinity may divide this part of this 

4 
narrow shelf into coastal, transitional and oceanic waters, the divisions are not stationary 

and may vary interannually with the strength and east/west position of the Kamchatka 

Current (Khen 1999). North of Cape Navarin, the shallow (50-100 m) Anadyr Basin and 

the most northern Chirikov Basin are northward extensions of the EBS shelf. 

The western main basin is divided into two sub-basins by the Shirshov Ridge: the 

Commander Basin, adjacent to the Commander Islands, Kamchatka Peninsula, and 

Shirshov Ridge; and the Aleutian Basin, north-eastward from the Shirshov Ridge, 

bordered by the Aleutian Arc on the south, and by the wide eastern Bering Sea shelf on 

the east. The area of the Aleutian basin included in the initial WBS model and listed in 

Table 1 is bounded by the EEZ boundary rather than by a natural boundary (Fig. 1). 

Table1. Surface area (thousands of km2

) of distinct biogeographical subareas included in the modeled 

regions. 

Eastern Bering Sea (EBS) Model subregions Area 

Inner Domain (20 km offshore-50 m depth 118.9 

Middle Domain (50-100 m depth) 211.1 

Outer Domain (100-200 m) 133.4 

Slope 21.1 

Total 484.5 

Western Bering Sea (WBS) Model subregions Area 

Shelf and slope model only 

The north-western Chirikov Basin 23.5 

The Anadyr Basin 145.0 

The western Bering Sea shelf area southward from Cape Navarin 55.0 

The western Bering Sea continental slope area 30.7 

Total shelf and slope area 254.2 

Additional area in shelf, slope and basin model 

The Commander Basin 226.0 

The north-western Aleutian Basin 222.0 

Total shelf, slope, and basin area 702.2 

Because the WBS shelf is much narrower than the EBS shelf, a greater relative 

proportion of shelf species might have significant inputs from basin food sources. 

Further, Russian stock assessments consider many major fish species to be single stocks 

throughout their EEZ. To reflect this, the initial WBS model was a combined shelf/basin 

model, bounded by the shore and the Russian EEZ boundary. This model, including a 

WBS literature review of both shelf and basin species, is presented in Appendix A. 

However, for the purposes of comparison with the EBS model, it was decided that 

the most meaningful initial comparison would result from restricting the WBS model to 

the shelf and slope, including shelf areas both north and south of Cape Navarin (Fig. 1; 

Table 1). The procedure used for restricting the WBS model in this manner is discussed 

below. The resulting WBS shelf/slope model was compared with the EBS shelf/slope 

model as described in the Results section. It is recognized that this large-scale averaging 

across shelf zones in the EBS and the shelf/basin split in the WBS may have introduced 

inaccuracies in the data which should be more thoroughly explored. Further, possible 

5 
stock migrations between regions, especially across the northern shelf boundaries which 

are nearly contiguous between the two modeled regions, are not explored. An important 

step in future modeling should be to create refined subregional models for each distinct 

biogeographic area. 

Data sources, time period, and model units 

The mass-balance model of the southeastern Bering Sea shelf and slope for the 

years 1979-85, including a substantial literature review of available data sources, is 

provided in Trites et al. (1999). The most detailed version of that model, with 40 

functional groups (Appendix 3 in Trites et al. 1999) formed the basis of both the EBS and 

WBS models presented here. The literature reviewed in Appendix 2 of Trites et al. 

(1999) was not substantially updated and thus continues to serve as the primary reference 

for the EBS model. 

A WBS literature review, not previously available in English, is presented in 

Appendix A. One of the main information sources was a regular series of reprint 

documents “Description of stocks’ condition of the major species and groups in the Far 

Eastern seas in (past year) and possible catches prediction in (next year).” This series 

(TINRO 1986-91, 1993, 1997-98) presents collective papers for all commercial fishery 

objects on the Russian Far East (analogous to NMFS documents “Stock assessment with 

yield consideration for year ...”). It is published by TINRO annually and has limited 

distribution through Russian fisheries agencies. Some western Bering Sea ecosystem 

information was taken from the preliminary report presented by Radchenko et al. (1991) 

at the PICES Workshop in December of 1991. All other literature sources are listed in 

Appendix A. 

The time period 1979-85 was used as the “base” model in Trites et al. (1999). 

This time period represents the ecosystem immediately following the great increase of 

walleye pollock biomass in the EBS, and this time period was chosen in Trites et al. 

(1999) in order to compare the 1980s EBS with limited data available from the 1950s, 

and thus capture some of the ecosystem changes resulting from this shift in dominant fish 

biomass over 30 years. For building the WBS model, this time period was extended 

slightly up to 1990 to increase the pool of available data. For the WBS, all existing data 

were averaged from 1981 to 1990 inclusively, when it was possible. If data from all 

years were not accessible, data from available years from that decade were used. Data 

from before 1980 and after 1990 were used for comparisons and model parameter 

verification. 

The unit of biomass used in the model was wet weight/ocean surface area (listed 

as metric tons per square kilometer, t/km2

). All results in this model are compared on a 

per-unit-area (km2) basis, to emphasize the characteristics of energy flows through each 

system. It is important to note in the following comparisons that WBS shelf model 

covers 254,000 km2

, while the EBS shelf model covers 485,000 km2 (Table 1). 

Therefore, if two fish stocks have the same density (or fishing pressure) per-unit area in 

each system, the total biomass (or catch) in the EBS region would be nearly twice that of 

the WBS region. While the per-area comparison stresses the role of competitors, it is 

important to remember this difference in total areas, especially when considering the 

relative magnitudes of fishing with respect to overall stock size. 

6 
Data were averaged over an entire year to remove seasonal effects. For many 

parameters, especially diet, winter estimates were unavailable, and summer estimates 

(May-September) were weighted by assumptions of extremely low production and/or 

biomass during winter months. 

Functional groups 

The Trites et al. (1999) EBS model began with the examination of over 50 

functional groups and was subsequently narrowed to 24 groups, although detailed 

information was preserved for many of the initial species groups (Trites et al. 1999, 

Appendix 2). The selection of species groups was based on taxonomic and functional 

identity, and emphasized diversity in the assessed fish groups while greatly aggregating 

lower trophic levels (phytoplankton and zooplankton), and the upper trophic level nonfish species (marine mammals and seabirds). 

For consistency, the WBS model began with a list of functional groups identical 

to that of the EBS model. However, this list was modified and adapted during the 

literature review process in several ways: large zooplankton categories were subdivided 

into many types; a few species of lesser importance in the WBS were dropped; and a 

protozoan group was added as a detrital recycling stage. In both models, the detrital flow 

was split into benthic and pelagic components. 

After the literature review and initial balancing, several of the groups were 

combined again based on similarity of habitat, dietary niche, or lack of data. The final 

models contained 38 functional groups in the EBS and 36 groups in the WBS. The only 

groups in the EBS model missing in the WBS model due to low biomass were sablefish 

(Anoplopoma fimbria) and rockfish (Sebastes spp., which were combined with sculpins, 

Family Cottidae). The full, final list, along with all input parameters is found in 

Appendix B. 

The two functional groups for which aggregation remained a serious problem 

were forage fish (“other pelagic fish”) and cephalopods. Each of these functional 

definitions combines pelagic and deepwater species into a single functional group, due to 

lack of data. In the diet analysis of larger fish and mammals, pelagic forage fish other 

than walleye pollock were lumped in with deepwater forage fish, primarily the extremely 

important lanternfishes (Myctophidae). This resulted in predictions of some spurious 

competitive interactions between shallow water nearshore marine mammals and 

deepwater slope fish for the “other pelagic fish” group. This same problem is seen to a 

lesser extent in the combining of the pelagic and benthic cephalopods. 

Balancing the Models and Preparations for Comparative Studies 

The steps for creating and balancing the EBS model are found in Trites et al. 

(1999). The initial stages of building the initial 50+ functional group combined 

basin/shelf/slope WBS model included many iterations of examination and data 

refinement on the part of the Russian colleagues; the details of this process are found in 

Appendix A. Many of the issues surrounding the balancing of the WBS model arose out 

of attempts to correctly apportion both diet proportions and overall biomass between 

basin and shelf/slope processes. 

7 
For most functional groups, the preferred mass-balancing technique was to 

calculate Ecotrophic Efficiency (EE) from the other provided input parameters. 

However, for a few functional groups, biomass estimates were not available and thus EE 

was set to a constant in order to estimate the biomass of these groups required to supply 

calculated predator demand. This was done for the same two prey groups in both the 

EBS and WBS models: “other” forage fish and shrimp. 

Some groups of prey species were aggregated if the majority of predator diet 

information did not distinguish between them, or the separate species filled almost 

identical ecosystem roles. The four groups created through aggregation were large 

zooplankton, infauna, epifauna, and small flatfish. Their component species and 

biomasses are listed in Table 5. This aggregation solved some of the mass-balance 

discrepancies (EE > 1.0) as it removed the models’ reliance on detailed diet composition 

where the information was missing. This aggregation simplified the food web structure 

of the lower trophic levels into a few primary flows and, as a side effect, created a degree 

of “cannibalism” within the epifauna and large zooplankton groups. While further 

specification of these groups would be helpful, it is probably not possible with the data 

currently available on the component species or their predators. 

To restrict the WBS model to shelf-only processes, the Russian researchers 

provided, in addition to the total biomass estimates for shelf/slope/basin areas combined, 

an estimated apportionment of the residence time or relative concentration of biomass 

and/or production between basin and shelf/slope for each functional group (Appendix 

Tables C1 and C2). Diet compositions in the shelf-only WBS model were initially left 

unadjusted due to the limitations of the data. However, this created a few imbalances 

which were fixed by lowering the occurrence of some primarily basin species in 

predators’ diets. No adjustments in diets of greater than 5% were made to achieve this 

balancing. Fisheries catch was apportioned between the basin and shelf/slope areas in 

proportion to the relative biomass in each region. This apportionment may have 

underestimated the extra fishing mortality on nearshore species. 

The final adjustments required to compare the EBS and WBS models involved the 

accounting of detritus and heat dissipation in the system overall. For estimating summary 

ecosystem statistics such as community respiration and biomass supported per unit 

production, it was important that the use of differing methodologies did not bias the 

results. Initially, the WBS model included protozoa as part of the microbial loop, which 

were not included in the EBS model. 

Little Bering Sea data exists on the apportioning of animal waste between 

respirative heat and detritus: of biomass lost during the consumption process, the 

proportion that was considered unassimilated energy (entering detritus) was set to 0.2 for 

all functional groups with the exception of infaunal, epifaunal, and benthic amphipod 

groups which were set to 0.4 due to the relative indigestibility of these species. The 

remainder of the lost biomass was considered to be burned as respirative heat. 

Additionally, all “other” mortality in the model [(1-EE) · Production] was considered to 

flow into detritus. 

Detritus was considered to be particulate organic matter (POM) only: the role of 

dissolved organic matter (DOM) nutrients such as ammonia was not considered in the 

8 
Ecopath models. Rather, phytoplankton production was considered to be wholly 

modeled by its measured production rate, assuming sufficient DOM for this growth. 

Pelagic POM may reenter the food web in several ways: it can be eaten directly as 

pelagic detritus; sink and be eaten as benthic detritus, or it can be “reprocessed” by 

microzooplankton, protozoa and bacteria. Data on the actual flow rates of each of these 

pathways may vary substantially from region to region. For these basic models, it was 

decided to remove the microbial loop from the accounting process. Part of the reason for 

this decision was to ensure that the calculation of trophic levels was consistent with 

previous studies. Including a substantial microbial loop has the effect of raising the 

estimations of trophic level in an ecosystem, leading to higher estimations of the trophic 

level of fisheries and community respiration. 

Therefore, POM (detritus) was considered to flow from living species into 

a single detrital box, and thereafter be partitioned into benthic and pelagic detritus. While 

microbial processes would occur along this pathway, these processes were not considered 

to raise the trophic level of the detritus before it was consumed by macrofauna. The 

relative flow of detritus to pelagic and benthic components was set by top-down demand 

of each detritus type’s predators. In the future, the detrital calculations in these models 

could benefit from the inclusion of results of more detailed lower trophic-level (nutrientphytoplankton-zooplankton) process models. 

9 
RESULTS AND DISCUSSION

Outline 

With the exception of the minor balancing adjustments discussed above, the 

results shown here are based on the independently assessed biomass, production, 

consumption and diets of individual species groups in the eastern and western Bering Sea 

models. Differences between the two system models may represent actual ecosystem 

differences or differences in methodologies used to estimate parameters from the data. 

Results are summarized either by model compartment (functional group), larger 

functional collections of groups, or trophic level or whole ecosystem. Summaries by 

model compartment may represent a taxonomic level between individual species on the 

upper trophic levels to large aggregations of species on the lower trophic levels. The 

preliminary notion of larger functional collections is both ecological and fisheries-based; 

for example, “groundfish” are considered as a single category in the initial analysis. This 

notion is refined based on predator and prey niches discussed in the Food Web Network 

Structure section. 

Trophic level has two distinct but related definitions depending on whether one is 

speaking of the flows through compartments or the biomass of compartments. First, the 

trophic level of energy flow through a compartment is a weighted average of the path 

lengths (number of compartments) through which energy needed to pass to reach the 

compartment, using phytoplankton and detritus as the first flow level. In this report, 

‘flow’ trophic level is referred to as “Pathway Level” and represented with Roman 

numerals (I-VII+) following Christensen and Pauly 1995. 

The “traditional” trophic level of each functional group, hereafter referred to as 

“Trophic Level,” is 1.0 plus the average of a group’s preys’ trophic levels. It may be 

computed directly from an input diet matrix, or a weighted average of pathway levels. 

The trophic level of a compartment may be fractional and is reported with Arabic 

numerals (1.0-5.0+) including a decimal placeholder for clarity. Note that a compartment 

with a Trophic Level of (for example) 4.0 may contribute to Pathway Levels of VIII and 

above, if complicated interconnections increase the number of steps that energy takes 

through a web. 

Overall Biomass and Flow Between Trophic Levels 

On a per-unit-area basis, the estimate of total biomass (excluding detritus) in the 

WBS (568 t/km2

) was 2.3 times higher than in the EBS (240 t/km2; Table 2). The total 

production requirements from Pathway Level I (phytoplankton and detritus) to support all 

consumers were similarly scaled between the two systems, with 6,031 t/km2

/year 

required in the WBS and 2,566 t/km2

 required in the EBS. The amount of production as 

a proportion of supported biomass was similar for the two systems: 10.7 in the EBS and 

10.6 in the WBS. 

However, the proportion of Pathway Level I production required from each of 

phytoplankton, benthic detritus and pelagic detritus differed between the two systems 

(Table 2). In the EBS, 57% of the production requirements were satisfied by 

10 
phytoplankton production versus 43% in the WBS. Pelagic detrital requirements were 

similar between the two systems at 18% and 20% for the EBS and WBS respectively, 

while benthic detritus made up a lesser proportion of the EBS food requirements (24%) 

than in the WBS (37%). 

Table 2. Total biomass and primary production rates (phytoplankton + recycling) per unit area in the EBS 

and WBS models. 

EBS WBS Units 

Total Biomass (excluding detritus) 240 568 t/km2 

Trophic Pathway Level I (Consumed) Production 

Phytoplankton 1,468 (57.2%) 2,591 (43.0%) 

Pelagic Detritus 474 (18.5%) 1,225 (20.3%) 

Benthic Detritus 624 (24.3%) 2,214 (36.7%) 

Total TL 1 Production 2,566 6,031 t/km2/year 

P(TL 1)/B(total) 10.7 10.6 1/year 

The throughput of each pathway level is defined as the pathway’s yearly input 

plus output, or in a steady state, double the pathway level’s production less production 

consumed within the pathway level. The throughput is consistently higher by a factor of 

two in the WBS for all levels between Pathway Levels I and VII (Table 3). The excess 

biomass, however, is not evenly spread: in the WBS, most of this excess occurs on 

Pathway Level II (Table 3; Fig. 2a). The biomass of Pathway Levels IV-V are similar or 

higher in the EBS (Fig. 2b). Further, the amount of throughput per unit biomass shows 

that, on all pathway levels except Pathway Level II, the EBS uses less throughput for 

each unit of supported biomass (Table 3). 

Table 3. Throughput (t/km2

/year), biomass (t/km2), throughput/biomass (1/Year) and transfer efficiency 

(percentage) by pathway (trophic) level in the EBS and WBS models. 

Path Throughput Biomass Through. /Bio. Transfer Eff. 

Level EBS WBS EBS WBS EBS WBS EBS WBS 

VII 0.003 0.017 0.001 0.003 3.0 5.7 0.0% 0.0% 

VI 0.20 0.57 0.05 0.11 3.9 5.1 2.5% 4.2% 

V 5.4 10.3 1.5 1.8 3.7 5.6 5.0% 6.4% 

IV 62 111 18 17 3.5 6.7 10.0% 9.6% 

III 466 1,151 66 111 7.1 10.4 13.6% 9.7% 

II 2,566 6,031 144 424 17.9 14.2 18.1% 19.1% 

I 4,904 10,442 12 15 416.8 696.1 84.6% 86.8% 

Transfer efficiencies (percentage of energy passed through each trophic level 

without being lost to heat or detritus) show a similar decreasing pattern in the two 

systems from near 20% on Pathway Level II to 2-4% on Pathway Level VI. The transfer 

efficiency near 85% of Pathway Level I is due to an accounting definition: the respirative 

assimilation of nutrients by phytoplankton, which creates considerable heat loss, is not 

directly modeled in Ecopath. Excluding Pathway Level I, a weighted (geometric) 

11 
�������� ���������

���������

���������

����

average of transfer efficiency gives a result of 13.5% flow passed up per level for the 

EBS and 12.1% per level in the WBS. 

�������� ���������

���������

��������� ��������� ���������

���� EBSh 

(A) WBSh

500 

400 

WB

S/E

B

S B Bi

o

mass 

300 

200 

100 

0 

I II III IV V VI 

10 

1 

(B) 

0.1 

I II III IV V VI 

Pathway Level 

Figure 2. (A) Biomass as a function of pathway level in the EBS and WBS shelves. (B) WBS/EBS 

biomass by pathway level on a log scale: values above 1 indicate higher values in the WBS. 

Biomass and Trophic Level of Individual Compartments 

Biomass and biomass estimates for individual compartments may fluctuate 

greatly from year to year: however, using the long-term averages highlights some 

fundamental differences between the two systems during the 1980s. For the purposes of 

this discussion, differences of per-unit-area biomass more than 100% and differences of 

trophic level of more than 5% between the two systems are considered “worth noting”: 

these cutoffs are arbitrary. 

The yearly average standing stock of phytoplankton biomass does not differ 

greatly between the EBS (11.8 t/km2

) and the WBS (15.0 t/km2). However, estimates of 

pelagic zooplankton—copepods and large zooplankton—are 2-3 times higher in the WBS 

than in the EBS (Table 4; Fig. 3). A closer examination of the “large zooplankton” 

functional group shows that this abundance of large zooplankton is not due to a higher 

euphausiid biomass in the WBS: euphausiid biomasses are comparable between the two 

systems (35 t/km2 in the EBS and 38 t/km2 in the WBS). Rather, the high biomasses are 

attributable to chaetognaths, pelagic amphipods, and gelatinous zooplankton, each of 

which have estimated biomasses 5-10 times higher in the WBS (Table 5a). 

The overall biomass of pelagic forage species is comparable between the two 

systems, with a total of 24 t/km2 in the EBS and 30 t/km2 in the WBS. The largest 

proportion of this biomass is attributable to miscellaneous (“other”) pelagic fish. Further, 

this group includes small pelagic and mesopelagic fish and thus captures at least two 

distinct types of forage fish. No biomass estimates were available for these species in 

12 
either system, and so the biomass levels indicated are the minimum requirement to satisfy 

the measured demands of predators in the system—the actual biomass of forage fish 

could be considerably higher in both systems. 

Table 4. Biomass (t/km2

) and trophic level of all boxes in the EBS and WBS models. Shaded trophic 

levels are higher in indicated system by more than 5%. Differences in biomass are also shown in Figure 3. 

Groups in bold italics are aggregated from original models. 

Trophic Level Biomass 

EBS WBS EBS WBS 

Lower trophic level Phytoplankton 1.0 1.0 11.77 15.00 

pelagic species Copepods 2.0 2.1 55.00 122.62 

Large zooplankton 2.3 2.6 44.00 120.74 

Pelagic forage species Juv. pollock age 0-1 3.1 3.4 6.00 3.76 

Pacific herring 3.2 3.3 0.78 0.79 

Other Pelagic Fish 3.2 3.4 (*)13.46 (*)19.08 

Cephalopods 3.8 3.7 3.50 4.83 

Salmon 3.5 3.7 0.05 0.04 

Jellyfish 3.3 3.1 0.05 1.40 

Lower trophic level Epifauna 2.4 2.2 5.86 114.96 

benthic species Infauna 2.0 2.0 46.50 125.69 

Benthic Amph. 2.0 2.0 3.62 13.81 

Benthic particulate Tanner crab 3.0 3.0 0.60 0.08 

species Snow crab 3.0 3.0 1.60 0.25 

King crab 3.0 3.0 0.60 0.12 

Shrimp 2.5 2.4 (*)3.00 (*)2.10 

Groundfish species Adult pollock age 2+ 

Pacific cod 

Pacific halibut 

Greenland turbot 

Arrowtooth flounder 

Small flatfish 

Skates 

Sculpins 

Sablefish 

Rockfish 

Macrouridae 4.1 3.9 0.20 1.16 

Zoarcidae 3.1 4.1 0.64 0.90 

Bird and marine Baleen whales 3.6 3.8 0.25 0.39 

mammal species Toothed whales 4.3 4.6 0.02 0.04 

3.3 3.4 27.45 15.00 

4.0 4.0 2.42 3.19 

4.1 4.6 

4.5 

4.3 

0.14 0.08 

4.1 0.96 0.06 

3.9 0.80 0.05 

3.1 3.2 9.18 0.99 

4.1 4.4 0.29 0.27 

3.9 3.8 0.56 (**)0.68 

4.2 - 0.11 -

3.6 (**) 0.09 (**) 

Sperm whales 4.7 4.7 0.21 0.02 

Walrus and bearded seals 3.5 3.2 

3.9 4.5 

0.16 0.26 

Other seals 0.06 0.10

Steller sea lions 4.3 4.5 0.01 0.04 

Seabirds 4.0 4.0 0.01 0.01 

(*) Biomass set by "top-down" demand. 

(**) rockfish are included with sculpins in the WBS. 

- no biomass assessed (minimal) 

13 
100 

W

BS/EBS Biomass 

Phytoplankton

10 

Copepods 

Large zooplankton 

1 

Juv. Pollock age 0-1 

Pacific herring 

Oth. Pelagic Fish

0.1 

Cephalopods 

Salmon 

0.01 

Jellyfish 

Epifauna 

Infauna

* 

Benthic Amph. 

Tanner crab 

* 

Snow crab

King crab

Shrimp

Adult pollock age 2+

Figure 3. WBS/EBS biomass density (t/km2

), log scale. A black bar indicates a higher value in the WBS 

Pacific cod

(WBS/EBS value greater than 1.0); a white bar indicates a higher value in the EBS (WBS/EBS value less 

Pacific halibut

than 1.0). (*)species biomass set by top-down balance (demand). 

Greenland turbot 

Arrowtooth flounder

The estimates of infaunal biomass are higher in the WBS (126 t/km2 vs. 47 t/km2 

Small flatfish

in the EBS), while the epifaunal biomass is almost 20 times higher in the WBS (115 Skates

t/km2

 vs. 6 t/km2 in the EBS) A breakdown of these groups shown in Table 5c-d Sculp. & Rock.

indicates that while all of these benthic species groups had a higher biomass in the WBS, 

Macrouridae 

the large majority of the WBS epifaunal biomass was due to a high estimated biomass 

Zoarcidae 

(96 t/km2

) of sea urchin populations. 

Baleen whales 

Toothed whales

On the other hand, the biomass of higher trophic-level benthic species is greater in 

Sper

m whales

the EBS. Tanner crab (Chionoecetes bairdi), snow crab (C. opilio) and king crabs 

Walrus & Brd. Seals 

(Paralithodes spp.) have biomass levels 2-6 times higher in the EBS. There were no Seals 

estimates for shrimp biomass in either system, so again these biomass levels were set by 

Steller sea lions 

Seabirds

top-down demand and the estimates are similar between the ecosystems. The biomass 

estimates of flatfish species—Greenland turbot (Reinhardtius hippoglossoides), 

Arrowtooth flounder (Atheresthes stomias) and Pacific halibut (Hippoglossus stenolepis), 

and especially the small flatfish community as a whole—was considerably higher in the 

EBS (Tables 4 and 5b). 

In both systems, the fish species with the largest biomass was walleye pollock, 

which due to the importance of cannibalism, was divided into juvenile and adult (age 2+) 

groups. Pollock have an age 2+ biomass of 27 t/km2

 in the EBS and 15 t/km2 in the 

WBS. 

Groundfish species other than flatfish showed similar per-area biomass levels 

between the two systems (Table 4; Fig. 3). Toothed whales and Steller sea lions 

(Eumetopias jubatus) have a higher biomass in the WBS, while estimates of sperm whale 

(Physeter macrocephalus) presence is higher in the EBS. The biomass estimates of other 

marine mammals and seabirds are comparable between the two systems. However, many 

14 
of the marine mammal estimates are based on Bering Sea or North Pacific-wide estimates 

of biomass weighted by residence time in each region: these residence time calculations 

are other potentially large sources of error. 

Table 5. Breakdown of biomass (t/km2

) of individual groups within post-balance aggregated groups in 

EBS and WBS models. (A) Large Zooplankton; (B) Small Flatfish; (C) Infauna; (D); Epifauna. 

(A) Large Zooplankton EBS WBS 

Pelagic amphipods 2.0 19.0 

Gelatinous plankton 2.0 13.6 

Euphausiids 35.0 38.0 

Mysiids 3.0 1.4 

Chaetognaths 6.0 (*)48.8 

Total 48.0 120.7 

(C) Infauna EBS WBS 

Clams 29.5 80.3 

Polychaetes 14.0 38.3 

Other worms 3.0 7.1 

Total 46.5 125.7 

(*)Lowered to 44 to achieve balance. 

(B) Small Flatfish EBS WBS 

Flathead sole 0.5 0.2 

Yellowfin sole 6.1 0.2 

Rock sole 1.3 0.2 

Alaska plaice 1.3 0.2 

Other small flatfishes(**) - 0.1 

Total 9.2 1.0 

(D) Epifauna EBS WBS 

Hermits & other decapods 1.0 2.1 

Snail 0.5 1.2 

Brittlestar 3.0 14.5 

Starfish 1.3 1.0 

Other benthos(**) - 96.2 

Total 5.9 115.0 

(**)See Appendix A for WBS “other species” groups not included in the EBS model. 

The trophic level (TL) of each species (Table 4) is determined entirely by the 

input diet matrix (Appendix Tables B4-B6). Since bacterial and micro-zooplankton 

processes have been removed from both models, phytoplankton and detrital biomass have 

a trophic level of 1.0 in both models, and copepods have a trophic level near 2.0. In the 

WBS model, cannibalism in copepods (5% of their diet) raises their trophic level with 

respect to the EBS, where cannibalism is not included in these species. 

The large zooplankton group consumes a mix of phytoplankton, detritus, and 

copepods in both models. The diet of large zooplankton in the WBS is considerably 

higher in copepods (48% vs. 25%) and correspondingly lower in phytoplankton and 

detritus. The higher proportion of copepods in large zooplankton diets and the existence 

of cannibalism in the WBS large zooplankton group is probably due to the considerably 

higher measured biomass of chaetognaths versus euphausiids in that model (Table 5). As 

large zooplankton are a major link in both pelagic food webs, their higher trophic level 

has the effect of increasing the modeled trophic level of many fish species in the WBS. 

Differential zooplankton apportionment does not explain all of the differences in 

fish trophic levels, however. The high trophic level of Zoarcidae (eelpouts) in the WBS, 

the only group with a difference of more than 0.5 of a trophic level, is due to a 

fundamental difference in the input diet data between the models: the EBS diet matrix 

shows them as primarily benthic feeders on infauna, while the WBS model places them 

as feeders on forage fish, cephalopods, and pollock. It is not known if this is an 

ecological or methodological difference. 

15 
In the benthic web, trophic levels of the EBS and WBS groups are similar, with 

infauna and amphipods (TL 2.0) feeding on benthic detritus (TL 1.0); while epifauna and 

shrimp feed on a combination of infauna and detritus. Crabs feed on these groups in 

similar proportions in the two systems. Walrus and bearded seals show a higher trophic 

level in the EBS due to a weighting of their diet towards benthic particulate feeders 

(crabs; TL 3.0) instead of infauna and epifauna in the WBS (TL 2-2.5). 

Production and Consumption of Individual Compartments 

Production-per-unit-biomass (P/B) and Consumption-per-unit-biomass (Q/B) 

represent a combination of the population age structure and the life-history characteristics 

for each functional group. These life-history traits are expected to vary less over time 

than biomass—in this study, differences are noted between systems if these quantities 

differ by more than 50%. It should be noted that, due to a lack of data, many of these 

quantities were shared between the two systems and thus do not represent independent 

estimates. The full list of values used for these parameters is found in Appendix Tables 

B1-3. 

10 

1 

0.1 

Figure 4. WBS/EBS production to biomass (P/B) ratio (1/year), log scale. A black bar indicates a higher 

value in the WBS (WBS/EBS value greater than 1.0); a white bar indicates a higher value in the EBS 

(WBS/EBS value less than 1.0). 

The difference between WBS and EBS P/B estimates for each system are shown 

in Figure 4. Generally, the two systems have very similar values, reflecting the 

derivation of P/B from similar estimates of mortality in both systems. Only a few species 

differ in P/B by more than 50% between the two systems. 

Estimates of Q/B, on the other hand, were more variable between the two systems 

(Fig. 5). The estimates of consumption rates for most fish species were 1.5-5 times 

higher in the WBS. However, at the same time, as mentioned above, P/B estimates were 

similar between the two systems. S/ . 

Phytoplankton 

Pacific herring 

Copepods 

Large zooplankton 

Juv. Pollock age 0-1 

Oth. Pelagic Fish 

Jellyfish 

Cephalopods 

Salmon 

Epifauna 

Infauna 

Benthic A

mph. 

Tanner crab 

Snow crab 

King crab 

Shrimp 

Adult pollock age 2+ 

Pacific cod 

Pacific halibut 

Greenland turbot 

Arrowtooth flounder 

Small flatfish 

Skates 

Sculp. & Rock. 

Macrouridae 

Zoarcidae 

Baleen whales 

Toothed whales 

Sper

m whales 

Walrus & Brd. Seals 

Seals 

Steller sea lions 

Seabirds 

16 
Taking P/B and Q/B estimates together, it is evident that a larger amount of 

respirative dissipation takes place in the WBS model, where respirative loss is defined in 

this case as the difference between the consumption and production of a species box (and 

includes material “unassimilated” during feeding). The relative apportionment of 

dissipative energy flow within the food webs into metabolic costs (respiration, including 

reproductive costs), unassimilated food, “other” mortality (disease, etc.), and bacterial 

recycling are difficult to compare between the two systems, as “other” mortality, 

calculated from the Ecotrophic Efficiency (EE) values in the models, represents aspects 

of the “balancing” terms in the population level mass-balance. At this juncture, it is not 

possible to accurately partition food web dissipation between detrital flows, recycled 

(bacterial) nutrients, and heat loss, therefore, further results on respirative flow are not 

presented here. 

W

B

S/EB

S Cons./Bio. 

Phytoplankton 

1 

1 

Figure 5. WBS/EBS consumption to biomass (Q/B) ratio (1/year), log scale. A black bar indicates a 

higher value in the WBS (WBS/EBS value greater than 1.0); a white bar indicates a higher value in the 

EBS (WBS/EBS value less than 1.0). 

Primary Production Required 

Regardless of the causes of energy dissipation, the effects of the overall 

dissipation may be compared. To compare the differences in compartment transfer 

efficiency of the two systems, the statistic PPR, or Primary Production (+Detritus) 

Required, was calculated for each compartment. The PPR statistic captures the overall 

transfer efficiency of each food web without differentiating between energy lost through 

respiration versus “other” (EE-calculated) mortality. 

For each compartment, the PPR value is the amount of Pathway Level I 

production required to support the biomass of that compartment, and in an iterative 

fashion to support its prey, and its prey’s prey, and so on. It thus reveals the effect that 

overestimating a prey’s energy consumption will have on the demand estimates of 

predators above it. The PPR value for all of the compartments in the system will sum to Large zooplankton 

Juv. Pollock age 0-1 

Pacific herring 

Oth. Pelagic Fish 

Salmon 

Jellyfish 

Copepods 

Cephalopods 

Epifauna 

Infauna 

Benthic Amph. 

Tanner crab 

Snow crab 

King crab 

Shrimp 

Pacific cod 

Small flatfish 

Macrouridae 

Adult pollock age 2+ 

Pacific halibut 

Greenland turbot 

Arro

wtooth flounder 

Skates 

Sculp. & Rock. 

Zoarcidae 

Baleen whales 

Toothed whales 

Sperm whales 

Walrus & Brd. Seals 

Seals 

Steller sea lions 

Seabirds 

17 
greater than the actual Pathway Level I production, as the “required” energy is counted 

for a prey species itself and for all of its predators. 

The per-group PPR values are shown in Figure 6, sorted in decreasing order. In 

both systems, the standing stocks of copepods and large zooplankton require the most 

primary production, followed by the species with highest biomass in the two systems: 

adult pollock, cephalopods, forage fish, infauna, and Pacific cod in the EBS; and 

epifauna, infauna, Pacific cod, and pollock in the WBS. 

As might be expected from higher standing stock per-unit-area in the WBS (Fig. 

2), the primary production required to support small and large plankton in the WBS is 

about double that in the EBS. However, the primary production required to support 

Pacific cod and pollock in the WBS is also about twice as high, despite the lower 

standing stock of these species: this is likely attributable to the higher 

consumption/biomass estimates used for these species in these models. 

1800 

(A) 1600 

1400 

1200 

1000 

800 

600 

400 

200 

0 

L. zooplankton 

Copepods 

Adult pollock 

Cephalopods 

Forage fish 

Infauna 

P.cod 

Small flatfish 

Juv. pollock 

Toothed whales 

Shrimp 

Seals 

Sculpins 

Epifauna 

Walrus& B.seals 

Sperm Whales 

Arrowtooth fl. 

Greenland turb. 

Skates 

Snow crab 

Benthic amph. 

Baleen whales 

P.halibut 

Seabirds 

Sablefish 

King crab 

Tanner crab 

P.herring 

Macrouridae 

Zoarcidae 

Rockfish 

Steller s.lions 

P.salmon 

Jellyfish 

3500 

3000 (B)

WBS PPR WBS PPR 2500 

2000 

1500 

1000 

500 

0 

Copepods 

L. zooplankton 

Epifauna 

Infauna 

P.cod 

Adult pollock 

Toothed whales 

Cephalopods 

Forage fish 

Juv. pollock 

Sculpins 

Seals 

Baleen whales 

Walrus& B.seals 

Small flatfish 

Benthic amph. 

Skates 

Macrouridae 

Shrimp 

Steller s.lions 

P.herring 

Zoarcidae 

P.halibut 

Seabirds 

Snow crab 

Greenland turb. 

Arrowtooth fl. 

Jellyfish 

Sperm Whales 

Tanner crab 

King crab P.salmon 

Phytoplankton 

Figure 6. Primary production required (PPR) to support the standing stock of each indicated predator, 

taking into account the energy required to support the prey of each predator (t PPR/km2

/year), Species are 

shown in order of decreasing PPR in the (A) EBS; (B) WBS. 

This difference is more noticeable if the PPR values are normalized by the 

biomass in each compartment, resulting in a measurement of the primary production 

required to support a single unit of predator biomass (Fig. 7; units are primary production 

required(t)/predator(t)/km

2

/year). From Figure 7, it is evident that a single unit of biomass 

of most groundfish species requires 2-4 times more primary production in the WBS than 

in the EBS, indicating the modeling of a less efficient food web between primary 

production and groundfish in the WBS. 

18 
Finally, normalizing the PPR values per unit supported biomass by total 

ecosystem primary production (Fig. 8) shows that the EBS utilizes more of each unit of 

primary production in supporting many of its functional groups. The implication here is 

that the EBS is a more efficient system in terms of the primary production required to 

support a unit of biomass. Overall, the standing stocks in the EBS utilize a larger 

Copepods Copepods

percentage of their primary production than those in the WBS. 

Large zooplankton Large zooplankton 

Juv. Pollock age 0-1 Juv. Pollock age 0-1

10 

Pacific herring Pacific herring 

Oth. Pelagic Fish Oth. Pelagic Fish 

Cephalopods Cephalopods 

Salmon Salmon 

Jellyfish Jellyfish

1 

Epifauna Epifauna 

Infauna Infauna 

Benthic Amph. Benthic Amph. 

Tanner crab Tanner crab 

Snow crab Snow crab

0.1 

King crab King crab 

Shrimp Shrimp 

Adult pollock age 2+ Adult pollock age 2+ 

Pacific cod Pacific cod 

Pacific halibut Pacific halibut 

Greenland turbot Greenland turbot

Figure 7. Primary production required to support a unit biomass each indicated predator, taking into 

Arrowtooth flounder Arrowtooth flounder

account the energy required to support the prey of each predator (t PPR/t predator/year; WBS/EBS, log Small flatfish Small flatfish

scale). A black bar indicates a higher value in the WBS (WBS/EBS value greater than 1.0); a white bar Skates Skates

indicates a higher value in the EBS (WBS/EBS value less than 1.0).

Sculp. & Rock. Sculp. & Rock. 

Macrouridae Macrouridae

Since the estimates of lower trophic level production were balanced and in a few Zoarcidae Zoarcidae 

cases augmented to account for upper trophic level consumption (demand) estimates, it is

Baleen whales Baleen whales 

Toothed whales Toothed whales

worth asking if this pattern is an artifact of a few artificially high consumption rates for 

Sperm whales Sperm whales

predators in the WBS. Energy required to support a single unit of biomass should Walrus & Brd. Seals Walrus & Brd. Seals

increase logarithmically with trophic level, as each successive jump represents a 80-90% 

Seals Seals

loss to dissipation (Table 3).

Steller sea lions Steller sea lions 

Seabirds Seabirds 

1 

0.1 

WBS/EBS WBS/EBS 

PP Required/Biomass/Tot PP PP Required/Biomass 

Figure 8. Primary Production Required (PPR)/Total Ecosystem Primary Production (PP) to support a unit 

biomass each indicated predator, taking into account the energy required to support the prey of each 

predator (PPR/Tot PP/t predator; WBS/EBS, log scale). A black bar indicates a higher value in the WBS 

(WBS/EBS value above 1.0); a white bar indicates a higher value in the EBS (WBS/EBS value below 1.0). 

19 
Figure 9 shows an exponential regression of EBS and WBS PPR by trophic level. 

The regression is significant for both ecosystems (R2

 ~ 0.60 for both systems; P < 

0.0001) As shown in the figure, while the slopes of the two regressions do not differ 

significantly, the intercepts of the WBS and EBS regressions do (P < 0.05), with the EBS 

having a higher PPR/Total Primary Production/Predator at any given trophic level. 

The residuals of the outliers do not reveal any major biases as might be expected 

if a limited group of species were “driving” the results. The consistency of a higher 

proportion of utilized primary production in the EBS than in the WBS suggest an 

ecological rather than methodological effect, although it is possible that a systematic bias 

of all consumption rates throughout one ecosystem could lead to the same result. 

10 

PP

R/ Biomass / TotPP 

1 

0.1 

0.01 

WBS 

EBS 

Expon. (EBS) 

Expon. (WBS) 

0.001 

1 1.5 2 2.5 3 3.5 4 4.5 5 

Trophic Level 

Figure 9. Primary production required (PPR)/Total ecosystem primary production (PP) to support a unit 

biomass each indicated predator, taking into account the energy required to support the prey of each 

predator (PPR/Tot PP/t predator), shown as a function of predator trophic level in the EBS (open circles) 

and the WBS (closed diamonds) The regressions shown are both significant (P < 0.0001) with R2

 values 

near 0.60. 

Fishing, Predation, and Unexplained (“other”) Mortality 

Total biomass mortality (Z) for each species grouping can be broken down into 

fishing mortality (F), predation mortality (M2) and “unexplained” mortality (M0). This 

latter quantity is a “balancing” term required to make the total mortality Z for each box 

equal to total per-unit production (P/B). 

In gauging the relative impact of fishing, the value F/(M2+M0) is a useful 

preliminary index to use—in the simplest single-species fisheries models, an F/Mtotal of 

1.0 implies that a population is being fished at its maximum sustainable yield (MSY; 

Hilborn and Walters 1994). Estimates of discards are included in the catch estimations. 

The values for F/ Mtotal varied greatly between the two systems during the 

modeled time period (Table 6). In particular, many of the groundfish species in the WBS 

were more heavily exploited according to this measure in the WBS than in the EBS— 

relative fish exploitation rates in the EBS during the 1980s were comparatively low. The 

highest values for this index came from indigenous catch of marine mammals: even 

though they were exploited at a low total tonnage during the 1980s, this represented a 

substantial fraction of their mortality. In the EBS, Pacific salmon are the only other 

species showing high exploitation rates during that time period due to the inclusion of the 

20 
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������������

������������

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Bristol Bay salmon fishery. BS, only Greenland turbot had an exploitation rate 

for which F > Mtotal. 

����������� �����������

�����������

������������

������������

������������ ������������

������������ ������������

������������ 0 

0.5 

1 

1.5 

2 

2.5 

II III IV V VI VII

Pathway level 

��� EBS 

WBS 

Figure 10. Biomass (t/km2

/year) of fisheries catch by pathway level in the EBS and WBS. 

The total overall biomass taken was greater in the EBS on both an overall and a 

per-unit area basis (Table 6). fisheries took a proportion of total primary 

productivity six times larger than in the WBS, 0.12% versus 0.028%. 

came from Pathway Levels III and IV in both systems (Fig. 10), the average trophic level 

of the catch was 3.35 in the EBS and 3.58 in the WBS. ary Production Required 

(PPR) to support the total catch of all fisheries was 278 t/km2/year in the EBS and 520 

t/km2

/year in the WBS, placing the fisheries of the 1980s on a similar scale to dominant 

fish predators such as cod and pollock as shown in Figure 6. 

In the W

The EBS 

Most of this catch 

The Prim

Percent of Total Mortality Z 

Phytoplankton 

0% 

WBS M2 

WBS F 

WBS M0 

EBS M0 

EBS F 

EBS M2 

100% 

0% 

Copepods 

Large zooplankton 

Juv. Pollock age 0-1 

Pacific herring 

Oth. Pelagic Fish (*) 

Cephalopods 

Salmon 

Jellyfish 

Epifauna 

Infauna 

Benthic Amph. 

Tanner crab 

Snow crab 

King crab 

Shrimp (*) 

Adult pollock age 2+ 

Pacific cod 

Pacific halibut 

Greenland turbot 

Arrowtooth flounder 

Small flatfish 

Skates 

Sculpins (**) 

Macrouridae 

Zoarcidae 

Baleen whales 

Toothed whales 

Sperm whales 

Walrus & Brd. Seals 

Seals 

Steller sea lions 

Seabirds 

Figure 11. Apportionment of total mortality Z between predation (M2; black and white solid bars), fishing 

(F; black and white dotted bars) and unexplained (“other”) mortality (M0; grey background with white or 

black dots). The line in the center is 100% mortality from the bottom for EBS, and from the top for WBS. 

(*) M0 set at 10% of Z for top-down balance; (**) includes rockfish. 

The apportionment of total natural mortality between predation and unexplained 

mortality varied greatly between the two models when compared by individual 

21 
compartments (Fig. 11), but it was not significantly different in the models when 

averaged over all species. The average M2/Z was 0.50 (SD 0.35) and 0.47 (SD 0.32) for 

the EBS and WBS, respectively. The average M0/Z was 0.41 (SD 0.31) and 0.40 (SD 

0.32) for the EBS and WBS, respectively. 

Table 6. Catch (t/year and t/km2

/year), fishing mortality F, and F/Natural mortality Mtotal in the EBS and 

WBS, averaged for the years 1980-85. 

Catch Catch 

EBS tons T/km2 F F/Mtot WBS tons t/km2 F F/Mtot 

Walrus & B. 

seals 

4,400 0.009 0.057 20.68 Baleen whales 1,800 0.007 0.018 8.54 

P. salmon 46,000 0.094 1.808 3.05 Greenland turb. 2,500 0.010 0.172 6.25 

Seals 630 0.001 0.023 0.63 P. halibut 2,500 0.010 0.120 0.93 

Steller sea lions 49 0.000 0.013 0.26 Arrowtooth fl. 1,800 0.007 0.135 0.73 

Greenland turbot 37,000 0.077 0.080 0.25 Walrus & 1,500 0.006 0.023 0.62 

B. seals 

Skates 9,000 0.019 0.064 0.19 Skates 10,500 0.041 0.151 0.61 

P. cod 73,000 0.151 0.062 0.19 Seals 500 0.002 0.021 0.52 

Adult pollock 1,010,000 2.080 0.076 0.18 Sculpins 18,000 0.070 0.103 0.35 

King crab 20,000 0.042 0.070 0.13 Zoarcidae 9,900 0.039 0.043 0.17 

Sablefish 2,400 0.005 0.045 0.13 Small flatfish 10,500 0.041 0.041 0.17 

Small flatfish 158,000 0.326 0.036 0.10 Adult pollock 267,000 1.051 0.070 0.16 

Rockfish 1,500 0.003 0.033 0.09 P. cod 57,500 0.226 0.071 0.16 

Sculpins 8,200 0.017 0.031 0.08 Macrouridae 10,500 0.041 0.035 0.13 

Macrouridae 2,900 0.006 0.030 0.08 King crab 2,000 0.008 0.067 0.13 

P. herring 26,500 0.055 0.070 0.08 P. herring 14,000 0.055 0.070 0.11 

Arrowtooth fl. 9,900 0.021 0.026 0.07 P. salmon 3,000 0.012 0.308 0.08 

P. halibut 1,400 0.003 0.021 0.05 Snow crab 1,500 0.006 0.024 0.03 

Tanner crab 9,300 0.019 0.032 0.03 Cephalopods 5,100 0.020 0.004 <0.01 

Snow crab 23,500 0.049 0.030 0.03 Shrimp 500 0.002 0.001 <0.01 

Zoarcidae 2,900 0.006 0.009 0.02 Forage fish 250 0.001 5x10-5 <0.01 

Cephalopods 3,400 0.007 0.002 <0.01 Epifauna 1,000 0.004 4x10-5 <0.01 

Total 1,450,000 2.990 Total 421,000 1.659 

Total Catch/Prim. Prod. 0.1165% Total Catch/Prim. Prod. 0.0275% 

Average trophic level of fishery 3.35 Average trophic level of fishery 3.58 

Most lower trophic level pelagic species had high predation mortality rates, while 

predation rates on epifauna and infauna were low in both models (Fig. 11). Higher 

trophic level benthic particulate feeders (crabs and shrimps) saw a larger degree of 

predation pressure in the EBS than in the WBS. Groundfish predation varied from 

relatively high for sculpins, macrouridae and zoarcidae to low for most flatfish species. 

Naturally, very low relative predation pressure existed on the upper trophic levels of 

marine mammals and seabirds. 

22 
Food Web Network Structure 

Overall network characteristics 

The Eastern Bering Sea shelf model contains 320 described predator/prey (diet) 

links between distinct functional groups, compared to 235 links in the Western Bering 

Sea (Fig. 12). The number of energy pathways between primary production and any 

given upper trophic level box was considerably larger in the EBS, with over 19,000 

energy pathways leading to the toothed whales in the EBS as compared to approximately 

9,000 in the WBS (the maximum for a predator in both systems). These complex 

pathways are the result of a more detailed set of cross-connections between fish modeled 

in Trophic Levels 3 and 4. 

(B) 

(A) 

Figure 12. The trophic webs of the (A) Eastern and (B) Western Bering Sea models. Trophic level is 

shown on the Y-axis; box areas are proportional to log biomass (t/km2

). All predator prey flows are shown; 

the width of each predator/prey flow is proportional to the square root of the volume of the flow 

(t/km2

/year). 

23 
It is important to distinguish between two hypotheses for the higher number of 

flow connections in the EBS Ecopath model: either more sampling effort or different data 

treatment gives rise to the differences as a data artifact, or the more complex set of shelf 

habitats available in the EBS has created a more complex set of ecological relationships. 

The number of pathways at any given trophic level in either model is set by the 

level of model aggregation. Figure 13 shows a logarithmic plot of number of pathways 

from primary production for each species, versus trophic level. It is expected that the 

number of pathways will show a natural exponential progression with trophic level, as the 

pathways for each trophic level are multiplied by the number of pathways in the trophic 

level below it. However, the sudden jump in number of pathways above Trophic Level 3, 

especially in the EBS, reveals the change in the level of diet detail available for each 

trophic level in the literature and data sources. 

1000000 

Nu

mber of Pathways 

from PP 100000 

10000 

1000 

100 

10 

WBS 

EBS 

1 

2 2.5 3 3.5 4 4.5 5 

Trophic Level 

Figure 13. Number of distinct pathways from primary production to each separate compartment (log 

scale), plotted by compartment trophic level for both the EBS and WBS. 

To investigate the relative importance of flows, each flow was ranked on an 

importance scale, where the “importance” of a flow was its percentage, measured in flow 

volume (t/km2

/year) in either the diet of the predator or the predation mortality of the 

prey, whichever was greater. Sorted by increasing importance, the number of flows for 

any given cumulative level of importance is shown in Figure 14: plotting by cumulative 

importance ensures that the most important predator and prey flows for every 

compartment are shown. As shown in Figure 14, 85% of the volume of predator and prey 

flows can be captured with a similar number of predator/prey flows in each system: 184 

in the EBS and 172 in the WBS. However, in the EBS, the remaining 15% of the flow 

volume is spread over 136 flows, while in the WBS this 15% is spread over only 63 

flows. 

This result does not distinguish whether the larger number of low volume flows in 

the EBS model are due to increased sampling effort in the EBS or the increased 

complexity of the broad shelf environment. However, it indicates that the large majority 

of these “excess” flows are low in importance to the predator and the prey involved and 

may be excluded in this preliminary analysis, in order to focus on major energy 

pathways. Note that some of these flows may be low in importance due to a limited 

24 
350 

spatial or temporal overlap between predator and prey: environmental shifts could change 

the relative importance of many prey items in a predator’s diet. 

WBS 

EBS 

Number of Pred/Prey Links 

300 

250 

200 

150 

100 

50 

0 

Least important 100 80 60 40 20 0 Most important

Cumulative Flow Importance 

Figure 14. Cumulative number of flows of all compartments plotted as a function of the cumulative 

“importance” of the included flows (the importance of a single flow is measured as the maximum of the 

percentage of diet for a predator and the percentage of predation mortality for a prey item that a flow 

volume represents). 

Another measure of food web complexity is degree of omnivory: the degree to 

which individual species feed on different trophic levels. Christensen and Pauly (1995) 

suggest using the variance of the measured trophic level of each compartment, calculated 

for each predator i by summing over all prey j: Σj(TLj-(TLi-1))2·DCij. This index is 

unrelated to diet diversity overall but, as opposed to diversity, is relatively independent to 

the level of aggregation within a single trophic level. An index of system omnivory is the 

average of all omnivory indices weighted by log(consumption) for all compartments. 

The overall omnivory index for the EBS is 0.147, and for the WBS is 0.193. This 

higher index is mainly due to a difference in apportioning the diet of small pelagic fish. 

In the WBS the diets of forage fish, juvenile pollock, and herring are an approximately 

equal mix of copepods and large zooplankton: in the EBS, each of these groups’ prey is 

generally in one trophic level or the other (Fig. 15). 

WBS/EBS Omniv. Index 

Phytoplankton 

10 

1 

0.1 

01 

Figure 15. Omnivory indices of species in both models, shown as WBS/EBS (log scale). A black bar 

indicates a higher value in the WBS (WBS/EBS value greater than 1.0); a white bar indicates a higher value 

in the EBS (WBS/EBS value less than 1.0). Large zooplankton 

Juv. pollock age 0-1 

Pacific herring 

Oth. Pelagic Fish 

Jellyfish 

Epifauna 

Benthic Amph. 

Adult pollock age 2+ 

Pacific cod 

Salmon 

Infauna 

Tanner crab 

Snow crab 

King crab 

Shrimp 

Pacific halibut 

Greenland turbot 

Small flatfish 

Sablefish 

Rockfish 

Zoarcidae 

Copepods 

Arrow tooth flounder 

Cephalopods 

Skates 

Sculpins 

Macrouridae 

Baleen w hales 

Toothed w hales 

Sperm w hales 

Seals 

Steller sea lions 

Walrus & B.seals 

Seabirds 

25 
Detailed dietary differences 

While trophic level gives us a first look at the links in the food web, one more 

detailed approach is to define functional groups using prey and predator overlap indices. 

Rather than examine all of the diet composition entries on a 38 by 38 matrix, the 

summary of differences and similarities presented here is based on niche statistics and 

trophic level calculated for the two ecosystems. Diet overlap (niche) and trophic level 

are both wholly dependent on the input diet composition matrices. Predator overlap 

indices of a prey further depend on the relative consumption rates of each predator. 

The diet (prey) overlap between two species boxes may be calculated from a diet 

matrix: for each pair of species boxes, the index takes a value between 0 (no diet overlap) 

and 1 (complete diet overlap). Similarly, the predator overlap between two species boxes 

may be calculated from a mortality matrix and also takes on a value between 0 (when two 

species have no predators in common) to 1 (when the percentage of predation mortality 

attributable to each of a set of predators is identical for the two species). 

Overlap indices may be calculated for multiple functional groups within a single 

ecosystem, or between identical functional groups in two ecosystems. The latter 

comparison is shown in Figure 16. Functional groups which have almost identical 

predator and prey niches in both systems are clustered near the upper right hand corner of 

Figure 16. Rockfish and sablefish have overlap indices of 0.0 since they are not modeled 

in the WBS. 

Figure 16. Prey (diet) overlap (X-axis) and predator, or mortality overlap of identical functional groups 

Seabirds 

Tanner crab 

Snow crab 

compared between the WBS and EBS systems. Groups with overlap indices near 1.0 have similar suites of 

predator or prey between the two systems. Functional groups near 1.0,1.0 are staggered slightly for 

legibility 

Of the ten functional groups that show a prey overlap of 0.7 or less between the 

two systems, several are due to a larger proportion of cephalopods in the diets of WBS 

fish species (Table 7). Also, juvenile pollock are in higher proportion in some species 

(especially flounder and turbot) diets in the EBS while adult pollock are in higher 

proportion same species’ diets in the WBS. 

26 
The average predator niche overlap between the two systems is less than the 

average prey niche overlap overall, with 18 functional groups with a predator overlap 

index of 0.6 or less (Fig. 16). Many of these differences are due to the inclusion of small 

amounts of predation on high trophic level fish by marine mammals: the marine mammal 

causing the most mortality varies greatly for each fish species between systems. 

However, the estimates in the marine mammal predation on these top fish predators may 

contain a greater degree of inaccuracy in both models, as often diet data for marine 

mammals broadly lumps fish together as a single category. 

Table 7. Primary prey (items with 10% or more presence in listed predators’ diets) of species with dietary 

niche overlaps of 0.70 or less between the EBS and WBS models. 

Predator (prey similarity) EBS diet WBS diet 

Seabirds (0.65) 60% Juv. pollock 32% L. Zoop 

12% L. Zoop. 26% Juv. Pollock 

Remainder diverse fish species 18% Forage fish 

Jellyfish (0.63) 65% L. Zoop. 

15% Copepods 

30% Copepods 

60% L. Zoop. 

Macrouridae (0.56) 42% Forage fish(*) 

32% Shrimp 

23% Cephalopods 

30% Cephalopods 

20% Infauna 

16% Forage fish (*) 

12% L. Zoop. 

Arrowtooth flounder (0.47) 48% Juv. Pollock 

20% L. Zoop. 

16% Adult Pollock 

50% Adult Pollock 

20% Cephalopods 

15% Shrimp 

Pacific halibut (0.37) 50% Adult pollock 

12% Epifauna 

Remainder diverse fish species 

50% Cephalopods 

18% Adult pollock 

15% Juvenile pollock 

Seals (0.36) 20% L. Zoop. 

15% Forage Fish 

14% Shrimp 

Remainder diverse fish species 

26% Cephalopods 

23% Adult Pollock 

20% Juvenile Pollock 

Steller sea lion (0.31) 60% Forage Fish 

19% Juv. Pollock 

31% Cephalopods 

23% Adult Pollock 

19% Juv. Pollock 

Greenland turbot (0.26) 71% Juv. Pollock 

24% Adult Pollock 

45% Adult Pollock 

30% Cephalopods 

10% Forage Fish 

Sculpins (0.19) 38% Sm. Flatfish 

28% Shrimp 

13% Snow crab 

25% Adult Pollock 

21% Epifauna 

14% Infauna 

13% Juv. Pollock 

Zoarcidae (0.18) 53% Infauna 35% Cephalopods 

23% Benthic amphipods 15% Forage Fish 

14% Epifauna 12% L. Zoop. 

10% Juv. Pollock 

(*) primarily myctophids 

This matrix of prey or predator pairwise overlap values within a single ecosystem 

may then be made into a “similarity tree” using a variety of algorithms: in this case, using 

the relatively simple unweighted arithmetic average clustering or UPGMA method (Rohlf 

1963, Sneath and Sokal 1973, Legendre and Legendre 1998). The resulting trees show 

functional “families” of increasing predator or prey overlap. 

27 
Figures 17-18 show prey and predator similarity trees, respectively, for the two 

ecosystems. In these trees, a branch is drawn on the x-axis at the similarity (overlap) that 

is the average pairwise overlap between all groups on each tree branch. In these figures, 

an arbitrary cutoff similarity of 0.70 was used to distinguish functional groups for the 

purposes of this discussion. The branches are sorted so that trophic level increases from 

bottom to top as much as the branching structure allows. 

For prey (dietary) overlap, the cutoff of 0.70 divided the EBS into 16 major 

dietary niche groupings, while dividing the WBS into 14 major groupings. Of these 

groups, phytoplankton and detritus make up four groups with no consumption, leaving 12 

groups in the EBS and 14 groups in the WBS. Some of these groups are the same in both 

systems while some differ (Table 8). 

(A) (B) 

Figure 17. Cladogram of prey (diet) similarity groups based on pairwise prey similarity indices. The xaxis position of each branch indicated the average similarity between all species on the two branches. Grey 

shading shows functional groups with a similarity greater than or equal to 0.70 (dotted line). (A) eastern 

Bering Sea shelf; (B) western Bering Sea shelf. 

28 
The first few divisions at low overlap levels indicate major functional groups 

common to both systems, but also reveal some fundamental differences. Examining the 

branching tree of Figure 17 from left (least diet overlap) to right (most diet overlap) 

shows that after the Trophic Level 1 producers that have no diet overlap with any group 

(overlap 0.0), the first group to branch out is copepods at an overlap index near 0.05; 

however, in the EBS, large zooplankton share this branch with copepods due to their 

shared consumption of phytoplankton. The second major branch separates the 

components into benthic and pelagic categories at approximately 0.10. 

(A) (B) 

Figure 18. Cladogram of predator (mortality source) similarity groups based on pairwise predator 

similarity indices. The x-axis position of each branch indicated the average similarity between all species 

on the two branches. Grey shading shows functional groups with a similarity greater than or equal to 0.70 

(dotted line). (A) eastern Bering Sea shelf; (B) western Bering Sea shelf. 

The benthic and pelagic group separation is identical for all functional groups in 

the two systems with the exception of Zoarcidae (eelpouts), which were placed in the 

benthic web in the EBS, and close to Macrouridae (grenadier) and sperm whales in the 

WBS: however, this may be an artifact of the collapsing of the benthic and pelagic forage 

fish and cephalopod categories on which they feed (Table 8). 

29 
Within the benthic web, a further division occurs in both the EBS and WBS near 

an overlap of 0.20-0.25, effectively dividing the benthic web into two trophic levels. The 

lower grouping feeds on detritus directly while the top grouping feeds primarily on 

infauna. The high level of aggregation in infauna may obscure a considerable amount of 

the specialization within the benthic community in these models. 

Table 8. Descriptions of major prey items of each group of predators sharing similar niches (groupings are 

made if diet niche similarity is greater than or equal to 0.70). 

Dominant Prey Group EBS predators WBS predators 

Phytoplankton and pelagic detritus Copepods, large zooplankton Copepods 

Benthic detritus with some infauna Benthic amphipods, infauna, Benthic amphipods, infauna,

(10-20%) epifauna, shrimp epifauna, shrimp 

Infauna, with some epifauna (10- Crabs, small flatfish, walrus Crabs, small flatfish, walrus 

15%) and bearded seals, Zoarcidae and bearded seals 

Copepods Large zooplankton 

Large zooplankton and copepods Juvenile pollock, adult Jellyfish, Pacific herring, 

pollock, Pacific salmon, 

baleen whales 

juvenile pollock, adult 

pollock, forage fish, 

cephalopods, Pacific 

salmon, baleen whales 

Large zooplankton Forage fish, Pacific herring, 

jellyfish, cephalopods, 

rockfish 

Small flatfish and shrimp Sculpins 

Diverse fish (differing proportions) Toothed whales, seals 

Juvenile pollock, forage fish, and Seabirds 

large zooplankton 

Forage fish and cephalopods (*) Macrouridae, Steller sea lions 

Diverse fish and benthic predators Pacific cod, sculpins and 

rockfish 

Juvenile pollock Arrowtooth flounder, 

seabirds, Greenland turbot 

Adult pollock, juvenile pollock, Skates arrowtooth flounder, 

and cephalopods Greenland turbot, seals 

Steller sea lions, toothed 

whales, Pacific halibut 

Mainly Adult pollock, some other Pacific cod, skates, Pacific 

fish halibut, 

sablefish 

Cephalopods, forage fish, and large Zoarcidae, Macrouridae 

zooplankton 

Cephalopods only Sperm whales Sperm whales 

(*) Strong niche overlap due to combining mesopelagic and pelagic forage fish, and mesopelagic and pelagic cephalopods. 

Outside of the benthic web, the primary distinction of dietary niche between 

Trophic Levels 3-4 is the extent to which species feed on copepods versus large 

zooplankton. On Trophic Level 4+, the primary distinction is the extent to which species 

feed on pollock (adult or juvenile) versus cephalopods (Table 8). 

30 
Predator niches (based on a partitioning of predation mortality by proportion for 

each prey) are shown in Figure 18. In general, there are more “types” of unique predator 

suites for individual prey items than prey suites for individual predators, and predator 

similarity values tend to be lower than prey similarity values. By grouping functional 

groups at the level of similarity ≥ 0.70, 19 distinct groupings are indicated. 

In each model, one of these is a detrital “flow through” compartment with no 

predation. Four groups in the EBS (sperm whales, marine mammals, and Steller sea lions 

and jellyfish) and four in the WBS (sperm whales, seabirds, toothed whales, and skates) 

are top predators with no predation mortality or cannibalism only. Much of this 

decreased similarity in predator niches was the result of less aggregation in the top 

trophic levels. Therefore, predator groups were broadly aggregated to find groups of 

prey items with “similar” predators between the two systems: these results are shown as 

12 distinct groups with associated important prey items in Table 9. 

Table 9. Descriptions of major predators of each group of prey sharing similar niches (groupings are made 

if predator (mortality) niche similarity is greater than or equal to 0.70). 

Dominant predator EBS prey group WBS prey group 

Copepods (30-60%) Large Phytoplankton, pelagic detritus Phytoplankton, pelagic 

zooplankton (30-60%) detritus 

Large zooplankton (60-80%), Copepods Copepods, large 

pollock (10-25%) zooplankton 

Pollock (30-35%), forage fish Large zooplankton 

(33%), cephalopods (17%) 

Infauna (60-80%) Benthic detritus Benthic detritus 

Epifauna (80%) Infauna, epifauna 

Small flatfish (35-40%), crabs Infauna, epifauna 

(20-30%), shrimp (5-10%), 

epifauna (5-10%) 

Cephalopods (40-80%) Forage fish, cephalopods Cephalopods, forage fish, 

benthic amphipods 

Adult pollock (40-70%), seals (5-

10%) 

no other common predators 

Shrimp, juvenile pollock, 

Pacific cod, arrowtooth 

flounder 

Pacific cod (34-85%), marine Small flatfish, tanner crab, Juvenile pollock, snow crab, 

mammals (5-40%) snow crab, king crab, 

Zoarcidae, Pacific herring 

adult pollock 

adult pollock, small flatfish, 

Sculpins and Rockfish, 

Zoarcidae 

Mixed fish species (no dominant) Sculpins, Greenland turbot Shrimp, tanner crab, 

Macrouridae 

Toothed whales (80-100%) Baleen whales, walrus and Baleen whales, walrus and 

bearded seals, other seals, bearded seals, other seals, 

toothed whales Steller sea lions, arrowtooth 

flounder, Pacific halibut, 

Greenland turbot 

Pinnipeds (30-80%), baleen Pacific salmon, Pacific halibut, Jellyfish, Pacific salmon, 

whales (20-30%) toothed whales rockfish, sablefish, skates, Pacific herring, king crab 

(10-50%), seabirds (5-25%) Macrouridae 

31 
Keystone Species, Top-down and Bottom-up Control 

Bottlenecks and control 

A key question in fisheries ecology is one of functional control: if a quantity of a 

species is removed from a system, how will it affect its predators (bottom-up control) or 

its prey (top-down control)? Developed functional responses between predator and prey 

are thought to depend on nonlinear interactions such as food saturation, schooling 

behavior or issues of refuge and foraging risk. The dynamic Ecosim model introduces 

such nonlinear control theory, while the Ecopath food web in itself is a static model. 

Investigating control using an Ecopath food web amounts to conducting various types of 

first-order (linear) perturbation tests. As such, these tests simultaneously answer two 

questions: (1) What is the first order effect of removing a quantity of a species from a 

system, assuming the removal is small enough that the effect is linear on affected 

predator and/or prey? (2) What effect would an error in data estimation for a species 

have on assumptions of predator/prey dynamics? In other words, the results presented 

here are simultaneously testing for biological sensitivity and model parameter sensitivity. 

The primary focus in the following results is the identification of keystone 

functional groups: functional groups for which a change in biomass (or estimation of 

biomass) would substantially change the model’s function. This will also help to narrow 

the view of 200-300+ trophic links into a smaller number of dominant pathways. 

The control analyses in this section focus on investigating small perturbations 

around the “mean” ecosystem, or balanced state. This methodology investigates which 

functional groups would have a greater effect on the food web, given a small change of 

fixed proportion (for example, 1%) in the throughput of that component (input + output, 

measured in t/km2

/year). Since throughput is calculated from biomass, P/B, and Q/B 

together, no distinction is made between these parameters in the following discussion: a 

1% increase in biomass is assumed to have the same effect as a 1% increase in P/B or 

Q/B. However, it is expected that the life-history traits P/B and Q/B are less variable 

than biomass, and that these results effectively focus on control implications resulting 

from changes in biomass. It should be noted, though, that P/B and Q/B are dependent on 

stock age structure and growth-at-age, and removals of biomass greater than a few 

percentage points may result in nonlinear compensatory changes in P/B and Q/B— 

calibrating such responses falls to dynamic modeling techniques such as Ecosim and is 

not addressed here. 

In most cases, this proportional scaling will result in the species with higher 

overall production having greater effects on the food web. These analyses do not address 

fixed removals; for example, we do not investigate which species are more vulnerable to 

the removal of 1 metric ton of biomass through fishing. Again, asking such questions 

would require investigations of compensatory and depensatory responses on a stock-bystock basis. 

32 
Trophic levels 1-2 (benthic vs. pelagic production) 

Defining functional groups on the lowest trophic levels (1-2) as “keystone” 

functional groups is not meaningful, as the high amount of aggregation at those trophic 

levels results in almost all functional groups—phytoplankton, copepods, large 

zooplankton, infauna and epifauna,—acting as important bottom-up conduits of energy 

for the rest of the system. Whereas the trophic level of upper trophic level species may 

be defined by the proportion of their diet, for example, split between ‘copepods’ and 

‘large zooplankton,’ groups in Trophic Levels 1 and 2 are already so aggregated as to 

make differentiating one or the other as a ‘primary control source’ unnecessary, although 

individual species within these aggregated groups may be keystones. 

Rather, the main functional split at Trophic Levels 1-2 is simply between the 

benthic components (feeding on benthic detritus) and pelagic components (feeding on 

phytoplankton and pelagic detritus). The ultimate source of all production, benthic and 

pelagic, is phytoplankton, and relatively few steps are taken from primary production 

before the majority of living material is respired or enters the detrital food web. 

In both the EBS and the WBS, the same top 7 groups produce 95% of the detritus 

in the system (Fig. 19): all of these except pollock are below Trophic Level 2.5. It should 

be noted, as discussed in the Methods section, that the overall detrital flows, 

phytoplankton flows, and apportionment of detritus between pelagic and benthic 

components are calibrated by predator demand rather than through direct knowledge of 

annual detrital accumulation in the Bering Sea. Phytoplankton, in particular, may have a 

greater contribution to detritus due to unexploited material from seasonal blooms. 

Adult pollock All Others 

Epifauna 

Benthic amph. 2%

3% 

1% 

Phytoplankton 

26% 

Infauna 

22% 

Copepods 

19% 

Large Zoop. 

17% 

Infauna 

15% 

Copepods 

18% 

Large Zoop. 

21% 

Phytoplankton 

37% 

2% 

Benthic amph. 

Epifauna 

Adult pollock 1% 

All Others 

4% 10% 

2% 

Total detrital flow: 1,452 t/km2/yr. Total detrital flow: 1452 t/km^2/yr. 

Total detrital flow: 3,466 t/km2/yr. Total detrital flow: 3466 t/km^2/yr.

Figure 19. The amount of material flowing from “living” boxes into detritus in the EBS (left small circle) 

and the WBS (right large circle). The area of each circle is proportional to the total detrital flow of the 

system. 

Despite the higher demand for benthic detritus in the WBS, it is evident that the 

benthic food web provides a greater proportion of food to Trophic Levels 3 and above in 

33 
the EBS than it does in the WBS (Fig. 20). This is in spite of the fact that demand for 

benthic detrital production is a greater proportion of the overall total production in the 

WBS than in the EBS (37% vs. 24%; Table 2). 

This dichotomy is the result of the structure of the benthic web between Trophic 

Levels 2 and 3. The consumption demands of the twenty-fold higher epifaunal biomass 

are modeled in the WBS ecosystem (biomass 115 t/km2

 in the WBS vs. 6 t/km2 in the 

EBS; Table 4). As shown in Figure 21 (A and B), epifauna consume a greater relative 

proportion of benthic detritus in the WBS than in the EBS. 

(B) WBS 

(A) EBS 

Energy Source 

100% from 

benthic 

100% from 

pelagic 

Figure 20. The proportion of energy flow into each compartment above Trophic Level 1 ultimately 

deriving from pelagic sources (phytoplankton and pelagic detritus; red) or benthic sources (benthic detritus; 

blue). (A) eastern Bering Sea shelf; (B) western Bering Sea shelf. Box and text size is proportional to 

log(biomass) of each compartment, while the area of each connection link is proportional to the volume of 

flow. 

Moreover, epifauna is the dominant predator of infauna in the WBS: in the EBS, 

the larger proportion of infaunal biomass passes upwards into crab and fish species (Figs. 

34 
21C and 21D; Table 9). The small flatfish community has approximately a 10 times 

higher biomass in the EBS in comparison to the WBS (Table 4). These flatfish species, 

especially yellowfin sole and rock sole, are a major source of energy for Pacific cod and 

other predators. Conversely, in the WBS, a great majority (84%) of the energy entering 

the epifaunal group is lost to “cannibalism”; that is, to a detailed trophic structure that is 

not visible in this model, within the highly aggregated epifaunal functional group (Table 

5). 

Keystone species on Trophic Levels 3+ 

Due to the aggregation of Trophic Levels 2-3 into copepod, large zooplankton, 

epifauna, and infauna, the function of omnivory and fractional trophic levels is not 

possible to examine thoroughly. Starting on Trophic Level 3, however, the increasing 

diversity of the energy pathways in the models allow a finer investigation of functional 

groups. 

(A) EBS (B) WBS 

(C) EBS (D) WBS 

Figure 21. A subsection of the EBS and WBS benthic food webs, showing the major prey (A,B, lighter 

grey) and predators(C,D, darker grey) of infauna and epifauna. A few predators for which these groups are 

of minor importance are not shown. In (A), some predation on higher trophic level crabs by epifauna is 

shown. Box and text size is proportional to log(biomass) of each compartment, while the width of each 

connection link is proportional to the square root of the volume of flow. The absolute scale of the flow 

differs between the prey flows (A and B) and the predator flows (C and D). 

35 
Figure 22 shows total consumption (A) and total utilized production (B) of each 

functional group regressed against trophic level (exponential regression) starting on 

Trophic Level 3.0. Consumption may partially determine the degree of top-down control 

each functional group may put on its prey, while utilized production, defined as all 

production of a group which is either consumed by predators or caught in a fishery), may 

partially determine the degree of bottom-up control. 

As expected by the 80-90% loss of energy per trophic level (Table 3), there is a 

significant trend for both consumption and production in both systems: this is a way of 

visualizing the “trophic pyramid” on a group-by-group basis. This trend is fit for 

fractional trophic levels rather than for “collapsed” levels shown in Table 3 (the 

aggregation of predator and prey below Trophic Level 3.0 leads to overall measurement 

error if these levels are included in the regression). 

1000 

100 

10 

1 

0.1 

0.01 

100 

EBS 

WBS 

Expon. (EBS) 

Expon. (WBS) 

(A) 

10 

1 

0.1 

0.01 

0.001 

0.0001 

2.8 3.0 3.2 3.4 3.6 3.8 4.0 4.2 4.4 4.6 4.8 5.0 5.2 

EBS 

WBS 

Expon. (EBS) 

Expon. (WBS) 

(B) 

Trophic level 

Figure 22. Total consumption (A; t/km2

/year, log-scale) and total utilized production (B; t/km2/year, log 

scale) as a function of trophic level, for functional groups of Trophic Level 3.0 and above in the WBS and 

the EBS. Lines show fits of the formula ln(Cons. Or Prod.) = TL0 + m*TL. All fits are significant 

(P<0.05) with R2

 values between 0.16 and 0.29. The fits are not significantly different between the EBS 

and the WBS. For Figure (B), unfished species with no predation (top predators) (species with no utilized 

production) are not included. 

Table 10 shows the functional groups which produce over 95% of utilized 

production in Trophic Levels 3+ in the EBS and WBS: this consists of eight species in 

the EBS and six species in the WBS. Given the regressions in Figure 22, it is not 

surprising that these species, except Pacific cod and cephalopods, are between Trophic 

Level 3.0-3.5. 

An examination of the predators of each of the species in Table 10 suggests three 

separate major routes through Trophic Levels 3.0-3.5: (1) forage fish and cephalopods; 

(2) pollock (adult and juvenile combined); and (3) benthic components such as crabs and 

small flatfish (Fig. 23). Cephalopods are included with forage fish as keystones because 

of their high ranking on Table 10, and despite their high trophic level, much of their 

consumption comes directly from large zooplankton, with forage fish as the other major Total consumption Total production passed upward 

36 
component of their diet other than cannibalism resulting from condensing multiple 

cephalopod species. 

Table 10. Trophic level, biomass (t/km2

), and utilized production above Trophic Level 3.0 (shown as 

percentage of all utilized production, in t/km2

/year, above Trophic Level 3.0), shown for groups 

contributing 1% or more of the utilized production above Trophic Level 3.0 in the EBS and WBS. Utilized 

production is that which is consumed by predators or the fishery. 

EBS TL 3+ WBS TL 3+ 

Group T.L. Biom. Prod. % Group T.L. Biom. Prod. % 

Juvenile pollock 3.1 6.0 30.7% 

Forage fish 3.2 13.5 22.2% 

Cephalopods 3.8 3.5 20.5% 

Adult pollock 3.3 27.5 12.4% 

Small flatfish 3.1 9.2 4.3% 

Tanner crab 3.0 1.6 3.6% 

Pacific cod 4.0 2.4 1.9% 

Snow crab 3.0 0.6 1.2% 

Forage fish 

Cephalopods 

Adult pollock 

Juvenile pollock 

Pacific cod 

Pacific herring 

3.4 19.1 36.4% 

3.7 4.8 31.7% 

3.4 15.0 15.9% 

3.4 3.8 10.5% 

4.0 3.2 1.3% 

3.3 0.79 1.0% 

Total Percent of T.L. 3.0+ prod. 96.7% Total Percent of T.L. 3.0+ prod. 96.7% 

To examine relative bottom-up importance of each of these three routes of energy 

through specific prey, the functional groups above Trophic Level 4 may then be 

categorized by the relative proportion of their consumption which comes from each of 

these groups. Figure 24 shows one such categorization scheme. Each of the functional 

groups in Table 10 is given a color based on its grouping (blue for benthic; green for 

small pelagic; red for pollock). Each functional group above Trophic Level 2.5 that is 

not on Table 10 is given a color that reflects the proportion of its diet that ultimately 

passes through functional boxes belonging to each of these three color groupings. 

9.4 

3 

Adult pollock 

Juv. pollock 

P.cod 

Small flatfish 

C. bairdi 

C. opilio 

Cephalopods Forage fish 

Mammals & Birds 

All Other Fish 

Jellyfish 

Turbot, flounder, halibut 

Cephalopods 

P.cod 

Adult pollock 

7.5 7.5 

0 

0.5 

1 

1.5 

2 

2.5 

Predator 

(A) EBS 

Adult pollock Juv.pollock 

P.cod 

P.herring 

Cephalopods 

orage fish 

Mammals & Birds 

All Other Fish 

Juv.pollock 

Sculp., Rock., Zor., Macro. 

Cephalopods 

P.cod 

Adult pollock 

6.0 

4.1 

6.2 7.7 

0 

0.5 

1 

1.5 

2 

2.5 

(B) WBS 

3 

Predator 

Prey 

Prey

Figure 23. Consumption rates (t/km2

/year) of dominant functional groups between Trophic Levels 3.0-3.5 

shown on Table 10. (A) EBS; (B) WBS. 

Consumption 

(t/km^2/year) 

F 

37 
As noted above, the benthic web plays a much smaller role in the WBS than in the 

EBS. Pollock are more dominant as prey of upper trophic level fish in the EBS, 

especially large flatfish (arrowtooth flounder and Greenland turbot). In the EBS, Pacific 

cod play a “bridging” role between pollock and small flatfish. Small pelagics, especially 

through cephalopods, are dominant in the WBS relative to pollock. Two groups in the 

EBS, baleen whales and seals, feed on an equal mix of all three groups, although seals 

feed on a higher trophic level. Baleen whales and seals do not have a benthic component 

in their diet in the WBS. 

(A) EBS 

TL 3-3.5 Energy Source 

(B) WBS 

100% 

benthic 

100% 

forage 

100% 

pollock 

Figure 24. Proportion of energy flow into each compartment above Tropic Level 3.5 that passed through 

Trophic Level 3-3.5 by way of pollock compartments (adult and juvenile; red); other pelagic forage species 

(forage fish, large zooplankton and herring, green); and benthic compartments (crab and small flatfish, 

blue). Energy not passing directly through these Trophic Level 3 compartments (for example, direct flow 

from zooplankton to Trophic Level 4+) are not shown. Box area is directly proportional to biomass 

(t/km2

). (A) eastern Bering Sea shelf; (B) western Bering Sea shelf. 

38 
The other two species groups in Table 10, cephalopods and Pacific cod, are the 

dominant predators between Trophic Levels 3.5-4.0. The cephalopod functional group in 

both ecosystems is an aggregation of species on more than one trophic level, and are 

more important as a prey item in the WBS than in the EBS (Figs. 25 A and B). Their diet 

includes a high degree of cannibalism. Pacific cod, as shown by their purple coloring in 

Figure 24A and in Figure 25 C and D, are a “bridge” species between benthic and pelagic 

components in the EBS, while in the WBS they feed primarily on pollock. 

(A) EBS (B) WBS 

(C) EBS (D) WBS 

Figure 25. Predator and prey of cephalopods (A,B) and Pacific cod (C,D) in the EBS and the WBS. Light 

gray boxes indicate prey; dark gray indicate predators. The width of the connecting flow lines is 

proportional to the volume of flow (t/km2

/year). 

For a more holistic examination of bottom-up and top-down control, there are 

multiple metrics that may be used. Two are presented here: residual fitting of the 

regressions in Figure 22, and trophic impact (Christensen and Pauly 1995). 

The first method is useful for species of Trophic Level 3.0 and above—it does not 

work for lower trophic levels due to the lower-level aggregation mentioned above. As 

seen in Table 10, Pacific cod (Trophic Level 4.0) and cephalopods (Trophic Level 3.7-

3.8) have production levels ranking with species on Trophic Level 3.0-3.5, suggesting 

that they represent a large proportion of production on the higher trophic levels. This 

examination can be generalized by calculating the standardized residuals from the 

regression in Figure 22. 

If a species has a greater level of utilized production than predicted for its trophic 

level from the regression in Figure 22B, it would be a source of relatively strong bottomup control. If a functional group has a positive deviation from the exponential regression 

39 
of consumption versus trophic level (Fig. 22A), then relative to other groups on near its 

trophic level, it would exert stronger top-down control. A species with a negative 

residual would exert relatively weak top-down control for its trophic level. A functional 

group could exhibit strong top-down and bottom-up control simultaneously (middle-out 

control). The measurement of the residuals takes into account control anomalies 

resulting from both high per-biomass production and consumption rates (P/B and Q/B) 

and the actual biomass of the species in the system. 

Figure 26 shows the residuals to the fit of ln(utilized production) to trophic level 

for groups of Trophic Level 3.0 and above, sorted in order of decreasing residuals. In 

both systems, the groups with the highest positive residuals (>1.0), and therefore most 

important for bottom-up forcing, are cephalopods, pollock (adult and juvenile), forage 

fish, and Pacific cod. Interestingly, cephalopods have a much higher residual than either 

adult or juvenile pollock in the EBS as well as the WBS: this is a reflection of the 

cephalopod’s high trophic level relative to its production. 

In the EBS, small flatfish, turbot and flounder also are stronger bottom-up 

providers. Crabs and “minor” fish tend to show little deviation from the production slope 

in either system. Species with negative deviations higher than 0.5 include jellyfish, all 

marine mammals, and seabirds: this is expected, as these species, regardless of their 

trophic level, represent uneaten “end points” for energy in their ecosystems. 

2 

Std. Resid. of useful prod. vs. TL Std. Resid. of useful prod. vs. TL 

(Bottom-up forcing) (Bottom-up forcing) 

1 

0 

-1 

-2 

-3 

(A) EBS 

Cephalopods 

P.cod 

Forage fish 

Juv. pollock 

Adult pollock 

Greenland turb. 

Sculpins 

Macrouridae 

Arrowtooth fl. 

Sablefish 

Small flatfish 

Skates 

Snow crab 

P.salmon 

Tanner crab 

P.halibut 

Zoarcidae 

Rockfish 

P.herring 

King crab 

Walrus& B.seals 

Seals 

Toothed whales 

Steller s.lions 

Baleen whales 

Jellyfish 

3 

2 

1 

0 

-1 

(B) WBS 

-2 

Cephalopods 

Forage fish 

Adult pollock 

Juv. pollock 

P.cod 

Zoarcidae 

Macrouridae 

Sculpins 

P.herring 

Skates 

P.halibut 

Small flatfish 

P.salmon 

Greenland turb. 

Arrowtooth fl. 

Snow crab 

Seals 

King crab 

Tanner crab 

Jellyfish 

Baleen whales 

Steller s.lions 

Walrus& B.seals 

Figure 26. Standardized residuals from the fit ln(utilized production) = TL0 + m·TL for (A) EBS and (B) 

WBS. Functional groups are sorted in order of decreasing residuals. Positive values indicate relatively 

strong bottom-up control for a group’s trophic level; negative values indicate relatively weak bottom-up 

control. 

40 
The residuals of the fit of ln(consumption) to trophic level, sorted in order of 

decreasing residuals, are shown in Figure 27. Again, the “top 5” groups listed above for 

bottom-up forcing—cephalopods, adult and juvenile pollock, Pacific cod, and forage 

fish—have the highest positive residuals for top-down forcing, indicating that these 

groups are sources of both top-down and bottom-up forcing within the web. On the 

negative side, jellyfish, rockfish, and Steller sea lions have little top-down effect in the 

EBS, while crabs have little top-down effect in the WBS. 

Plotting predator and prey residuals on a single XY graph results in Figure 28. The five 

species responsible for high levels of both bottom-up and top-down control are visible in 

the upper right for both the EBS and the WBS. In the EBS, a secondary tier of species 

with both top-down and bottom-up residuals are small flatfish and large flatfish 

(Greenland turbot and arrowtooth flounder). 

Jellyfish show the lowest level of bottom-up and top-down importance of any species in 

the EBS given their trophic level. While weak bottom-up forcing is not unexpected (few 

species consume large jellyfish), the weak top-down forcing may result from an 

underestimate of jellyfish consumption rates in the EBS—the estimate of 2.0/year in the 

EBS is 33% lower than the estimate of 3.0/year in the WBS, and both values should be 

considered relatively uncertain. 

3 (A) EBS 

Std. Resid. of Consumption vs. TL Std. Resid. of Consumption vs. TL (Top-down forcing) 

2 

(Top-down forcing) 

1 

0 

-1 

-2 

-3 

Cephalopods Adult pollock 

Forage fish 

Juv. pollock 

P.cod 

Small flatfish 

Sperm Whales 

Greenland turb. 

Arrowtooth fl. 

Sculpins 

Snow crab 

Skates 

Baleen whales 

Seals 

Macrouridae 

Walrus& B.seals 

P.herring 

Toothed whales 

P.halibut 

Sablefish 

Tanner crab 

King crab P.salmon 

Seabirds 

Zoarcidae 

Steller s.lions 

Rockfish 

Jellyfish 

3 

(B) WBS 

2 

1 

0 

-1 

-2 

-3 

Forage fish 

P.cod 

Baleen whales 

Figure 27. Standardized residuals from the fit ln(consumption) = TL0 + m·TL for (A) EBS and (B) WBS. 

Functional groups are sorted in order of decreasing residuals. Positive values indicate relatively strong topdown control for a group’s trophic level; negative values indicate relatively weak top-down control. 

41 

Adult pollock Cephalopods 

Juv. pollock 

P.herring 

Macrouridae 

Seals 

Zoarcidae 

Small flatfish 

Skates 

Toothed whales 

Sculpins 

Steller s.lions 

Walrus& B.seals 

Jellyfish 

P.salmon 

Seabirds P.halibut 

Sperm Whales 

Greenland turb. 

Arrowtooth fl. 

Snow crab 

Tanner crab 

King crab 
(A) EBS (B) WBS 

Figure 28. Standardized residuals by functional group of the regression ln(utilized production) = TL0 + 

m*TL (bottom-up residual) and ln(consumption) = TL0 + m·TL (top-down residual), where regression is 

performed for all groups with a trophic level of 3.0 and above. (A) EBS; (B) WBS. 

A final method of examining top-down vs. bottom-up forcing is the trophic 

impact graph, described in Christensen and Pauly (2000). The graph shows the 

normalized, expected linear perturbation in one component, the “impacted” group (up or 

down) given a proportional increase in production and consumption of a second 

component, the “impacting” group. This calculation is performed for every pair of 

functional groups in each system: the fishery (total catch) may be similarly treated. 

The results for each pairwise interaction of trophic impact are shown in Figure 29 

(EBS) and Figure 30 (WBS). The grid shows the effect of the impacting species (shown 

in the left-hand column) on the impacted species (shown on the top). Black circles 

indicate a positive effect (an increase in the impacting species leads to an increase in the 

impacted species) while white circles indicate a negative effect (an increase in the 

impacting species leads to a decrease in the impacted species). Effect size is proportional 

to circle area, with the largest circles indicating effects of ±1.0 and no circle indicating 

effects near zero. 

The bars along the left and top of Figures 29 and 30 are the sums of the absolute 

values of each impact value in the row or column respectively, divided by the number of 

species in each system. This gives a measure of how much a species impacts all other 

species in the system (left bars) or is impacted by all other species in the system (top 

bars). The diagonal line of white circles on both Figures 29 and 30 indicates the selflimiting (density-dependent) effect of each species on itself. Groups below this diagonal, 

tending to be lower trophic levels, show a large number of black circles indicating 

general bottom-up forcing and an overall high upward impact. 

The fishery creates a strong negative effect on most fished species—this is largest 

in salmon in the EBS (Bristol Bay salmon fishery) and is also large for marine mammals 

due to their low growth rates relative to indigenous harvest. Some positive effects of the 

fishery are due to the removal of competitors. 

42 
Impacted Group 

0

0.05

0.1

Detrital poolBenthicPelagicPhytoplankton

CopepodsLarge Zoop.Juv. pollockP.herringForage fish

CephalopodsP.salmonJellyfishEpifaunaInfaunaBenthicC. bairdiC. opilioKing crabShrimpAdult pollockP.codP.halibutGreenland

Arrowtooth fl.Small flatfish

SkatesSculpinsSablefishRockfishMacrouridae

ZoarcidaeBaleenToothedSpermWalrus&SealsSteller s.lions

Marine birdsFishery

0.2 0.15 0.1 0.05 0

Detrital pool

Benthic detritus

Pelagic detritus

Phytoplankton

Copepods

Large Zoop.

Juv. pollock

P.herring

Forage fish

Cephalopods

P.salmon

Jellyfish

Epifauna

Infauna

Benthic amph.

C. bairdi

C. opilio

King crab

Shrimp

Adult pollock

P.cod

P.halibut

Greenland turb.

Arrowtooth fl.

Small flatfish

Skates

Sculpins

Sablefish

Rockfish

Macrouridae

Zoarcidae

Baleen whales

Toothed whales

Sperm Whales

Walrus& B.seals

Seals

Steller s.lions

Marine birds

Fishery

Impacting Group 

Figure 29. Trophic impact graph and impacting/impacted indices for each species in the EBS. See text for 

explanation of figure.

Aside from the fishery, the groups producing the most impact (left hand bars in 

Figs. 29-30) are adult pollock in both models. The effect of adult pollock is mixed but 

generally negative on many species, as they act as a competitor rather than a food source. 

Juvenile pollock, on the other hand, have a positive effect on a wide range of species in 

both ecosystems, particularly seabirds, arrowtooth flounder, and Greenland turbot. 

Next to pollock, Pacific cod have one of the highest degrees of impact on both 

systems, comparable in effect to that of the lower aggregated trophic levels (benthic and 

pelagic bottom-up production). ffects caused by Pacific cod are negative: 

this highlights Pacific cod’s role as a top, structuring predator in both ecosystems. 

43 

Most of the e
The impacting graphs (top bars in Figures 29-30) indicate that while impacts are 

caused by a few keystone groups, the effects of these impacts are spread more evenly 

across the groups in both systems. ost sensitive (impacted) species are those with 

the highest fishing mortality in proportion to their total mortality (Table 6). -

30 also indicate the importance of a small amount of predation on groups with slow lifehistories: for example, in the WBS, a small proportion (0.1%) of toothed whales’ diet 

consists of Steller sea lions, and this shows up as a large negative effect—it is unclear if 

this interaction is overemphasized through the rounding up of this diet interaction to 

measurable levels. dition to predation pressure, some secondary competitive effects 

may occur. ple, jellyfish experience a positive effect from fisheries; this may 

result from fisheries removing the jellyfish’s competition for food. 

Impacted Group 

0.2 0.15 0.1 0.05 0

Detrital pool

Benthic detritus

Pelagic detritus

Phytoplankton

Copepods

Large Zoop.

Juv. pollock

P.herring

Forage fish

Cephalopods

P.salmon

Jellyfish

Epifauna

Infauna

Benthic amph.

C. bairdi

C. opilio

King crab

Shrimp

Adult pollock

P.cod

P.halibut

Greenland turb.

Arrowtooth fl.

Small flatfish

Skates

Sculp. & Rock.

Macrouridae

Zoarcidae

Baleen whales

Toothed whales

Sperm Whales

Walrus& B.seals

Seals

Steller s.lions

Marine birds

Fishery

0

0.05

0.1

Detrital pool

BenthicPelagicPhytoplankton

CopepodsLarge Zoop.Juv. pollockP.herringForage fishCephalopodsP.salmonJellyfish

EpifaunaInfaunaBenthicC. bairdiC. opilioKing crabShrimpAdult pollock

P.codP.halibutGreenland

Arrowtooth fl.

Small flatfish

SkatesSculp. &Macrouridae

ZoarcidaeBaleenToothedSpermWalrus&SealsSteller s.lions

Marine birds

Fishery

Impacting Group 

Figure 30. Trophic impact graph and impacting/impacted indices for each species in the WBS. See text 

for explanation of figure.

44 

The m

Figures 29

In ad

For exam
CONCLUSIONS 

Ecosystem maturity and development is not always straightforward to calculate 

between systems. Clearly, the EBS and WBS shelf/slope areas are dominated by 

differing production regimes. The WBS, with higher production (Tables 2-3) is a more 

active ecosystem on the lower trophic levels, with higher primary and secondary 

production. This is probably due to having a larger percentage of its area associated with 

the “green belt” of high production along the shelf break. 

However, this large energy supply does not translate into higher supported 

biomass for upper trophic levels. Our results point to the complexity of the broad shelf 

habitat in the EBS as supporting a more “mature” system, perhaps due to the relative 

stability of the oceanographic frontal structures in the EBS and sheer area of benthic 

habitat. 

This maturity is visible in the number of interconnections within the web, even if 

this is considered to be a sampling artifact, the suggestion of maturity is further supported 

by the relatively high proportion of its production that actually “supports” biomass, as 

seen from examining PPR values (Fig. 8) and the average transfer efficiency above 

Trophic Level 2 (13.5% in the EBS vs. 12.1% in the WBS). 

One fundamental difference in flow between the two systems occurs in the 

benthic web at Trophic Level 3: in the WBS, a tremendous amount of detrital energy is 

consumed by epifaunal species and passed out of the system through respiration, while in 

the EBS the small flatfish community provides a pathway between detritus and larger 

fish. If this pattern is not a data artifact, it may indicate that competition between small 

flatfish and epifauna has a strong structuring effect on the benthic community. The 

species composition of both groups (Table 5) is worth further investigation. Specifically, 

it is not clear if estimation methods for epibenthic biomass were comparable between the 

two systems. 

The other large area of uncertainty in the models is in the cephalopod groups: it 

is not clear if their dominant position in the WBS is due to the accounting of off-shelf 

(deep basin) food consumption; furthermore, estimates of their biomass in the EBS vary 

from 0.5-3 million t overall. Their role in both ecosystems is an important area for future 

research. 

The high consumption rates in some fish species in the WBS may be an artifact of 

the estimation method. It is possible that this is an accounting dichotomy: the estimates of 

consumption in the WBS were taken from daily ration estimations using field 

observations of stomach weight and evacuation rates while the EBS estimations generally 

came from bioenergetics models assessing minimum food requirements for observed 

growth. On the other hand, the low impact of jellyfish relative to their trophic level in the 

EBS suggests that jellyfish ration in the EBS may have been underestimated. 

Some of the differences in consumption rate estimation may simply shift the 

balance of the loss to the “balancing” loss term, Ecotrophic Efficiency (or “unexplained” 

mortality). The relative apportionment of dissipative characteristics of energy flow 

within the food webs into metabolic costs (respiration, including reproductive costs), 

unassimilated food, “other” mortality (disease, etc.), and bacterial recycling are difficult 

45 
to compare between the two systems as they primarily represent the “balancing” terms in 

the population level mass-balance. 

As such their measure is subject to considerable noise: this noise may create order 

of magnitude differences in estimates of “true” respiration or other loss which may not be 

captured in the Ecopath accounting methods. Particularly, it is not possible at this 

juncture to partition food web dissipation between detrital flows, recycled (bacterial) 

nutrients, and heat loss accurately. Considerably more work with bioenergetics is 

required as a next step. 

The appropriate apportioning of a species’ loss terms between respiration and 

unexplained mortality is one of the more important unexplored areas of Ecopath at this 

moment. While the accounting difference has little effect on the overall mass-balance of 

a “snapshot” of energy flows, the difference in apportionment will have a strong effect in 

dynamic simulations such as Ecosim—it is thought that the accounting methods used for 

many current Ecopath models may cause overoptimistic compensation in fished species 

when applied to dynamic predictions (Aydin and Friday 2001). On the other hand, it is 

possible that if the WBS is a more productive system overall, greater feeding levels may 

exist even if those are not translated into fish growth. 

Five functional groups: adult pollock, juvenile pollock, cephalopods, forage fish, 

and Pacific cod are important keystone predator and prey species in both systems. Two 

of these groups, forage fish and cephalopods, are aggregations of many species and 

existing data on their actual production rates are very poor. Investigating the dynamics of 

these forage species is a high priority for examining future fluctuations in predator stocks. 

Pacific cod are an important predator of both the benthic and pelagic food webs, and thus 

as a keystone species they represent a “uniting” of the two food webs. Overall, top fish 

predators (Greenland turbot, arrowtooth flounder and Pacific cod in particular) show 

indications of exerting more top-down control on pollock and other fish, when compared 

to with marine mammals. 

The most important next step in this work is the further geographical refinement 

of the models, especially with regard to basin versus shelf processes. In particular, until 

the keystone forage fish and cephalopod groups are broken into shelf and basin 

components in the predators’ diets, it will be hard to gauge the relative contributions of 

the many different regional environmental forcing factors. The develop of sub-regional 

ecosystem models using this common framework, with the addition of migration and 

relative area utilization across the Bering Sea basin and north shelf areas would lend 

greatly to continued investigations. 

46 
APPENDICES

47 
48 
APPENDIX A: WESTERN BERING SEA MODEL 

This Appendix describes the sources for all of the data used to construct the 

western Bering Sea shelf+slope+basin combined model covering all of the Bering Sea 

within the Russian EEZ (702,000 km2, dotted line in Fig. 1). A similar data summary for 

the eastern Bering Sea model may be found in Appendix 2 of Trites et al. 1999. The 

main input biological parameters for the western Bering Sea shelf+slope+basin combined 

model are presented in Appendix Table B3, and the diet matrix for the shelf+slope+basin 

model is shown in Appendix Table B5. Appendix Tables C1 and C2 show the 

conversion factors used to convert from the shelf+slope+basin model to the shelf+slope 

model described in the main body of the text. 

Table A1 shows the summary statistics, produced by Ecopath, calculated for the 

shelf+slope+basin. A more detailed treatment of the statistics for the shelf+slope only 

model is found in the Results and Discussion section of this report. 

Appendix Table A1. Basic output parameters calculated by Ecopath for the WBS Shelf+Slope+Basin 

combined model. 

Parameter Value Units 

Sum of all consumption 

Sum of all exports 

Sum of all respiratory flows 

Sum of all flows into detritus 

Total system throughput 

Sum of all production 

Mean trophic level of the catch 

Gross efficiency (catch/net prim. prod) 

Input total net primary production

Calculated total net primary production 

Unaccounted primary production

Total prim. prod./total respiration

Net system production 

Total prim. prod./total biomass 

Total biomass/total throughput

Total biomass (excluding detritus) 

Total catches

Connectance Index 

System Omnivory Index 

8319

123 

2451

4522

15415

5163

3.6 

0.000367

-

2,574 

-

1.05

123.14

6.39

0.026

403 

0.945 

0.168 

0.203 

t/km2/year 

t/km2

/year 

t/km2

/year 

t/km2

/year 

t/km2

/year 

t/km2

/year 

t/km2

/year 

t/km2

/year 

t/km2

/ 

t/km2

/year 

Parameter Sources by Functional Group 

For the groups listed below, all of the estimates of fishes include all age classes 

(ages 0+ and above). In the case of pollock, juvenile pollock consist of fish age 0+ to 1+, 

while adult pollock are age 2+ and older. The biomass of marine mammals includes all 

age groups; seabirds include all age groups excluding chicks; and benthic crustaceans 

include all age groups excluding planktonic larvae stages. 

49 
Fisheries catch statistics, including best estimates of discards, are presented in 

Appendix Table B3. It was difficult to estimate the bycatch of species that were 

completely discarded. Much of the catch of less valuable species is processed to produce 

a fish meal and are considered landings. Some groups (such as myctophids, skates, small 

sculpins) are often thrown overboard and not recorded. As a preliminary estimate, about 

half of “other small flatfishes” catch was considered discarded (0.001 t/km2

), “other 

pelagic” discards were set at 0.001 (mainly myctophids and capelin). For “skates”, the 

whole catch is discarded (0.021); for “sculpin and rockfishes”, 10% discard (0.004) was 

assumed for 90% landings (0.032). For “Macrouridae” and “Zoarcidae”, about one-third 

of each catch discarded: 0.014 landings and 0.007 discard for Macrouridae; and 0.013 

and 0.007 for Zoarcidae, respectively. 

Literature sources and estimation procedures for individual groups are as follows: 

Marine Mammals and Seabirds 

Baleen whales: This group of marine animals consists mainly of bowhead 

whales (Balaena glacialis), gray whales (Eschrichtius robustus), minke whales 

(Balaenoptera acutorostrata), fin whales (Balaenoptera physalus), and humpback whales 

(Megaptera novaeangliae). The basic parameters for baleen whales as well as for other 

mammals were found in Sobolevsky (1983); however, the estimates contained therein 

were for the whole Bering Sea. We used one-third of Sobolevsky’s estimations 

according to the proportion of areas of Russian EEZ and whole Bering Sea, 

approximately equal to 1:3 (702.2 / 2304). The diet and annual consumption were 

obtained from the same source, but the species composition of diet was reconstructed 

from reports on food supply structure changes (Borets and Dulepova 1985; Efimkin and 

Radchenko 1991; Radchenko 1992, 1994a; Shuntov and Dulepova 1995; Shuntov et al. 

1990). The P/B ratio was taken from Trites et al. (1999). 

Toothed whales: The toothed whale compartment is composed of killer whales 

(Orcinus orca), other toothed whales (e.g., Delphinapterus leucas), dolphins and 

porpoises (mainly Phocoenoides dalli and Phocoena phocoena) and beaked whales 

(Mesoplodon stejnegeri and Berardius bairdii) after Sobolevsky (1983). The estimated 

whale and dolphin abundance was compared with data from sea observations (Shuntov 

1993). All other parameters were extracted from Sobolevsky (1983), as were data for the 

separately grouped sperm whales (Physeter macrocephalus, with an addition from Bersin 

1971). 

Pinnipeds: Pinnipeds were placed in three functional groups: Steller sea lions 

(Eumetopias jubatus); Pacific walrus and bearded seals (Odobenus rosmarus divergens 

and Erignathus barbatus); and all other seals including northern fur seals (Callorhinus 

ursinus), Phoca vitulina, Phoca larga, Phoca fasciata, and Phoca hispida. 

The diet compositions of seals and sea lions were difficult to obtain. Sobolevsky 

(1983) writes: “...Fur seals feed mainly on lower value fishes such as pollock, sand 

lance, lanternfishes and Atka mackerel. At the same time, there were found Pacific 

salmon in the stomachs of the seals killed on Commander Islands. In several seasons 

50 
weight share of salmon in the seals’s stomachs can reach 24.5%. However, as supposed 

by Panina (1970), these fishes look to be a temporary item in the seal’s diet...”. 

Finally, Sobolevsky concluded that annual ration of fur seals consists of fishes 

(80%) and cephalopods (20%). Unfortunately, there were not any quantitative data 

regarding composition of “fishes” group in his paper, excluding presented above citation. 

Data of Panina (1970) were collected near Commander Islands in 1965-1968 and, thus, 

do not satisfy the necessary time limits. The most recent monograph of Kuzin (1999) 

contains only general information about seals diet composition in the WBS. He 

mentioned that the proportion of fish in the seals’ ration amounts to 75% of the wet 

weight without any comments regarding species composition of prey and proportion of 

their weights. For this model, seal diet was spread among several candidate fish groups. 

A similar situation arose regarding sea lion diet composition. Sobolevsky noted 

that sea lions feed mainly on pollock, herring, large flatfishes, Atka mackerel and in 

several years, salmon. Overall he reports a diet composed of fishes (about 80%), 

cephalopods (17%) and other prey items (decapods < 3%). We could not find more 

accurate and detailed information. 

Seabirds: This group consists of both migrating and settled species. Seabird 

abundance was calculated by assuming a time of residence for each species in the western 

Bering Sea by averaging the individual weight and number of birds separately for cold 

and warm seasons. Food consumption was similarly weighted by residence time. Basic 

parameters we applied were taken from Artyukhin (1991), Kondratiev (1992), Schneider 

and Shuntov (1993), Shuntov (1988a, 1988b, 1998), Smirnov and Velizhanin (1986), 

Springer and Byrd (1989), Vyatkin (1986), Vyatkin and Artyukhin (1994); P/B ratios – 

from Trites et al. (1999). 

Fish and Cephalopods 

Adult pollock and juvenile pollock: Walleye pollock (Theragra chalcogramma) 

were the most common groundfish in the Bering Sea during the 1980s. The basic 

characteristics came from Shuntov (1991), Shuntov et al. (1993), Radchenko (1994a), 

with some information from Balykin (1992), Kachina and Savicheva (1987), Livingston 

(1989), Mito (1990), Markina (1987), Okada (1986), Volkov et al. (1990). However to 

balance a model we had to decrease Q/B for adult and juveniles from 13 and 20 as in 

Shuntov et al. (1993) to 10 and 13, respectively. 

Pacific cod: In the 1980s, Pacific cod (Gadus macrocephalus) was the most 

numerous demersal fish and main consumer of pollock and benthos on the Bering Sea 

shelf (Borets 1997). Borets (1990, 1997) estimated cod biomass in Russian EEZ as 

900,000 metric tons (t). Diet composition and annual consumption were taken from the 

same source with corrections from Moiseev (1953) and Tokranov (1986), P/B came from 

Dulepova and Borets (1994). 

Pacific halibut: The biomass (0.049) and catches (0.005 t/km2

) of Pacific halibut 

(Hippoglossus stenolepis) were obtained from TINRO (1986-97) P/B came from 

Dulepova et al. (1984). Daily ration was estimated as 1.95% body weight/day 

(Chuchukalo, personal communication) in the fall, but we decreased it because of winter 

51 
abatement in feeding intensity (Novikov 1974). The final annual Q/B was assessed as 

3.5/year. 

Arrowtooth flounder and Greenland turbot: Data on biomass and catches of 

Atheresthes stomias and Reinhardtius hippoglossoides were obtained from TINRO 

(1986-97) with corrections from Fadeyev (1986). P/B was calculated by Dulepova et al. 

(1984). Diet composition was found in Novikov (1974) with corrections by Chuchukalo 

(personal communication). 

Small flatfish: Biomasses of flathead sole (Hippoglossoides elassodon), 

yellowfin sole (Pleuronectes asper), rock sole (P. bilineatus) and Alaska place (P. 

quadrituberculatus) were obtained from Borets (1990, 1997) with corrections from 

TINRO (1986-97) and Lapko et al. (1999). We applied Q/B after Borets (1990), and P/B 

after Dulepova et al. (1984). Other small flatfishes consisted mainly of Pleuronectes 

sakhalinensis and P. proboscideus. Basic parameters for these species were taken from 

the same source. As the EE of small flatfishes was calculated to be near 1.0 in the initial 

model, we set EE = 0.95 and got B other small flatfishes = 0.049 t/km2

. 

Pacific herring: According to Radchenko (1994a), in the 1980s Pacific herring 

(Clupea pallasi) biomass in the Russian EEZ of the Bering Sea was near 200,000 t. 

Taking into account coastal waters inside of 12–miles zone and Naumenko’s estimations 

(Naumenko et al. 1990), we increased biomass of herring up to 250,000 t. Diet 

composition, Q/B, and P/B we also took from Radchenko (1994a) with achievement data 

from Kachina (1981). 

Pacific salmon: This group consists of pink salmon (Oncorhynchus gorbuscha), 

chum salmon (O. keta), sockeye salmon (O. nerka), coho salmon (O. kisutch) and 

chinook salmon (O. tshawytscha). For estimation of the average biomass of these fish, 

we assumed that 120,000-140,000 t of pink salmon were resident in the western Bering 

Sea for 4 months, 60,000 t of chum salmon were resident for 6 months and 50,000 t of 

other salmon were resident for 6 months. Data on Pacific salmon abundance and the 

Bering Sea residence were received from Karpenko (1998); Radchenko (1994b); 

Sobolevsky et al. (1994). So, average annual biomass can be calculated as following: 

140×1/3 + 60×1/2 + 50×1/2 ≈ 100,000 t. We estimated P/B and Q/B from Radchenko 

(1994a). Salmon food composition and diet ration estimations were taken from the same 

sources with addition of information from Ito (1964), Pearcy et al. (1988), and Volkov 

(1994). 

Skates: Data about skate (Rajidae) biomass and diets were obtained from Borets 

(1990, 1997), Dulepova and Borets (1984), and P/B from Trites et al. (1999). 

Sculpins and rockfishes: Such widely distributed and relatively numerous 

species as Myoxocephalus polyacanthocephalus, M. jaok, Hemilepidotus gilberti, 

H.jordani, Gymnacatthus spp., Sebastes spp. compose this group. According to Borets 

(1990, 1997) the total biomass of these fishes was about 250,000 t, with a Q/B = 3.5. We 

used P/B ratio from Trites et al. (1999). There was no targeted fishery on these groups 

(except for rockfishes); they were usually caught as bycatch (TINRO 1986-97). 

Macrouridae and Zoarcidae (grenadier and eelpouts): Mainly deepwater and 

locally abundant fishes. Albatrossia pectoralis, Coryphaenoides cinereus, Lycodes spp., 

52 
Lycogramma spp. make up the majority of these groups. We used the data regarding 

abundance from Borets (1997) and TINRO 1986-97. Q/B ratios were calculated using 

daily rations determined by Chuchukalo et al. (1989, 1990). P/B is assumed to be equal 

to 0.3 based on Dulepova et al.(1984). 

Forage fish (“other pelagic fish”): This forage fish group contained both 

pelagic and mesopelagic species, including capelin (Mallotus villosus), sandlance 

(Ammodytes hexapterus), Atka mackerel (Pleurogrammus monopterygius), Polar cod 

(Boreogadus saida), lanternfish (Myctophidae) and bathylagids (Bathylagidae). The 

main portion of total group biomass is composed of mesopelagic fishes – approximately 

6 million t (Shuntov et al. 1988, 1993). Information on their diet composition was taken 

from Balanov and Ilyinsky (1992), Balanov et al. (1994), Gorbatenko and Ilyinsky 

(1991). Data about other fishes’ biomasses were also taken from Radchenko (1994a) and 

TINRO 1986-97. As the EE of other pelagics was above 1.0 initially, we set EE = 0.95 

and got B (other pelagics) = 9.685 t/km2

. 

Cephalopods: Biomass, P/B, Q/B and diet information were obtained from 

Radchenko (1992, 1994a) with some corrections from TINRO 1986-97. As assumed in 

Trites et al. (1999), we considered the Gonatidae squids, especially Berryteuthis magister 

as the most abundant squid in the Bering Sea overall. 

Benthic Invertebrates 

Crabs: The main sources of information regarding commercially valuable crabs 

(Chionoecetes opilio, C. bairdi, Paralithodes platypus) were the results of three trawl 

surveys conducted in 1985-1988 by RVs Tamga, Gornyi, and Donchak, for which data 

are contained in the TINRO (1986-97) documents. Composition of the diet was obtained 

from Tarverdieva (1979, 1981) and Nadtochyi et al. (1999). P/B and Q/B ratios were 

used from Dulepova et al. (1984), Borets and Dulepova (1985) and Trites et al. (1999). 

Shrimp: The most numerous species that made up this group were Pandalus 

goniurus and P. borealis. It is very difficult to estimate these species’ biomass precisely 

by trawl surveys because of the wide range of vertical migration and interannual stock 

fluctuations. Besides, demersal shrimps such as Sclerocrangon spp., Crangon spp., and 

Nectocrangon spp. were also included into this group, for which biomass information is 

poorly known. So, we accepted the biomass to be equal to about 0.974 t/km2

 to balance 

the WBS model (with EE = 0.95 for this group). 

Infauna: As in Trites et al. (1999), we accepted an infauna to be composed of 

clams, polychaetes and other worms (Appendix Table A2). Estimation of clam and 

polychaete biomass was made according to Volkov (1986), other worms – Lus and 

Kuznetsov (1961), Sagaydachnyi and Chistikov (1987). There are not any precise data 

regarding P/B and Q/B ratios of the Bering Sea’s infauna. Approximate estimates of P/B 

for clams were made from Warwick and Price (1975), Banse and Mosher (1980), Zaika 

(1983), Asmus (1987), for polychaetes – Warwick and Price (1975), Bagheri and 

McLusky (1982), Zaika (1983), Asmus (1987), Rainer (1991), for other worms – Banse 

and Mosher (1980), Bagheri and McLusky (1982), Asmus (1987) taking into account 

species composition of these hydrobionts and a latitude of their habitat. We also used 

53 
Q/B ratios from Trites et al. (1999). Diet of these animals consists of detritus (100%). 

No commercial fishery is known in the western Bering Sea concerning these groups. 

Epifauna: The groups assessed by Trites et al. (1999) as epifauna (hermit crabs, 

snails, brittlestars and starfishes), accounted for only 13% of the epifauna biomass in the 

western Bering Sea (Appendix Table A2). The other 87% consists of barnacles (27%), 

sea urchins (37%), holoturias (6%), ascidias (11%), actinias (5%) and spongias (2%). 

Biomass of these hydrobionts, excluding hermit crabs, has been estimated according to 

Volkov (1986). Hermit crab abundance was roughly assessed after Filatova and 

Barsanova (1964). 

Appendix Table A2. Detailed information on ECOPATH parameters for benthic infauna and epifauna 

“In” – Infauna; “Epi” - Epifauna.; "?" – no data. Bold fonts indicates groups included by Trites et al. 

(1999) into the eastern Bering Sea model. 

* Group 

B 

(t/km2

) 

P/B 

(1/year) 

Q/B 

(1/year) 

Catch 

(t/km2

) 

In 

In 

In 

Epi 

Epi 

Epi 

Epi 

Clams 

Polychaetes 

Other worms 

Hermit crabs 

Snail 

Brittlestar 

Starfish 

118.59 

55.5 

3.42 

1.37 

0.86 

9.99 

0.66 

1.47 

2.97 

2.23 

0.82 

1.81 

1.21 

1.23 

12.00 

12.00 

12.00 

8.00 

8.00 

5.00 

5.00 

0.0000 

0.0000 

0.0000 

0.0000 

0.0023 

0.0000 

0.0000 

Epi 

Epi 

Epi 

Epi 

Epi 

Epi 

Urchins 

Holoturia 

Barnacles 

Ascidia 

Actinia 

Spongia 

36.34 

6.10 

26.24 

10.57 

4.45 

2.27 

0.61 

0.26 

0.95 

3.58 

? 

? 

5.00 

5.00 

8.00 

? 

? 

? 

0.0019 

0.0000 

0.0000 

0.0000 

0.0000 

0.0000 

We could not locate exact data for production, P/B and Q/B, for the Bering Sea 

epifauna. Rough estimates of P/B for hermits were made by Volvenko (1995), Dulepov 

(1995), for urchins – by Banse and Mosher (1980), Zaika (1983), for barnacles – by 

Zaika (1983), Asmus (1987), for snails, sea stars and ascidias – by Asmus (1987), for 

brittlestars and holoturias – by Zaika (1983), taking into account species composition of 

these hydrobionts and a latitude of their habitat. P/B of actinias and spongias are 

unknown. Q/B of all crustaceans composing epifauna may be accepted to be equal to 8.0, 

and all Echinodermata equal to 5.0, as in Trites et al. (1999). There are not ideas 

regarding ascidias, actinias, and spongias. The food habits of snails, brittlestars, 

holoturias and hermits was assessed from Sokolova (1957), Tabunkov and Chernysheva 

(1985), Volvenko (1994), and Tsyhon-Lukanina (1982). Data for the fisheries catch of 

snails and urchins were obtained from TINRO (1986-97); other groups were not fished. 

To balance the shelf/basin model from these initial estimates, a weighting of the 

overall model area by shallow and deep-sea regions in the western Bering Sea resulted in 

decreasing the biomass of clams and polychaetes by a factor of 3. The biomass of 

urchins, holoturias, barnacles, ascidias, actinias, and spongias was grouped into “other 

benthos”, and the initial biomass estimate (85.97 t/km2

) was decreased by 25%. This 

adjustment was made due to the following consideration: Assessment of the benthos 

54 
biomass was made over the shelf and continental slope area only. Shelf+slope area 

composes about one-third of the WBS region (if to be precise, 254,200 km2

 from 

702,200 km2 is 36%). So, we assumed that such groups as clams and polychaetes are very 

scarce in deep basins and took a third of their abundance. On the other hand, the groups 

forming “other benthos”, especially holoturias and spongias, are known to inhabit a deepsea zone and they may be even quite abundant there (although there are no proper 

quantitative data). Therefore, we decreased a biomass by 25%, although to take a half is 

also looking appropriate, as deep-basin processes are not fully detailed in this model. 

Zooplankton 

Copepods, euphausiids, and chaetognaths are the most abundant zooplankton in 

the Bering Sea. Amphipods (mainly hyperiids), mysids, ostracods, cladocerans, jellyfish, 

comb jellies, tunicates, pteropods and heteropods all play an important role in trophic 

structure of planktonic communities due to high abundance and wide distribution 

(Raymont 1988). Additionally, about 70-80% of benthic animals have a pelagic larvae, 

the so-called meroplankton (Mileykovsky et al. 1977). 

Total plankton biomass per square meter in the western Bering Sea (for the upper 

200 m of the water column), amounts to 62 g/m2

 in winter; 135 g/m2 in spring; 179 g/m2 

in summer; and 125 g/m2

 in autumn (Shuntov et al. 1993). A seasonal maximum of 

zooplankton biomass in the upper pelagic layer was usually observed in May – June 

owing to planktonic animals’ reproduction and their lifting from mesopelagic layers 

(Tseytlin et al. 1994). For the 1980s, total zooplankton biomass was assessed at 103–401 

million t for different seasons in the Bering Sea epipelagic layer, and at 453–601 million t 

for the water column overall (Shuntov et al. 1993, Shuntov and Dulepova 1995). The 

average annual zooplankton biomass was estimated at 500 million t (Radchenko 1994a). 

Production was calculated for euryphagous and predatory zooplankton based on 

data on planktonic communities composition and generalized P/B – ratios for these 

groups. Chaetognaths (mainly Parasagitta elegans), hyperiids (mainly Themisto 

japonica, T. libellula) and gelatinous zooplankton have been regarded as predatory group 

(Dulepova 1993, 1994; Shuntov et al. 1993; Shuntov and Dulepova 1995). 

Copepods: Copepods constituted the major portion of planktonic crustaceans – 

102.18 t/km2

 (Efimkin and Radchenko 1991, Shuntov et al. 1988, Volkov and Efimkin 

1990, Dulepova 1993). Diet composition was taken from Raymont (1988), Pavlutin 

(1987), Beklemishev (1954). Although this group’s biomass composed of mainly such 

large species as Neocalanus plumchrus and N. cristatus, a significant portion of the 

produced organic substance is contributed by small copepods (Oithona similis, 

Pseudocalanus minutus), species with a high growth rate and therefore high P/B ratios 

(Kozhevnikov 1979, Andreeva 1977). So we accepted P/B = 9.5. 

Euphausiids: Euphausiid abundance has been regularly estimated during marine 

surveys (Efimkin and Radchenko 1991, Shuntov et al. 1988, Volkov and Efimkin 1990). 

Taking into account the square of whole Russian EEZ and that these crustaceans inhabit 

not only in the epipelagic layer but also deeper, we assumed a biomass of 30.44 t/km2

. 

55 
The P/B ratio for euphausiids was calculated by Pogodin (1990) as 1.55 in the 

Tatarsky Strait (Sea of Japan). However, it was not enough to balance the model, so we 

set EE = 0.95, which increased the annual P/B up to 3.129. Diet composition of this 

group was taken from Ponomareva (1990). Total Q/B was determined to be17 using a 

K2 = 0.35, U=0.5. 

Mysiids: Mysiids composed a small portion of zooplankton in the western Bering 

Sea. For its parameters, both euphausiids (P/B) and chaetognaths (Q/B) were used as a 

rough estimate. 

Amphipods and Chaetognaths: The amphipods group consists of planktonic and 

bottom amphipods. The biomass of planktonic amphipods varied considerably by 

season: in fall – 0.4–18.3 t/km2

, in winter – 0.3-6.5, in spring-summer – 0.6-17.8 

(Efimkin and Radchenko 1991, Shuntov et al. 1988, Volkov and Efimkin 1990). Overall 

the biomass averaged 15.22 t/km2

. The abundance of bottom amphipods was taken for 

shelf region from Belyaev (1960) and Lus (1970) – 14 t/km2 and decreased down to 

5 t/km2 because of deep-sea areas (as was the case with clams and polychaetes). Thus, 

total biomass of amphipods was estimated to be 20.22 t/km2

. 

The P/B ratio varies from 1.5 for pelagic amphipods (Dulepova 1991) to 7.4 for 

bottom ones (Dulepov 1995) and averaged 2.5/year. Diet composition was determined 

by Raymont (1988) and Sheader and Evans (1975). The annual consumption of food was 

calculated using net growth efficiency (K2 = 0.35) and digestion efficiency (U = 0.5) in 

equation C = P/K2/U, where C – ration, P – production. 

Chaetognaths were very abundant in the plankton data – the second after 

copepods (Efimkin and Radchenko 1991, Shuntov et al. 1988, Volkov and Efimkin 1990, 

Dulepova 1993, Kotori 1976), though its portion varied from 0.6% in summer to 40% in 

fall of the average zooplankton biomass. Chaetognaths are typical predators (Terazaki 

1998, Slabinsky 1982, Kosihina 1982) and feed on abundant planktonic animals. Ration 

was determined as 10% of body weight while feeding one time per 3 days (Fraser 1969, 

Wimpenny 1937), so daily diet is about 3.3%, annual Q/B – 12/year. 

It is known that chaetognaths, especially Sagitta spp., are often mentioned as 

eating fish eggs and larvae and it has been assumed that chaetognaths predate on pollock 

juveniles. However, accurate analysis revealed no direct records of predation on pollock 

juveniles by chaetognaths or amphipods. Such fish juveniles as anchovy, herring, sardine 

and simply “fish larvae” are recorded as prey, but never pollock. Furthermore, fish 

larvae are always noted as secondary and temporary preys in the food of chaethognaths in 

comparison to copepods. So, we presumed that chaetognaths should be considered as 

competitors rather than predators for juvenile pollock, and removed pollock from the list 

of food items to balance the model. Furthermore, amphipods usually feed on the dead 

bodies of hydrobionts including fishes: no predation on live fish juveniles is recorded. 

Gelatinous plankton: This group contains comb jellies (Ctenophora) and hydroid 

medusae, with the latter (mainly Aglanta digitale) composing a major portion. The total 

averaged biomass of this group is about 10.5 t/km2

. Because of high rate of growth 

(Timokhina 1968) we accepted P/B = 5. Diet composition was taken from Bamsted 

(1990). For annual consumption estimation, we applied the method shown under 

amphipods. 

56 
Jellyfish: Estimation of jellyfishes’ biomass has been made based on both 

pelagic and bottom trawl survey results (Shuntov et al. 1996). The most abundant species 

among jellies is Chrysaora melenaster. The total biomass of jellyfishes according to our 

data reaches 0.5 t/km2

, P/B ratio is about 1.5 (Zaika 1983). We have calculated an annual 

consumption and diet composition with the help of our own data (using production and 

K2) and literature sources (Mironov 1987, Raymont 1988, Fancet 1988). 

Protozoa 

This group was composed of bacteria and protozoa. Bacterial bioactivity was 

considered to include tripton (suspended particulate organic matter, or POM), dissolved 

organic matter, and bottom sediments resulting from planktonic ecosystem metabolism 

(Sorokin 1985). Bacteria also synthesize primary production through the oxidation of 

inorganic matter (chemosynthesis). Bacterioplankton of Far-Eastern seas remains poorly 

studied. Available data were primarly collected during the summer and autumn. 

Biomass of bacteria was estimated from Sorokin et al. (1995) and averaged as 15 g/m2

. 

The decline of bacterial production during the winter and early spring 

undoubtedly occurs. The vertical distribution of bacterial biomass is characterized by 

three peaks: in the surface layer, near the pycnocline and on the bottom. In the summer, 

the maximal bacterial productivity occurs above the thermocline. In the cold 

intermediate layer, the bacterial bioactivity is low despite the average level of their 

biomass there. We presume that 80% of bacterial primary production is synthesized 

during the summer and autumn, 5% - during winter, 15% - during spring. Daily P/B does 

not exceed 0.1, so annual P/B is about 36.5. 

The microzooplankton group is formed by protozoa (zooflagellates, infusoria, 

amoebas, etc.) and small pluricellular zooplankton (rotifers, early stages of 

appendicularians and crustaceans). Infusoria and zooflagellates absolutely predominate 

in microzooplankton composition in quantitative ratio (Raymont 1988). In ecosystem 

structures, protozoa can be regarded as an important intermediate trophic link between 

bacteria and small phytoplankton fractions, from one side, and mesozooplankton, from 

the other side. Fish larvae and predatory zooplankton, also feed on protozoa. 

Protozoa biomass including zooflagellates varied from 4 to 6 g/m2

, daily P/B = 

0.2-0.6 (Sorokin 1995). So the total biomass of the whole group was about 20 t/km2

, 

annual P/B = 47. Protozoa have close trophic linkages to bacteria and their distribution is 

rather similar. Usually, the protozoa concentrated near the sea surface and thermocline 

layer to depths of about 30 m (Sorokin 1995, Moiseev 1987). Annual Q/B was calculated 

as 2,848 t/km2 assuming K2 = 0.55, U = 0.6. 

Phytoplankton 

Many issues of phytoplankton biology and ecology remain poorly studied due to 

methodological and technical difficulties of the research. Not only nanoplankton (cell 

size at 2 – 30 μm) but also larger algae filter through the planktonic nets used in marine 

expeditions. Until recently, the smallest and most active fraction of phytoplankton (so 

57 
called picoplankton) remained beyond the view of researchers.. However, these smallest 

algae fractions include many systematic groups (blue-green, yellow-green, cryptomonadic, and diatom algae, dinoflagellates, etc.) that play an exceptionally important role 

in the primary production of organic matter due to their high abundance and growth rate 

(Raymont 1988; Vinogradov and Shushkina 1987). 

The most important Bering Sea phytoplankton species is Thalassiosira 

nordenskioldii, which can contribute up to 70% of the total phytoplankton biomass in the 

spring (Semina 1981). Additional important species include: Thalassiosira gravida, T. 

rotula, Fragilaria oceanica, Chaetoceros furcellatus, C. socialis, Bacterosira fragilis, 

Amphiprora hyperborea, Biddulphia sinensis, and Rhizosolenia spp. 

During late autumn and winter, phytoplankton is not abundant in the Bering Sea 

(Geinrikh 1959, Lapshina 1998). However, biological processes do not tail away 

completely even in these northern latitudes. Glacial forms of algae that develop on the 

ice underside mainly consist of diatom species. Chlorophyll A concentrations range from 

7-60 mg/m3

 here, considerably higher than winter pelagic phytoplankton. Glacial algae 

contribution is estimated at 9-10% from annual primary production in the Bering Sea, 

whereas winter phytoplankton contributes 2% only (McRoy and Goering 1976). 

The phytoplankton bloom begins in the western Bering Sea immediately near the 

ice break in April. At this time, developing vertical water stratification, significant 

nutrient supply, longer day-time duration, and decreasing salinity in the upper layers 

make favorable conditions for planktonic algae growth (Mordasova 1994, Sapozhnikov et 

al. 1995a). Primary phytoplankton production totaled 25 gC/m2

 for the algae bloom 

period in the outer shelf and upper continental slope regions (e.g., in Karaginsky and 

Oljutorsky Bays). In the Bering Sea offshore waters, primary production is noticeably 

less – 1-5 gC/m

2

 in spring. Later, nutrients concentrations are rather depleted. About 

20% of primary production are originated owing to nutrients re-cycling. 

Vertical phytoplankton distribution must be considered for the correct assessment 

of primary productivity. Studies of 1987-1990 show that summer penetration of large 

diatom phytoplankton in deeper layers can be regarded as a rule for the Bering Sea. In 

the upper layers, it is replaced by small diatoms and dinoflagellates, and sometimes by 

yellow-green and other algae groups. However, large diatoms save photosynthetic 

bioactivity in deeper layers (20-70 m). These aggregations on the pycnocline board 

produce 20-25% from total primary production of phytoplankton (Sapozhnikov 1995; 

Sapozhnikov et al. 1995a, 1995b). 

Most published estimations of daily and annual phytoplankton primary production 

range between 0.4-1.0 gC/m2

 per day and 1.9-4.8×108 metric tons of C per year (McRoy 

and Goering 1976, Tsyban et al. 1987, Tsyban and Korsak 1987, Nezlin et al. 1997). 

Ivanenkov (1961) has found from diurnal dynamics of oxygen concentrations that daily 

primary production varies in limits of 1.2-9.5 gC/m

2

 in spring and 1.1-3.5 gC/m

2

 in 

summer. Total primary production amounts to 387 gC/m

2

, or 8.74×108 tC. These 

estimations are confirmed by results of modern hydro-chemical research, which estimate 

annual primary production levels between 276-336 gC/m

2

, or 6,4-7,8×108 tC 

(Sapozhnikov and Naletova 1995). Shuntov and Dulepova (1995) concluded that the 

58 
annual primary production in the Bering Sea could be characterized as near 420 gC/m2 

when the contributions of macrophytobenthos and periphyton are included. 

To convert phytoplankton biomass from gC to wet weight, we applied a 

proportion from Trites et al. (1999): “...assuming 0.4 g C per g dry weight and 0.5 g dry 

weight per g wet weight” (p. 86), that in total results this ratio to be equal to about 5. 

Russian scientists usually use greater values. For example, Sorokin (1999) used a ratio of 

16.5 (averaged), Shushkina and Vinogradov (1988) used 16.7, while Moiseev (1989) and 

Gershanovich and Muromtsev (1982) used a ratio of 20. Detailed information was found 

in the last cited paper only (Appendix Table A3). Using these tables, it can be concluded 

that about 0.5 g C is in 1g of dry weight and 0.1 g of dry weight is in 1 g of wet weight, 

which results in a ratio of 20. 

Appendix Table A3. Reference values for phytoplankton conversions. 

(A) Composition (%) of wet substance according to Bogorov (1974). 

Phyto- Phyto- Zoo- Zoo- Nekton 

plankton benthos plankton benthos 

Water 80 80 80 63 73 

Organic substance 11 15 18 14 24 

Ashes 9 5 2 23 3 

(B) Elemental composition of some water plants (% of de-ashed substance) found in Muromtsev (1982). 

Green algae 

Zostera spp. 46.11 7.12 43.26 3.4 0.50 

Groups C H O N P 

Diatoms 50.54 10.21 28.83 7.0 1.55 

Peridinias 48.12 7.50 33.85 10.40 0.80 

54.55 7.54 31.21 7.7 2.94 

Phytoplankton biomass can be calculated from Lapshina’s (1998) data on 

seasonal dynamics of “net” fraction (i.e., microalgae kept by planktonic nets). Averaged 

value of “net” phytoplankton amounts to 14.7 g/m2

 for shelf and slope areas and 5.0 g/m2 

for offshore waters. Maximal averaged estimations of phytoplankton biomass have been 

given for June as 100 and 15 g/m2

 for shelf and offshore areas, respectively (Ventzel et 

al. 1995). In this paper, the portion of microalgae from total phytoplankton biomass is 

estimated at 98% in shelf and slope areas and 53% for deepwater basins. It allows 

assessing of annual value of averaged phytoplankton biomass as 15.0 and 9.3 g/m2

 for the 

two regions, or 11.0 g/m2 for the western Bering Sea overall. If the mean estimation of 

primary production is about 306 gC/m2 (Naletova and Sapozhnikov 1995), it means about 

1,530 t/km2

 (wet weight) per year. In this case, P/B – ratio for phytoplankton reached 

210/year. We increased this value by about 11% to 234/year to balance the model with a 

phytoplankton EE of 0.85—the extra 0.15 of “lost” production was required to satisfy 

benthic detrital demands. 

59 
APPENDIX B: ALL MODEL INPUT TABLES 

Appendix Table B1. ECOPATH input parameters describing the 38-functional group 1980s eastern 

Bering Sea (EBS) shelf+slope ecosystem (485,000 km2

). See Trites et al. (1999) for parameter references. 

Biomass and catch estimates are in t/km2

, Production/Biomass (P/B) and Consumption/Biomass (Q/B) are 

rates (1/year); Ecotrophic Efficiency (EE), Conversion Efficiency (PC) and and Unassimilated 

Consumption (Unassim) are proportions. Blank cells were estimated by the model: gray cells are not 

applicable to the given group. 

Group Biomass P/B Q/B EE PC Unassim Catch 

1 Baleen whales 0.245 0.02 8.032 0.2 0 

2 Toothed whales 0.017 0.02 13.753 0.2 0 

3 Sperm whales 0.208 0.02 4.553 0.2 0 

4 Walrus & bearded seals 0.159 0.06 10.687 0.2 0.009 

5 Seals 

6 Steller sea lions

7 Seabirds 

8 Adult pollock

9 Juvenile pollock

10 Pacific cod 

11 Pacific halibut

12 Greenland turbot

13 Arrowtooth flounder

14 Small flatfish 

15 Skates 

16 Sculpins 

17 Sablefish 

18 Rockfish 

19 Macrouridae 

20 Zoarcidae 

21 Tanner crab

22 Snow crab

23 King crab 

24 Shrimp

25 Epifauna

26 Infauna 

27 Benthic amphipods 

28 Pacific herring

29 Pacific salmon 

30 Cephalopods 

31 Forage fish

32 Jellyfish 

33 Large Zooplankton 

34 Copepods 

35 Phytoplankton 

36 Pelagic detritus 

37 Benthic detritus 

0.056 0.06 17.278 0.2 0.001 

0.008 0.06 12.703 0.2 0 

0.006 0.8 60 0.2 0 

27.451 0.5 2.64 0.2 2.08 

6 2.5 0.3 0.2 0 

2.421 0.4 2.04 0.2 0.151 

0.14 0.4 2.49 0.2 0.003 

0.96 0.4 2.04 0.2 0.077 

0.8 0.4 2.92 0.2 0.021 

9.181 0.4 2.968 0.2 0.326 

0.288 0.4 2.56 0.2 0.018 

0.555 0.4 2.56 0.2 0.017 

0.11 0.4 2.49 0.2 0.005 

0.094 0.4 2.49 0.2 0.003 

0.203 0.4 2.49 0.2 0.006 

0.64 0.6 2.49 0.2 0.006 

0.6 1 5 0.2 0.019 

1.6 1 5 0.2 0.049 

0.6 0.6 5 0.2 0.042 

10.2 0.9 0.2 0.2 0 

5.858 1.578 5.777 0.4 0 

46.5 1.373 11.226 0.4 0 

3.5 22 0.9 0.4 0 

0.779 1 3.65 0.2 0.055 

0.052 2.4 20 0.2 0.094 

3.5 3.2 0.3 0.2 0.007 

0.8 3.65 0.9 0.2 0 

0.048 0.875 2 0.2 0 

44 5.5 22 0.2 0 

55 6 22 0.2 0 

0 

0 

0 

11.765 170 

38 Detrital pool(*) 0 

(*) 100% of all detritus from living groups flowed into Group 38, the Detrital pool. From this pool, detritus 

moved to either benthic or pelagic detritus depending on demand for each group: 43.2% went to pelagic, 

56.8% to benthic. 

60 
Appendix Table B2. ECOPATH input parameters describing the 36-functional group 1980s western 

Bering Sea (WBS) shelf+slope ecosystem (254,000 km2

). See Appendix A for parameter references. 

Biomass and catch estimates are in t/km2

, Production/Biomass (P/B) and Consumption/Biomass (Q/B) are 

rates (1/year); Ecotrophic Efficiency (EE), Conversion Efficiency (PC) and and Unassimilated 

Consumption (Unassim) are proportions. Blank cells were estimated by the model: gray cells are not 

applicable to the given group. 

Group Biomass P/B Q/B EE PC Unassim Catch 

1 Baleen whales 0.391 0.02 8.312 0.2 0.007 

2 Toothed whales 0.042 0.02 17.5 0.2 0 

3 Sperm whales 0.02 0.02 9.8 0.2 0 

4 Walrus & bearded seals 0.262 0.06 13.9 0.2 0.006 

5 Seals 

6 Steller sea lions

7 Seabirds 

8 Adult pollock

9 Juvenile pollock

10 Pacific cod 

11 P.halibut

12 Greenland turbot

13 Arrowtooth flounder

14 Small flatfish

15 Skates 

16 Sculpins & Rockfish

17 Macrouridae

18 Zoarcidae 

19 Tanner crab

20 Snow crab

21 King crab

22 Shrimp

23 Epifauna

24 Infauna 

25 Benthic amphipods 

26 Pacific herring

27 Pacific salmon 

28 Cephalopods 

29 Forage fish

30 Jellyfish 

31 Large Zooplankton 

32 Copepods 

33 Phytoplankton

34 Pelagic detritus 

35 Benthic detritus 

0.097 0.06 13.34 0.2 0.002 

0.035 0.06 18 0.2 0 

0.01 0.8 87 0.2 0 

15 0.5 10 0.2 1.051 

3.757 2.5 13 0.2 0 

3.187 0.521 3.3 0.2 0.226 

0.083 0.25 3.5 0.2 0.01 

0.058 0.2 3.6 0.2 0.01 

0.052 0.32 4.5 0.2 0.007 

0.992 0.288 6.849 0.2 0.041 

0.271 0.4 4 0.2 0.041 

0.677 0.4 3.5 0.2 0.07 

1.156 0.3 3.7 0.2 0.041 

0.9 0.3 2.52 0.2 0.039 

0.083 0.8 5 0.2 0 

0.249 0.8 5 0.2 0.006 

0.119 0.6 2.7 0.2 0.008 

2.04 10.2 0.9 0.2 0.002 

114.962 1.159 5.087 0.4 0.004 

125.687 1.97 12 0.4 0 

13.812 2.5 14 0.4 0 

0.787 0.7 14.6 0.2 0.055 

0.039 4 16 0.2 0.012 

4.83 3.2 10.67 0.2 0.02 

0.95 3.5 0.9 0.2 0.001 

1.4 1.5 3 0.2 0 

120.74 4.399 14.457 0.2 0 

122.62 9.5 26.2 0.2 0 

0 

0 

0 

15 234 

36 Detrital pool(*) 0 

(*) 100% of all detritus from living groups flowed into Group 38, the Detrital pool. From this pool, 

detritus moved to either benthic or pelagic detritus depending on demand for each group: 35.6% went to 

pelagic, 64.4% to benthic. 

61 
Appendix Table B3. ECOPATH input parameters describing the 1980s western Bering Sea 

shelf+slope+basin ecosystem (702,000 km2

) with 48 functional groups. Biomass and catch estimates are in 

t/km2

, Production/Biomass (P/B) and Consumption/Biomass (Q/B) are rates (1/year); Ecotrophic Efficiency 

(EE) is a proportion. All EE values are estimated by Ecopath except for underlined values which were 

input. All trophic levels (T.L.) are estimated from the diet consumption matrix (Apendix Table B6). 

Group T.L. Biomass P/B Q/B Catch EE 

1. Baleen whales 3.8 0.283 0.02 8.312 .005 0.942 

2. Toothed whales 4.7 0.019 0.02 17.5 0 

3. Sperm whales 4.8 0.012 0.02 9.8 0 

4. Walrus & Bearded 3.4 0.095 0.06 13.9 .002 0.409 

5. Seals 4.6 0.044 0.06 13.34 .001 0.631 

6. Steller sea lion 4.6 0.016 0.06 18 0.346 

7. Seabirds 4 0.006 0.8 87 0 

8. Adult pollock 3.4 8.47 0.5 10 .634 0.772 

9. Juvenile pollock 3.3 1.7 2.5 13 0.517 

10. Cod 4.1 1.282 0.521 3.3 .091 0.411 

11. Halibut 4.6 0.043 0.25 3.5 .005 0.908 

12. Greenland turbot 4.5 0.03 0.2 3.6 .005 0.931 

13. Arrowtooth flounder 4.3 0.021 0.32 4.5 .003 0.996 

14. Flathead sole 3.6 0.074 0.37 4.7 .001 0.939 

15. Yellowfin sole 3.2 0.071 0.26 9.8 .009 0.885 

16. Rock sole 3.2 0.083 0.24 6.5 0.888 

17. Alaska plaice 3 0.081 0.25 6.8 .003 0.648 

18. Other small flatfishes 3.5 0.05 0.35 6.5 .002 0.94 

19. Herring 3.5 0.356 0.7 14.6 .025 0.912 

20. Salmon 3.8 0.142 4 16 .043 0.397 

21. Other pelagics 3.5 9.685 0.95 3.5 .001 0.95 

22. Skates 4.4 0.14 0.4 4 .021 0.375 

23. Sculpins, rockfish 3.9 0.35 0.4 3.5 .036 0.808 

24. Macrouridae 4 0.598 0.3 3.7 .021 0.731 

25. Zoarcids 4.1 0.427 0.3 2.52 .020 0.843 

26. Cephalopods 3.8 2.3 3.2 10.67 .009 0.98 

27. Tanner crab 3.1 0.03 0.8 5 0.94 

28. Snow crab 3.1 0.09 0.8 5 .002 0.975 

29. King crab 3.2 0.043 0.6 2.7 .003 0.936 

30. Shrimps 2.5 0.974 2.04 10.2 .001 0.95 

31. Clams 2 38.75 1.47 12 0.133 

32. Polychaetes 2 18.496 2.97 12 0.658 

33. Other worms 2 3.42 2.23 12 0.116 

34. Hermits, other decapods 2.5 1.43 0.82 8 0.966 

35. Snail 2.6 0.86 1.81 8 .002 0.954 

36. Brittlestar 2 9.99 1.21 5 0.071 

37. Starfish 2.8 0.66 1.23 5 0.163 

38. Other benthos 2.2 66.33 1.15 5 0.236 

39. Jellyfish 3.2 0.535 1.5 3 0.374 

40. Amphipods 3 20.22 2.5 14 0.808 

41. Gelatinous plankton 3 10.87 5 17 0.462 

42. Euphausiids 2.3 30.44 3.129 17 0.956 

43. Copepods 2.2 102.18 9.5 26.2 0.901 

44. Mysiids 2.1 1.09 3 12.5 0.842 

45. Chaetognaths 3.1 39.06 6 12 0.217 

46. Protozoa 2 20 47 142 0.583 

47. Phytoplankton 1 11 234 - 0.852 

48. Detritus 1 - - - 0.973 

62 
Table B4. Diet matrix (proportion of prey for each predator) for 

eastern Bering Sea shelf + slope ECOPATH model (2 pages). 

Predator 

Prey 1 10 11 12 13 14 15 16 17 

1 Baleen whales 0.002 

2 Toothed whales 0.001 

3 Sperm Whales 

4 Walrus& B.seals 0.001 

5 Seals 0.002 

6 Steller s.lions 

7 Seabirds 

8 Adult pollock 0.041 0.081 0.012 0.02 0.037 0.063 0.295 0.503 0.236 0.16 0.646 0.707 

9 Juv. pollock 0.042 0.081 0.013 0.02 0.115 0.185 0.604 0.13 0.074 0.055 0.707 0.48 0.018 0.034 0.017 0.236 

10 P. cod 0.033 0.031 0.012 0.029 0.019 0.007 0.003 0.015 0.002 0.005 

11 P. halibut 0.004 0.001 0.003 

12 Greenland turb. 0.027 0.01 0.023 0.002 0.001 

13 Arrowtooth fl. 0.022 0.008 0.019 0.001 0.001 

14 Small flatfish 0.053 0.02 0.046 0.003 0.109 0.075 0.015 0.011 0.044 0.379 

15 Skates 0.004 0.004 0.001 0.003 0.002 

16 Sculpins 0.008 0.007 0.003 0.007 0.004 0.106 0.005 0.017 0.003 0.001 0.007 0.018 

17 Sablefish 0.014 0.014 0.005 0.012 

18 Rockfish 0.012 0.012 0.005 0.011 

19 Macrouridae 0.026 0.02 0.01 0.02 0.002 0.003 

20 Zoarcidae 0.009 0.008 0.003 0.008 0.005 0.03 0.021 0.002 0.01 0.037 0.01 

21 Tanner crab 0.006 0.017 0.026 0.028 0.045 0.036 0.004 0.01 0.002 

22 Snow crab 0.015 0.046 0.069 0.074 0.146 0.035 0.007 0.063 0.15 

23 King crab 0.006 0.017 0.026 0.028 0.02 

24 Shrimp 0.028 0.085 0.129 0.14 0.031 0.055 0.026 0.009 0.071 0.044 0.064 0.358 0.01 

25 Epifauna 0.06 0.25 0.001 0.067 0.111 0.001 0.084 0.049 0.02 

26 Infauna 0.342 0.001 0.016 0.064 0.008 0.002 0.637 0.01 0.004 

27 Benthic amph. 0.039 0.006 0.032 0.07 0.02 0.011 0.001 0.003 0.1 0.025 0.003 0.001 

28 P. herring 0.005 0.009 0.001 0.002 0.009 0.035 0.01 0.004 0.001 0.01 

29 P. salmon 0.001 0.001 0.002 

30 Cephalopods 0.161 0.247 0.854 0.007 0.08 0.053 0.022 0.006 0.008 0.022 

31 Forage fish 0.079 0.152 0.024 0.038 0.148 0.599 0.05 0.013 0.02 0.083 0.03 0.059 0.006 0.018 0.011 

32 Jellyfish 

33 Large Zoop. 0.245 0.04 0.2 0.116 0.431 0.33 0.024 0.009 0.003 0.201 0.085 0.002 0.001 0.004 

34 Copepods 0.273 0.35 0.67 

35 Phytoplankton 

36 Pelagic detritus 

37 Benthic detritus 0.012 

38 Detrital pool 

Import 

Sum 1 

2 3 4 5 6 7 8 9 

1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 

63
 

1

2

3

4

5

6

7

8

9

10

11

12

13

14

Table B4 (Cont.) 

Predator 

Prey 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 

Baleen whales 

Toothed whales 

Sperm Whales 

Walrus& B.seals 

Seals 

Steller s.lions 

Seabirds 

Adult pollock 

Juv. pollock 0.1 0.001 

P. cod 0.001 

P. halibut 0.001 

Greenland turb. 0.04 0.001 

Arrowtooth fl. 0.04 0.001 

Small flatfish 0.004 

15 Skates 0.001 

16 Sculpins 0.001 

17 Sablefish 0.001 

18 Rockfish 0.001 

19 Macrouridae 0.001 

20 Zoarcidae 0.015 0.001 

21 Tanner crab 0.029 0.001 0.04 

22 Snow crab 0.039 0.001 0.04 

23 King crab 0.04 

24 Shrimp 0.36 0.322 0.021 0.01 0.002 0.001 0.011 

25 Epifauna 0.02 0.144 0.118 0.118 0.118 0.009 

26 Infauna 0.525 0.792 0.792 0.792 0.24 0.303 0.005 0.005 

27 Benthic amph. 0.01 0.002 0.227 0.15 0.051 0.005 0.05 0.005 0.04 

28 P. herring 0.004 0.001 

29 P. salmon 

30 Cephalopods 0.232 0.03 0.2 0.001 

31 Forage fish 0.423 0.05 0.2 0.001 

32 Jellyfish 0.001 

33 Large Zoop. 0.45 0.001 0.1 0.9 0.065 0.6 0.9 0.65 0.01 

34 Copepods 0.09 0.05 0.09 0.15 0.25 

35 Phytoplankton 0.2 0.5 0.8 

36 Pelagic detritus 0.01 0.24 0.2 

37 Benthic detritus 0.09 0.09 0.09 0.5 0.633 1 0.8 

38 Detrital pool 

Import 0.75 

Sum 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 

64
 

Table B5. Diet matrix (proportion of prey for each predator) for 

western Bering Sea shelf + slope ECOPATH model (2 pages). 

Predator 

Prey 1 10 11 12 13 14 15 16 17 

1 Baleen whales 0.001 

2 Toothed whales 

3 Sperm Whales 

4 Walrus& B.seals 0.001 

5 Seals 0.002 

6 Steller s.lions 0.001 

7 Seabirds 

8 Adult pollock 0.04 0.15 0.01 0.18 0.17 0.386 0.19 0.45 0.5 0.37 0.25 

9 Juv. pollock 0.06 0.1 0.01 0.15 0.2 0.25 0.005 0.2 0.17 0.1 0.021 0.2 0.13 

10 P. cod 0.02 0.1 0.01 0.05 0.03 0.06 0.033 0.02 

11 P. halibut 0.01 0.005 

12 Greenland turb. 0.005 

13 Arrowtooth fl. 0.005 0.005 0.005 

14 Small flatfish 0.02 0.01 0.01 0.02 0.01 0.015 

15 Skates 

16 Sculp. & Rockf. 0.02 0.015 0.005 0.01 0.005 

17 Macrouridae 0.03 0.09 0.01 0.04 

18 Zoarcidae 0.01 0.005 0.05 0.01 0.01 

19 Tanner crab 0.001 0.01 0.001 0.005 0.002 0.01 

20 Snow crab 0.005 0.01 0.005 0.002 0.005 0.01 

21 King crab 0.01 0.005 0.02 0.001 0.001 

22 Shrimp 0.045 0.1 0.005 0.05 0.015 0.07 0.15 0.145 0.02 0.08 0.02 

23 Epifauna 0.319 0.126 0.07 0.06 0.209 0.1 

24 Infauna 0.435 0.03 0.075 0.534 0.01 0.14 0.2 

25 Benthic amph. 0.1 0.04 0.059 0.05 0.05 

26 P. herring 0.02 0.1 0.07 0.05 0.04 0.005 0.02 

27 P. salmon 0.012 0.017 0.015 0.01 

28 Cephalopods 0.1 0.26 0.9 0.2 0.25 0.05 0.01 0.02 0.03 0.5 0.3 0.2 0.01 0.2 0.01 0.3 

29 Forage fish 0.13 0.045 0.075 0.01 0.19 0.04 0.021 0.025 0.1 0.006 0.1 0.005 0.16 

30 Jellyfish 0.02 0.01 

31 Large Zoop. 0.315 0.005 0.01 0.32 0.495 0.505 0.02 0.05 0.094 0.045 0.12 

32 Copepods 0.27 0.1 0.445 0.45 0.049 

33 Phytoplankton 

34 Pelagic detritus 0.025 

35 Benthic detritus 

36 Detrital pool 

Import 0.153 0.228 0.205 

Sum 1 

2 3 4 5 6 7 8 9 

1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 

65
 

1

2

3

4

5

6

7

8

9

10

11

12

13

Table B5 (Cont.) 

Predator 

Prey 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 

Baleen whales 

Toothed whales 

Sperm Whales 

Walrus& B.seals 

Seals 

Steller s.lions 

Seabirds 

Adult pollock 0.05 

Juv. pollock 0.1 0.01 

P. cod 

P. halibut 

Greenland turb. 

Arrowtooth fl. 

Small flatfish 

14 Skates 

15 Sculp. & Rockf. 

16 Macrouridae 

17 Zoarcidae 

18 Tanner crab 

19 Snow crab 

20 King crab 

21 Shrimp 0.07 0.1 0.1 0.09 0.03 0.04 

22 Epifauna 0.09 0.33 0.33 0.38 0.047 0.03 0.025 

23 Infauna 0.07 0.37 0.37 0.33 0.2 0.095 

24 Benthic amph. 0.1 0.1 0.1 0.1 0.002 0.005 0.15 0.095 0.14 0.055 

25 P. herring 

26 P. salmon 

27 Cephalopods 0.35 0.095 0.12 0.02 

28 Forage fish 0.15 0.03 0.12 0.15 

29 Jellyfish 

30 Large Zoop. 0.12 0.41 0.525 0.39 0.525 0.3 0.079 

31 Copepods 0.1 0.35 0.1 0.2 0.4 0.6 0.484 0.05 

32 Phytoplankton 0.04 0.196 0.7 

33 Pelagic detritus 0.05 0.241 0.25 

34 Benthic detritus 0.1 0.1 0.1 0.6 0.856 1 0.995 

35 Detrital pool 

36 Import 

Sum 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 

66
 

Table B6. Diet matrix (proportion of prey for each predator) for 

western Bering Sea shelf + slope+basin ECOPATH model (3 pages). 

Predator 

Prey 1 10 11 12 13 14 15 16 17 

1 Baleen whales 0.001 

2 Toothed whales 

3 Sperm whales 

4 Walrus & Bearded 0.001 

5 Seals 0.002 

6 Steller sea lion 0.001 

7 Marine birds 

8 Adult pollock 0.04 0.15 0.01 0.18 0.17 0.386 0.19 0.45 0.5 

9 Juv. pollock 0.06 0.1 0.01 0.15 0.2 0.25 0.005 0.2 0.17 0.1 0.1 

10 Cod 0.02 0.1 0.01 0.05 0.03 0.06 

11 Halibut 0.01 0.005 

12 Greenland turbot 0.005 

13 Arrowtooth flounder 0.005 0.005 0.005 

14 Flathead sole 0.005 0.004 

15 Yellowfin sole 0.005 0.005 0.001 

16 Rock sole 0.005 0.005 0.002 

17 Alaska plaice 0.005 0.002 

18 O. sm. flatfishes 0.001 0.02 0.01 

19 Herring 0.02 0.1 0.07 0.05 0.04 0.005 

20 Salmon 0.12 0.17 0.13 0.01 

21 Other pelagics 0.13 0.09 0.15 0.1 0.19 0.04 0.021 0.025 0.1 0.03 

22 Skates 

23 Sculpins & rockfish 0.02 0.015 0.005 0.01 

24 Macrouridae 0.03 0.09 0.01 

25 Zoarcids 0.01 0.005 0.05 0.05 

26 Cephalopods 0.1 0.26 0.9 0.2 0.25 0.05 0.01 0.02 0.03 0.5 0.3 0.2 0.05 

27 Tanner crab 0.001 0.01 0.001 0.005 

28 Snow crab 0.005 0.01 0.005 0.01 

29 King crab 0.01 0.005 0.02 0.001 

30 Shrimps 0.045 0.1 0.005 0.05 0.015 0.07 0.15 0.35 0.16 0.15 

31 Clams 0.31 0.03 0.35 0.2 0.2 0.3 

32 Polychaetes 0.065 0.02 0.04 0.4 0.35 0.65 

33 Other worms 0.06 0.01 0.005 

34 Hermits & o.decapods 0.07 0.06 

35 Snail 0.149 0.005 

36 Brittlestar 0.01 0.005 0.05 0.14 0.1 0.04 

37 Starfish 

38 Other benthos 0.09 0.056 

39 Jellyfish 0.02 0.01 

40 Amphipods 0.065 0.1 0.01 0.05 0.065 0.05 0.04 0.1 0.1 0.01 

41 Gelatinous plankton 0.02 0.05 0.01 

42 Euphausiids 0.25 0.25 0.34 0.43 0.01 0.01 0.05 

43 Copepods 0.27 0.1 0.445 0.45 

44 Mysiids 0.005 0.015 0.01 0.01 0.05 0.05 

45 Chaetognaths 0.025 0.005 

46 Protozoa 0.005 

47 Phytoplankton 0.02 

48 Detritus 

Sum 1 

2 3 4 5 6 7 8 9

1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1

67
 

1

2

3

4

5

6

7

8

9

10

11

12

13

14

Table B6 (Cont.) 

Predator 

Prey 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 

Baleen whales 

Toothed whales 

Sperm whales 

Walrus & Bearded 

Seals 

Steller sea lion 

Marine birds 

Adult pollock 0.37 0.25 0.05 

Juv. pollock 0.2 0.13 0.1 

Cod 0.033 0.02 

Halibut 

Greenland turbot 

Arrowtooth flounder 

Flathead sole 0.005 

15 Yellowfin sole 

16 Rock sole 0.005 

17 Alaska plaice 

18 O. sm. flatfishes 0.005 

19 Herring 0.02 

20 Salmon 

21 Other pelagics 0.03 0.12 0.1 0.005 0.16 0.15 0.15 

22 Skates 

23 Sculpins & rockfish 0.005 

24 Macrouridae 0.04 

25 Zoarcids 0.01 

26 Cephalopods 0.095 0.02 0.2 0.01 0.3 0.35 0.12 

27 Tanner crab 0.002 0.01 

28 Snow crab 0.005 0.01 

29 King crab 0.001 

30 Shrimps 0.05 0.03 0.04 0.02 0.08 0.02 0.07 0.1 0.1 0.09 0.01 

31 Clams 0.01 0.02 0.2 0.07 0.14 0.14 0.2 0.1 0.01 

32 Polychaetes 0.11 0.1 0.1 0.08 0.1 0.06 

33 Other worms 0.01 0.13 0.13 0.05 0.06 

34 Hermits & o.decapods 0.03 0.025 0.01 0.09 0.04 

35 Snail 0.03 0.12 0.12 0.2 0.01 

36 Brittlestar 0.01 0.05 0.03 0.19 0.19 0.15 0.03 

37 Starfish 0.005 0.05 0.02 0.02 0.03 

38 Other benthos 0.05 0.074 0.06 0.08 

39 Jellyfish 

40 Amphipods 0.1 0.15 0.095 0.055 0.05 0.05 0.14 0.1 0.1 0.1 0.1 0.1 

41 Gelatinous plankton 0.1 0.02 0.235 0.14 0.005 0.03 0.04 

42 Euphausiids 0.35 0.35 0.26 0.35 0.02 0.02 0.04 0.3 

43 Copepods 0.35 0.35 0.1 0.4 0.2 0.1 

44 Mysiids 0.02 0.02 0.01 0.005 0.02 0.07 0.08 0.025 

45 Chaetognaths 0.03 0.02 0.02 0.03 0.025 

46 Protozoa 

47 Phytoplankton 

48 Detritus 0.1 0.1 0.1 0.6 1 1 1 0.6 

Sum 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1

68
 

Table B6 (Cont.) 

Predator 

Prey 35 36 37 38 39 40 41 42 43 44 45 46 

1 Baleen whales 

2 Toothed whales 

3 Sperm whales 

4 Walrus & Bearded 

5 Seals 

6 Steller sea lion 

7 Marine birds 

8 Adult pollock 

9 Juv.pollock 0.01 

10 Cod 

11 Halibut 

12 Greenland turbot 

13 Arrowtooth flounder 

14 Flathead sole 

15 Yellowfin sole 

16 Rock sole 

17 Alaska plaice 

18 O.sm.flatfishes 

19 Herring 

20 Salmon 

21 Other pelagics 

22 Skates 

23 Sculpins & rockfish 

24 Macrouridae 

25 Zoarcids 

26 Cephalopods 

27 C.bairdi 

28 C.opilio 

29 King crab 

30 Shrimps 

31 Clams 0.4 0.6 

32 Polychaets 0.1 

33 Other worms 

34 Hermits & o.decapods 

35 Snail 0.1 0.1 

36 Brittlestar 

37 Starfish 

38 Other benthos 0.05 

39 Jellyfish 0.001 

40 Amphipods 0.05 0.005 0.05 

41 Gelatinous plankton 0.05 

42 Euphausiids 0.25 0.01 0.03 0.005 0.04 

43 Copepods 0.6 0.5 0.5 0.2 0.05 0.71 

44 Mysiids 

45 Chaetognaths 0.1 0.1 

46 Protozoa 0.1 0.1 0.1 0.15 0.1 0.1 

47 Phytoplankton 0.04 0.054 0.07 0.545 0.7 0.7 

48 Detritus 0.5 1 0.3 0.85 0.05 0.18 0.2 0.15 0.1 0.2 0.1 1 

Sum 1 1 1 1 1 1 1 1 1 1 1 1

69
 

APPENDIX C: WBS SHELF/BASIN PARTITIONING 

Appendix Table C1. Biomass, Production/Biomass (PB), and Consumption/Biomass (Q/B) partitioned 

between western Bering Sea shelf/slope and basin. Biomasss estimates are per-unit-area, and thus were 

used directly as Ecopath inputs. 

Shelf/Slope Basin 

B 

(t/km2

) 

P/B 

(1/year) 

Q/B 

(1/year) 

B 

(t/km2) 

P/B 

(1/year) 

Q/B 

(1/year) 

Phytoplankton 15.0 234 9.3 234 

Protozoa 30 47 142 15 47 142 

Copepods 122.62 9.5 26.2 91.96 9.5 26.2 

L. Zoop. (amph., euph., chaet.) 107.7 4.24 14.15 76.23 4.24 14.15 

Gel. Plankton 13.04 5.0 17.0 9.785 5.0 17.0 

Sm. Pelagics 5.81 0.95 3.5 11.62 0.95 3.5 

Cephalapods 4.83 3.2 10.67 1.04 3.2 10.67 

Jellyfish 1.4 1.5 3.0 0.1 1.5 3.0 

Appendix Table C2. Proportion of total assessed stock size for each functional group(tons) resident in the 

Western Bering sea shelf+slope and Basin, respectively. Since proportional estimates were provided in 

tons, densities (t/km2

) were calculated by dividing the total tons calculated in each area by the total 

shelf+slope or basin area shown in Table 2.1. 

Shelf/ Shelf/ 

Group slope Group slope 

Pacific salmon 0.1 0.9 Seabirds 0.6 0.4 

Pacific herring 0.8 0.2 Steller sea lions 0.8 0.2 

O. small flatfishes 1.0 0 Seals 0.8 0.2 

Alaska plaice 1.0 0 Walrus & brd. seals 1.0 0 

Rock sole 1.0 0 Sperm whales 0.6 0.4 

Yellowfin sole 1.0 0 Toothed whales 0.8 0.2 

Flathead sole 0.9 0.1 Baleen whales 0.5 0.5 

Arrowtooth flounder 0.9 0.1 

Greenland turbot 0.7 0.3 Epifauna 0.7 0.3 

Pacific halibut 0.7 0.3 Shrimps 0.6 0.4 

Pacific cod 0.9 0.1 Snow crab 1.0 0 

Juvenile pollock 0.8 0.2 Tanner crab 1.0 0 

Adult pollock 0.6 0.4 King crabs 1.0 0 

Basin Basin 

70 
ACKNOWLEDGEMENTS 

This publication is partially funded by the Joint Institute for the Study of the 

Atmosphere and Ocean (JISAO) under NOAA Cooperative Agreement No. 

NA17RJ1232, Contribution # 935. The authors would like to thank Sarah Gaichas and 

Paul Spencer for comments on earlier drafts of this manuscript. 

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78 
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