Embed Size (px)
Citation preview
University of South FloridaScholar Commons
Marine Science Faculty Publications College of Marine Science
2018
Ecosystem Model of the Entire Beaufort SeaMarine Ecosystem: A Temporal Tool for AssessingFood-Web Structure and Marine AnimalPopulations from 1970 to 2014Paul M. SuprenandMote Marine Laboratory, [email protected]
Cameron H. AinsworthUniversity of South Florida, [email protected]
Carie HooverUniversity of Manitoba
Follow this and additional works at: https://scholarcommons.usf.edu/msc_facpub
Part of the Marine Biology Commons
This Technical Report is brought to you for free and open access by the College of Marine Science at Scholar Commons. It has been accepted forinclusion in Marine Science Faculty Publications by an authorized administrator of Scholar Commons. For more information, please [email protected].
Scholar Commons CitationSuprenand, Paul M.; Ainsworth, Cameron H.; and Hoover, Carie, "Ecosystem Model of the Entire Beaufort Sea Marine Ecosystem: ATemporal Tool for Assessing Food-Web Structure and Marine Animal Populations from 1970 to 2014" (2018). Marine Science FacultyPublications. 261.https://scholarcommons.usf.edu/msc_facpub/261
1
Ecosystem model of the entire Beaufort Sea marine ecosystem: a temporal tool for assessing food-
web structure and marine animal populations from 1970 to 2014
Paul Mark Suprenand1,* Cameron H. Ainsworth2, and Carie Hoover3
1Mote Marine Laboratory, 1600 Ken Thompson Parkway, Sarasota, FL 34236 USA
2University of South Florida, College of Marine Science, 140 7th Avenue South, Saint Petersburg, FL
33701 USA
3Centre for Earth Observation Science, 535 Wallace Building, University of Manitoba, Winnipeg, MB R3T
2N2 Canada
*Email: [email protected]
Keywords: Beaufort Sea, Arctic Climate Change, Ecopath with Ecosim, Ecological Model, Nature
Resource Management
Abstract
The Beaufort Sea coastal-marine ecosystem is a 476,000 km2 area in the Arctic Ocean, which
extends from -112.5 to -158.0° longitude to 67.5 to 75.0° latitude. Within this polar area the United
States indigenous communities of Barrow, Kaktovik, and Nuiqsut, and the Canadian indigenous
communities of Aklavik, Inuvik, Tuktoyaktuk, Paulatuk, Ulukhaktok, and Sachs Harbour, subsist by
harvesting marine mammals, fish, and invertebrates to provide the majority of their community foods.
The Beaufort Sea coastal-marine ecosystem includes many specialized marine animals whose life history
is tied to the sea ice, such as polar bears that rely on sea-ice for foraging activities and denning, or ice
algae that attach to the seasonal cryosphere. Changes in sea-ice extent and sea surface temperature
affect the ecosystem through losses of animal habitat, alterations to trophodynamics, and/or impacts to
indigenous community harvesting. The present study focuses on developing a dynamic whole-
ecosystem model that can be used for natural resource management. The resulting Ecopath with
Ecosim (EwE) temporal model (1970 to 2014) utilizes forcing and mediation functions that describe food
2
web and relationships between sea-ice extent, SST, and Inuit community harvesting efforts. Following
model calibrations, vulnerability estimates, trophic level validation, and sensitivity analyses, the
Beaufort Sea model produces population and dietary changes over time that are analogous to
observations. Changes in temporal whole-ecosystem trophodynamics highlight a potential
climatological tipping point in 1993, followed by a biological tipping point in 1998.
Introduction
Global mean temperatures have increased due to anthropogenic induced climate change, with polar
regions experiencing more extreme climatic fluctuations (ACIA 2004, Hansen et al. 2006, IPCC 2014).
The most significant changes caused by increased temperatures are reductions in Arctic sea ice by more
than 50% since the 1970s (Manabe & Stouffer 1995, Stirling 1997, Stirling 2002, Derocher et al. 2004,
Johannessen et al. 2004, Stirling & Smith 2004, Higdon & Ferguson 2009, Stroeve et al. 2007, NOAA
2015, NRDC 2015), increases in the length of the ice-free season at a rate of 5 days per decade (Stroeve
et al. 2011, Stroeve et al. 2014), and changes in permafrost altering terrestrial and coastal habitat (ACIA
2004, Schuur et al. 2015). The loss of sea-ice extent includes physical changes in polar ecosystems such
as increased storm and wave action, faster snow melt, increased river runoff to oceans resulting in lower
salinity (ACIA 2004), as well as changes to the biological community through altered habitats and
changes in species interactions (Horner & Murphy 1985, Francis et al. 1998, Benson & Trites 2002,
Gradinger 2002, Krupnik & Jolly 2002). Species residing at these high latitudes have adapted to thrive in
the cold harsh Arctic conditions. Yet, changes in climate are altering ocean productivity, food web
dynamics, habitats of species, and species’ distributions under unprecedented environmental conditions
(Hoegh-Guldberg & Bruno 2010). In coastal-marine polar ecosystems, the loss of sea-ice is most
pronounced, which has been shown to alter the sea-ice-pelagic-benthic connections in the food-web
and corresponding trophodynamics from the benthos to apex predators (Bradstreet & Cross 1982,
3
Grebmeier & Barry 1991, Wassmann & Slagstad 1993, Feder et al. 1994b, Feder et al. 1994a, Grebmeier
et al. 1995, Hoover et al. 2013a, Hoover et al. 2013b).
The Beaufort Sea coastal-marine ecosystem spans Canada and the U.S., and includes the Beaufort
shelf and the deeper Canada Basin. It is heavily influenced by wind, which drives the Beaufort gyre and
movement of sea ice, as well as freshwater output from the Mackenzie River and other smaller Arctic
rivers (Carmack & Macdonald 2002, Dunton et al. 2006). This region is home to many indigenous
communities, and migratory marine mammals and fish species are harvested along the coasts by the
Iñupiat (U.S.) and Inuit (Canada) (Joint-Secretariat 2003, Allen & Angliss 2010) subsistence communities.
Subsistence harvesting of marine resources primarily consists of marine mammals, fish, and birds, and is
an important factor in local food security (Usher 2002, Huet et al. 2012, Hoover et al. 2016). Changes in
the ecosystem driven by climate have reduced the availability of harvestable species in Arctic
communities, leading to significant declines in essential nutrients for northern community members
(Rosol et al. 2016).
These climate-induced changes are anticipated to bring shifts in species distributions towards poles
and changes in migration patterns (Walther et al. 2002). Changes in production, increased freshwater
input into coastal-marine areas, and longer summers favor smaller zooplankton (picoplankton in the
Canadian Basin) over colder water species important to predators (Uye 1994, Li et al. 2009). These
changes are predicted to alter zooplankton species such as Pseudocalanus spp. along with other
herbivorous species over omnivorous and carnivorous species (Darnis et al. 2008). Ice-dependent
species such as Arctic cod (Boreogadus saida), who are known to be an important link in the food web,
are expected to be replaced by capelin (Mallotus villosus) (Orlova et al. 2005, Hop & Gjøsæter 2013).
Declining trends have been observed for arctic cod predators (e.g., ringed seals, beluga, black guillemot
chicks), while other species have improved (Arctic char, bowhead) during the same time frame
(Harwood et al. 2015). Yet, the dynamics of the food web and the interactions responsible for these
4
changes is currently unknown. Furthermore, changes to species distribution and food web changes
impact their availability to indigenous communities that harvest and consume these species, something
expected to worsen with climate change (Council 2012).
In order to understand what alterations these cumulative impacts have made on the food web, an
ecosystem model was developed to summarize the Beaufort Sea coastal-marine ecosystem. Here all
components of the food web are represented in an Ecopath with Ecosim model (Walters et al. 1997,
Christensen et al. 2005). Available datasets are combined to provide a holistic representation of the
ecosystem and evaluate reasons for changes in individual species and the ecosystem as a whole. The
Ecopath model represents the 1970 mass-balance ecosystem, whereas the Ecosim model represents
trophodynamic changes from 1970 to 2014. Known harvest and climate trends are incorporated into
the Ecosim model to identify and assess changes in the ecosystem. We present individual species
trends, ecosystem drivers, potential ecosystem tipping points, and suggest key species for ongoing
monitoring.
Methods and Materials
Area of Consideration
The present EwE and Ecospace models considered the entire Beaufort Sea marine ecosystem area
ranging from 67.5 to 75° N and -112.5 to -158° W, or approximately 476,000 km-2, which included
estuarine, coastal, and oceanic habitats ranging from 0 to 3000 m of water depth (Fig. 1). The Beaufort
Sea marine ecosystem also encompasses Iñupiat subsistence use areas of northern Alaska (United States
of America), the Inuvialuit Settlement Regions (ISR) of the Inuit in northern Canada (Canada 1984), and
the southern Beaufort Sea (SB) management unit for polar bears established by the International Union
for the Conservation of Nature and Natural Resources (IUCN) Polar Bear Specialist Group (IUCN 2010).
The model area represents a little over three percent of the Arctic Ocean’s area, yet it is an important
5
habitat for migratory bowhead and beluga whales (Fraker & Bockstoce 1980, Harwood & Smith 2002,
DFO 2013), a distinct population of polar bears (Amstrup et al. 2007), and at least nine indigenous
(Iñupiat and Inuvialuit) communities that practice subsistence harvesting in coastal waters from Alaska
to the Northwest Territories (Fig. 1). The Beaufort Sea Iñupiat communities live in Barrow, Kaktovik, and
Nuiqsut, and the Canadian Inuvialuit communities live in Aklavik, Inuvik, Tuktoyaktuk, Paulatuk,
Ulukhaktok, and Sachs Harbour (Fig. 1).
Fig. 1 Map of the Beaufort Sea marine ecosystem. Subsistence harvesting communities indicated by red
dots.
Ecopath
Functional Groups
Our Ecopath model considers 36 functional groups, which includes single species and aggregated
groups of species. These functional groups range from top predators (marine mammals) to primary
producers and detritus, covering taxa throughout the food web. There are 8 marine mammal groups, 1
bird, 9 fish groups, 6 benthic, 6 zooplankton, and 6 producer/ detritus groups (see Table 1 for a full list of
model groups), which are referred to as the functional groups of: 1) Polar Bears, 2) Beluga Whales, 3)
Gray Whales, 4) Bowhead Whales, 5) Walrus, 6) Ringed Seals, 7) Bearded Seals, 8) Spotted Seals, 9)
Birds, 10) Char & Dolly Varden, 11) Ciscoes & Whitefish, 12) Salmonids, 13) Herring & Smelt, 14) Arctic &
6
Polar Cods, 15) Capelin, 16) Flounder & Benthic Cods, 17) Small Benthic Marine Fish, 18) Other Fish, 19)
Arthropods, 20) Bivalves, 21) Echinoderms, 22) Molluscs, 23) Worms, 24) Other Benthos, 25) Jellies, 26)
Macro-Zooplankton, 27) Medium Copepods, 28) Large Copepods, 29) Other Meso-Zooplankton, 30)
Micro-Zooplankton, 31) Producers > 5 μm, 32) Producer < 5 μm, 33) Ice Algae, 34) Benthic Plants, 35)
Pelagic Detritus, and 36) Benthic Detritus. A list of species for aggregated functional groups, from birds
to fish, are detailed in Table S1 (supplemental materials below), and all other aggregated functional
groups are listed in the Biomass, Diets, and Harvesting Rates supplimental section according to their
Phylum, Class, Order, Family, and/or individual species.
In general, an Ecopath model represents an instantaneous ‘snap-shot’ of material fluxes in the
ecosystem according to the constraints of mass-balance and the conservation of energy. The Ecopath
portion of the Beaufort Sea model (year 1970) required biomass (tonnes (t) km-2) for each functional
group, as well as the functional group dietary proportions, respective ratios of production per unit
biomass (production ratio), and consumption per unit biomass (consumption ratio) according to Hoover
et al. (2016)(Table 1), and a life table based on natural mortality (Barlow & Boveng 1991). For this
Beaufort Sea model, biomass is calculated using information provided from stock assessments, fishery
independent monitoring samples, harvest reports, and other published literature. Production of a
functional group is determined for all components of the food web, and linked through diet proportions
(equation (Eq.) 1), where the production P of the functional group i is represented as:
𝑃𝑖 = ∑ 𝐵𝑗 ∗ 𝑀2𝑖𝑗 + 𝑌𝑖 + 𝐸𝑖 + 𝐵𝐴𝑖 + 𝑃𝑖 ∗ (1 − 𝐸𝐸𝑖) Eq. 1
Pi was dependent upon the biomass Bj of each predator group j, with predation mortality on group i
from group j as M2ij. Here Yi represents the fishery catch, the net migration rate Ei is the emigration-
immigration, biomass accumulation is BAi, and the ecotrophic efficiency EEi represents the proportion of
production accounted for within the system (consumed by predators, exported from the system, fishing
or migration)(Christensen et al. 2005).
7
Table 1. Balanced WAP Ecopath model parameters for basic input. TL is trophic level, PB (Production/Biomass ratio year -1), and QB (Consumption/Biomass ratio year-1) are described y−1 (Hoover et al. in press). Ecotrophic Efficiency (EE), PB, and QB are ratios, therefore dimensionless.
Functional Group TL B PB QB EE
Polar Bears 4.82 0.0015 0.15 3.03 0.43 Beluga Whales 4.19 0.0305 0.07 17.00 0.16 Gray Whales 3.33 0.0265 0.06 4.00 0.86
Bowhead Whales 3.38 0.1219 0.07 5.48 0.64 Walrus 3.13 0.0092 0.07 21.66 0.68
Ringed Seals 3.84 0.0217 0.80 16.05 0.57 Bearded Seals 3.73 0.0150 0.12 13.85 0.82 Spotted Seals 4.40 0.0046 0.07 18.70 0.77
Birds 3.82 0.0026 0.90 10.00 0.08 Char & Dolly Varden 3.61 0.1407 0.68 2.30 0.67 Ciscoes & Whitefish 3.23 0.7057 0.95 3.80 0.44
Salmonids 3.59 0.0977 0.85 6.00 0.99 Herring & Smelt 3.10 0.6640 1.50 4.90 0.90
Arctic & Polar Cods 3.45 0.6511 0.80 3.90 0.76 Capelin 3.45 0.1050 0.95 4.00 0.74
Flounder & Benthic Cods 3.34 0.2965 0.75 2.40 0.81 Small Benthic Marine Fish 3.22 0.7243 1.06 3.50 0.55
Other Fish 3.08 0.4733 0.51 2.40 0.84 Arthropods 2.35 3.5000 0.75 3.50 0.91
Bivalves 2.00 1.9890 0.60 2.40 0.87 Echinoderms 2.23 5.0000 0.55 1.80 0.53
Molluscs 2.00 3.0000 0.85 3.40 0.88 Worms 2.07 2.5000 0.95 4.00 0.83
Other Benthos 2.08 1.7000 0.80 3.00 0.97 Jellies 2.33 0.9237 10.00 25.00 0.26
Macro-Zooplankton 2.64 0.2590 7.50 28.00 0.85 Medium Copepods 2.12 0.7154 18.00 45.00 0.97
Large Copepods 2.31 2.7242 5.50 20.00 0.42 Other Meso-Zooplankton 2.34 1.6612 22.00 80.00 0.24
Micro-Zooplankton 2.00 1.0530 55.00 150.00 0.85
Producers > 5 µm 1.00 3.7018 30.00
0.51 Producers < 5 µm 1.00 4.8081 60.00
0.64
Ice Algae 1.00 3.5117 20.00
0.78 Benthic Plants 1.00 5.5000 10.00
0.040
Pelagic Detritus 1.00 0.5000
0.188 Benthic Detritus 1.00 0.0500
0.957
In general, there must be energy produced by each group to balance energy removed through
predation, fishing, migration, and other mortality under the mass-balance assumption. Animal
populations (biomass), animal weights (if necessary), diets of each predator based on the mean
8
proportion (%) of prey it consumes, and subsistence and commercial harvest rates (if harvested) of
functional groups are discussed in detail for each functional group in the Biomass, Diets, and Harvest
Rates supplemental section and outlined in Table 1. Diets of functional groups are based on published
literature, which includes ecological isotopes, stomach contents, and observations in predation studies
(e.g., animals observed eating particular prey).
Validation of Ecosystem Structure
To validate the EwE models we compare trophic levels (Lindeman 1942, Odum & Heald 1975)
calculated for each of our functional groups to two Chukchi Sea Ecopath models (Whitehouse 2013,
Whitehouse & Aydin 2016), one Mackenzie Delta (Beaufort Sea) Ecopath model (Hoover et al. 2016),
and several stable isotope studies throughout the Beaufort Sea marine ecosystem (Hobson & Welch
1992, Hobson 1993, Hoekstra et al. 2003) (Fig. S1). In estimating the dimensionless trophic levels, EwE
assigns primary producers a level of one, whereas all other functional groups have a trophic level of one
plus the diet weighted average of their prey item’s trophic levels. For trophic level comparisons across
all studies and to our functional groups, we aggregate single species into similar functional groups, and
calculate their mean trophic level.
Assessing Food-Web Structure
As Ecopath predator-prey relationships (trophodynamics) define the movement of energy
throughout the ecosystem, we use a methodology described in Clarke et al. (2008) to run a series of
similarity profile routine (SIMPROF) tests with dissimilarity profile analyses (DISPROF; (Jones 2014)),
Euclidean distance, and unconstrained agglomerative (UPGMA) clustering methods. This produces
significant (P < 0.05) hierarchical clusters of predator groups according to their similarities in prey, and
prey with similarities in their predators. In general, hierarchical clusters reveal similarities among and
between functional groups (or species) with regards to energy consumption by predators or energy
contributions from prey, respectively. Once significant hierarchical clusters are identified, we identify
9
the top indicator functional group that is significantly (P < 0.05) characteristic of each hierarchical cluster
(if possible), as well as the Indicator Value (IV) among potential indicator species (Dufrene & Legendre
1997). The IV is the percent similarity (0% meaning no similarity and 100% meaning total similarity) that
an indicator functional group has with all functional groups within a cluster. For example, a hierarchical
cluster of predators based on similarities in prey could have one prey functional group that occurred in
all predator diets and in similar proportions, and that indicator functional group could have a high IV
(100%) or a low IV (0%). If an indicator functional group occurred in two or more hierarchical clusters,
this would lower the overall IV value of the indicator functional group, as its total percent of the IV
would be shared between all hierarchical clusters where it was a significant indicator functional group.
SIMPROF tests are also used on the Mixed Trophic Impacts (MTI) matrix (Ulanowicz & Puccia 1990),
which is an output in Ecopath that assesses direct and indirect trophodynamic interactions of each
functional group when considering all other functional groups. The MTI assigns positive or negative
interaction values based on trophic links (see Christensen et al. 2005 for equations and description). The
MTI SIMPROF tests are used to reveal which functional groups are most significant in structuring
energetic the pathways of the Beaufort Sea marine ecosystem. This method reveals Beaufort Sea’s
keystone functional groups, similar to the functional groups that show a high level of keystoneness
(Libralato et al. 2006) in Ecopath, with the added benefit of identifying the keystone functional groups
that significantly (P < 0.05) structures Beaufort Sea energetic pathways .
Ecosim Model
Forcing and Mediation Functions
As Ecopath provides the instantaneous snap-shot of the energy balance between predator-prey
relationships according to biomass and parameters in Hoover et al. (Table 1; unpublished model), our
Ecosim model performs temporal simulations beginning in 1970 and ending in 2014, and uses the diet
10
proportions, harvest rates (fishing/subsistence mortality, if included in the supplementary section), and
old age (natural mortality, ecotrophic efficiency). These temporal simulations use equation 2:
𝑑𝐵𝑖
𝑑𝑡= 𝑔𝑖 ∑ 𝑄𝑗 𝑗𝑖 − ∑ 𝑄𝑗 𝑖𝑗 + 𝐼𝑖 − (𝑀𝑂𝑖 + 𝐹𝑖 + 𝑒𝑖)𝐵𝑖 Eq. 2
Where the change in biomass dBi/dt over time t is equal to the net growth efficiency (gi) or
production/consumption ratio, times the total consumption of group i(∑ 𝑄𝑗 𝑗𝑖), minus the predation
from all predators on group i(∑ 𝑄𝑗 𝑗𝑖), combined with the mortality associated with the old age (MOi),
the fishing mortality rate (Fi), immigration rate (𝐼𝑖), and emigration rate (ei) where net migration equals
Bi * ei – 𝐼𝑖. Ecosim adds a temporal dimension for predicting biomass changes in primary producers and
consumers when considering forcing functions according to equations 3 and 4 (below), respectively.
𝑑𝐵𝑖
𝑑𝑡 = 𝑐𝐵𝑖(𝑃 − 𝐵)𝑖 𝐸𝐸𝑖 − ∑ 𝑓𝑛
𝑗=1 (𝐵𝑖 , 𝐵𝑗) − 𝑀𝑖𝐵𝑖 Eq. 3
𝑑𝐵𝑖
𝑑𝑡 = 𝑐𝑔𝑖 ∑ 𝑓𝑛
𝑗=1 (𝐵𝑗, 𝐵𝑖) − ∑ 𝑓𝑛𝑗=1 (𝐵𝑖, 𝐵𝑗) + 𝐼𝑖 − 𝐵𝑖(𝑀𝑖 + 𝐹𝑖 + 𝐸𝑖) Eq. 4
Where Bi and Bj are biomasses of prey (i) and predator (j), P is production rate, EE is ecotrophic
efficiency, f is a relationship predicting consumption, I is immigration, M and F are natural and fishing
mortality, E is emigration, g is growth efficiency, and n is the number of functional groups. The scalar c
is used in this model to introduce forcing functions on productivity, and EE is the proportion of the
production used in the marine ecosystem.
To reflect the influences of climatological changes from 1970 to 2014 in Ecosim model simulations
two forcing and two mediation functions are developed. Using the data from the British Atmospheric
Data Centre (2010) the first forcing function considers the mean percent of sea-ice cover within the
model area in 1970, and then divides each month’s mean percent of sea-ice cover from 1970 to 2014 by
the 1970 mean to create sea-ice extent anomalies (Fig. S2). This sea-ice forcing function is used to drive
the productivity of the Ice Algae functional group in Ecosim simulations. Similarly, using the data from
the British Atmospheric Data Centre (2010) the second forcing function considers the mean sea surface
11
temperature within the model area in 1970, then divides each month’s mean sea surface temperature
(°C) from 1970 to 2014 by the 1970 mean to create sea surface temperature anomalies (Fig. S3). As sea
surface temperature data is limited to a minimum of -1.8°C, when sea-ice is formed, we first add 1.8 to
all monthly sea surface temperatures from 1970 to 2014, then calculate the mean sea surface
temperature in the Beaufort Sea in 1970 (a 12-month period), and finally divide each month’s mean sea
surface temperature from 1970 to 2014 by the 1970 mean. This sea surface temperature forcing
function is used to drive the productivity of the Producers > 5 μm and Producers < 5 μm functional
groups.
There are two mediation functions for Ecosim simulations that describe the relationships between
sea-ice extent and the predation success of the Polar Bears, Beluga Whales, Gray Whales, Bowhead
Whales, Walrus, Ringed Seals, Bearded Seals, and Spotted Seals functional groups, as these functional
groups have ecological associations with the cryosphere. For instance, the first mediation function is
created to describe the positive effects of an increasing sea-ice extent for specific functional groups,
such as polar bears, that maintain their blubber-rich diets by consuming ice seals (particularly ringed
seals) from sea-ice platforms. In this instance, a reduction in the availability of ice seals during months
with a reduced sea-ice extent, will decrease polar bear productivity (i.e. hunting success) and/or
increase instances of cannibalism and/or decrease reproductive success (i.e. maintaining the population)
(Stirling et al. 1999, Schliebe et al. 2008, Stirling et al. 2008). In contrast, the second mediation function
is created to describe the positive effects of a decreasing sea-ice extent on predatory success. A positive
effect, for example, is observed in whales who migrate into the Beaufort Sea though flaw leads in the
ice, and a reduction in sea-ice extent likely increases their ability to surface and breathe unobstructed,
therefore increases their potential for prey consumption in the model area (George et al. 2009). The
first mediation function, when applied to Walrus, Ringed Seals, Bearded Seals, and Spotted Seals,
increases the vulnerability of their prey functional groups in the Beaufort Sea, or foraging arena (area),
12
when sea-ice is present (Fig. S4), whereas the second mediation function, when applied to Beluga
Whales, Gray Whales, and Bowhead Whales, increases the vulnerability of their prey and foraging arena
when sea-ice is not present (Fig. S5). The Polar Bears functional group was unique, in that we applied
the first mediation function to their typical prey items (seals, etc.), and we applied the second mediation
function to polar bears themselves. This was done to describe increased potential of polar bear
cannibalism as the sea-ice decreases (Amstrup et al. 2006). In both cases the Ice Algae functional group
was used as the facilitator, or proxy, for sea-ice extent in mediation functions.
Temporal Simulation Calibration
To make the temporal simulations more dynamic in the Ecosim model we used documented
changes in the biomass of Polar Bears and Bowhead Whales from 1970 to 2014 (discussed above) as a
time series to fit Ecosim model simulations to data. Similarly, we used documented annual harvest
(“catch”) rates for Polar Bears, Beluga Whales, Bowhead Whales, Walrus, Bearded Seals, Ringed Seals,
Spotted Seals, and Birds (discussed in supplemental section) as a time series to fit the Ecosim model
temporal simulations to empirical data. Lastly, we also used the ratio of biomass to catch, or harvest
mortality (Catch divided by Biomass), as a time series to fit the model when both biomass and catch
were available (i.e., Polar Bears and Bowhead Whales).
Harvesting Efforts by Community
In addition to the annual harvest rates for the aforementioned functional groups (Supplemental
section, Table S2) we also define the harvest (“fishing”) effort per month for each of the Ecopath
fisheries, so that each indigenous community and each functional group harvested by that community
are considered in Ecosim temporal simulations. To accomplish this we use reports of subsistence
harvesting efforts that were unique to each indigenous community, and in Ecosim define each fishery’s
percent of harvesting effort between 100% (1.0) and 0% (0.0) according to literature (Braund 1993, DFO
1999a, Joint-Secretariat 2003, Stephenson 2004, BLM 2005, Aklavik 2008, Inuvik 2008, Paulatuk 2008,
13
Sachs-Harbour 2008, Tuktoyaktuk 2008, Ulukhaktok 2008, Bacon et al. 2009, ADNR 2011, Braund 2012,
NSB 2014, ARLIS 2015), then created individual percent effort anomalies for each fishery (e.g., Barrow
Polar Bear; Fig. S6) to drive seasonal fishing effort. For Ecosim percent effort anomalies the percent
effort is divided by the average annual harvest effort per community and functional group, so that effort
increases or decreases proportionally to the mean effort. Commercial fisheries are allowed to harvest
throughout the year.
Vulnerability
The foraging arena theory dictates that the biomass of a group is split between vulnerable and
invulnerable states, whereas the prey is only vulnerable to predators during the vulnerable state
(Walters et al. 1997). Once biomass trends, harvest trends, fishing efforts, and forcing and mediation
functions are developed for the Ecosim model, the vulnerability for each functional groups is
determined in the model fitting to time series process. This is accomplished using the prey-control
(bottom-up) vulnerability calculation and multiple iterations of the fit to time series routine in order to
reduce errors (measured by the sum of squares: SS) in the model (Buszowski et al. 2009).
Sensitivity Analyses
Sensitivity analysis (Majkowski 1982) is performed using Monte Carlo trials (1000 iterations) in
Ecosim that vary the initial (1970) biomass of SIMPROF-identified keystone functional groups within the
Beaufort Sea marine ecosystem using a coefficient of variation (CV) of 0.1. During trials all other
Ecopath parameters (production per unit biomass, consumption per unit biomass, etc.) are held
constant, because biomass is one of the most challenging metrics to measure (hence fishery
independent monitoring and stock assessments), and ratios of production or consumption per unit
biomass for all functional groups are defined by available literature. The goal of the sensitivity analysis
is to assess how initial changes in the biomass of keystone functional groups would result in long-term
changes in biomass given model calibrations. The better initial estimates of biomass, in terms of
14
trophodynamics, the lower the sum of squared deviations (SS). Thus, sensitivity analysis tests how
robust the model is to uncertainty in field data by allowing initial biomass to be either 10% greater or
less than initial model estimates, then returns an optimal estimate of biomass based on the whole
ecosystem response. To examine how the initial functional group biomass estimates could impact the
Beaufort Sea marine ecosystem’s stability over time, we examine SS, as well as changes in biomass for
each functional group in year 1971, 1980, 1990, 2000, and 2010 in context of trial-derived minimum
biomass, maximum biomass, 1st quartile biomass, 3rd quartile biomass, median biomass, and model
biomass.
Assessing Food-Web Structural Changes
The 1970 and 2014 clustered predator groups are compared according to their similarities in prey
and clustered prey items are compared to their similarities in predators using SIMPROF and binary
connectivity matrices (Jones 2014) in order to reveal congruency between hierarchical clusters. In the
continuum of congruency, 100% congruence means an identical hierarchical clustering (of prey or
predators), indicating two species or groups occupy a similar trophic link in the food web, and the
number of cluster groups produced. Whereas, 0% indicates no identical clustering and therefore
complete dissimilarity in cluster groups produced. Additionally, indicator functional groups and IV are
produced for hierarchical clusters at year 2014. Therefore, we are able to compare changes in the
number of cluster groups produced in SIMPROF analyses, congruency between hierarchical cluster
groups, and/or changes in the indicator functional group or IV per hierarchical cluster, all of which reveal
potential changes in Beaufort Sea trophodynamics from 1970 compared to 2014.
Furthermore, as Arctic & Polar Cods have historically been a critical energetic link between lower
and higher trophic levels (Bain & Sekerak 1978, Welch et al. 1993, Christiansen et al. 2012, Hop &
Gjøsæter 2013), we examine the variability of their biomass explained by the variability in the biomass
of all other functional groups using Redundancy Analysis (RDA) with Akaike’s information criterion (AIC)
15
(Godínez-Domínguez & Freire 2003). This method reveals relationships between population dynamics,
and the resulting affects to Arctic & Polar Cods’ populations over time, as well as implications to the
greater food web.
Biodiversity and Detecting Ecological Tipping Points
After calculating vulnerability, calibrating temporal biomass and catch data, and considering
sensitivity analysis results, biodiversity is assessed using the Shannon Index (Shannon 1948, Shannon &
Weaver 1949), which measures evenness as the model has a fixed number of species (functional
groups). The Shannon Index is then statistically examined for significant relationships with annual sea-
ice extent, sea surface temperature, whole ecosystem biomass, and mean ecosystem trophic level using
RDA with AIC. Mean ecosystem trophic level is calculated using the trophic level of each individual
functional group, and is dependent on the trophic level of a functional group’s prey. Following statistical
examinations R-values are reported. Increases in evenness (Shannon Index) over time indicate a less
trophodynamic complexity.
Lastly, we compare temporal Shannon Index values using the Student T-test to examine if
biodiversity values always come from distributions with equal means (null hypothesis) between 1970
and 2014. If unequal means are detected at any time in this temporal period, we conclude a significant
change in biodiversity at that year, reject the null hypothesis (alpha 0.05), and report a P-value.
Furthermore, if unequal means are detected, we use RDA with AIC to examine the relationships
between functional group biomass values from Monte Carlo Trials at the year biodiversity changes and
the biomass values of Polar Bears and Bowhead Whales at year 2014. These two functional groups are
chosen for further examination because of their annual population monitoring and estimation. This
method reveals which functional group(s) best predict the 2014 population of two internationally
managed marine mammals with well-documented biomass values (stock assessments), and R-values are
reported.
16
Results
Ecopath Model
Validation
Trophic levels calculated in other studies, ranging from the Chukchi-Beaufort Sea to the Stefansson
Sound, indicate that our Ecopath model’s trophic level calculations are consistent with observations
throughout the Beaufort Sea marine ecosystem (Fig. S1). Functional groups having a wider range of
calculated trophic levels correspond to our model’s aggregated functional groups, such as Salmonids,
Other Fish, or Molluscs, although our model trophic level values were closer to single species of salmon
(Hoekstra et al. 2003), snailfish (Hobson 1993), and gastropod (Buccinum sp.; Hobson and Welch
(1992)), respectively. Wider ranges are also mostly due to higher trophic level calculations from the
Chukchi Sea (e.g., Whitehouse (2013)), which is expected as the Chukchi Sea occupies a region extending
into lower, temperate latitudes.
Assessing Food-Web Structure
The trophodynamic SIMPROF hierarchical clusters produced in Ecopath, year 1970, are organized
into eight groups based on predators, according to similarities in their prey (“Predators”), and 12 groups
for prey according to similarities in their predators (“Prey”) (Fig. 2). The 1970 Predators cluster groups
all have indicator prey functional groups and corresponding IV (Indicator Values) of at least 60% or
greater, indicating a significant values, with the exception of Polar Bears. The Polar Bears functional
group/cluster has no statistically significant indicator prey or corresponding IV. The highest IV among
the Predators cluster groups is 100%, which reveals that the hierarchical cluster of Benthic Plants are
consumed by all invertebrates functional groups. Of the 12 Prey cluster groups identified in 1970, seven
have a statistically significant indictor predator functional group and corresponding IV. The lowest IV in
the Prey cluster groups is 20%, which indicates that Small Benthic Marine Fish and Flounder & Benthic
Cods are important prey items for Bearded Seals, and the highest IV in the Prey cluster groups was 98%,
17
which reveals that Ringed Seals were the main energetic pathway for Polar Bears. Other Predators
cluster groups capture known trophodynamic relationships, such as those observed between Beluga
Whales and Arctic & Polar Cods (Predators; Lowry et al. (1985)), or Walrus and Bivalves (Predators and
Prey; Fay (1982)).
Fig. 2 Similarity profile routine (SIMPROF) clusters of Predators and Prey, 1970. Predators 1970 are
clustered according to prey items in common, with indicator prey (and indicator values (%)), if identified,
shown on lines for the predator cluster. Similarly, Prey 1970 are clustered according to predators that
commonly eat them, with indicator predators, if identified, shown on lines for the prey cluster.
18
In SIMPROF tests considering MTI, a total of nine functional groups are identified as having the
significant trophodynamic structuring roles throughout the Beaufort Sea marine ecosystem, and these
keystone functional groups are (in order of importance): Arthropods, Bivalves/Walrus, Ringed Seals,
Micro-Zooplankton, Arctic & Polar Cods, Polar Bears, Producers < 5 µm, and Other Meso-Zooplankton
(Fig. 3). All other functional groups have less impactful trophodynamic structuring roles in Beaufort Sea
marine ecosystem; therefore, we examine the previously identified keystone functional groups to detect
important changes in diets (with the exception of the primary producer functional group; Producers < 5
µm) and biomass (results below).
Fig. 3 Similarity profile routine (SIMPROF) clusters identifying keystone functional groups. Keystone
functional groups identified significantly structure the Beaufort Sea marine food-web, with the most
keystone functional group at the top (Arthropods), and All Others indicate that functional groups not
listed are not consider keystone.
19
Ecosim Model
Calibration
Based on reviewed literature published from 1970 to 2014, and it was evident that marine mammals
have the most comprehensive temporal biomass data sets. This is particularly Polar Bears and Bowhead
Whales. For example, Beaufort Sea population estimates for polar bears and bowhead whales were
available for each of the last 45 years (n = 45). In most marine mammal functional groups annual
populations and growth rates are not available for each year in model calibrations. However, there is far
more data available for marine mammal functional groups when compared to fish (intermittent
sampling in August or September throughout the ecosystem), invertebrate (sampling usually limited to
areas from the coast to the continental shelf), or plankton functional groups (sampling mainly occurs in
ice-free seasonal periods/areas). In addition to population and growth rate estimates, marine mammals
also have the most comprehensive annual harvest data sets for each of the nine Beaufort Sea
indigenous communities. We find that our model captures changes in Polar Bears and Bowheads
Whales’ temporal biomass (Fig. S7a,c) and harvest (catch; Fig. S7b,d), when considering the whole-
ecosystem trophodynamics and forcing functions relating sea-ice extent and sea surface temperature.
These two functional groups have the most information in terms of biomass and harvest rates, and are
tightly regulated by national and international governances. All other functional groups that have
reported harvests in the Beaufort Sea marine ecosystem have limited biomass estimates (all pinnipeds),
are far less regulated (if at all), and have various reporting inconsistencies. The latter point comes from
differences in the number of animals harvested in a given year when comparing harvest reports. For
instance, in 1992 Kaktovik is reported to have harvested 17 bearded seals in Ice Seal Committee (2014),
and 24 according to Braund (2010). For these reasons we believe other EwE model calibrations for
harvest did not as accurately reflect temporal data, as R2 values ranged from less than 0.01 (n = 14) to
0.74 (n = 33). Thus, we use calculated mean harvesting rates (t km-2 y-1) assigned in Ecopath (Table S2).
20
Sensitivity Analysis
Sensitivity analysis demonstrates that our calculated functional group biomass values are all within
the 1st and 3rd quartiles (e.g., Fig. S8a), which are the potential ranges of initial biomass values evaluated
in Monte Carlo Trials, with the exception of Salmonids and Medium Copepods (e.g., Fig. S8b). Monte
Carlo iterations reveal that our model SS is 119.92, while the minimum produced is 119.10 and the
maximum produced is 138.68. Although our model does not have the lowest SS, less than 10% of the
Monte Carlo Trials produce a SS value lower than our model SS and the difference in SS values is
marginal. After examining 1000 Monte Carlo Trials our initial Salmonids biomass value is 0.5% less than
the 1st quartile biomass values in 1970, which increases to 3.2% less than the 1st quartile biomass value
by year 2010. Similarly, our initial Medium Copepods biomass value is 0.5% less than the 1st quartile
biomass values in 1970, which increases to 2.5% less than the 1st quartile biomass value by year 2010. It
is possible that our initial biomass calculations are low for these two functional groups; however, neither
of these functional groups (nor any other functional group) demonstrated biomass collapses, and we
conclude that our Beaufort Sea Ecosim model is robust for temporal analyses.
Assessing Food-Web Structural Changes
The trophodynamic SIMPROF hierarchical clusters produced in Ecopath, year 2014, is organized into
nine groups for predators according to similarities in their prey (“Predators”), and eight groups for prey
according to similarities in their predators (“Prey”; Fig. 4). Six out of the nine 2014 Predators cluster
groups have significant indicator prey functional groups and corresponding IV (Indicator Values) of at
least 56% or greater with the exception of Gray Whales, Herring & Smelt, and Polar Bears. These three
cluster groups have no statistically significant indicator prey or corresponding IV in year 2014. The
highest IV in 2014 among the Predators cluster groups is 96%, which reveals that the hierarchical cluster
of Benthic Plants are almost equally consumed by all invertebrates functional groups. Of the 12 Prey
cluster groups identified in 2014, seven have a statistically significant indictor prey functional group and
21
corresponding IV. The highest IV in the Prey cluster groups is 100%, which reveals that Bearded Seals,
Beluga Whales, Birds, Bowhead Whales, Gray Whales, Ringed Seals, Polar Bears, Spotted Seals, and
Walrus are an important energetic pathway for Polar Bears. As the ecosystem biomass and evenness go
up, the specialization of predators goes down, and more energetic pathways are created. A comparison
between 1970 and 2014 hierarchical clusters shows a 67% congruency for predators and a 42%
congruency for prey, indicating important predators have remained more similar than the prey items.
Throughout operating model simulations Arctic & Polar Cods have significant relationships with
Capelin and all of the keystone functional groups, except Arthropods (R2 = 100%; Fig. S9). These include
positive and negative trophodynamic relationships. For instance, as the biomass of Arctic & Polar Cods
increases, so does the biomass of Capelin, Mico-Zooplankton, Other Meso-Zooplankton, Polar Bears,
and Producers < 5 µm. Whereas, as the biomass of Arctic & Polar Cods increases, the biomass of
Walrus, Ringed Seals, and Bivalves decreases.
22
Fig. 4 Similarity profile routine (SIMPROF) clusters of Predators and Prey, 2014. Predators 2014 are
clustered according to prey items in common, with indicator prey (and indicator values (%)), if identified,
shown on lines for the predator cluster. Similarly, Prey 2014 are clustered according to predators that
commonly eat them, with indicator predators, if identified, shown on lines for the prey cluster.
Temporal Changes in Diet and Biomass
Changes in keystone functional group diets and biomass are presented in Table 2 and Figure 5(a-i),
respectively. Table 2 provides details of mean annual diet changes for keystone functional groups in
2014 when compared to 1970, whereas Figure 5 illustrates mean annual biomass changes for every year
23
from 1970 to 2014. In general keystone functional groups have a net-neutral or net-positive increase in
biomass, with the exception of the Walrus and Ringed Seals functional groups that have a net-negative
decrease in biomass (Fig. 5c,d). Notably, Bivalves and Polar Bears, have downward trends in biomass
beginning in the 1990s (Fig. 5b,g). Biomass increases across all functional groups increase proportionally
faster in lower biomass functional groups than in higher biomass functional groups (Fig. 5j), with
Bowhead Whales having the most growth (Fig. 6), reaching a population size in 2014 that is five times
greater than the initial population in 1970 (a near exponential increase). The dramatic increase in the
Bowhead Whales’ population consequently increases the predation mortality of five out of the nine
keystone functional groups. When examining all other model functional groups we find that the
majority experience net-positive increases in biomass from 1970 to 2014 (Fig. 5j). Non-keystone
functional groups that have net-negative changes in biomass include: Bearded Seals, Echinoderms,
Worms, Macro-Zooplankton, Ice Algae (due to forcing function), and Benthic Detritus. When we
examine temporal changes in biomass according to trophic level, we generally see increases in biomass
from 1970 to 2014 with the exception of the tropic level range of 2.0 to 2.5 (Fig. 6 inset), which
decreases due to the reductions in the Macro-Zooplankton functional group’s biomass.
24
Fig. 5 Historical reconstruction of keystone functional group relative biomass from 1970 to 2014 (a-i),
and percent change in biomass of all functional groups from 1970 to 2014 (i). Biomass is expressed in
relative changes, with one being the starting point biomass according to Table 1. The equation included
in 5i indicates that biomass increases proportionally faster for lower biomass functional groups than
higher biomass functional groups from 1970 to 2014.
25
Table 2. Changes in keystone functional group diets from 1970 to 2014. Trophic levels are averaged annually, resulting in temporal values that are different than initial values reported in Table 1.
Prey/Keystone Functional Group
Trophic Level 1970
Trophic Level 2014 Arthropods Bivalves Walrus
Ringed Seals
Micro-Zooplankton
Arctic & Polar Cods
Polar Bears
Other Meso-Zooplankton
Arctic & Polar Cods 3.45 3.46
1.11% 5.59% Arthropods 2.36 2.39
-0.19% -0.97%
1.01%
Bearded Seals 3.71 3.86
7.79%
-1.99% Beluga Whales 4.18 4.30
-0.23%
Benthic Detritus 1.00 1.00 -5.06% -5.35%
0.44% Benthic Plants 1.00 1.00 -0.21% -0.21%
Birds 3.82 3.97
0.24% Bivalves 2.00 2.00 -0.22%
-8.50%
Bowhead Whales 3.37 3.42
7.32% Capelin 3.45 3.51
0.66%
Char & Dolly Varden 3.61 3.67
3.46% Ciscoes & Whitefish 3.24 3.28
1.99%
Echinoderms 2.22 2.23 -0.25%
-0.31% -1.23%
-0.14% Flounder & Benthic Cods 3.34 3.43
-0.12%
Gray Whales 3.33 3.37
-0.29% Herring & Smelt 3.14 3.15
-0.37%
-1.70%
Ice Algae 1.00 1.00
-0.86%
2.06%
0.56% Import -- --
7.65%
Jellies 2.39 2.45 3.46% Large Copepods 2.29 2.28
-0.79%
-0.85%
Macro-Zooplankton 2.64 2.66
-0.50% -5.45% Micro-Zooplankton 2.00 2.00
-3.05%
-0.17%
Molluscs 2.00 2.00 -0.42%
-0.96% -1.17%
0.29% Other Benthos 2.08 2.08 -0.13%
-1.13%
0.04%
Medium Copepods 2.13 2.14
-0.39%
-0.48%
-1.00% Other Fish 3.10 3.13
0.04%
Other Meso-Zooplankton 1.00 1.00
1.19%
4.83%
0.30% Pelagic Detritus 1.00 1.00 3.43% 4.98%
1.34%
0.40%
Polar Bears 4.70 4.52
4.01% Producers < 5 µm 1.00 1.00
1.27%
-3.83%
0.40%
Producers > 5 µm 1.00 1.00
0.17%
-0.02%
-0.49% Ringed Seals 3.82 4.00
1.91%
-15.80%
Salmonids 3.60 3.78
0.82% Small Benthic Marine Fish 3.22 3.25
0.10% 0.29%
Spotted Seals 4.40 4.47
0.01%
-0.15% Walrus 3.14 3.36
-0.76%
Worms 2.07 2.07 -0.60%
-0.46% -1.61%
-0.74%
26
Fig. 6 Biomass (relative and t km-2) and trophic level (TL) changes for all functional groups from 1970,
1990, and 2014. Inset figure shows the percent change of biomass (t km-2) per trophic level from 1970
to 2014.
Biodiversity and Detecting Ecological Tipping Points
Shannon Index values indicate changes in ecosystem biodiversity, and significant associations to
climatological and model output variables (Fig. 7a-e). The Shannon Index increases from 1970 to 2014,
indicating an increase in ecosystem evenness, attributed to the initially lower biomass functional groups
(e.g., Capelin) increasingly proportionally faster than higher biomass functional groups (e.g.,
Echinoderms). As a proxy for richness, the change in biomass of fish, invertebrates, and plankton
(relative to 1970) are illustrated in Fig. 7a. In general marine mammal biomass increases from 1970 to
2014 by 9% (58% if bowhead whales are included). The fish biomass increases by 59%, invertebrate
biomass by 11%, zooplankton biomass by 18%, and phytoplankton biomass by 23%. Significant
associations are observed between the Shannon Index and sea-ice extent anomaly (Fig. 7b), sea surface
temperature anomaly (Fig. 7c), ecosystem biomass (Fig. 7d), and mean trophic level (Fig. 7e).
27
Fig. 7 Temporal changes in the Shannon index according to: a) Fish, Invertebrates, and Phytoplankton
relative biomass; b) Sea-ice anomaly (mean monthly difference compared to mean in 1970), c) Sea
surface temperature (SST) anomaly (mean monthly difference compared to mean in 1970), d) Whole-
ecosystem biomass (t km-2), and e) Whole-ecosystem mean trophic level. Climatological tipping point
refers to statistically significant tipping point in whole-ecosystem biodiversity, with R2 values revealing
the variability in the Shannon Index explained by accompanying variable and whether it is a positive (+)
or negative (-) relationship. In 7a the Biodiversity Tipping Point describes the time at which preceding
biodiversity values are significantly different than subsequent biodiversity values.
28
In analyzing the variability the Shannon Index when associated with sea-ice extent anomalies, we
find a negative relationship and corresponding R2 value of 0.41 between 1970 and 1992, and a positive
relationship and corresponding R2 value of 0.21 between 1993 and 2014. Conversely, in analyzing the
variability in the Shannon Index when associated with sea surface temperature anomalies we find a
positive significant relationship and corresponding R2 value of 0.10 between 1970 and 1992, and a
significant negative relationship and corresponding R2 value of 0.69 between 1993 and 2014. With
increasing biomass in the Beaufort Sea marine ecosystem, we find that 42% of the variability in Shannon
Index can be explained by a positive association with biomass from 1970 to 1992 (R2 = 0.42), and a
negative association from 1993 to 2014 (R2 = 0.49). When examining temporal changes in biomass, we
see changes (positive or negative) in all keystone functional groups starting in 1998 (Fig. 5a-i). For
example, we observe an acute increase in Micro-Zooplankton biomass and concomitant decrease in
Ringed Seals biomass. Variability in the Shannon Index can be explained by a positive association with
the Beaufort Sea ecosystem’s mean trophic level from 1970 to 1992 (R2 = 0.64); however, after 1992 the
Shannon Index has no statistically significant relationship with the mean trophic level.
As the Shannon Index has statistically significant associations with sea-ice extent anomalies, sea
surface temperature anomalies, biomass, and mean trophic level before and predominantly after 1992,
we regard this temporal transition as the “Climatological Tipping Point” in the operating model’s
historical reconstruction (Fig. 7a-e). A few years after the Climatological Tipping Point an abrupt
increase in the Shannon Index occurs in 1998. In Student T-tests examining the temporal Shannon Index
values the null hypotheses is rejected (P-value less than 0.003), indicating that biodiversity values are
different before and after 1998. With this result, and as 1998 is a year when sea-ice extent reaches a
historical low, we regard this temporal transition as the “Biodiversity Tipping Point”. The Biodiversity
Tipping Point reveals the whole-ecosystem response to enduring climatological changes expressed in
29
operating model forcing and mediation functions, and therefore the period of time when significant
food-web structural changes begin to occur.
When we examine the influences of the post-Biodiversity Tipping Point (post 1998) biomass of all
functional groups in 1999, with the biomass of Polar Bears and Bowhead Whales in 2014 (using RDA
with AIC), we find that significant relationships emerge. The Polar Bears’ biomass is positively
influenced by Ice Algae, Bowhead Whales, Arthropods, and Producers < 5 µm, and is negatively
influenced by Micro-Zooplankton, Benthic Plants, and Large Copepods; explaining 61% of the
population’s variability overall (Fig. 8a). Likewise, the Bowhead Whales’ biomass is positively influenced
by Polar Bears, Producers < 5 µm, and Micro-Zooplankton, and is negatively influenced by Macro-
Zooplankton, Ringed Seals, Arctic & Polar Cods, Other Meso-Zooplankton, and Other Fish; explaining
57% of the population’s variability overall (Fig. 8b).
Fig. 8 Results of redundancy analysis (RDA) for a) Polar Bears, and b) Bowhead Whales. As the
dependent variable is univariate (green) only the x-axis describes the relationship to and variability
explained by independent variables (red).
30
Discussion
In terms of SIMPROF and simulated Beaufort Sea food-web structural changes over the last 45 years,
predators are progressively diversifying their diets, depending less on traditional predator-prey
relationships, and increasing their intake of prey groups once less frequently consumed. These food-
web structural changes led to a 33% reduction in the similarities in predatory hierarchical clusters
between 1970 and 2014. Consequently, prey groups have been reducing their energetic contributions
to specialized predators, but provide more energy to a greater number of predators overall. However,
this trend towards predatory generalists likely minimizes more specialized and/or highly co-evolved
trophodynamic exchanges within the Beaufort Sea marine ecosystem. An example of this includes Polar
Bears and Ringed Seals. These food-web structural changes led to a 58% reduction in similarities in prey
hierarchical clusters, suggesting that Beaufort Sea trophodynamics have been distinctly restructured
over the last 45 years. The main drivers changing Beaufort Sea marine trophodynamics are the bottom-
up forcing and mediation functions expressing decreases in sea-ice extent and increases in sea surface
temperature. Examples of food-web structural changes that affect keystone functional groups include:
increases in the biomass of Arthropods, Micro-Zooplankton, and Other Meso-Zooplankton with
increases in primary production and pelagic detritus, a small reduction in Bivalves’ biomass following a
decrease in benthic detritus (greater overall pelagic biomass/consumption), an increase in the
competition between Walrus and Gray Whales for Bivalves, an increase in the competition between
Ringed Seals and several other Beaufort Sea predators for Arctic & Polar Cods, and Polar Bears eating
less of their traditional prey, Ringed Seals, and increasing their incidents of cannibalism and foraging
outside of the model area.
Operating model trophodynamics indicate that the annual growth of phytoplankton biomass, +23%
by year 2014, will benefit zooplankton (+18%; all groups), yield mixed impacts to invertebrates (+11%),
and benefit only three marine mammals, Beluga Whales (+56%), Gray Whales (+18%), and Spotted Seals
31
(+16%). While increases in primary production benefit the keystone functional groups of Arthropods,
Micro-Zooplankton, Other Meso-Zooplankton, and Arctic & Polar Cods (e.g., Michaud et al. (1996)),
either directly as prey and/or indirectly through the diets of their prey, the benefits to Arctic & Polar
Cods are likely limited. With increasing sea surface temperatures the Arctic cod, Boreogadus saida, may
reach its upper thermal limit (Graham & Hop 1995, Drost et al. 2014)(Fig. S3), thereby reducing suitable
Arctic & Polar Cods habitats in the Beaufort Sea, and inhibit their energetic contributions to the entire
Arctic food-web (e.g. Nahrgang et al. (2014)). As Arctic & Polar Cods are critical links in trophodynamic
pathways across trophic levels (Bain & Sekerak 1978, Welch et al. 1993, Christiansen et al. 2012, Hop &
Gjøsæter 2013), a reduction in their biomass would likely have a negative impact the Beaufort Sea
marine ecosystem and directly impact the keystone functional groups of Walrus and Ringed Seals.
Arctic & Polar Cods’ biomass is positively influenced by Producers < 5 µm, Micro-Zooplankton, Other
Meso-Zooplankton, and Polar Bears. While Arctic & Polar Cods consume these functional groups, Polar
Bears limit Ringed Seals’ predatory pressure on Arctic & Polar Cods, thus yielding an indirect positive
influence overall. As Walrus eat both Bivalves and Arctic & Polar Cods, increases in Bivalves’ biomass
would benefit Walrus biomass, but negatively influence Arctic & Polar Cods. According to the operating
model’s historic reconstruction from 1970 to 2014, Walrus and Ringed Seals are becoming increasingly
reliant on their Arctic & Polar Cods prey, which constitute a larger percentage of their overall diets. The
latter functional group, Ringed Seals, also has a direct influence on the health the Polar Bears keystone
functional group. If a sudden decrease in the energetic contributions from the Arctic & Polar Cods
occurs as the Beaufort Sea warms, higher trophic level predators (Beluga Whales, Ringed Seals, Arctic
Charr) reliant on Arctic & Polar Cods (Bradstreet et al. 1986, DFO 1999b, Loseto et al. 2009) will have to
alter their prey, possibly opening the door for sub-Arctic species such as Capelin (Rose 2005b, Rose
2005a, Walkusz et al. 2013). Capelin are still considered low abundance in the region, compared to
Arctic & Polar Cods; however, they co-occur across the Beaufort Sea and have dietary overlaps with
32
Arctic & Polar Cods (Cobb et al. 2008, McNicholl et al. 2015). Furthermore, while Capelin are consumed
by marine mammals in other Arctic regions (Bluhm & Gradinger 2008), their importance to marine
mammals (Beluga Whales and Ringed Seals) in the Beaufort Sea is has not been noted until recently
(Choy et al. 2016). Increases in Capelin as a forage fish have occurred in Hudson Bay (Gaston et al. 2003)
and the Barents Sea (Hop & Gjøsæter 2013), highlighting the potential for large increases in the Beaufort
Sea. However. the energetic contributions of Arctic & Polar Cods and Capelin are similar (5-7 kJ g-1 ww
vs. 4-5 kJ g-1 ww respectively (Hop & Gjøsæter 2013), with higher values up to 8.4 5-7 kJ g-1 ww reported
by Lawson et al. (1998)) and few energetic impacts may occur with an increase in Capelin biomass.
Although, Ringed Seals’ diets may be negatively impacted and this could further imperil Polar Bears’
diets as well.
Beaufort Sea Polar Bears forage from the sea-ice habitat for prey ranging from whales to pinnipeds
to seabirds, and the diminishing sea-ice extent reduces their foraging success, therefore survival
potential (Amstrup 2003, Derocher et al. 2004, Stirling & Parkinson 2006, Gormezano & Rockwell 2013b,
Gormezano & Rockwell 2013a, Iles et al. 2013). The recent decline in the population of Beaufort Sea
polar bears has been attributed to reductions in sea-ice extent and consequential shifts in the polar
bear’s access to traditional prey (Derocher et al. 2004, Dyck et al. 2007, Meier et al. 2007, Schliebe et al.
2008, Stirling et al. 2008, Bromaghin et al. 2015). For example, polar bears eat more bowhead whales
and less ringed seals in low ice years, and more ringed seals in high ice years (Bentzen et al. 2007). In
the Arctic marine ecosystem polar bears heavily rely on ringed seals for the majority of their energetic
requirements (Lønø 1970, Smith 1980, Gjertz & Lydersen 1986, Derocher et al. 2002). Our operating
model captures these real-world observations, suggesting that by 2014 Polar Bears eat about 16% less
Ringed Seals, have increased incidents of cannibalism (Amstrup et al. 2006), and increased energy
demands from terrestrial-based (import) diets (Gormezano & Rockwell 2013b).
33
With a diminishing mean monthly sea-ice extent and increasing mean monthly sea surface
temperatures, the biomass from 1970 to 2014 has increased for the majority of Beaufort Sea functional
groups. The functional group with the single greatest increase in biomass is the Bowhead Whales with a
five-fold growth of their population; however, the fish functional groups, when considered collectively,
had the largest biomass increases overall (59%). One of the issues with the Bowhead Whales’ near-
exponential growth over the last 45 years is their potential to reach carrying capacity (Brandon & Wade
2006). At their carrying capacity, the energetic demand of the Bowhead Whales functional group as a
whole will be the greatest, which directly impacts the biomass of five of the nine keystone functional
groups. Furthermore, as the seasonal sea-ice extent decreases, the area of the Arctic will likely include
more suitable habitats for more whales (bowhead whales, beluga whales, gray whales, and killer
whales). This will increase their seasonal residence time, as migrations into the Beaufort Sea are likely
to take place earlier in the year, and migrations out of the Beaufort Sea are likely to take place later in
the year. The potential for ecological imbalances with the Bowhead Whales is great when considering
resource limitations alone. Furthermore, the increase in fish biomass does not necessary translate to
increased biomass of apex predators. As fish functional groups increase in biomass with climatological
changes, the middle trophic levels receive the greatest trophodynamic benefits, leading to decreases in
the biomass of Polar Bears, Ringed Seals, and Walrus within the model.
When examining Shannon Index values from 1970 to 2014, the relationships between biodiversity
and environmental variables indicates that the Beaufort Sea may already be experiencing food-web
structural impacts due to climate change, and tipping points may have already been reached (Lindsay &
Zhang 2005). With the assumption that the 1970 trophodynamics, sea-ice extents, and sea surface
temperatures characterize the time when the Beaufort Sea marine ecosystem was stable, statistical
analyses indicate that a significant Climatological Tipping Point was reached in the early 1990s, and a
significant Biodiversity Tipping Point was reached in the late 1990s. Arctic-wide the late 1980s have
34
been identified as a plausible climatological tipping point, as thinning of sea ice has resulted in reduced
summer sea ice extent and concentration (Lindsay & Zhang 2005, Lindsay et al. 2009). In general, the
loss of multi-year sea ice in the Beaufort Sea, coupled with positive feedbacks, has left the region unable
to recover (Maslanik et al. 2011). Following the Climatological Tipping Point the mean annual whole-
ecosystem biomass values and trophic levels significantly increase. And, following the Biodiversity
Tipping Point, the Beaufort Sea marine ecosystem displays an increasing mean annual evenness. The
changes in predator diets, and an increase in the biomass of the middle trophic levels, support these
observations. However, even as the majority of the Beaufort Sea functional groups have benefited from
the increased primary productivity, the biomass of Polar Bears, Walrus, Ringed Seals, Bearded Seals,
Bivalves, Echinoderms, Worms, and Benthic Detritus have been steadily decreasing since the
Biodiversity Tipping Point. This indicates feedback loops through the Beaufort Sea food-web that
negatively affects almost half of the ecosystem’s keystone species. As the other keystone species
mostly benefit from these inter-ecosystem feedback loops and given a keystone species’ potential
impact to the ecosystem, it is very likely that the entire Beaufort Sea marine ecosystem will continue to
undergo significant food-web restructuring in the decades to come.
As available biomass (energy) is the currency in feedback loops and trophodynamics, we use RDA
with AIC and the post-Biodiversity Tipping Point (1999) biomass values calculated for each functional
group in the Monte Carlo Trials to identify functional groups that, positively or negatively, influence the
2014 biomass of Polar Bears and Bowhead Whales. These two marine mammals are chosen for this
method of analysis because they are actively managed by state, local, and/or international governances,
their annual biomass estimates are available from 1970 to 2014, and they are dissimilarly influenced by
the diminishing sea-ice extent. We find that the functional groups that explain the majority of the
variability in the Polar Bears’ biomass are Benthic Detritus and Micro-Zooplankton biomass, and for the
Bowhead Whales’ biomass are Macro-Zooplankton and Ringed Seals. Additionally, the Polar Bears and
35
Bowhead Whales functional groups positively influence each other. While the Bowhead Whales directly
benefit Polar Bears’ diet, the Polar Bears eat prey, such as Ringed Seals, who eat prey, such as Arctic &
Polar Cods, who compete with Bowhead Whales for food. Therefore, the functional groups influential
to Polar Bears and Bowhead Whales biomass are also keystone functional groups, which includes Arctic
& Polar Cods as a common and critical energetic link. Ongoing management of Polar Bears and
Bowhead Whales in the Beaufort Sea would likely benefit from increased monitoring efforts of the
keystone functional groups; specifically, population assessments and trends for Ringed Seals, Arctic &
Polar Cods, Micro-Zooplankton, and Primary Producers < 5 µm.
Conclusions
From the advent of whaling and subsequent protection of endangered/threatened species, to the
physiological adaption of Arctic marine animals to sub-freezing water temperatures and recent declines
in sea-ice extent, the Beaufort Sea marine ecosystem has likely been experiencing great changes in its
trophodynamic structure for decades. However, with more recent reductions in the sea-ice extent and
increases in sea surface temperature, natural trophodynamic variability has likely been superseded by
food-web restructuring, and this is most evident in biomass trends of the Beaufort Sea’s keystone
functional groups. Operating model results suggest that a tipping point in the food-web restructuring
has already occurred. Then again, as the Arctic sea-ice extent continues to decrease and the sea surface
temperature continues to increase, and the population of whales reaches carrying capacity while the
keystone functional groups continue to change biomass, much greater changes to the Beaufort Sea
marine ecosystem are likely to occur.
36
Acknowledgements
This project was supported by a Mote Marine Laboratory Postdoctoral Research Fellowship. Carie
Hoover would like to thank funding sources contributing to an earlier version of the model: Fisheries and
Oceans Canada: the Ecosystem Research Initiative and Aquatic Climate Change Adaptation Services
Program under Fisheries and Oceans Canada, ArcticNet, and the National Sciences and Engineering
Research Council of Canada. In addition, expertise from Lisa Loseto, Wojciech Walkusz, Shanon
MacPhee, Andrew Majewski, and Andrea Niemi contributed to the ecological knowledge necessary for
model development.
37
Manuscript References
Acia (2004) Impacts of a warming Arctic: Arctic climate impact assessment. Arctic Climate Impact Assessment
Adnr (2011) North Slope foothills areawide oil and gas lease sales, final finding of the Director. Alaska Department of Natural Resources, Division of Oil & Gas
Aklavik CO (2008) Aklavik Inuvialuit community conservation plan (Akaqvikmiut Nunamikini Nunutailivikautinich). The Community of Aklavik, the Wildlife Management Advisory Council (NWT) and the Joint Secretariat
Allen BM, Angliss RP (2010) Alaska marine mammal stock assessments, 2009. U.S. Department of Commerce, NOAA Technical Memorandum NMFS-AFSC-206: 276
Amstrup SC (2003) Wild mammals of North America, Amstrup SC, Marcot BG, Douglas DC (2007) Forecasting the range-wide status of polar bears at selected
times in the 21st century. Administrative Report. US Geological Survey Amstrup SC, Stirling I, Smith TS, Perham C, Thiemann GW (2006) Recent observations of intraspecific
predation and cannibalism among polar bears in the southern Beaufort Sea. Polar Biol 29: 997-1002
Arlis (2015) Subsistence use patterns. Alaska Resources & Library Information Services Bacon JJ, Hep TR, Brower HK, Jr., Pedereson M, Olemaun TP, George JC, Corrigan BG (2009) Estimates of
Subsistence Harvest for Villages on the North Slope of Alaska, 1994-2003. North Slope Borough Department of Wildlife Management
Bain H, Sekerak AD (1978) Aspects of the biology of Arctic cod, (Boreogdus saida), in the central Canadian Arctic. Unpublished Report by LGL Ltd for Polar Gas Project:
Barlow J, Boveng P (1991) Modeling age-specific mortality for marine mammal populations. Marine Mammal Sci 7: 50-65
Benson AJ, Trites AW (2002) Ecological effects of regime shifts in the Bering Sea and eastern North Pacific Ocean. Fish Fisheries 3: 95-113
Bentzen TW, Follmann EH, Amstrup SC, York GS, Wooller MJ, O’hara TM (2007) Variation in winter diet of southern Beaufort Sea polar bears inferred from stable isotope analysis. Can. J. Zool. 85: 596-608
Blm (2005) Northeast national petroleum reserve – Alaska, FINAL amended integrated activity plan/environmental impact assessment: Appendix J. Bureau of Land Management
Bluhm BA, Gradinger RR (2008) Regional variability in food availability. Ecological Applications 18: 77-96 Bradstreet MSW, Cross WE (1982) Trophic relationships at high Arctic ice edges. Arctic 35 Bradstreet MSW, Finley KJ, Sederak AD, Griffiths WB, Evans CR, Fabijan MF, Stallard HE (1986) Aspects of
the Biology of Arctic Cod (Boreogaduc saida) and its Importance in Arctic Marine Food Chains Canadian Technical Report of Fisheries and Aquatic Sciences:
Brandon JR, Wade PR (2006) Assessment of the Bering-Chukchi-Beaufort Seas stock of bowhead whales using Bayesian model averaging. Journal of Cetacean Research Management 8: 225-239
Braund SR (1993) North Slope subsistence study Barrow, 1987, 1988 and 1989. OCS Study MMS 91-0086. U. S. Department of the Interior, Minerals Management Service
Braund SR (2010) Subsistence mapping of Nuiqsut, Kaktovik, and Barrow. MMS OCS Study Number 2009-003. United States Department of the Interior
Braund SR (2012) Point Thompson Project EIS, final environmental impact assessment, Appendix Q. Bromaghin JF, Mcdonald TL, Stirling I, Derocher AE, Richardson ES, Regehr EV, Douglas DC, Durner GM,
Atwood T, Amstrup SC (2015) Polar bear population dynamics in the southern Beaufort Sea during a period of sea ice decline. Ecological Applications 25: 634-651
38
Buszowski J, Christensen V, Gao F, Hui J, Lai S, Steenbeek J, Walters C, Walters W (2009) Ecopath with Ecosim 6.
Canada I-IaNA (1984) The Western Arctic Claim, The Inuvialuit Final Agreement. Ottawa: Indian Affairs and Northern Development: 115
Carmack EC, Macdonald RW (2002) Oceanography of the Canadian Shelf of the Beaufort Sea: A Setting for Marine Life. Arctic 55
Centre BaD (2010) HadISST 1.1 - Global sea-ice coverage and SST (1870-present). Christensen V, Walters C, Pauly D (2005) Ecopath with Ecosim: a user’s guide Version 5. Fisheries Centre:
University of British Columbia Christiansen JS, Hop H, Nilssen EM, Joensen J (2012) Trophic ecology of sympatric Arctic gadoids,
Arctogadus glacialis (Peters, 1872) and Boreogadus saida (Lepechin, 1774), in NE Greenland. Polar Biol 35: 1247-1257
Clarke KR, Somerfield PJ, Gorley RN (2008) Testing of null hypotheses in exploratory community analyses: similarity profiles and biota-environment linkage. Journal of Experimental Marine Biology and Ecology 366: 56-69
Cobb D, Fast H, Papst MH, Rosenberg D, Rutherford R, Sareault JE (2008) Beaufort Sea Large Ocean Management Area (LOMA): Ecosystem overview and assessment report.
Council IC (2012) Food security across the Arctic: Background paper of the steering committee of the Circumpolar Inuit Health Strategy. Inuit Circumpolar Council - Canada: 12
Darnis G, Barber DG, Fortier L (2008) Sea ice and the onshore–offshore gradient in pre-winter zooplankton assemblages in southeastern Beaufort Sea. Journal of Marine Systems 74: 994-1011
Derocher AE, Lunn NJ, Stirling I (2004) Polar Bears in a Warming Climate. Integrative and Comparative Biology 44: 163-176
Derocher AE, Wiig Ø, Andersen M (2002) Diet composition of polar bears in Svalbard and the western Barents Sea. Polar Biology 25: 448-452
Dfo (1999a) Annual summary of fish and marine mammal harvest data for the Northwest Territories, 1996-1997. Department of Fisheries and Ocean
Dfo (1999b) Hornaday River Arctic Charr. DFO Stock Status Report Dfo (2013) Tarium Niryutait: Marine Protected Area management plan. Fisheries and Oceans Canada:
Fisheries and Oceans Canada & Fisheries Joint Management Committee, Winnipeg, MB Drost HE, Carmack EC, Farrell AP (2014) Upper thermal limits of cardiac function for Arctic cod
Boreogadus saida , a key food web fish species in the Arctic Ocean. Journal of Fish Biology 84: 1781-1792
Dufrene M, Legendre P (1997) Species Assemblages and Indicator Species: The Need for a Flexible Asymmetrical Approach. Ecological Monographs 67: 345
Dunton KH, Weingartner T, Carmack EC (2006) The nearshore western Beaufort Sea ecosystem: Circulation and importance of terrestrial carbon in arctic coastal food webs. Progress in Oceanography 71: 362-378
Dyck MG, Soon W, Baydack RK, Legates DR, Baliunas S, Ball TF, Hancock LO (2007) Polar bears of western Hudson Bay and climate change: Are warming spring air temperatures the “ultimate” survival control factor? Ecological Complexity 4: 73-84
Fay FH (1982) Ecology and biology of the pacific walrus, odobenus rosmarus divergens Illiger. North American Fauna 74: 1-279
Feder HM, Foster NR, Jewett SC, Weingartner TJ, Baxter R (1994a) Mollusks in the Northeastern Chukchi Sea. Arctic 47
Feder HM, Naidu AS, Jewett SC, Hameedi JM, Johnson WR, Whitledge TE (1994b) The northeastern Chukchi Sea: benthos-environmental interactions. Marine Ecology Progress Series 111: 171-190
39
Fraker MA, Bockstoce J (1980) Summer distribution of bowhead whales in the eastern Beaufort Sea. Mar. Fish. Rev.: 57-64
Francis RC, Hare SR, Hollowed AB, Wooster WS (1998) Effects of interdecadal climate variability on the oceanic ecosystems of the NE Pacific. Fisheries Oceanography 7: 1-21
Gaston AJ, Woo K, Hipfner JM (2003) Trends in forage fish populations in northern Hudson Bay since 1981, as determined from the diet of nestling thick-billed murres Uria lomvia. Arctic 56: 227-233
George JC, Nicolson CR, Drobot S, Maslanik J, Suydam R, Rosa C (2009) Progress Report: Update on sea ice density and bowhead whale body condition. Paper SC/57/E13 workshop on climate change and cetaceans.
Gjertz IaN, Lydersen C (1986) Polar bear predation on ringed seals in the fast-ice of Hornsund, Svalbard. Polar Research 4: 65-68
Godínez-Domínguez E, Freire J (2003) Information-theoretic approach for selection of spatial and temporal models of community organization. Marine Ecology Progress Series 253: 17-24
Gormezano LJ, Rockwell RF (2013a) Dietary composition and spatial patterns of polar bear foraging on land in western Hudson Bay. BMC Ecol 13: 51
Gormezano LJ, Rockwell RF (2013b) What to eat now? Shifts in polar bear diet during the ice-free season in western Hudson Bay. Ecol Evol: n/a-n/a
Gradinger RR (2002) Sea ice, a unique realm for microorganisms. In: BITTEN, G. (ed.) Encyclopedia of Environmental Microbiology. Wiley
Graham M, Hop H (1995) Aspects of reproduction and larval biology of Arctic cod (Boreogadus saida). Arctic 48
Grebmeier JM, Barry JP (1991) The influence of oceanographic processes on pelagic-benthic coupling in polar regions: A benthic perspective. Journal of Marine Systems 2: 495-518
Grebmeier JM, Smith WO, Jr., Conover RJ (1995) Biological processes on Arctic continental shelves: ice-ocean-biotic interactions. In: SMITH, W. O., JR. & GREBMEIER, J. M. (eds.) Arctic Oceanography: marginal ice zones and continental shelves. Washington: American Geophysical Union
Hansen J, Sato M, Ruedy R, Lo K, Lea DW, Medina-Elizade M (2006) Global temperature change. Proceedings of the National Academy of Sciences 103: 14288-14293
Harwood LA, Smith TG (2002) Whales of the Inuvialuit Settlement region in Canada's Western Arctic: An overview and outlook. Arctic 55
Harwood LA, Smith TG, George JC, Sandstrom SJ, Walkusz W, Divoky GJ (2015) Change in the Beaufort Sea ecosystem: Diverging trends in body condition and/or production in five marine vertebrate species. Progress in Oceanography 136: 263-273
Higdon JW, Ferguson SH (2009) Loss of Arctic sea ice causing punctuated change in sightings of killer whales (Orcinus orca) over the past century. Ecological Applications 19: 1365-1375
Hobson KA (1993) Trophic relationships among high Arctic seabirds: insights from tissue-dependent stable-isotope models. Marine Ecology Progress Series 95: 7-18
Hobson KA, Welch HE (1992) Determination of trophic relationships within a high Arctic marine food web using δ13C and δ15N analysis. Marine Ecology Progress Series 84: 9-18
Hoegh-Guldberg O, Bruno JF (2010) The Impact of Climate Change on the World's Marine Ecosystems. Science 328: 1523-1528
Hoekstra PF, O'hara TM, Fisk AT, Borgå K, Solomon KR, Muir DCG (2003) Trophic transfer of persistent organochlorine contaminants (OCs) within an Arctic marine food web from the southern Beaufort–Chukchi Seas. Environmental Pollution 124: 509-522
Hoover C, Ostertag S, Hornby CA, Parker C, Loseto LL, Pearce T (2016) The continued importance of the hunter for inuit food security. Solutions 7: 40-51
40
Hoover C, Pitcher T, Christensen V (2013a) Effects of hunting, fishing and climate change on the Hudson Bay marine ecosystem: I. Re-creating past changes 1970–2009. Ecological Modelling 264: 130-142
Hoover C, Pitcher T, Christensen V (2013b) Effects of hunting, fishing and climate change on the Hudson Bay marine ecosystem: II. Ecosystem model future projections. Ecological Modelling 264: 143-156
Hop H, Gjøsæter H (2013) Polar cod (Boreogadus saida) and capelin (Mallotus villosus) as key species in marine food webs of the Arctic and the Barents Sea. Marine Biology Research 9: 878-894
Horner R, Murphy D (1985) Species composition and abundance of zooplankton in the nearshore Beaufort Sea in winter-spring. Arctic 38
Huet C, Rosol R, Egeland GM (2012) The prevalence of food insecurity is high and the diet quality poor in Inuit communities. Journal of Nutrition 142: 541-547
Iles DT, Peterson SL, Gormezano LJ, Koons DN, Rockwell RF (2013) Terrestrial predation by polar bears: not just a wild goose chase. Polar Biol 36: 1373-1379
Inuvik CO (2008) Inuvik Inuvialuit community conservation plan. The Community of Inuvik, the Wildlife Management Advisory Council (NWT) and the Joint Secretariat
Ipcc (2014) Climate change 2014: Synthesis report. In: PACHAUIR, R. K. & MEYER, L. A. (eds.) Contribution of working groups I, II and III to the fifth assessment report of the Intergovernmental Panel on Climate Change IPCC, Geneva, Switzerland:
Iucn (2010) Polar bears. Proceedings of the 15th working meeting of the IUCN/SSC Polar Bear Specialist Group. Gland, Switzerland and Cambridge, UK:
Johannessen OM, Bengtsson L, Miles MW, Kuzmina SI, Semenov VA, Alekseev GV, Nagurnyi AP, Zakharov VF, Bobylev LP, Pettersson LH, Hasselmann K, Cattle HP (2004) Arctic climate change: Observed and modelled temperature and sea-ice variability. TELLUSA
Joint-Secretariat (2003) Inuvialuit harvest study, data methods report 1988-1997. Inuvik, NWT: Joint Secretariat
Jones DL (2014) Fathom toolbox for Matlab: software for multivariate ecological and oceanographic data analysis. St. Petersburg, FL: College of Marine Science, University of South Florida
Krupnik I, Jolly D (2002) The earth is faster now: indigenous observations of Arctic environmental change. Arctic Research Consortium of the United States: 356
Lawson JW, Magalhaes AM, Miller EH (1998) Important prey species of marine vertebrate predators in the northwest Atlantic: proximate composition and energy density. Marine Ecology Progress Series 164: 13-20
Li WKW, Mclaughlin FA, Lovejoy C, Carmack EC (2009) Smallest algae thrive as the arctic ocean freshens. Science 326: 539-539
Libralato S, Christensen V, Pauly D (2006) A method for identifying keystone species in food web models. Ecological Modelling 195: 153-171
Lindeman RL (1942) The trophic-dynamic aspect of ecology. Ecology 23: 399-417 Lindsay RW, Zhang J (2005) The thinning of Arctic sea ice, 1998-2003: Have we passed the tipping point?
American Meteorological Society 18: 4879-4894 Lindsay RW, Zhang J, Schweiger A, Steele M, Stern H (2009) Arctic sea ice retreat in 2007 follows
thinning trend. Journal of Climate 22: 165-176 Lønø OO (1970) The polar bear (Ursus maritimus Phipps) in the Svalbard area. Norsk Polarinstitutt
Skrifter 149: 1-115 Loseto LL, Stern GA, Connelly TL, Deibel D, Gemmill B, Prokopowicz A, Fortier L, Ferguson SH (2009)
Summer diet of beluga whales inferred by fatty acid analysis of the eastern Beaufort Sea food web. Journal of Experimental Marine Biology and Ecology 374: 12-18
41
Lowry LF, Frost KJ, Seaman GA (1985) Investigations of Beluhka whales in coastal waters of western and northern Alaska. III. Food habits.
Majkowski J (1982) Usefulness and applicability of sensitivity analysis in a multispecies approach to fisheries management. In: PAULY, D. & MURPHY, G. I. (eds.) Theory and management of tropical fishes. ICLARM
Manabe S, Stouffer RJ (1995) Simulation of abrupt climate change induced by freshwater input to the North Atlantic Ocean. Nature 378: 165-167
Maslanik J, Stroeve JC, Fowler C, Emery W (2011) Distribution and trends in Arctic sea ice age through spring 2011. Geophys. Res. Lett. 38: LI3502
Mcnicholl D, Walkusz W, Davoren G, Majewski AR, Reist JD (2015) Dietary characteristics of co-occurring polar cod (Boreogadus saida) and capelin (Mallotus villosus) in the Canadian Arctic. Polar Biology
Meier WN, Stroeve J, Fetterer F (2007) Whither Arctic sea ice? A clear signal of decline regionally, seasonally and extending beyond the satellite record. Annals of Glaciology 46: 428-434
Michaud J, Fortier L, Rowe P, Ramseier R (1996) Feeding success and survivorship of Arctic cod larvae, Boreogadus saida, in the Northeast Water polynya (Greenland Sea). Fisheries Oceanography 5: 120-135
Nahrgang J, Varpe Ø, Korshunova E, Murzina S, Hallanger IG, Vieweg I, Berge J (2014) Gender specific reproductive strategies of an Arctic key species (Boreogadus saida) and implications of climate change. PLoS ONE 9: e98452
Noaa (2015) Happening now: Arctic sea ice sets record low. National Oceanic and Atmospheric Administration
Nrdc (2015) Global warming put the Arctic on thin ice. Nsb (2014) Kaktovik comprehensive development plan, final draft December 2014. Department of
Planning and Community Services, North Slope Borough Odum WE, Heald EJ (1975) The detritus-based food web of an estuarine mangrove community. In:
CRONIN, L. E. (ed.) Estuarine Research. New York: Academic Press Orlova E, Boitsov V, Dolgov A, Rudneva G, Nesterova V (2005) The relationship between plankton,
capelin, and cod under different temperature conditions. ICES Journal of Marine Science 62: 1281-1292
Paulatuk CO (2008) Paulatuk Inuvialuit community conservation plan. The Community of Paulatuk, the Wildlife Management Advisory Council (NWT) and the Joint Secretariat
Rose GA (2005a) Capelin (Mallotus villosus) distribution and climate: a sea “canary” for marine ecosystem change. ICES Journal of Marine Science 62: 1524-1530
Rose GA (2005b) On distributional responses of North Atlantic fish to climate change. ICES Journal of Marine Science 62: 1360-1374
Rosol R, Powell-Hellyer S, Chan HM (2016) Impacts of decline harvest of country food on nutrient intake among Inuit in Arctic Canada: impact of climate change and possible adaptation plan. International Journal of Circumpolar Health 75
Sachs-Harbour (2008) Sachs Harbour Inuvialuit community conservation plan. The Community of Sachs Harbour, the Wildlife Management Advisory Council (NWT) and the Joint Secretariat
Schliebe S, Rode KD, Gleason JS, Wilder J, Proffitt K, Evans TJ, Miller S (2008) Effects of sea ice extent and food availability on spatial and temporal distribution of polar bears during the fall open-water period in the Southern Beaufort Sea. Polar Biol 31: 999-1010
Schuur EaG, Mcguire AD, Schädel C, Grosse G, Harden JW, Hayes DJ, Hugelius G, Koven CD, Kuhry P, Lawrence DM, Natali SM, Olefeldt D, Romanovsky VE, Schaefer K, Turetsky MR, Treat CC, Vonk JE (2015) Climate change and the permafrost carbon feedback. Nature 520: 171-179
Shannon CE (1948) A mathematical theory of communication. Bell System Technical Journal 27: 623-656
42
Shannon CE, Weaver W (1949) The mathematical theory of communication, Urbana, IL, University of Illinois Press
Smith TG (1980) Polar bear predation of ringed and bearded seals in the land-fast sea ice habitat. Can. J. Zool. 58: 2201-2209
Stephenson SA (2004) Harvest studies in the Inuvialuit Settlement Region, Northwest Territories, Canada: 1999 and 2001-2003. Canadian Manuscript Report of Fisheries and Aquatic Sciences 2700: 41
Stirling I (1997) The importance of polynyas, ice edges, and leads to marine mammals and birds. Journal of Marine Systems 10: 9-21
Stirling I (2002) Polar bears and seals in the eastern Beaufort Sea and Amundsen Gulf: A synthesis of population trends and ecological relationships over three decades. Arctic 55
Stirling I, Lunn NJ, Iacozza J (1999) Long-term trends in the population ecology of polar bears in western hudson bay in relation to climatic change. Arctic 52
Stirling I, Parkinson CL (2006) Possible effects of climate warming on selected populations of polar bears (Ursus maritimus) in the Canadian Arctic. Arctic 59: 261-275
Stirling I, Richardson E, Thiemann GW, Derocher AE (2008) Unusual predation attempts of polar bears on ringed seals in the southern Beaufort Sea : Possible significance of changing spring ice conditions. Arctic 61: 14-22
Stirling I, Smith TG (2004) Implications of warm temperatures and an unusual rain event for the survival of ringed seals on the coast of southeastern Baffin Island. Arctic 57
Stroeve J, Holland MM, Meier W, Scambos T, Serreze M (2007) Arctic sea ice decline: Faster than forecast. Geophys. Res. Lett. 34
Stroeve JC, Markus T, Boisvert L, Miller J, Barrett A (2014) Changes in Arctic melt season and implications for sea ice loss. Geophys. Res. Lett. 41: 1216-1225
Stroeve JC, Serreze MC, Holland MM, Kay JE, Malanik J, Barrett AP (2011) The Arctic’s rapidly shrinking sea ice cover: a research synthesis. Climatic Change 110: 1005-1027
Tuktoyaktuk CO (2008) Tuktoyaktuk Inuvialuit community conservation plan. The Community of Tuktoyaktuk, the Wildlife Management Advisory Council (NWT) and the Joint Secretariat
Ulanowicz RE, Puccia CJ (1990) Mixed trophic impacts in ecosystems. Coenoses 5: 7-16 Ulukhaktok CO (2008) Olokhaktomiut Inuvialuit community conservation plan. The Community of
Ulukhaktok, the Wildlife Management Advisory Council (NWT) and the Joint Secretariat Usher PJ (2002) Inuvialuit use of the Beaufort Sea and its resources, 1960-2000. Arctic 55 Uye S-I (1994) Replacement of large copepods by small ones with eutrophication of embayments: cause
and consequence. Hydrobiologia 292-293: 513-519 Walkusz W, Majewski AR, Reist JD (2013) Distribution and diet of the bottom dwelling Arctic cod in the
Canadian Beaufort Sea. Journal of Marine Systems 127: 65-75 Walters C, Pauly D, Christensen V (1997) Structuring dynamic models of exploited ecosystems from
trophic mass-balance assessments. Reviews in Fish Biology and Fisheries 7: 139-172 Walther G-R, Post E, Convey P, Menzel A, Parmesan C, Beebee TJC, Fromentin J-M, Hoegh-Guldberg O,
Bairlein F (2002) Ecological responses to recent climate change. Nature 416: 389-395 Wassmann P, Slagstad D (1993) Seasonal and annual dynamics of particulate carbon flux in the Barents
Sea. Polar Biol 13: 363-372 Welch HE, Crawford RE, Hop H (1993) Occurrence of Arctic cod (Boreogadus saida) schools and their
vulnerability to predation in the Canadian high arctic. Arctic 46 Whitehouse GA (2013) Preliminary mass-balance food web model of the Eastern Chukchi Sea. NOAA
Technical Memorandum Whitehouse GA, Aydin KY (2016) Trophic structure of the Eastern Chukchi Sea: An updated mass balance
food web model. NOAA Technical Memorandum
43
Supplemental Materials
Biomass, Diets, and Harvesting Rates
Polar Bears
Based on ecological and genetic research the International Union for the Conservation of Nature
and Natural Resources (IUCN) Polar Bear Specialist Group recognizes that there are 19 different
populations of polar bears (Ursus maritimus) in the Arctic Ocean region (Aars et al. 2006, Elvin 2014). Of
the 19 populations, two polar bear populations with disparate distributional ranges continuously reside
in Alaska (Amstrup et al. 2007); one in the Chukchi Sea and the other in the Beaufort Sea (Aars et al.
2006). According to Amstrup et al. (2007) the Beaufort Sea polar bear population inhabits the pelagic
region of the polar basin, which is comprised of semi-permanent, open ocean sea-ice throughout much
of the year. Beaufort Sea polar bears can be found from Barrow, Alaska (U.S.) to just south of Banks
Island and east of the Baillie Islands in Canada (Paetkau et al. 1999, Regehr et al. 2006, Allen & Angliss
2010a). In the United States the Beaufort Sea polar bear stock is currently classified as depleted under
the Marine Mammal Protection Act and considered threatened under the United States‘ Endangered
Species Act (Allen & Angliss 2010a). Population estimates of the Beaufort Sea polar bears were 1778
from 1972-1983, 1800-3000 in 1986 , 3000 in 1993-2000, 2272 in 2001, and 2185 in 2006 (Amstrup et al.
1986, Wiig et al. 1995, Derocher et al. 1998, COSEWIC 2002, Lunn et al. 2002, Gleason & Rode 2009,
Allen & Angliss 2010a). As a whole, the Beaufort Sea population has had little or no growth during the
1990s (Amstrup et al. 2001a, Amstrup et al. 2001b), followed a decline of 3% a year in 2001-2005
(Hunter et al. 2007). In our current EwE model the 1970 biomass is calculated to be 0.0015 t km-2 based
on a population size of 1778 polar bears (Amstrup et al. 1986), and a mean weight of 300 kg (Stirling &
Parkinson 2006).
Polar bears diets consist of Polar Bears (0.5%), Beluga Whales (2.0%), Gray Whales (1.0%), Bowhead
Whales (2.0%), Walrus (2.0%), Ringed Seals (83.5%), Bearded Seals (6.5%), Spotted Seals (0.5%), Birds
44
(1.0%), and an energy import (assumed to be land-based) of 1.0% (Stirling et al. 1977, Forsyth 1985,
COSEWIC 2002, Stirling 2002, Amstrup 2003, LOMA 2005, Bentzen et al. 2007, COSEWIC 2008, Stirling et
al. 2008, Allen & Angliss 2010a, Peacock et al. 2010, Fissel et al. 2013, Gormezano & Rockwell 2013a, b,
Iles et al. 2013, Secretariat 2015). To capture their prey polar bears hunt from coastal areas and, as
seasonal ice dictates, oceanic areas. Using satellite tracking studies, denning site data, and harvest
reports the preferred habitats for polar bears are between 0 and 300 m, and up to 3000 m when sea-ice
is present (Forsyth 1985, Amstrup et al. 2000, Amstrup et al. 2001a, Amstrup et al. 2001b, Ashjian et al.
2010, Stirling et al. 2011, Clarke et al. 2013, Fissel et al. 2013, Bromaghin et al. 2015, NAEC 2015,
Secretariat 2015).
Within these habitat ranges the mean annual harvest rate has been approximately 65 polar bears
per year, when considering all subsistence community harvests, and the years from 1970 to 2014 (Smith
and Taylor 1977, IUCN 1981, Braund 1993, Wiig et al. 1995, Derocher et al. 1998, Lunn et al. 2002,
Stirling 2002, Joint Secretariat 2003, Amstrup et al. 2005, COSEWIC 2008, Bacon et al. 2009, Evans et al.
2009, FWS 2009, Allen and Angliss 2010a, FWS 2010, Obbard et al. 2010, ADNR 2011, DeBruyn 2011,
Fissel et al. 2013, FWS 2011, FWS 2013, Joint Secretariat 2015). Our calculated polar bear harvesting
rate did not include recreational hunting. We calculated Individual polar bear subsistence community
harvesting rates for Barrow, Nuiqsut, Kaktovik, Alavik, Inuvik, Tuktoyaktuk, Paulatuk, Sachs Harbour, and
Ulukhaktok, as well as several other Ecopath fisheries, in order to describe harvesting rates per
community and functional group(s) (including five commercial fisheries; Table S2).
Beluga Whales
Beluga whales (Delphinapterus leucas) are seasonal migrants to the Beaufort Sea, and can be found
in waters extending from Alaska to the ISR in Canada’s Western Arctic (Canada 1984, DFO 2002). Beluga
whales arrive though flaw leads and polynyas along the coast of Alaska during the spring, and spend the
summer in coastal and oceanic waters between the Mackenzie Delta and Banks Island (Gurevich 1980,
45
Lowry 1985, Hazard 1988, Richard et al. 2001, Hornby et al. 2016). In the fall beluga whales return to
the Bering Sea for overwintering and migrate through the Chukchi Sea (Shelden 1994). Although the
current Beaufort Sea population of beluga whales may be stable, the rate of the population increase is
estimated at 4.0% per year (Duval 1993, Wade & Angliss 1997, Angliss & Outlaw 2008, Allen & Angliss
2013). In our Ecopath model the 1970 biomass is calculated to be 0.0305 tonnes km-2 based on a
Bering-Chukchi-Beaufort Sea population estimate of 20,000 beluga whales, which is a 50% reduction of
their total population estimate (40,000) in order to reflect their seasonal duration in the model area
(Duval 1993, Harwood et al. 1996, DFO 2000), and a mean weight of 725 kg (DFO 2002, NAMMCO 2005).
During their spring-summer-fall migrations within the Beaufort Sea beluga whales primarily inhabit
coastlines and water depths up to 300 m (Vladykov 1946, Kleinenberg et al. 1964, Brodie 1971, Sergeant
1973, Fraker et al. 1979, Fraker 1980, Ognetov 1981, Smith & Martin 1994, DFO 2000, 2002, Harwood &
Smith 2002, LOMA 2005, BOWFEST 2009, Allen & Angliss 2010a, Braund 2010, BOWFEST 2011, Clarke et
al. 2013, Harwood et al. 2014). Occasionally beluga whales travel to deeper waters (up to 3000 m)
where they may spend weeks diving for food (Smith & Martin 1994, Richard et al. 2001, Richard 2002).
In the Beaufort Sea habitat Beluga whales eat Char & Dolly Varden (1.0%), Ciscoes & Whitefish (16.0%),
Herring & Smelt (7.0%), Arctic & Polar Cods (42.0%), Capelin (5.0%), Flounder & Benthic Cods (2.0%),
Small Benthic Marine Fish (10.0%), Other Fish (2.0%), Bivalves (1.0%), Molluscs (1.0%), Worms (1.0%),
Macro-Zooplankton (5.0%), Medium Copepods (2.0%), Large Copepods (3.0%), and Other Meso-
Zooplankton (2.0%) (Vladykov 1946, Forsyth 1985, Lowry et al. 1985, Watts & Draper 1986, Finley et al.
1990, Welch et al. 1993, Byers & Roberts 1995, LOMA 2005, Loseto et al. 2009, Allen & Angliss 2010a).
Beluga whales are harvested by U.S. indigenous communities in near Barrow, Alaska (Lowry et al.
1989, Adams et al. 1993, Frost 1999, 2003, Frost & Suydam 2010), and Canadian indigenous
communities near around the Mackenzie Delta and throughout the Inuvialuit Settlement Region (ISR)
(Fraker et al. 1979, DFO 2000, Harwood et al. 2002, Joint-Secretariat 2003). The Beaufort Sea
46
indigenous communities who have reported beluga whale strikes/landings between 1970 and 2014 are:
Barrow, Nuiqsut, Kaktovik, Alavik, Inuvik, Tuktoyaktuk, Paulatuk, and Ulukhaktok (Fig. 1) (Fraker 1980,
Strong 1989, DFO 1991, Weaver 1991, DFO 1992a, b, 1993, 1994, 1995, 1996, 1997, 1999a, Frost 1999,
DFO 2000, Harwood et al. 2002, Harwood & Smith 2002, Joint-Secretariat 2003, Frost & Suydam 2010).
In the United States indigenous communities have harvested an estimated 41 beluga whales per year
from 1987 to 2006 (Frost 1999, 2003, Frost & Suydam 2010), whereas Canadian indigenous communities
have harvested an estimated 111 per year from 1990 to 1999 (Harwood et al. 2002). However, the
mean annual removal by both the United States and Canada is estimated at 189 (Harwood & Smith
2002). Based on harvest reports from individual indigenous community harvests from 1970 to 2014 we
set our harvesting rate at 142 beluga whales per year, which did not include accounts of when a whale
was struck and lost, therefore this harvesting rate is considered conservative (references above, as well
as (Byers & Roberts 1995, ADNR 2011, Fissel et al. 2013)).
Gray Whales
The Eastern North Pacific stock of gray whales feed in the Chukchi and Bering Seas, and less
frequently in the Beaufort Sea (Rugh & Fraker 1981, Bickham et al. 2013, NOAA 2013). The populations
of gray whales in the Atlantic Ocean were hunted to extinction in the 1800s, and a similar fate was
almost met for the Pacific Ocean stock of gray whales in the 1800 and 1900s; however, protective
legislation was enacted in 1937 and 1947 (Frost & Karpovich 2008). Today the Eastern North Pacific
stock of gray whales contains approximately 26,000 whales, which is listed as depleted under the
Marine Mammal Protection Act of 1972 (Frost & Karpovich 2008, NOAA 2013). Given the limited use of
the Beaufort Sea habitats the 1970 Ecopath estimate of biomass for Gray Whales was calculated to be
90% of the biomass estimated in Whitehouse (2013), or 0.0265 t km-2, and a mean weight of 35,000 kg
(http://www.nmfs.noaa.gov/pr/species/mammals/cetaceans/graywhale.htm).
47
Gray whales typically occupy depths ranging from 20 to 100 m (Nelson et al. 1994, Frost & Karpovich
2008, Clarke et al. 2013), and their diet consists of Small Benthic Marine Fish (1.0%), Arthropods (86%),
Bivalves (2.0%), Echinoderms (1.0%), Molluscs (2.0%), Worms (2.0%), Other Benthos (2.0%), Medium
Copepods (2.0%), and Large Copepods (2.0%) according to literature (Nelson et al. 1994, Frost and
Karpovich 2008). Subsistence harvesting of gray whales primarily occurs in Russia (Huelsbeck 1988,
Reeves 2002), although two whales were harvested by the Makah Tribe in 1995 (Angliss & Outlaw
2008). Therefore, no subsistence harvesting is included in the current Ecopath model.
Bowhead Whales
The western Arctic stock of bowhead whales spend the summer in the Beaufort Sea, arriving
through flaw leads in the spring, and remain in the model area until the fall (Braham et al. 1980, Fraker
& Bockstoce 1980, Braham 1984, Braham et al. 1984b, Moore & Reeves 1993, Quakenbush et al. 2010).
During the spring migration bowhead whales enter the Beaufort Sea near Barrow, Alaska, then travel
eastward towards the Sachs Harbour area, and in the fall they migrate towards the Barrow, Alaska
traveling along the coasts until they reach the Chukchi Sea (Fig. 1). The population of the western Arctic
stock of bowhead whales from 1978 to 2001 has increased by approximately 3.4%, from 5000 to 8000
whales, and in 2011 the population had almost 17,000 whales (Moore & Reeves 1993, Zeh & Raftery
1996, Clark & Ellison 1998, George et al. 2002, George et al. 2004, Koski et al. 2005, Zeh & Punt 2005,
Allen & Angliss 2010a, Schweder et al. 2010, Allen & Angliss 2013, Givens et al. 2013). The biomass for
bowhead whales in 1970 is calculated to be 0.1219 t km-2, approximately 50% of the population
estimate of 1867 whales (Zeh & Punt 2005) to reflect their seasonal duration in the model area, and
using a mean weight of 31,076 kg (Trites & Pauly 1998).
Along their migration routes within the Beaufort Sea bowhead whales travel in water depths ranging
from 20 to 3000 meters (Bodish 1936, Braham et al. 1984b, George et al. 2004, COSEWIC 2005,
BOWFEST 2009, COSEWIC 2009, Koski & Miller 2009, Ashjian et al. 2010, Braund 2010, Moore et al.
48
2010, Quakenbush et al. 2010, BOWFEST 2011, Quakenbush et al. 2012, Christman et al. 2013, Clarke et
al. 2013), and eat Arctic & Polar Cods (0.5%), Small Benthic Marine Fish (1.0%), Other Fish (1.0%),
Arthropods (1%), Bivalves (0.5%), Molluscs (1.0%), Jellies (1.0%), Macro-Zooplankton (30.0%), Medium
Copepods (20.0%), Large Copepods (29.0%), Other Meso-Zooplankton (10%), and Micro-Zooplankton
(0.5%) according to literature and direct observations (Braham 1984, Forsyth 1985, Lowry et al. 1987,
Schell et al. 1989, Lischka et al. 2001, Harwood & Smith 2002, Lowry et al. 2004, Lee et al. 2005, LOMA
2005, BOWFEST 2009, COSEWIC 2009, Moore et al. 2010, Pomerleau et al. 2010, Walkusz et al. 2010,
BOWFEST 2011).
While commercial whaling dramatically reduced the bowhead whale population in the late 1800s
and early 1900s, their population has continually increased with legislative protections and stock
management (see the Aboriginal subsistence whaling section of the International Whaling Commission;
iwc.int/aboriginal), which entails a moratorium of commercial whaling and managed subsistence
harvesting. Beaufort Sea indigenous communities harvest bowhead whales as they migrate along the
coasts of the United States and Canada (Braham et al. 1980), and communities that reported bowhead
whale strikes/landings between 1970 and 2012 were Barrow, Nuiqsut, Kaktovik, and Aklavik. Alaskan
indigenous communities have averaged a harvest of 41 whales per year between 1997 and 2006, and a
total of 1,149 whales harvested between 1974-2011 (Koski et al. 2005, Suydam et al. 2007, Suydam &
George 2012). In the Northwest Territories only 2 bowheads have been landed over the last few
decades; one in 1991 and another in 1996 (Harwood & Smith 2002). The EwE models’ mean annual
harvest rate for bowhead whales is calculated to be 43 whales per year between 1970 and 2014
(Braham et al. 1984b, Braund 1993, Joint-Secretariat 2003, Suydam & George 2004, Koski et al. 2005,
Suydam et al. 2005, 2006, Suydam et al. 2007, 2008, ADNR 2009, Bacon et al. 2009, Suydam et al. 2009,
Ashjian et al. 2010, Braund 2010, Suydam et al. 2010, ADNR 2011, Suydam et al. 2011, Fissel et al. 2013,
Kishigami 2013), and the mean annual harvest rates for the communities of Barrow, Nuiqsut, Kaktovik,
49
and Aklavik are detailed in Table S2. Mean harvest rates did not include accounts of when a whale was
struck and lost.
Walrus
Of the two walrus populations in the Pacific Ocean, the sub-species of Odobenus rosmarus divergens
primarily occupies the Bering and Chukchi Seas, and occasionally travels to the Beaufort Sea near
Barrow, Alaska (Allen & Angliss 2010b). As this is a subset of the larger home range, a reliable
population estimate for this Beaufort Sea sub-species of walrus, covering just the model area, is
unavailable. Estimates of the total population from 1970 to 2014 were reconstructed from literature,
which includes a starting population of approximately 221,000 walrus in the 1970s, 246,000 in the
1980s, 201,000 in the 1990s, and 129,000 in the 2000s and 2010s (Johnson et al. 1982, Estes & Gol'tsev
1984, Fedoseev 1984, Gilbert et al. 1992, Hills & Gilbert 1994, Udevitz et al. 2001, Speckman et al. 2010,
MacCracken 2012, Allen & Angliss 2013). For our EwE model biomass in 1970 is set to 0.0092 t km-2
using a mean weight of 375 kg (Trites & Pauly 1998), which is 10% of the biomass estimated in the
Chukchi Sea model by Whitehouse (2013), and calculated to reflect the small number of O. r. divergens
that travel into the Beaufort Sea.
The subspecies O. r. divergens can be found along the Alaskan coasts and up to approximately 200
m in water depth (Stirling 1974, Fay 1982, Estes & Gol'tsev 1984, BOWFEST 2009, Braund 2010, Clarke et
al. 2013). In this depth range walrus eat Ringed Seals (3.0%), Bearded Seals (0.5%), Spotted Seals
(0.05%), Arctic & Polar Cods (2.0%), Small Benthic Marine Fish (1.0%), Arthropods (4.0%), Bivalves
(74.5%), Echinoderms (2.0%), Molluscs (10.0%), Worms (1.95%), and Macro-Zooplankton (1.0%)
according to literature (Frost & Lowry 1981, Nelson et al. 1994, Sheffield et al. 2001, Sheffield &
Grebmeier 2009, Seymour et al. 2014, ADFG 2015). Within the Beaufort Sea the total mean subsistence
harvest of walrus is 70 walrus per year according to harvest reports for the communities of Barrow,
Nuiqsut, Kaktovik, Tuktoyaktuk, Paulatuk, and Sachs Harbour (DFO 1991, 1992a, b, Braund 1993, DFO
50
1993, 1994, 1995, 1996, 1997, Fuller & George 1997, DFO 1999a, Joint-Secretariat 2003, ADNR 2009,
Bacon et al. 2009, Braund 2010, Fissel et al. 2013). Harvest rates do not include accounts of when a
walruses were struck and lost.
Ringed Seals
Ringed seals (Phoca hispida hispida) can be found circumpolarly in the Arctic Ocean, including in ice
covered areas, on pack ice, and within coastal waters throughout most of the year (Stirling et al. 1975,
King 1983, Kelly 1988, Frost et al. 2002, Harwood et al. 2012, Allen & Angliss 2014). Ice provides ringed
seals with habitat for reproduction, whelping (giving birth), nursing pups, molting, resting, foraging, and
minimizing vulnerability to predators (McLaren 1958, Burns 1970, Hammill & Smith 1989, Ferguson et al.
2005, Stirling et al. 2008, Kelly et al. 2010). A reliable population estimate for Beaufort Sea ringed seals
is considered unavailable; however, estimates in the 1970s range from 11,612 seals along the shores of
Alaska’s North Slope (Burns & Harbo 1972), to 26,660 and 7,657 in 1974 and 1975, respectively, near the
MacKenzie Delta (Stirling et al. 1977), to 41,983 in the Beaufort and Amundsen Gulf areas (Stirling et al.
1977). There are also estimates that the population has over a million seals in Alaskan waters (Frost
1985). Although some migration may occur among the ringed seal population, in our EwE models they
are assumed to remain in the Beaufort Sea area throughout the year (Frost & Lowry 1984, Frost 1985,
Crawford et al. 2011). The biomass of ringed seals is estimated to be 0.0217 t km-2 based on a mean
density estimate of 0.51 ringed seals km-2, which is calculated from the Kingsley (1984) estimate of 0.21
ringed seals km-2 in the Beaufort Sea and Amundsen Gulf, the Frost et al. (2004) estimate of 0.81 ringed
seals km-2 in the Alaskan Beaufort Sea, and a mean weight of 42.5 kg (Trites & Pauly 1998).
In the Beaufort Sea ringed seals typically occupy water depths ranging from 0 to 300 m, and
sometimes in waters more than 1000 m deep (Smith 1987, Schliebe et al. 2008, Braund 2010, Harwood
et al. 2012, Clarke et al. 2013), where they forage for food and are harvested by subsistence
communities. Ringed seals eat Char & Dolly Varden (10.0%), Ciscoes & Whitefish (8.0%), Herring &
51
Smelt (3.0%), Arctic & Polar Cods (12.0%), Capelin (3.0%), Flounder & Benthic Cods (5.0%), Small Benthic
Marine Fish (9.0%), Other Fish (1.0%), Arthropods (9.0%), Echinoderms (5.0%), Molluscs (5.0%), Worms
(5.0%), Other Benthos (5.0%), Macro-Zooplankton (10.0%), Medium Copepods (3.0%), Large Copepods
(5.0%), and Other Meso-Zooplankton (2.0%) (Forsyth 1985, Lowry et al. 1987, Holst et al. 2001, LOMA
2005, Outridge et al. 2009). Subsistence harvesting of ringed seals generally occurs in coastal waters
(Braund 2010), with the total mean annual harvest rate of 1,016 seals, which is calculated from Barrow,
Nuiqsut, Kaktovik, Aklavik, Inuvik, Tuktoyaktuk, Paulatuk, Sachs Harbour, and Ulukhaktok community
harvests reports and detailed in Table S2 (Braund 1993, Brower et al. 2000, Joint-Secretariat 2003,
Stephenson 2004, ADNR 2009, Braund 2010, Harwood et al. 2012, Fissel et al. 2013, Ice-Seal-Committee
2014). Harvesting rates did not include accounts of when ringed seals were struck and lost.
Bearded Seals
The bearded seal (Erignathus barbatus) is considered a boreoarctic species (Allen & Angliss 2014),
mostly found near coastal shelves and on sea-ice and/or ice pack, which they use for whelping, pupping,
and molting (Burns & Frost 1979, Smith 1981, Cleater & Smith 1984). Bearded seals can be found
throughout the Beaufort Sea (Stirling et al. 1975); however, a reliable population estimate is considered
unavailable. Population estimates of bearded seals come from surveys of the southeastern Beaufort,
including the Amundsen Gulf and offshore areas (Stirling et al. 1975, Smith 1981, Stirling et al. 1982),
which yielded a population estimate of 2757 seals in 1974 or approximately 0.019 seals km-2. Beaufort
Sea bearded seal population estimates, such as the study performed by Stirling et al. (1982), are thought
to be: 1) greatly impacted by presence/absence of sea-ice, 2) may have covered too small of survey area
considering the range that the species may occupy, and 3) have no correction factors for submerged
seals that were missed in surveys (Stewart 2006, Cameron et al. 2010). Therefore, the starting biomass
of bearded seals is based on the ratio of the number of ringed seals to bearded seals published by
Stirling et al. (1975), applying the bearded seal weight of 275 kg (Kovacs 2002), and then multiplying the
52
answer by 50% (e.g., method applied for whales when seasonal surveys miss clustering of mammals
(Harwood et al. 2010)). A final biomass of 0.0150 t km-2 is calculated for bearded seals in our EwE
model.
Bearded seals are found waters depths ranging from 0 to over a 1000 m, with a mean population
concentration in waters depths between 25 to 75 m (Stirling et al. 1975, Burns & Frost 1979, Smith
1981, Cleater & Smith 1984, Braund 2010, Clarke et al. 2013) where they forage for food and are
harvested by subsistence communities. Bearded seals eat Char & Dolly Varden (5.0%), Ciscoes &
Whitefish (4.0%), Salmonids (4.0%), Herring & Smelt (1.0%), Arctic & Polar Cods (6.0%), Capelin (2.0%),
Flounder & Benthic Cods (10.0%), Small Benthic Marine Fish (10.0%), Other Fish (3.0%), Arthropods
(25.0%), Echinoderms (9.0%), Molluscs (11.0%), Worms (5.0%), and Other Benthos (5.0%) (Lowry et al.
1980, Smith 1981, Finley & Evans 1983, Cleater & Smith 1984, Forsyth 1985, LOMA 2005, Stewart 2006,
Quakenbush et al. 2011). Approximately 240 bearded seals are harvested each year by the communities
of Barrow, Nuiqsut, Kaktovik, Aklavik, Inuvik, Tuktoyaktuk, Paulatuk, Sachs Harbour, and Ulukhaktok,
and detailed in Table S2 (Smith 1981, Braund 1993, Brower et al. 2000, Joint-Secretariat 2003,
Stephenson 2004, ADNR 2009, Bacon et al. 2009, Braund 2010, Fissel et al. 2013, Ice-Seal-Committee
2014).
Spotted Seals
Spotted seals (Phoca largha) remain along continental shelf waters of the Beaufort Sea, spanning
from Barrow, Alaska to Yukon, Canada, and are considered members of the Bering Distinct Populations
Segments, also called the Alaskan stock (Allen & Angliss 2013). This distinct population of spotted seals
primarily resides in the Bering or Chukchi Seas, but travels to the Beaufort Sea during the summer and
fall (Porsild 1945, Shaughnessy & Fay 1977). Spotted seal migrations are prompted by the changing
southern extent of the oceanic ice edge and ice pack, as spotted seals prefer remaining near ice margins,
and enter more coastal habitats as the sea-ice seasonally retreats (Fay 1974, Shaughnessy & Fay 1977,
53
Lowry et al. 2000, Simpkins et al. 2003). As with other Beaufort Sea pinnipeds, a reliable population
estimate of the Alaskan stock of spotted seals is considered unavailable. In 1976 the Bering Sea’s
population density is estimated to be 1.27 seals km-2 (Braham et al. 1984a), and in 1992 0.96 seals km-2
(Rugh et al. 1995). Unfortunately, since these population estimates were calculated using only seals
observed on ice, made no adjustments for seals in the water, and may have included habitats outside of
the model area (Burkanov et al. 1988), we use the updated estimate of the spotted seal population
density of 0.51 seals km-2, which is based on surveys of known breeding areas and accounted for
uncertainty in the detection rates and availabilities (Conn et al. 2013, Conn et al. 2014). To correct for
the short amount of time each year that a small proportion of the spotted seal population migrates into
a small fraction of the Beaufort Sea, we multiplied the Bering Sea density estimate by a mean weight of
90.7 kg (e.g., http://www.afsc.noaa.gov/nmml/education/pinnipeds/spotted.php), then reduced that
biomass estimate by 90%, to produce the final Beaufort Sea biomass of 0.0046 t km-2.
Spotted seals can be found in water depths ranging from 0 to 400 m, but generally stay in waters
200 m or less (Chugunkov 1970, Gol'tsev 1971, Bukhtiyarov et al. 1984, Braund 2010). Spotted seals eat
Char & Dolly Varden (15.0%), Ciscoes & Whitefish (15.0%), Salmonids (15.0%), Herring & Smelt (12.0%),
Arctic & Polar Cods (30.0%), Capelin (6.0%), Flounder & Benthic Cods (5.0%), Arthropods (1.0%), and
Macro-Zooplankton (1.0%) (Chugunkov 1970, Gol'tsev 1971). Within spotted seal habitats of the
Beaufort Sea approximately 11 seals have been harvested by subsistence communities each year from
1970 to 2014 (Braund 1993, Rugh et al. 1995, ADNR 2009, Bacon et al. 2009, Braund 2010, Ice-Seal-
Committee 2014). Subsistence communities that have reported harvesting of spotted seals are Barrow,
Nuiqsut, and Kaktovik.
Birds
The Birds functional group considered in our EwE model represents several subsistence harvested
species throughout the Beaufort Sea marine ecosystem (Table S1). Bird species vary from more
54
terrestrial (e.g., Sandhill cranes) to more aquatic (e.g., Scaups), and also include migratory (e.g., Eiders)
and non-migratory species (e.g., Snowy Owls). Surveys for many of these bird species have been
completed throughout the Beaufort Sea marine ecosystem, typically when populations are at annual
maximums (June through August), and generally in waters between 0 and 50 m water depth (Barry
1976, Barry et al. 1981, Barry & Barry 1982, Alexander et al. 1988, Fischer & Larned 2004, Dau & Larned
2005, Noel et al. 2005, Powell et al. 2005, Dau & Larned 2008). In these studies is it apparent that bird
densities vary dramatically by the date of survey and survey location (Alexander et al. 1988), but they
generally revealed that the largest bird densities were due to flocking eider species, long-tailed ducks,
and scoter species (Alexander et al. 1988, Fischer & Larned 2004). Using the data from these
aforementioned surveys, and weight estimates for common birds in surveys and harvest reports (Table
S3) (Bromley 1993, Joint-Secretariat 2003, Braund 2010), we calculated the mean biomass of birds in the
Beaufort Sea marine ecosystem, multiplied that number by 10.8% (the area of ocean the Beaufort Sea
ecosystem that has a water depth between zero and 50 m), and then multiplied that number by 50% to
account for season migration. The resulting biomass of the aggregated bird functional group in the
Ecopath model was 0.0026 t km-2.
Birds collectively eat Char & Dolly Varden (5.0%), Ciscoes & Whitefish (6.0%), Salmonids (5.0%),
Herring & Smelt (10.0%), Arctic & Polar Cods (11.0%), Capelin (2.0%), Flounder & Benthic Cods (3.0%),
Small Benthic Marine Fish (9.0%), Other Fish (1.0%), Arthropods (5.0%), Bivalves (2.0%), Echinoderms
(2.0%), Molluscs (2.0%), Worms (3.0%), Other Benthos (2.0%), Jellies (6.0%), Macro-Zooplankton (5.0%),
Medium Copepods (8.0%), Large Copepods (8.0%), and Other Meso-Zooplankton (5.0%) (Divoky et al.
2015, Harwood et al. 2015). Birds are an important dietary component of subsistence communities
(Bromley 1993, Fuller & George 1997, Brower & Hepa 1998, Brower et al. 2000, Wolfe & Utermohle
2000, Joint-Secretariat 2003, Bacon et al. 2009, Braund 2010, ADNR 2011), and calculated rates of
harvest per community between 1985 and 2003 are detailed in Table S2.
55
Fish Functional Groups
Fish present on the Beaufort Sea model include anadromous, semi-anadromous, and marine
species, therefore they can be found throughout the marine ecosystem. Although migratory fish species
do not remain in the Ecospace area year round, it was assumed that they feed within the Ecospace area,
and therefore their biomass is not adjusted to compensate for the time they spent outside of the
Beaufort Sea. Species in our EwE model are based on fish reported to be present and/or have estimates
of catch per unit effort (CPUE; e.g., t km-2) in Beaufort Sea marine ecosystem, and these species can be
found from the northeastern Chukchi Sea (Alaska) to the Amundsen Gulf ecozone (Northwest
Territories) (Frost & Lowry 1983, Schmidt et al. 1983, Chiperzak et al. 1991, Thorsteinson et al. 1991,
Bond & Erickson 1992, Barber et al. 1997, Coad & Reist 2004, ADNR 2009, Logerwell & Rand 2010, ADNR
2011, Johnson et al. 2012, Meuter et al. 2013, Norcross et al. 2013).
Offshore surveys of fish (and invertebrates) in the Beaufort Sea marine ecosystem have only
occurred a few times since the 1970s (Frost & Lowry 1983), with the recent survey (Logerwell & Rand
2010) being considered the first dedicated sampling effort for offshore fish species (e.g., Arctic cod,
eelpouts, sculpin, etc.) since the 1970s. However, surveys of fish have occurred in offshore areas of the
northwestern, Alaska, as well as in nearshore waters during the 1990s (Thorsteinson et al. 1991, Barber
et al. 1997) and 2000s (Norcross et al. 2013). In both offshore and nearshore surveys sample results
have indicated changes in species abundance between sampling years, seasonal periods, latitude, and
gear-types. For instance, Logerwell and Rand (2010) reported some significant changes in abundance
for some fish species when sampling with lined and unlined trawls, and no changes for other fish
species. In the same study notable similarities and differences were noted among species’ biomass,
presence and absence, as well as distribution (depth or proximity to the shoreline) comparing the 1976-
77 survey data by Frost and Lowry (1983) and the 2008 survey data by Logerwell and Rand (2010).
Similarities between these two Beaufort Sea surveys included the abundances of Arctic cod, several
56
species of eelpout (Small Benthic Fish), and sculpin (Other Fish). Differences between the two surveys
indicate the potential increase in the distributions or biomass of opilio crab (Chionoecetes opilio;
Arthropods), and the presence of Bering flounder (Hippoglossoides robustus; Founder & Benthic Cods),
walleye pollock (Theragra chalcogramma; Other Fish), and Pacific cod (Gadus microcephalus; Flounder &
Benthic Cods) in recent surveys, which were absent in earlier surveys. This could indicate an extended
distribution range for some fish species, including the festive snailfish (Liparis marmoratus; Other Fish)
and eyeshade sculpin (Nautichthys pribilovius; Small Benthic Marine Fish).
Additionally, when comparing the Frost and Lowry (1983) and Logerwell and Rand (2010) surveys
there were reported differences in the abundances or presence/absence of fish species when caught in
lined versus unlined nets. For instance, no marbled eelpout were caught in unlined nets, but were
caught in lined nets; some sculpin species were only captured in lined nets while other sculpin species
were only captured in unlined nets; and almost twice as many Arctic cod were captured in lined nets
when compared to unlined nets. Thus, it is evident that many fish species have significantly different
abundances when caught in different months (Norcross et al. 2013), areas (Bond & Erickson 1992), and
gear-types (e.g., lined versus unlined nets); therefore, the Ecopath biomasses for all fish functional
groups are estimated using all nearshore and offshore survey data between 1970 and 2014. This
method is also required because of the lack of fish survey data throughout the Beaufort Sea, almost all
Beaufort Sea fish surveys are conducted in the months of August and September, and population sizes,
habitat preferences, and other ecologically important information is largely unknown for all fish
functional groups. Mean fish functional group weights are detailed in Table S4.
The calculated Ecopath biomass for Char & Dolly Varden is 0.1407 t km-2, and this functional group is
primarily limited to water depths ranging from 0 to 100 m (Schmidt et al. 1983, Karasiuk et al. 1993,
Billard 1997, LOMA 2005, ADNR 2009). In these water depths Char & Dolly Varden eat Ciscoes &
Whitefish (1.0%), Herring & Smelt (20.0%), Arctic & Polar Cods (1.0%), Capelin (1.0%), Flounder &
57
Benthic Cods (9.0%), Small Benthic Marine Fish (5.0%), Other Fish (1.0%), Other Benthos (2.0%), Macro-
Zooplankton (3.0%), Medium Copepods (5.0%), Large Copepods (20.0%), and Other Meso-Zooplankton
(3.0%) (Bendock 1977, Hulley 1990, DFO 1999b, ADNR 2009). Our calculated mean annual subsistence
harvest rate for Char & Dolly Varden is 7.64x10-5 t km-2, and the mean annual commercial harvest rate is
6.29x10-6 t km-2 (Patterson 1974, Walker et al. 1988, Pedersen 1990, DFO 1991, 1992a, b, 1993, 1994,
1995, 1996, 1997, Brower & Hepa 1998, DFO 1999a, Brower et al. 2000, ADNR 2009, Bacon et al. 2009,
Braund 2010).
Biomass for Ciscoes & Whitefish is 0.7057 t km-2, and this functional group is limited to water depths
ranging from 0 to 200 m (Morin et al. 1981, Schmidt et al. 1983, Chiperzak et al. 1991, Karasiuk et al.
1993, Coad & Reist 2004, LOMA 2005, Harwood et al. 2008, ADNR 2009, Johnson et al. 2010, Johnson et
al. 2012). In these water depths Ciscoes & Whitefish eat Herring & Smelt (6.0%), Small Benthic Marine
Fish (2.0%), Other Fish (2.0%), Arthropods (10.0%), Echinoderms (3.0%), Molluscs (2.0%), Worms (5.0%),
Macro-Zooplankton (5.0%), Medium Copepods (10.0%), Large Copepods (30.0%), Other Meso-
Zooplankton (10.0%), Micro-Zooplankton (5.0%), Producers > 5 μm (7.0%), and Ice Algae (3.0%)
(Nikol'skii 1961, Kogl 1971, Bendock 1977, Morrow 1980, Lacho 1991, Coad & Reist 2004, Kottelat &
Freyhof 2007). The calculated mean annual subsistence harvest rate for Char & Dolly Varden is 2.87x10-
4 t km-2, and the mean annual commercial harvest rate is 1.02x10-4 t km-2 (DFO 1991, 1992a, b, 1993,
1994, 1995, 1996, 1997, Brower & Hepa 1998, DFO 1999a, Harwood et al. 2008, ADNR 2009, Bacon et al.
2009, Braund 2010).
Biomass for Salmonids is calculated to be 0.0977 t km-2, and this functional group is limited to water
depths ranging from 0 to 250 m (Schmidt et al. 1983, Chiperzak et al. 1991, Page & Burr 1991, Fedorov
et al. 2003, LOMA 2005, Kottelat & Freyhof 2007, Harwood et al. 2008, ADNR 2009, Irvine et al. 2009,
Johnson et al. 2012). From these depths Salmonids eat Ciscoes & Whitefish (10.0%), Arctic & Polar Cods
(12.0%), Capelin (3.0%), Small Benthic Marine Fish (5.0%), Other Fish (5.0%), Arthropods (31.0%), Worms
58
(5.0%), Other Benthos (2.0%), Macro-Zooplankton (3.0%), Medium Copepods (2.0%), Large Copepods
(15.0%), Other Meso-Zooplankton (2.0%), and Producers > 5 μm (5.0%) (Fuller 1955, Morrow 1980,
Haldorson & Craig 1984, Hoekstra et al. 2003, Stewart et al. 2007). The calculated mean annual
subsistence harvest rate for Char & Dolly Varden is 1.76x10-4 t km-2, and the mean annual commercial
harvest rate is 1.37x10-4 t km-2 (DFO 1991, 1992a, b, Braund 1993, DFO 1993, 1994, 1995, 1996, 1997,
Fuller & George 1997, Brower & Hepa 1998, Brewster et al. 2008, ADNR 2009, Bacon et al. 2009, Cotton
2012, Carothers et al. 2013).
Biomass for Herring & Smelt is calculated to be 0.6640 t km-2, and this functional group is limited to
water depths ranging from 0 to 50 m in (Schmidt et al. 1983, Chiperzak et al. 1991, Karasiuk et al. 1993,
Barber et al. 1997, LOMA 2005, Johnson et al. 2012). From these depths Herring & Smelt eat Ciscoes &
Whitefish (3.0%), Flounders & Benthic Cods (2.0%), Small Benthic Marine Fish (2.0%), Arthropods (5.0%),
Echinoderms (2.0%), Molluscs (2.0%), Worms (5.0%), Other Benthos (1.0%), Macro-Zooplankton (20.0%),
Medium Copepods (5.0%), Large Copepods (20.0%), Other Meso-Zooplankton (5.0%), Micro-
Zooplankton (5.0%), Producers > 5 μm (10.0%), Producers < 5 μm (10.0%), and Ice Algae (3.0%) (Wailes
1936, Haldorson & Craig 1984, Evans & Loftus 1987, Lacho 1991, Hrabik et al. 1998, Hipfner & Galbraith
2013). The calculated mean annual subsistence harvest rate for Char & Dolly Varden is 3.94x10-6 (ADNR
2009, 2011).
Biomass for Arctic & Polar Cods is calculated to be 0.6511 t km-2, and this functional group is limited
to water depths ranging from 0 to 400 m (Frost & Lowry 1983, Cohen et al. 1990, Karasiuk et al. 1993,
Barber et al. 1997, LOMA 2005, Johnson et al. 2010, Norcross et al. 2013). From these depths Arctic &
Polar Cods eat Salmonids (2.0%), Herring & Smelt (20.0%), Arthropods (5.0%), Echinoderms (2.0%),
Molluscs (2.0%), Worms (4.0%), Other Benthos (1.0%), Macro-Zooplankton (7.0%), Medium Copepods
(10.0%), Large Copepods (40.0%), Other Meso-Zooplankton (5.0%), and Producers > 5 μm (2.0%)
(Bendock 1977, Craig et al. 1982, Frost & Lowry 1983, Lacho 1986, Hoekstra et al. 2003, Darnis et al.
59
2008, Walkusz et al. 2011). The calculated mean annual subsistence harvest rate for Arctic & Polar Cods
is 2.84x10-7 (ADNR 2009, 2011).
Biomass for Capelin is calculated to be 0.1050 t km-2, and this functional group is limited to water
depths ranging from 0 to 200 m (Schmidt et al. 1983, Karasiuk et al. 1993, Barber et al. 1997,
Mecklenburg et al. 2002, LOMA 2005, Johnson et al. 2010, Logerwell & Rand 2010, Rand & Logerwell
2010, Johnson et al. 2012). From these depths Capelin eat Salmonids (2.0%), Herring & Smelt (20.0%),
Arthropods (5.0%), Echinoderms (2.0%), Molluscs (2.0%), Worms (4.0%), Other Benthos (1.0%), Macro-
Zooplankton (7.0%), Medium Copepods (10.0%), Large Copepods (40.0%), Other Meso-Zooplankton
(5.0%), and Producers > 5 μm (2.0%) (Lacho 1991, Gjøsæter 1998, Vilhjálmsson 2002, Orlova et al. 2010,
Hedeholm et al. 2012). The calculated mean annual subsistence harvest rate for Arctic & Polar Cods is
2.88x10-7 (ADNR 2009, 2011).
Biomass for Flounder & Benthic Cods is calculated to be 0.2965 t km-2, and this functional group is
limited to water depths ranging from 0 to 50 m (Schmidt et al. 1983, Chiperzak et al. 1991, Barber et al.
1997, Fedorov et al. 2003, LOMA 2005, ADNR 2009, Johnson et al. 2009, Johnson et al. 2010, Logerwell
& Rand 2010, Rand & Logerwell 2010, Johnson et al. 2012, Norcross et al. 2013). From these depths
Flounder & Benthic Cods eat Herring & Smelt (2.0%), Arctic & Polar Cods (2.0%), Capelin (1.0%),
Flounder & Benthic Cod (1.0%), Small Benthic Marine Fish (9.0%), Other Fish (2.0%), Arthropods (20.0%),
Bivalves (15.0%), Echinoderms (5.0%), Molluscs (10.0%), Worms (17.0%), Other Benthos (5.0%), Macro-
Zooplankton (2.0%), Medium Copepods (2.0%), Large Copepods (5.0%), and Other Meso-Zooplankton
(2.0%) (Bendock 1977, Mikhail & Welch 1989, Lacho 1991, Atkinson & Percy 1992, Ghan & Sprules 1993,
Coyle et al. 1994, Johnson et al. 2009). The calculated mean annual subsistence harvest rate for Arctic &
Polar Cods is 3.79x10-5, and the mean annual commercial harvest rate is 1.36x10-4 (DFO 1991, 1992a, b,
1993, 1994, 1995, 1996, 1997, Brower & Hepa 1998, DFO 1999a, ADNR 2009, Bacon et al. 2009).
60
The biomass of Small Benthic Marine Fish is calculated to be 0.7243 t km-2, and this functional group
is limited to water depths ranging from 0 to 1000 m (Frost & Lowry 1983, Schmidt et al. 1983, Chiperzak
et al. 1991, Karasiuk et al. 1993, Barber et al. 1997, LOMA 2005, Johnson et al. 2010, Logerwell & Rand
2010, Rand & Logerwell 2010, Johnson et al. 2012, Norcross et al. 2013). From these depths Small
Benthic Marine Fish eat Flounder & Benthic Cods (1.0%), Small Benthic Marine Fish (3.0%), Other Fish
(3.0%), Arthropods (21.0%), Bivalves (10.0%), Echinoderms (10.0%), Molluscs (10.0%), Worms (15.0%),
Other Benthos (8.0%), Jellies (0.5%), Macro-Zooplankton (3.0%), Medium Copepods (2.0%), Large
Copepods (3.0%), Other Meso-Zooplankton (5.0%), Micro-Zooplankton (3.0%), Producers > 5 μm (2.5%)
(Ennis 1969, Bendock 1977, Leonardsson et al. 1988, Lacho 1991, Atkinson & Percy 1992, Coyle et al.
1994, Hoekstra et al. 2003). The calculated mean annual subsistence harvest rate for Arctic & Polar
Cods is 4.29x10-8 (ADNR 2009, Bacon et al. 2009).
Biomass of Other Fish is calculated to be 0.4733 t km-2, and this functional group is limited to water
depths ranging from 0 to 200 m (Frost & Lowry 1983, Muus et al. 1990, Karasiuk et al. 1993, Barber et al.
1997, LOMA 2005, Johnson et al. 2010, Logerwell & Rand 2010, Rand & Logerwell 2010, Johnson et al.
2012, Norcross et al. 2013). From these depths Other Fish eat Arthropods (13.0%), Bivalves (7.0%),
Echinoderms (4.0%), Molluscs (4.0%), Worms (5.0%), Other Benthos (4.0%), Jellies (1.0%), Macro-
Zooplankton (5.0%), Medium Copepods (4.0%), Large Copepods (30.0%), Other Meso-Zooplankton
(5.0%), Micro-Zooplankton (5.0%), Producers > 5 μm (10.0%), Producers< 5 μm (1.0%), Ice Algae (2.0%)
(Scott & Scott 1988, Lacho 1991, Atkinson & Percy 1992). We calculated subsistence harvest rates of
fish functional groups for each individual indigenous community in Table S2.
Benthic Invertebrates: Arthropods, Bivalves, Echinoderms, Molluscs, Worms, and Other Benthos
The biomass mass of benthic organisms (functional groups of Arthropods, Echinoderms, Molluscs,
Worms, and Other Benthos) generally increases with increasing depth between 0 and 100 m, with a
peak of biomass between 70 and 100 m; however, bivalves are an exception to this observation as their
61
biomass peaks between 40 and 70 m (Wacasey 1975, Carey 1976, Carey & Ruff 1977, Wacasey et al.
1977, Carey 1978, Bernard 1979, Frost & Lowry 1983, Carey et al. 1984, Heath & Thomas 1984, Braun
1985, Carey 1991, Hopky et al. 1994b, c, a, Hopky et al. 1994d, Dunton et al. 2006, Bessière et al. 2007,
Cobb et al. 2008, Logerwell & Rand 2010). We noted that many Beaufort Sea invertebrate sampling
studies lack information regarding the meiofauna in sediments, as this is where worms are often found
in high abundances, and this lack of information would likely impact estimates of the Worms functional
group’s biomass (Braun 1985, Bessière et al. 2007).
Biomass ranges from Wacasey et al. (1977), Carey Jr. (1976, 1978), and Logerwell and Rand (2010)
are detailed in Table S5, and these publications are used to calculate benthic (invertebrate) functional
groups biomass values for the current Ecopath model because of their sampling years and/or sampling
insights into population size. All functional group biomass values used in the current model fell within
reported high and low biomass values from benthic surveys (Table S5). The Logerwell and Rand (2010)
study is included in our calculations of invertebrate functional groups biomass values because it
demonstrates a large discrepancy in invertebrate biomass values when captured in lined versus unlined
net tows. In general, lined nets captured far more of the benthic organisms, with a couple of
exceptions, indicating that the biomass may be higher depending on the gear-type used for surveying
the benthos, and therefore earlier studies might underestimate invertebrate biomass. These four
studies were also used in our invertebrate biomass calculations because of the comprehensive sampling
area covered throughout the Beaufort Sea marine ecosystem.
The Ecopath model functional group Arthropods includes the classes/subclasses of: Acari,
Amphipoda, Cladocera, Cumacea (hooded shrimp), Decapoda, Insecta, Isopoda, Maxillopoda, Mysida
(opossum shrimp), Pycnogonida (sea spiders), Ostracoda, and Tanaidacea (Wacasey 1975, Wacasey et
al. 1977, Carey 1978, Atkinson & Wacasey 1989, Hopky et al. 1994b, c, a, Hopky et al. 1994d, Logerwell
& Rand 2010, Piepenburg et al. 2010). Although only a few studies have documented the distribution
62
and abundance of this functional group in the Beaufort Sea, biomass estimates indicate a moderate to
high biomass compared to other benthic functional groups (Table S5). Arthropods can be herbivores,
carnivores, and detritivores (Carey & Ruff 1977, Scott et al. 2001, Arndt & Swadling 2006); therefore
their diet includes Bivalves (2.0%), Echinoderms (5.0%), Molluscs (6.0%), Worms (4.0%), Other Benthos
(3.0%), Jellies (10.0%), Benthic Plants (3.0%), Pelagic Detritus (10.0%), and Benthic Detritus (57.0%).
The Bivalves functional group includes the class Pelecypoda separate from the Mollusc functional
group, because it is one of the most prevalent molluscs throughout the Arctic (Logerwell & Rand 2010,
Piepenburg et al. 2010), and it contributes significantly to benthic biomass (Carey 1976, Wacasey et al.
1977, Carey 1978). In general, the biomass of Bivalves is considered low to moderate when compared
to other benthic functional groups (Table S5). Bivalves are suspension feeders and also consume kelp
detritus (Dunton & Schell 1987, Loo & Rosenberg 1989, Hawkins et al. 1996, Sauriau & Kang 2000);
therefore, the diet of this functional group includes Producers > 5 μm (2.0%), Producers < 5 μm (3.0%),
Ice Algae (10.0%), Benthic Plants (5.0%), Pelagic Detritus (10.0%), and Benthic Detritus (70.0%).
The Echinoderm functional group includes the classes of: Asteroidea (sea stars), Crinoidea (sea lilies
and feather stars), Echinoidea (urchins), Holothuroidea (sea cucumbers), Ophiuroidea (brittle stars)
(Carey 1978, Logerwell & Rand 2010, Piepenburg et al. 2010). Biomass of Echinoderms is considered
high when compared to other benthic functional groups (Table S5). Echinoderms can be suspension
feeders, predators, scavengers, and mud ingesters (Fratt & Dearborn 1984, McClintock 1994, Dearborn
et al. 1996, Howell et al. 2003); therefore, the diet of this functional group includes Arthropods (4.0%),
Bivalves (2.0%), Molluscs (7.0%), Worms (3.0%), Other Benthos (5.0%), Benthic Plants (4.0%), Pelagic
Detritus (10.0%), and Benthic Detritus (65.0%).
The Molluscs functional group includes the classes of: Aplacophora, Caudofavaeta
(Chaeitodermomorpha), Cephalopoda, Gastropoda (snails and slugs), Polyplacophora (Chiton), and
Scaphopoda (tusk shells) (Carey 1978, Logerwell & Rand 2010, Piepenburg et al. 2010). Biomass of
63
Molluscs is considered moderate when compared to other benthic functional groups (Table S5).
Molluscs are primarily detritivores and suspension feeders (Aitken & Gilbert 1996, Vanderklift & Ponsard
2003); therefore, the diet of this functional group includes Benthic Plants (10.0%), Pelagic Detritus
(15.0%), and Benthic Detritus (75.0%).
The Worm functional group includes the classes of: Annelida (segmented worms: Polychaetes and
Ciltellata), Entoprocta, Nematoda (round worms), Nemertea (ribbon worms), and Priapulida (penis
worms) (Wacasey et al. 1977, Carey 1978, Logerwell & Rand 2010, Piepenburg et al. 2010). Biomass of
Worms is considered low to moderate when compared to other benthic functional groups (Table S5).
The most abundant polychaetes from Table S5 survey studies were surface deposit and filter feeders
(Carey 1978); however, they also eat other benthic organisms (Fauchald & Jumars 1979). The diet of
this functional group includes Arthropods (1.0%), Echinoderms (2.0%), Molluscs (2.0%), Other Benthos
(1.0%), Benthic Plants (1.0%), Pelagic Detritus (13.0%), and Benthic Detritus (80.0%).
The Other Benthos functional group includes the classes of: Ascidiacea (sea squirts), Brachiopoda,
Bryozoa (moss animals), Cnidaria (Anthozoa: sea anenomes and Hydrozoa: sea serpent), Kinorhyncha
(mud dragons), and various unidentified eggs (Wacasey et al. 1977, Piepenburg et al. 2010). Biomass of
Worms is considered low when compared to other benthic functional groups (Table S5). Other Benthos
can be suspension feeders (bryozoans), pelagic and benthic feeders (brachiopods), as well as omnivores
(hydroids, anthozoans) (Barnes & Clarke 1995, Orejas et al. 2001, Peck et al. 2005); therefore, the diet of
this functional group includes Arthropods (2.0%), Echinoderms (1.0%), Molluscs (1.0%), Worms (3.0%),
Benthic Plants (2.0%), Pelagic Detritus (16.0%), and Benthic Detritus (75.0%).
Jellies, Zooplankton, and Copepods
The Jellies are a separate functional group in our EwE models due to their intermittently high
biomass (e.g., Forest et al. 2012) of the phyla Ctenophora, Cnidaria (Scyphozoa and Hydrozoa), and
Larvacea (Hopky et al. 1994c, Hopky et al. 1994d, Forest et al. 2012), while the Zooplankton and
64
Copepod functional groups are separated primarily by macro (> 2 cm), meso (0.2 mm - 2 cm), and micro
(< 0.2 mm) size ranges. The Macro-Zooplankton functional group has rarely ever been sampled for in
the Beaufort Sea, but what information exists in regards to quantity and composition included the
orders of Euphausiacea (krill), Decapoda (shrimp), Mysida, and Amphipoda, and the phylum of
Chaetognatha (arrow worms) (Hopky et al. 1994b, Darnis et al. 2008, Forest et al. 2012). Meso-
Zooplankton, although they were an individual functional group, were further subdivided into copepod
groups, as copepods are influenced by different environmental variables and contribute differently to
predators’ diets (Pirtle & Meuter 2011). The functional group Large Copepods included larger copepod
species (Calanus glacialis, Calanus hyperboreus, Metridia longa) that favor cold waters; the functional
group Medium Copepods includes the Pseudocalanus species (e.g., elongates, newmani), Oithona simils,
and Limnocalanus grimaldi (or macrurus), which are considered less influential to the Beaufort Sea food
web and favors warmer waters when compared to Large Copepods; and the Other Meso-Zooplankton
and Micro-Zooplankton functional groups, are aggregated groups of organisms that did not fit into the
aforementioned functional groups (Horner & Murphy 1985, Hopky et al. 1994b, Hopky et al. 1994d,
Llinás et al. 2008, McLaughlin et al. 2009, Walkusz et al. 2010, Forest et al. 2012).
Based on these functional group designations and supporting literature we estimate their biomass
from a series of Beaufort Sea zooplankton surveys that use bongo, neuston, and conical nets, as well as
net mesh sizes ranging from 85 to 763 μm. Beaufort Sea surveys reveal that the combined zooplankton
biomass of Jellies, Medium Copepods, Large Copepods, Other Meso-Zooplankton, and Micro-
Zooplankton functional groups range from 0.22 t km-2 to 17.14 t km-2, with a mean biomass across all
surveys (Beaufort Sea to Amundsen Gulf) of approximately 5.88 t km-2. In these surveys the majority of
the biomass mass is comprised of Jellies, which range from 2% (Hopky et al. 1994d) to 67% of the total
biomass/biovolume (Forest et al. 2012), as well as medium copepods (primarily pseudocalanus spp. and
Large Copepods, which range from 16% (Walkusz et al. 2010) to 89% of the total biomass/biovolume;
65
particularly in waters less than 100 m (Hopky et al. 1994d). Macro-Zooplankton and Other Meso-
Zooplankton functional groups contribute to varying proportions of the biomass depending on area
sampled and sampling method, as revealed in shelf surveys using various sampling gear-types
(Chaetognatha; Forest et al. 2012), and very little literature was available to estimate their biomass
throughout the Beaufort Sea.
We estimated the biomass of Jellies by multiplying the mean biomass (5.8800 t km-2) by the mean of
their biomass/biovolume across all surveys (15.8%) (Hopky et al. 1994b, Hopky et al. 1994d, Walkusz et
al. 2010, Forest et al. 2012), which equated to 0.9237 t km-2. This is considered a conservative estimate
of the Jellies biomass, as their biovolume can be more than double that of copepods (Forest et al. 2012).
The Jellies diet includes Jellies (5.0%), Medium Copepods (6.0%), Large Copepods (6.0%), Other Meso-
Zooplankton (5.0%), Micro-Zooplankton (5.0%), Producers > 5 μm (15.0%), Producers < 5 μm (48.0%),
and Pelagic Detritus (10.0%) (Sullivan & Reeve 1982, Purcell 1991, Purcell & Sturdevant 2001, Haddock
2007, Ceh et al. 2015).
Due to the lack of sampling of the Macro-Zooplankton and Micro-Zooplankton functional groups,
their biomass is estimated by Ecopath to be 0.2590 t km-2 and 1.0530 t km-2, respectively, based on the
ecosystem needs of predators. The diet of Macro-Zooplankton includes Macro-Zooplankton (3.0%),
Medium Copepods (10.0%), Large Copepods (20.0%), Other Meso-Zooplankton (15.0%), Micro-
Zooplankton (2.0%), Producer > 5 μm (15.0%), Producers < 5 μm (5.0%), Ice Algae (15.0%), and Pelagic
Detritus (15.0%) (Auel & Werner 2003, Haberman et al. 2003). The diet of Micro-Zooplankton, a
functional group of grazers, includes Producers < 5 μm (85.0%), Ice Algae (5.0%), Pelagic Detritus (5.0%),
and Benthic Detritus (5.0%) (Sherr et al. 2009).
For the Medium and Large Copepod groups biomass, values are calculate by first multiplying the
mean biomass (5.8800 t km-2) by the mean of all copepod biomass/biovolume across surveys (58.5%)
(Hopky et al. 1994b, Hopky et al. 1994d, Walkusz et al. 2010, Forest et al. 2012), which equates to total
66
copepod biomass of 3.4397 t km-2. As Pseudocalanus spp. (Medium Copepod group) biomass ranged
from <1 to 10% of the zooplankton biomass, and the larger copepods biomass ranged from 9 to 38% of
the zooplankton biomass (McLaughlin et al. 2009, Walkusz et al. 2010), a ratio of approximately 1:3.8
(peudocalanus: Large Copepods), the copepod biomass was apportioned accordingly to calculate the
Medium Copepods biomass at 0.7154 t km-2, and the Large Copepods biomass at 2.7242 t km-2. The diet
of Medium Copepods includes Other Meso-Zooplankton (5.0%), Micro-Zooplankton (5.0%), Producer > 5
μm (30.0%), Producers < 5 μm (40.0%), Ice Algae (10.0%), and Pelagic Detritus (10.0%) (Darnis et al.
2008, Campbell et al. 2009). The diet of Large Copepods includes Medium Copepods (5.0%), Micro-
Zooplankton (25.0%), Producers > 5 μm (15.0%), Producers < 5 μm (5.0%), Ice Algae (40.0%), Pelagic
Detritus (3.0%), and Benthic Detritus (7.0%) (Campbell et al. 2009, Forest et al. 2010).
The mean percent biomass of Other Meso-Zooplankton in Beaufort Sea surveys is approximately
28.2 % (Hopky et al. 1994b, Hopky et al. 1994d, Walkusz et al. 2008, Walkusz et al. 2010). When this
mean percentage is multiplied by the mean biomass of all zooplankton (5.88 t km-2), it yields a biomass
estimate of 1.6612 t km-2. The diet of Other Meso-Zooplankton includes Marco-Zooplankton (5.0%),
Other Meso-Zooplankton (3.0%), Micro-Zooplankton (24.0%), Producers > 5 μm (25.0%), Producers < 5
μm (18.0%), Ice Algae (15.0%), and Pelagic Detritus (10.0%). Although the methods used to estimate the
biomass of Jellies, Zooplankton, and Copepod functional groups yields a total biomass of 7.2009 t km-2
for all invertebrate functional groups considered, a total biomass higher than the average of 5.88 t km-2,
the biomass calculations for each these functional groups falls within the range of biomass values
reported in all Beaufort Sea surveys (Horner & Murphy 1985, Hopky et al. 1994b, Hopky et al. 1994d,
Llinás et al. 2008, Walkusz et al. 2008, McLaughlin et al. 2009, Walkusz et al. 2010, Forest et al. 2012),
and the standard deviation for the total biomass of 5.88 t km-2 was + 1.2 t km-2, which could mean our
biomass calculations may be very close to the 7.2009 t km-2 total biomass estimate. Additionally, these
biomass values were needed to balance the Ecopath model.
67
Primary Producers and Detritus
In the Ecopath model we created three types of primary producers, the open ocean functional
groups (divided by size class into Producers > 5 μm and Producers < 5 μm), the ice dependent functional
group of Ice Algae, as well as the benthic functional group of Benthic Plants (Horner & Schrader 1982,
Gosselin et al. 1997, Sukhanova et al. 2009). Available studies from the Chukchi-Beaufort Sea to the
Amundsen Gulf indicate that these three types of primary producers span seasonal periods, as well as
years of high and low sea-ice extent (1970s to present day) (Alexander 1974, Hsiao et al. 1977, Grainger
1979, Dunbar & Acreman 1980, Homer 1980, Hsiao 1980, Homer & Schrader 1981, Horner & Schrader
1982, Schell et al. 1982, Macdonald et al. 1987, Carmack et al. 2004, Riedel et al. 2007, Riedel et al.
2008, Sukhanova et al. 2009, Sergeeva et al. 2010). In only a few of these studies Benthic Plants are
included, however high density patches have been identified (Boulder Patch near Steffanson sound, AK)
(Hsiao 1980, Dunton et al. 1982, Horner & Schrader 1982). For biomass (t km-2) estimations of
Producers > 5 μm, Producers < 5 μm, and Ice Algae we use the following conversion when necessary: 1)
converting grams carbon to grams wet weight we multiplied grams carbon by 9 (Pauly & Christensen
1995), or 2) converting chlorophyll a to grams carbon we multiplied chlorophyll a by 53 (Kang et al.
2001).
The Beaufort Sea biomass estimates for Producers > 5 μm and Producers < 5 μm ranged from 0.5830
t km-2 (Brugel et al. 2009) to 58.5000 t km-2 (Hsiao 1980), with a mean biomass of 16.3964 t km-2
(Alexander 1974, Andersen 1977, Hsiao et al. 1977, Grainger 1979, Dunbar & Acreman 1980, Homer
1980, Hsiao 1980, Horner & Schrader 1982, Schell et al. 1982, Brugel et al. 2009, Sergeeva et al. 2010).
To account for the areas of low productivity in deeper waters (Gosselin et al. 1997)( Giovanni Chl a data
discussed below), and the seasonal highs and lows of annual productivity, the mean biomass is
multiplied by 50% to yield a total biomass for the Producers > 5 μm and Producers < 5 μm functional
groups of 8.5100 t km-2. The percent of the Producers > 5 μm functional group relative to the total
68
biomass can range from 25 to 62% (Riedel et al. 2007, Brugel et al. 2009); therefore, we allocate 43.5%
of the total biomass (midpoint of the range) to yield a biomass estimate of 3.7018 t km-2. The Producers
< 5 μm functional group biomass is similarly estimated at 4.8081 t km-2. Producers > 5 μm include
Diatoms, Dinoflagellates, Cryptophytes, Crysophytes, Haptophytes, Eulenophytes, Chlorophytes, and
Cyanophytes (Cobb et al. 2008), while Producers < 5 μm include any small autotroph.
Ice Algae biomass ranges from almost undetectable (Horner & Schrader 1982) to 11.7000 t km-2
(Hsiao 1980), with a mean biomass of 4.0833 t km-2 (Alexander 1974, Andersen 1977, Grainger 1979,
Dunbar & Acreman 1980, Homer 1980, Hsiao 1980, Horner & Schrader 1982, Schell et al. 1982,
Macdonald et al. 1987, Carmack et al. 2004). To account for the high area of sea-ice extent and duration
during the colder seasons, therefore increased ice algae productivity, we multiplied the mean biomass
by 86%, the mean of the annual Beaufort Sea ice cover (%) in 1970 (according to the Hadley Centre Data
Sea Ice and Sea Surface Temperature data set (HadISST) (British Atmospheric Data Centre (2010)), to
yield a starting biomass of 3.5117 t km-2. It is assumed that if ice was present then ice algae were
productive.
Benthic Plants are a relatively understudied functional group in the model area, with the exception
of a few areas in the Beaufort Sea that have dense kelp and algal communities (Dunton et al. 1982,
Wilce & Dunton 2014), and this functional group most likely consists largely of benthic microalgal
communities (Horner & Schrader 1982) with documented annual cycles of high and low productivity .
The Matheke and Horner (1974) study indicates that benthic communities are most productive in the
summer months. Microalgae biomass can range from 0.7155 t km-2 (Horner & Schrader 1982) to
52.4700 t km-2 (Hopky et al. 1994c). To address the patchiness of the Benthic Plants functional group
throughout the Beaufort Sea marine ecosystem area we used the minimum biomass necessary to
balance the model, 5.500 t km-2; thus, this is considered a conservative biomass estimate.
69
Lastly, two detrital groups were created, Pelagic Detritus and Benthic Detritus, as primary
productivity rates relate to the amount of detritus produced and transported from the pelagic to
benthic habitats (Schell et al. 1982, Juul-Pedersen et al. 2008). For instance, flux rates at 25 m depths
during spring melt are at least double the values during the early spring or winter, 42.3 mg of Particulate
Organic Carbon (POC) m-2 d-1 versus 19.2 and 19.7 mg POC m-2 d-1, respectively (Juul-Pedersen et al.
2008). During melting of sea ice the values of POC reach levels of 123.5 mg POC m-2 d-1 for 1 m depths
(compared to the 42.3 mg POC m-2 d-1 at 25 m depths), indicating that large amounts of organic matter
are utilized by the food web before reaching deeper water depths. In contrast, during the winter and
early spring, the sinking fluxes are constant at all sampled depths (1m, 15m, 25m), identifying the lack of
retention in the water column and the potential increased contribution to the benthos (see Table S5 in
Juul-Pedersen et al. (2008)). The June to September sinking rates of POC (average 80.3 mg POC m-2) are
reported to be lower than the spring melt values, but higher than times when ice algae dominates
(winter, early spring) (Sergeeva et al. 2010). This likely demonstrates the importance of the spring
bloom derived detritus to the water column and food web. To balance the Ecopath model a
conservative estimate of 0.500 t km-2 is used for Pelagic Detritus and 0.0500 t km-2 for Benthic Detritus.
70
Supplemental Tables Table S1. List of species for birds and fish functional groups.
Functional Group Common Name(s) Specie(s) Functional Group Common Name(s) Specie(s)
Birds Brant Branta bemicia Birds Scoter (Surf) Melanitta perspicillata
Canvasback Aythya valisineria Scoter (White-winged) Melanitta fusca
Crane (Sandhill) Grus canadensis Shoveler (Northern) Anas clypeata
Eider (Common) Sometaria mollissima Swan (Trumpeter) Cygnus buccinator
Eider (King) Sometaria spectabilis Swan (Swan) Cygnus columbianus
Goldeneye (Barrow's) Bucephala islandica Teal (Green-winged) Anas crecca
Goldeneye (Common) Bucephala clangula Widgeon (American) Anas americana
Goose (Canada) Branta canadensis Char & Dolly Varden Arctic Char Salvelinus alpinus
Goose (Greater White-fronted)
Answer albifrons Dolly varden Salvelinus malma
Goose (Ross) Chen rossii Ciscoes & Whitefish Arctic Cisco Coregonus autumnalis
Goose (Snow) Chen caerulescens Broad Whitefish Coregonus nasus
Loon (Common) Gavia immer Lake Herring/Cisco Coregonus artedi
Loon (Pacific Arctic) Gavia pacifica Lake Whitefish Coregonus clupeaformis
Loong (Yellow-billed) Gavia adamsii Least Cisco Coregonus sardinella
Mallard Anas platyrhynchos Round Whitefish Prosopium cylindraceum
Merganser (Common) Mergus merganser Salmonids Arctic Grayling Thymallus arcticus
Merganser (Red-breasted)
Mergus serrator Chinook Salmon Oncorhynchus tshawytscha
Oldsquaw Clangula hyemalis Chum Salmon Oncorhynchus keta
Owl (Snowy) Nyctea scandiaca Coho Salmon Oncorhynchus kisutch
Pintail (Northern) Anus acuta Inconnu Stenodus leucichthys
Ptarmigan (Rock) Lagopus mutus Pink Salmon Oncorhynchus gorbuscha
Ptarmigan (Willow) lagopus lagopus Sockeye Salmon Oncorhynchus nerka
Scaup (Greater) Aythya marila Herring & Smelt Northern Sand Lance Ammodytes dubius
Scaup (Lesser) Aythya affinis Pacific Herring Clupea pallasii
Scoter (Black) Melanitta nigra Pacific Sand Lance Ammodytes hexapterus
71
Table S1. Continued
Functional Group Common Name(s) Specie(s) Functional Group Common Name(s) Specie(s)
Herring & Smelt Rainbow Smelt Osmerus mordax Small Benthic Marine Fish
Longear Eelpout Lycodes seminudus
Arctic & Polar Cods Arctic Cod Arctogadus glacialis Northern Sculpin Icelinus borealis
Polar Cod Boreogadus saida Ribbed Sculpin Triglops pingelii
Capelin Capelin Mallotus villosus Saddled Eelpout Lycodes mucosus
Flounder & Benthic Cods
Arctic Flounder Liopsetta glacialis Shorthorn Sculpin Myoxocephalus scorpius
Bering Flounder Hippoglossoides robustus Spatulate Sculpin Icelus spatula
Burbot Lota lota Threespot Eelpout Lycodes rossi
Pacific Cod Gadus macrocephalus Twohorn Sculpin Icelus bicornis
Saffron Cod Eleginus gracilis Twolip Pout Gymnelus bilabrus
Starry Flounder Platichthys stellatus Warty Sculpin Myoxocephalus verrucosus
Walleye Pollock Theragra chalcogramma White Sea Eelpout Lycodes marisalbi
Small Benthic Marine Fish
Antlered Sculpin Enophrys diceraus Other Fish Arctic Alligatorfish Aspidophoroides olriki
Archer Eelpout Lycodes sagittarius Blackline Prickleback Acantholumpenus mackayi
Arctic Sculpin Myoxocephalus scorpioides
Daubed Shanny (Prickleback)
Lumpenus maculatus
Arctic Staghorn Sculpin Gymnocanthus tricuspis Festive Snailfish Liparis marmoratus
Bigeye Sculpin Triglops nybelini Fourline Snakeblenny Eumesogrammus praecisus
Canadian Eelpout Lycodes polaris Gelatinous Seasnail Liparis fabricii
Eyeshade Sculpin Nautichthys pribilovius Greenland Halibut Reinhardtius hippoglossoides
Fish Doctor Gymnelus viridis Kelp Snailfish Liparis tunicatus
Fourhorn Sculpin Myoxocephalus quadricornis
Leatherfin Lumpsucker Eumicrotremus derjugini
Hamecon Artediellus scaber Ninespine Stickleback Pungitius pungitius
Hookear Sculpin Artediellus uncinatus Northern Pike Esox lucius
Knipowitsch’s Pout Gymnelus knipowknipowitschi
Poacher Leptagonus sp.
Marbled Eelpout Lycodes raridens Salmon Snailfish Careproctus rastrinus
72
Table S1. Continued
Functional Group Common Name(s) Specie(s)
Other Fish Slender Eelblenny Lumpenus fabricii
Stout Eelblenny Lumpenus medius
Variegated Snailfish Liparis gibbus
Whitespotted Geenling Hexagrammos stelleri
73
Table S2. Subsistence and commercial fisheries created in the Ecopath model to describe each community’s mean harvesting rate (t km-2 year-1) for each functional group harvested.
Barrow Nuiqsut Kaktovik Aklavik Inuvik Tuktoyaktuk Paulatuk Sachs Harbour Ulukhaktok Commercial
Polar Bears 2.22E-05 2.12E-06 4.32E-06 1.85E-06 8.05E-08 1.12E-05 7.22E-06 1.14E-05 1.50E-05
Beluga Whales 2.34E-06 3.54E-08 1.45E-06 3.59E-05 8.33E-05 8.32E-05 9.88E-06
3.54E-07
Gray Whales
Bowhead Whales 1.08E-03 1.17E-04 1.67E-04 3.04E-06
Walrus 5.69E-05 1.24E-07 4.22E-06
8.09E-08 2.43E-07 3.03E-07
Ringed Seals 3.39E-05 4.64E-06 3.66E-06 8.04E-08 3.57E-08 1.73E-06 7.50E-06 9.38E-06 5.54E-05
Bearded Seals 1.99E-04 5.20E-06 9.82E-06 5.78E-08 5.78E-08 8.09E-07 2.60E-06 6.93E-06 4.62E-06
Spotted Seals 2.29E-06 3.81E-07 3.81E-07
Birds 3.83E-05 6.89E-06 3.61E-06 3.75E-06 8.02E-06 3.60E-05 2.17E-05 1.94E-05 8.37E-06
Char & Dolly Varden 1.11E-06 3.00E-06 1.07E-05 5.74E-06 3.06E-07 1.50E-08 1.36E-05 3.17E-06 3.87E-05 6.29E-06
Ciscoes & Whitefish 3.58E-05 9.41E-05 1.05E-05 3.97E-05 3.63E-05 6.58E-05 4.93E-06 2.35E-08 1.60E-07 1.02E-04
Salmonids 7.93E-05 1.30E-05 6.30E-07 2.32E-05 2.16E-05 3.78E-05 2.30E-07
1.37E-04
Herring & Smelt 2.70E-07
4.68E-07 8.88E-08 3.06E-06 5.40E-08
Arctic & Polar Cods 2.79E-07
2.88E-09 4.69E-11
1.49E-11
1.37E-09 1.43E-09
Capelin
2.88E-07
Flounder & Benthic Cods 4.63E-06 2.93E-06 3.58E-08 1.07E-05 1.54E-05 3.06E-06 9.87E-07 1.17E-07 1.30E-08 1.36E-04
Small Benthic Marine Fish 1.23E-09
4.16E-08
Other Fish 5.46E-09 9.41E-09
4.30E-07 5.57E-07 1.76E-08 1.41E-09
7.85E-10 1.52E-05
74
Table S3. Weights used to calculate the Birds functional group biomass in surveys and harvest reports.
Common Name Weight (kg) Source
Brant 1.4 Braund (2010)
Canvasback 1.1 NG (2015)
Crane 4.5 Braund (2010)
Duck 0.5 EPD (2001)
Eider 0.7 Braund (2010)
Goldeneye 1.0 EPD (2001)
Goose 5.0 Braund (2010)
Loon 1.4 Braund (2010)
Mallard 1.2 EPD (2001)
Merganser 1.5 EPD (2001)
Owl 2.3 Cornell Lab of Ornithology (2015c)
Oldsquaw 0.7 Braund (2010)
Pintail 0.8 Fredrickson and Heitmeyer (1991)
Ptarmigan 0.3 Braund (2010)
Scaup 0.8 EPD (2001)
Scoter 0.7 Braund (2010)
Shoveler 0.6 Cornell Lab of Ornithology (2015b)
Swan 4.5 Braund (2010)
Teal 0.3 Cornell Lab of Ornithology (2015a)
Widgeon 0.8 EPD (2001)
75
Table S4. Weights used to calculate the fish functional groups biomasses in surveys and harvest reports.
Functional Group Mean Weight (kg) Reference(s)
Char & Dolly Varden
2.70 George et al. (2009), fishbase.org
Ciscoes & Whitefish 1.60 Chiperzak et al. (1991), Majewski et al. (2006), Brewster et al. (2008), George et al. (2009), fishbase.org
Salmonids 8.00 Chiperzak et al. (1991), George et al. (2009), fishbase.org
Herring & Smelt 0.20 Majewski et al. (2006), Tokranov (2007), www.fishbase.org, www.nmfs.noaa.gov
Arctic & Polar Cods 0.03 Süfke et al. (1998), Majewski et al. (2006), Logerwell and Rand (2010)
Capelin 0.10 Logerwell and Rand (2010)
Flounder & Benthic Cods
3.70 Chiperzak et al. (1991), Majewski et al. (2006), George et al. (2009), Logerwell and Rand (2010)
Small Benthic Marine Fish
0.15 Chiperzak et al. (1991), Majewski et al. (2006), Logerwell and Rand (2010), Chouinard and Hurlbut (2011)
Other Fish 0.19 Houston (1990), Majewski et al. (2006), George et al. (2009), Logerwell and Rand (2010)
76
Table S5. Biomass mass estimates (t km-2) for the functional groups of Arthropods, Bivalves, Echinoderms, Molluscs, Worms, and Other Benthos from 0 to 100 m of water depth.
Functional Groups
Biomass (t km-2
) Wacasey et al.
(1977) High Low
Biomass (t km-2
) Carey Jr. (1976,
1978) High Low
Biomass (t km-2
) Logerwell and Rand
(2010) High (lined nets) Low (unlined nets)
Model Biomass (t km
-2)
(Required to Balance)
Arthropods 5.7236 0.7872 7.7741 0.0716 9.2470 0.3630 3.5000
Bivalves 3.7745 1.9798 -- -- -- -- 1.9889
Echinoderms 36.1283 0.0510 0.2142 0.0000 40.5700 1.1820 5.0000
Molluscs 1.7938 0.0919 0.7351 0.0068 7.8220 0.0630 3.0000
Worms 3.5630 0.0000 1.8321 0.2244 0.6610 0.0020 2.5000
Other Benthos 1.9704 1.4300 0.0943 0.0000 2.4230 1.1860 1.7000
77
Table S6. Vulnerability calculated in Ecosim using multiple iterations and time series data.
Prey \ Predator 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16
1 Polar Bears 3.35 2 Beluga Whales 3.75 3 Gray Whales 2.00 4 Bowhead Whales 1.44 5 Walrus 1.53 6 Ringed Seals 1.06
1.01 7 Bearded Seals 1.70
1.00
8 Spotted Seals 1.33
1.02 9 Birds 2.12
10 Char & Dolly Varden
2.05
2.94 1.91 33.55 1.20 11 Ciscoes & Whitefish
1.64
1.32 2.22 15.35 1.38 1.85
7.33 2.50
12 Salmonids
11.92 2.36 1.23
1.55 1.63 13 Herring & Smelt
2.28
4.10 1.46 1.87 1.00 1.05 2.60
1.17 3.14 4.49
14 Arctic & Polar Cods
1.42
3.82 2.08 1.73 1.83 1.44 2.45 1.88
2.52
2.07 15 Capelin
1.75
2.21 1.66 3.16 1.66 1.43
6.89
2.70
16 Flounder & Benthic Cods
2.24
4.20 1.98 1.84 1.90 2.08
2.00
4.52 17 Small Benthic Marine Fish
2.08 2.71 2.62 1.96 5.40 4.25
1.75 1.91 1.44 1.90 1.52
1.67
18 Other Fish
2.18
1.76
1.93 1.43
1.98 1.81 1.62 1.69
2.04 19 Arthropods
1.81 2.05 4.42 2.04 60.95 3.30 1.97 2.00 1.15 1.66 6.56 2.07 1.34 2.79
20 Bivalves
1.93 2.14 2.19 1.13
1.96 1.83
1.23 21 Echinoderms
2.14
1.48 1.90 1.97
2.12 1.39 1.83
2.36 1.61 3.29 1.71
22 Molluscs
2.26 1.98 2.38 1.07 1.99 1.85
2.04 1.93 1.67
2.04 2.88 3.64 2.42 23 Worms
1.98 2.26
1.53 1.66 2.39
1.98 2.04 3.50 1.63 1.82 1.50 2.01 1.84
24 Other Benthos
2.50
1.70 1.17
1.83 2.25
1.63 1.70 2.05 1.60 2.03 25 Jellies
3.49
1.11
26 Macro-Zooplankton
2.31
152.45 1.82 6.19
2.15 1.48 2.99 1.97 1.53 2.76 2.57 2.00 2.06 27 Medium Copepods
2.38 1.96 3.40
1.78
1.26 1.81 1.39 2.77 1.10 2.03 2.10 3.00
28 Large Copepods
2.14 1.91 3.95
2.61
1.36 1.03 1.64 1.30 1.04 1.50 2.19 2.21 29 Other Meso-Zooplankton
2.02
3.16
1.52
1.10 2.02 2.15 2.27 2.04 3.34 2.79 2.49
30 Micro-Zooplankton
4.29
1.72
1.19 31 Producers >5um
1.09 1.38 1.13 2.26 2.03
32 Producers <5um
1.07 33 Ice Algae
3.41
1.55
34 Benthic Plants 35 Pelagic Detritus 36 Benthic Detritus
78
Table S6. Vulnerability
Prey \ Predator 17 18 19 20 21 22 23 24 25 26 27 28 29 30
1 Polar Bears 2 Beluga Whales 3 Gray Whales 4 Bowhead Whales 5 Walrus 6 Ringed Seals 7 Bearded Seals 8 Spotted Seals 9 Birds 10 Char & Dolly Varden 11 Ciscoes & Whitefish 12 Salmonids 13 Herring & Smelt 14 Arctic & Polar Cods 15 Capelin 16 Flounder & Benthic Cods 1.64
17 Small Benthic Marine Fish 1.68 18 Other Fish 1.52 19 Arthropods 1.16 1.91
2.18
1.60 1.46
20 Bivalves 8.90 1.32 1.11
1.67 21 Echinoderms 2.75 1.85 2.63
3.26 1.66
22 Molluscs 1.98 2.32 1.63
1.35
2.43 1.85 23 Worms 2.82 2.01 2.23
2.54
2.16
24 Other Benthos 2.35 2.05 1.99
1.87
2.42 25 Jellies 2.41 1.93 2.52
2.35
26 Macro-Zooplankton 1.99 2.55
1.91 27 Medium Copepods 2.49 2.11
5.44 2.22
2.16 3.69
28 Large Copepods 5.94 2.04
2.61 1.35 29 Other Meso-Zooplankton 2.25 2.06
1.93 1.09 1.62
2.34
30 Micro-Zooplankton 3.61 2.03
1.97 1.90 2.18 5.12 3.69 31 Producers >5um 1.55 1.53
1.80
1.57 1.25 2.36 1.86 20.17
32 Producers <5um
1.95
1.66
1.07 2.29 1.50 2.11 3.56 1.86 33 Ice Algae
2.10
1.56
1.49 2.63 1.75 1.78 3.82
34 Benthic Plants
2.47 1.71 2.43 1.88 2.19 3.19 35 Pelagic Detritus
2.22 1.98 1.98 3.16 3.29 1.65 1.37 1.61 1.58 3.48 1.62 5.49
36 Benthic Detritus
2.98 2.52 1.24 1.15 1.79 1.46
1.08
35.47
79
Supplemental Figure Captions
Fig. S1 Beaufort Sea functional group trophic level (TL) calculations and comparisons. Ecosim model TL
is indicated by the black bars, whereas gray bars indicate the range of trophic levels from literature
(Hobson & Welch 1992, Hoekstra et al. 2003, Whitehouse 2013, Whitehouse & Aydin 2016, Norcross et
al. 2017).
Fig. S2 Ecosim sea-ice extent anomaly forcing function from 1970 to 2014. The anomaly is calculated by
dividing each monthly value from 1970 to 2014 by the 1970 mean sea-ice extent.
Fig. S3 Ecosim sea surface temperature (SST) anomaly forcing function from 1970 to 2014. The anomaly
is calculated by dividing each monthly value from 1970 to 2014 by the 1970 mean SST.
Fig. S4 Ecosim mediation function describing an increase in ice-dependent functional group biomass
with increasing sea-ice extent (e.g. Polar Bears, and ice seals). The Ice Algae functional group is used as
a proxy for sea-ice extent.
Fig. S5 Ecosim mediation function describing a decrease in ice-independent functional group biomass
with increasing sea-ice extent (e.g., whales). The Ice Algae functional group is used as a proxy for sea-ice
extent.
Fig. S6 Ecosim harvesting of Polar Bears for the community of Barrow described as the seasonal effort
anomaly (or success) from January to December.
Fig. S7 Ecosim calibration fits for Polar Bear biomass (a) and catch (b), as well as Bowhead Whale
biomass (c) and catch (d). For Bowhead Whales the observed biomass was used to calibrate the model
(circles no fil) with a biomass accumulation rate of 3.2% (Allen & Angliss 2014).
Fig. S8 Sensitivity analysis whisker plots for 1971 (one-year model equilibration period), 1980, 1990, and
2010. Whisker plots reveal results of Monte Carlo trails (1000 iterations) to test model robustness.
Changes in biomass for each functional group, in context of trial-derived minimum biomass, show
maximum biomass, 1st quartile biomass (line at the bottom of the box), 3rd quartile biomass (line at the
top of the box), median biomass (line in the middle of the box), and Ecosim model biomass (black dot).
Fig. S9 Redundancy analysis (RDA) plot for Arctic & Polar Cod biomass. One hundred percent of the
variability of Arctic & Polar Cods’ biomass (green) is explained by positive relationships with the biomass
Capelin, Micro- and Other Meso-Zooplankton, Polar Bears, and Producers < 5 µm, and negative
relationships with Walrus, Ringed Seals, and Bivalves (red). Arctic & Polar Cods is univariate, therefore
only the x-axis is used to illustrate relationships.
80
Fig. S1
81
Fig. S2
82
Fig. S3
83
Fig. S4
84
Fig. S5
85
Fig. S6
86
Fig. S7
87
Fig. S8
88
Fig. S9
89
Supplemental References
Aars J, Lunn NJ, Derocher AE (2006) Polar bears: Proceedings of the 14th working meeting of the IUCN/SSC polar bear specialist group, 20-24 June 2005, Seattle, Washington. Occasional Paper 32
Adams M, Frost KJ, Harwood LA (1993) Alaska and Inuvialuit Beluga Whale Committee (Aibwc) - an Initiative in at Home Management. Arctic 46:134-137
ADFG (2015) Walrus research projects. Village-based Walrus Habitat Use Studies in the Chukchi Sea, Alaska Department of Fish and Game
ADNR (2009) Beaufort Sea areawide oil and gas lease sales, final finding of the Director. Alaska Department of Natural Resources, Division of Oil & Gas
ADNR (2011) North Slope foothills areawide oil and gas lease sales, final finding of the Director. Alaska Department of Natural Resources, Division of Oil & Gas
Aitken AE, Gilbert R (1996) Marine mollusca from expedition Fiord, western axel Heiberg Island, northwest territories, Canada. Arctic 49:29-43
Alexander SA, Barry TW, Dickson DL, Prus HD, Smyth KE (1988) Key areas for birds in coastal regions of the Canadian Beaufort Sea. Canadian Wildlife Service:1-146
Alexander V (1974) The coast and shelf of the Beaufort Sea. The Arctic Institute of North America, Arlington, V.A.
Allen BM, Angliss RP (2010a) Alaska marine mammal stock assessments, 2009. US Department of Commerce, NOAA Technical Memorandum NMFS-AFSC-206:276
Allen BM, Angliss RP (2010b) Pacific walrus (Odobenus rosmarus divergens); Alaska stock. National Oceanic and Atmospheric Administration
Allen BM, Angliss RP (2013) Alaska marine mammal stock assessments, 2012. US Department of Commerce, NOAA Technical Memorandum NMFS-AFSC-245:282
Allen BM, Angliss RP (2014) Alaska marine mammal stock assessments, 2013. NOAA Technical Memorandum
Amstrup SC (2003) Wild mammals of North America Amstrup SC, Durner GM, McDonald TL, Mulcahy DM, Garner GW (2001a) Comparing movement
patterns of satellite-tagged male and female polar bears. Can J Zool 79:2147-2158 Amstrup SC, Durner GM, Stirling I, Lunn NJ, Messier F (2000) Movements and distribution of polar bears
in the Beaufort Sea. Can J Zool 78:948-966 Amstrup SC, Marcot BG, Douglas DC (2007) Forecasting the range-wide status of polar bears at selected
times in the 21st century. Administrative Report. US Geological Survey Amstrup SC, McDonald TL, Stirling I (2001b) Polar bears in the Beaufort Sea: A 30-year mark-recapture
case history. Journal of Agricultural, Biological, and Environmental Statistics 6:221-234 Amstrup SC, Stirling I, Lentfer JW (1986) Past and present status of polar bears in Alaska. Wildlife Soc B
14:241-254 Andersen OGN (1977) Primary production associated with sea ice at Godhavn, Disko, west Greenland.
Ophelia 16:205-220 Angliss RP, Outlaw RB (2008) Alaska marine mammal stock assessments, 2007. US Department of
Commerce, NOAA Technical Memorandum NMFS-AFSC-180:263 Arndt CE, Swadling KM (2006) Crustacea in Arctic and Antarctic Sea Ice: Distribution, Diet and Life
History Strategies. Advances in Marine Biology. Elsevier BV Ashjian CJ, Braund SR, Campbell RG, George JCC, Kruse J, Maslowski W, Moore SE, Nicolson CR, Okkonen
SR, Sherr BF, Sherr EB, Spitz YH (2010) Climate variability, oceanography, bowhead whale distribution, and Inupiat subsistence whaling near barrow, Alaska. Arctic 63
90
Atkinson EG, Percy JA (1992) Diet comparison among demersal marine fish from the Canadian Arctic. Polar Biol 11
Atkinson EG, Wacasey JW (1989) Benthic invertebrates collected from the Western Canadian Arctic, 1951 to 1985. Arctic Biological Station of the Institut Maurice-Lamontagne, Ste-Anne-de-Bellevue, QC
Auel H, Werner I (2003) Feeding, respiration and life history of the hyperiid amphipod Themisto libellula in the Arctic marginal ice zone of the Greenland Sea. Journal of Experimental Marine Biology and Ecology 296:183-197
Bacon JJ, Hep TR, Brower HK, Jr., Pedereson M, Olemaun TP, George JC, Corrigan BG (2009) Estimates of Subsistence Harvest for Villages on the North Slope of Alaska, 1994-2003. North Slope Borough Department of Wildlife Management
Barber WE, Smith RL, Vallarino M, Meyer RM (1997) Demersal fish assemblages of the northeastern Chukchi Sea, Alaska. Fish B-Noaa 95:195-208
Barnes DA, Clarke A (1995) Seasonality of feeding activity in Antarctic suspension feeders. Polar Biol 15 Barry SJ, Barry TW (1982) Sea-bird surveys in the Beaufort Sea, Amundsen Gulf, and Prince of Wales
Strait 1981 season. Report for Dome Petroleum Ltd, Esso Resources Canada Ltd, Canadian Wildlife Service
Barry TW (1976) Seabirds of the southeastern Beaufort Sea: summary report. Canadian Wildlife Service, Department of the Environment, Beaufort Sea Technical Report 3a:47
Barry TW, Barry SJ, Jacobson B (1981) Sea-bird surveys in the Beaufort Sea, Amundsen Gulf, Prince of Wales Strait and Viscount Melville Sound-1980 season. Report for Dome Petroleum Ltd and Esso Resources Canada Ltd, Calgary
Bendock TN (1977) Beaufort Sea estuarine fishery study. In: Alaska Department of Fish and Game AR, Contract 03-5-022-69 (ed) Environmental Assessment of the Alaskan Continental Shelf, Annual Reports of Principal Investigators for the year ending in March 1977, Vol VIII Receptors – Fish, Littoral, Benthos
Bentzen TW, Follmann EH, Amstrup SC, York GS, Wooller MJ, O’Hara TM (2007) Variation in winter diet of southern Beaufort Sea polar bears inferred from stable isotope analysis. Can J Zool 85:596-608
Bernard FR (1979) Contributions in Science Natural History Museum of Los Angeles County. Natural History Museum of Los Angeles County, Los Angeles, C.A.
Bessière A, Nozais C, Brugel S, Demers S, Desrosiers G (2007) Metazoan meiofauna dynamics and pelagic–benthic coupling in the Southeastern Beaufort Sea, Arctic Ocean. Polar Biol 30:1123-1135
Bickham JW, Dupont JM, Broker K (2013) Review of the status of the western North Pacific gray whale; stock structure hypotheses, and recommendations for methods of future genetic studies. Book 65a. IWC Scientific Committee
Billard R (1997) Les poissons d'eau douce des rivières de France. Identification, inventaire et répartition des 83 espèces. Lausanne, Delachaux & Niestlé:192
Bodish HH (1936) Chasing the bowhead. Harvard University Press, Cambridge, MA Bond W, Erickson R (1992) Fishery data from the Anderson River estuary, Northwest Territories, 1990.
Canadian Manuscript Report of Fisheries and Aquatic Sciences Book 2171. Central and Arctic Region Department of Fisheries and Oceans
BOWFEST (2009) Bowhead whale feeding ecology study (BOWFEST) in the western Beaufort Sea: 2009 Annual report. National Marine Mammal Laboratory, Alaska Fisheries Science Center, National Marine Fisheries Service, National Oceanic and Atmospheric Administration
BOWFEST (2011) Bowhead whale feeding ecology study (BOWFEST) in the western Beaufort Sea. In: Shelden KEW, Mocklin JA (eds). National Marine Mammal Laboratory, Alaska Fisheries Science
91
Center, National Marine Fisheries Service, National Oceanic and Atmospheric Administration, 7600 Sand Point Way NE, Seattle, WA 98115
Braham HW (1984) The bowhead whale, Balaena mysticetus. Marine Fishery Review 46:45-53 Braham HW, Burns JJ, Fedoseev GA, Krogman BD (1984a) Habitat partitioning by ice-associated
pinnipeds: distribution and density of seals and walruses in the Bering Sea, April 1976. In: Fay FH, Fedoseev GA (eds) Soviet-American Cooperative Rsearch on Marine Mammals, Book 1-Pinnipeds. NOAA Technical Report NMFS 12, U.S. Department of Commerce, NOAA, Washington, D.C.
Braham HW, Fraker MA, Krogman BD (1980) Spring migration of the western Arctic population of bowhead whales. Marine Fishery Review 42:36-46
Braham HW, Krogman BD, Carroll GM (1984b) Bowhead and white whale migration, distribution, and abundance in the Bering, Chukchi, and Beaufort Seas, 1975-78. NOAA Technical Report NMFS SSRF-779. U.S. Department of Commerce, National Oceanic and Atmospheric Administration, National Marine Fisheries Service
Braun GM (1985) The structure of an Arctic shallow water benthic community: effects of ice gouging. Masters, Oregon State University,
Braund SR (1993) North Slope subsistence study Barrow, 1987, 1988 and 1989. OCS Study MMS 91-0086. U. S. Department of the Interior, Minerals Management Service
Braund SR (2010) Subsistence mapping of Nuiqsut, Kaktovik, and Barrow. MMS OCS Study Number 2009-003. United States Department of the Interior
Brewster K, George C, Aiken M, Brower A, Sr., Itta M, Itta N, Leavitt ML, Leavitt O, Matumeak W (2008) Iñupiat knowledge of selected subsistence fish near Barrow, Alaska. Report prepared for the Bureau of Land Management through an assistance agreement to the North Slope Borough Department of Wildlife Management
Brodie PF (1971) A Reconsideration of Aspects of Growth, Reproduction, and Behavior of the White Whale ( Delphinapterus leucas ), with Reference to the Cumberland Sound, Baffin Island, Population. J Fish Res Bd Can 28:1309-1318
Bromaghin JF, McDonald TL, Stirling I, Derocher AE, Richardson ES, Regehr EV, Douglas DC, Durner GM, Atwood T, Amstrup SC (2015) Polar bear population dynamics in the southern Beaufort Sea during a period of sea ice decline. Ecological Applications 25:634-651
Bromley RG (1993) Comparison of results from two waterfowl harvest studies in three Inuvialuit communities, Northwest Territories, 1988-1990. Report No 111. Northwest Territories Renewable Resources
Brower HK, Jr., Hepa R (1998) North Slope Borough subsistence harvest documentation project: data form Nuiqsut, Alaska for the period July 1, 1995, to June 30, 1995. Department of Wildlife Management, North Slope Borough
Brower HK, Jr., Olemaun TP, Hepa TR (2000) North Slope Borough subsistence harvest documentation project: data for Kaktovik, Alaska for the period December 1, 1994 to November 30, 1995. Department of Wildlife Management, North Slope Borough
Brugel S, Nozais C, Poulin M, Tremblay JE, Miller LA, Simpson KG, Gratton Y, Demers S (2009) Phytoplankton biomass and production in the southeastern Beaufort Sea in autumn 2002 and 2003. Marine Ecology Progress Series 377:63-77
Bukhtiyarov YA, Frost KJ, Lowry LF (1984) New information on the foods of the spotted seal, Phoca largha, in the Bering Sea in spring. In: Fay FH, Feoseev GA (eds) Soviet-American Cooperative Research on Marine Mammals, Book 1 - Pinnepeds. Under Project V.6. Marine Mammals, of the US-USSR Agreement on Cooperation in the Field of Environmental Protection. U.S. Department of Commerce, NOAA Technical Report NMFS 12
92
Burkanov VN, Semenove AR, Mashagin SA, Kitayev EV (1988) Data on abundance of ice forms of seals in the Karaginski Gulf of the Bering Sea in 1986-1987. In: Chernysheva NS (ed) Scientific Research on Sea Mammals of the Northern Part of the Pacific Ocean in 1986-1987. All-Union Scientific Research Institute of Sea Fisheries and Oceanography (VNIRO), Moscow, Russia. (Translated from Russian by Canada Institute for Scientific and Technical Information, National Research Council, Ottawa, Canada)
Burns JJ (1970) Remarks on the Distribution and Natural History of Pagophilic Pinnipeds in the Bering and Chukchi Seas. Journal of Mammalogy 51:445
Burns JJ, Frost KJ (1979) The natural history and ecology of the bearded seal, Erignathus barbatus. Alaska Department of Fish and Game:77
Burns JJ, Harbo SJ (1972) An aerial census of ringed seals, northern coast of Alaska. Arctic 25:279-290 Byers T, Roberts LW (1995) Harpoons and Ulus: Collective wisdom and traditions of Inuvialuit regarding
the beluga (qilalugaq) in the Mackenzie River estuary. Unpublished Report to the Department of Indian and Northern Affairs (Arctic Environmental Strategy) and the Fisheries Joint Management Committee, Inuvik
Cameron MF, Bengston JL, Boveng PL, Jansen JK, Kelly BP, Dahle SP, Logerwell EA, Overland JE, Sabine CL, Waring GT, Wilder JM (2010) Status review of the bearded seal (Erignathus barbatus). NOAA Technical Memorandum NMFS-AFSC-211
Campbell RG, Sherr EB, Ashjian CJ, Plourde S, Sherr BF, Hill V, Stockwell DA (2009) Mesozooplankton prey preference and grazing impact in the western Arctic Ocean. Deep Sea Research Part II: Topical Studies in Oceanography 56:1274-1289
Canada I-IaNA (1984) The Western Arctic Claim, The Inuvialuit Final Agreement. Ottawa: Indian Affairs and Northern Development:115
Carey AG, Jr. (1976) The distribution, abundance, diversity and productivity of the western Beaufort Sea benthos. Environmental Assessment of the Alaskan Continental Shelf, Annual Reports of Principal Investigators for the Year Ending March 1977 vol VI Receptors – Fish, Littoral, Benthos, Book 6
Carey AG, Jr. (1978) The distribution, abundance, diversity and productivity of the western Beaufort Sea benthos. Environmental Assessment of the Alaskan Continental Shelf, Annual Reports, Book 4
Carey AG, Jr. (1991) Ecology of North American Arctic continental shelf benthos: a review. Continental Shelf Research 11:865-883
Carey AG, Jr., Ruff R (1977) Ecological studies of the benthos in the Western Beaufort Sea with special reference to molluscs. In: Dunbar M (ed) Polar Oceans Arctic Institute of North America, Calgary, Canada
Carey AG, Scott PH, Walters KR (1984) Distributional ecology of shallow south-western Beaufort Sea (Arctic Ocean) bivalve Mollusca. Marine Ecology Progress Series 17:125-134
Carmack EC, Macdonald RW, Jasper S (2004) Phytoplankton productivity on the Canadian Shelf of the Beaufort Sea. Marine Ecology Progress Series 277:37-50
Carothers C, Cotton S, Moerlein K (2013) Subsistence use and knowledge of salmon in Barrow and Nuiqsut, Alaska. University of Alaska, Coastal Marine Institute
Ceh J, Gonzalez J, Pacheco AS, Riascos JM (2015) The elusive life cycle of scyphozoan jellyfish – metagenesis revisited. Scientific Reports 5:12037
Centre BAD (2010) HadISST 1.1 - Global sea-ice coverage and SST (1870-present). Chiperzak DB, Hopky GE, Lawrence MJ (1991) Fish catch data from the landfast ice of the Mackenzie
River Estuary, March 1985, and May 1986, 1987. Canadian Data Report of Fisheries and Aquatic Sciences Report 847:1-35
93
Chouinard GA, Hurlbut TR (2011) An atlas of the January distribution of selected marine fish species in the Cabot Strait from 1994 to 1997. Fisheries and Oceans Canada, Canadian Technical Report of Fisheries and Aquatic Sciences
Christman CL, Citta JJ, Quakenbush LT, Clarke JT, Rone BK, Shea RA, Ferguson MC, Heide-Jørgensen MP (2013) Presence and behavior of bowhead whales (Balaena mysticetus) in the Alaskan Beaufort Sea in July 2011. Polar Biol 36:1851-1856
Chugunkov DI (1970) Pinipedia of Kamchatcka. Priroda 6 Clark CW, Ellison WT (1998) Numbers and distribution of bowhead whales, Balaena mysticetus, based
on the 1985 acoustic study of Pt. Barrow, Alaska. Report for the International Whaling Commission 38:365-370
Clarke JT, Christman CL, BRower AA, Ferguson MC (2013) Distribution and relative abundance of marine mammals in the northeastern Chukchi and western Beaufort Seas, 2012. Annual Report, National Marine Mammal Laboratory, Alaska Fisheries Science Center, National Marine Fisheries Service, National Oceanic and Atmospheric Administration, Bureau of Ocean Energy Management
Cleater H, Smith TG (1984) Vocal behaviour and distribution of bearded seals, Erignathus barbatus, in Amundsen Gulf and along western Banks Island, Northwest Territories. Report prepared for Dome Petroleum Limited and Gulf Canada Resources Inc, and the Polar Continental Shelf Project, Department of Energy, Mines and Resources
Coad BW, Reist JD (2004) Annotated list of the arctic marine fishes of Canada. Canadian Manuscript Reports of Fisheries and Aquatic Sciences 2674:iv:+112
Cobb D, Fast H, Papst MH, Rosenberg D, Rutherford R, Sareault JE (2008) Beaufort Sea Large Ocean Management Area (LOMA): Ecosystem overview and assessment report.
Cohen DM, Inada T, Iwamoto T, Scialabba N (1990) FAO species catalogue. Vol. 10. Gadiform fishes of the world (Order Gadiformes), Vol 125. FAO Fisheries Synopsis, Rome
Conn PB, McClintock BT, Cameron MF, Johnson DS, Moreland EE, Boveng PL (2013) Accommodating species identification errors in transect surveys. Ecology 94:2607-2618
Conn Paul B, Ver Hoef Jay M, McClintock Brett T, Moreland Erin E, London Josh M, Cameron Michael F, Dahle Shawn P, Boveng Peter L (2014) Estimating multispecies abundance using automated detection systems: ice-associated seals in the Bering Sea. Methods Ecol Evol 5:1280-1293
COSEWIC (2002) COSEWIC assessment and update status report on the polar bear Ursus maritimus in Canada. Committee on the Status of Endangered Wildlife in Canada
COSEWIC (2005) COSEWIC assessment and update status report on the bowhead whale Balaena mysticetus, Bering-Chukchi-Beaufort population and Eastern Canada-West Greenland population, in Canada.vii-51
COSEWIC (2008) COSEWIC assessment and update status report on the polar bear Ursus maritimus in Canada. Committee on the Status of Endangered Wildlife in Canada
COSEWIC (2009) COSEWIC assessment and update status report on the bowhead whale Balaena mysticetus, Bering-Chukchi-Beaufort population and Eastern Canada-West Greenland population, in Canada.
Cotton S (2012) Subsistence salmon fishing in Beaufort Sea communities. Master's, University of Alaska Fairbanks, Fairbanks, Alaska
Coyle KO, Gillispie JG, Smith RL, Barber WE (1994) Food habits of four demersal Chukchi Sea fishes. In: Barber WE, Smith RL, Weingartner TJ (eds) Fisheries oceanography of the northeast Chukchi Sea, Final Report. Alaska OCS Region
Craig PC, Griffiths WB, Haldorson L, McElderry H (1982) Ecological Studies of Arctic Cod ( Boreogadus saida ) in Beaufort Sea Coastal Waters, Alaska. Can J Fish Aquat Sci 39:395-406
94
Crawford JA, Frost KJ, Quakenbush LT, Whiting A (2011) Different habitat use strategies by subadult and adult ringed seals (Phoca hispida) in the Bering and Chukchi seas. Polar Biol 35:241-255
Darnis G, Barber DG, Fortier L (2008) Sea ice and the onshore–offshore gradient in pre-winter zooplankton assemblages in southeastern Beaufort Sea. Journal of Marine Systems 74:994-1011
Dau CP, Larned WW (2005) Aerial population survey of common eiders and other waterbirds in near shore waters and along barrier islands of the Arctic Coastal Plain of Alaska, 24-27 June 2005. USFWS-Migratory Bird Management:1-19
Dau CP, Larned WW (2008) Aerial population survey of common eiders and other waterbirds in near shore waters and along barrier islands of the Arctic Coastal Plain of Alaska, 24-26 June 2008. USFWS-Migratory Bird Management:1-21
Dearborn JH, Hendler G, Edwards KC (1996) The diet of Ophiosparte gigas (Echinodermata: Ophiuroidea) along the Antarctic Peninsula, with comments on its taxonomic status. Polar Biology 16:309-320
Derocher AE, Garner GW, Lunn NJ, Wiig Ø (1998) Polar bears: Proceedings of the twelfth working meeting of the IUCN/SSC Polar Bear Specialist Group. IUCN, Gland, Switzerland and Cambridge, UK.
DFO (1991) Annual summary of fish and marine mammal harvest data for the Northwest Territories, 1988-1989. Book 1. Department of Fisheries and Ocean
DFO (1992a) Annual summary of fish and marine mammal harvest data for the Northwest Territories, 1989-1990. Department of Fisheries and Ocean
DFO (1992b) Annual summary of fish and marine mammal harvest data for the Northwest Territories, 1990-1991. Book 3. Department of Fisheries and Ocean
DFO (1993) Annual summary of fish and marine mammal harvest data for the Northwest Territories, 1991-1992. Book 4. Department of Fisheries and Ocean
DFO (1994) Annual summary of fish and marine mammal harvest data for the Northwest Territories, 1992-1993. Book 5. Department of Fisheries and Ocean
DFO (1995) Annual summary of fish and marine mammal harvest data for the Northwest Territories, 1993-1994. Book 6. Department of Fisheries and Ocean
DFO (1996) Annual summary of fish and marine mammal harvest data for the Northwest Territories, 1994-1995. Book 7. Department of Fisheries and Ocean
DFO (1997) Annual summary of fish and marine mammal harvest data for the Northwest Territories, 1995-1996. Book 8. Department of Fisheries and Ocean
DFO (1999a) Annual summary of fish and marine mammal harvest data for the Northwest Territories, 1996-1997. Book 9. Department of Fisheries and Ocean
DFO (1999b) Hornaday River Arctic Charr. DFO Stock Status Report DFO (2000) Department of Fisheries and Ocean, Eastern Beaufort Sea beluga whales. Stock Status
Report. Department of Fisheries and Ocean DFO (2002) Department of Fisheries and Ocean, Beluga. Underwater World Series. Department of
Fisheries and Ocean Divoky GJ, Lukacs PM, Druckenmiller ML (2015) Effects of recent decreases in arctic sea ice on an ice-
associated marine bird. Progress in Oceanography 136:151-161 Dunbar MJ, Acreman JC (1980) Standing crops and species composition of diatoms in sea ice From
Robeson Channel to the Gulf of St. Lawrence. Ophelia 19:61-72 Dunton KH, Reimnitz E, Schonberg S (1982) An Arctic Kelp Community in the Alaskan Beaufort Sea. Arctic
35 Dunton KH, Schell DM (1987) Dependence of consumers on macroalgal (Laminaria solidungula) carbon
in an arctic kelp community: ?13C evidence. Marine Biology 93:615-625
95
Dunton KH, Weingartner T, Carmack EC (2006) The nearshore western Beaufort Sea ecosystem: Circulation and importance of terrestrial carbon in arctic coastal food webs. Progress in Oceanography 71:362-378
Duval WS Proceedings of a workshop on Beaufort Sea beluga: February 3-6, 1992. Environmental Studies Research Funds Report No. 123.
Elvin SS (2014) The large marine ecosystem approach to assessment and management of polar bears during climate change. Environmental Development 11:67-83
Ennis GP (1969) The biology of the shorthorn sculpin Myoxocephalus scorpius (L.) in Newfoundland waters. Memorial University of Newfoundland,
EPD (2001) Animal weights and their food and water requirements. Environmental Protection Division, Ministry of Environment
Estes JA, Gol'tsev VN (1984) Abundance and distribution of the Pacific walrus (Odobenus rosmarus divergens): results of the first Soviet American joint aerial survey, autumn 1975. In: Fay FH, Fedoseev GA (eds) Soviet American Cooperative Research on Marine Mammals, vol 1, Pinnipeds
Evans DO, Loftus DH (1987) Colonization of inland lakes in the great lakes region by rainbow smelt, osmerus mordax: their freshwater niche and effects on indigenous fishes. Can J Fish Aquat Sci 44:s249-s266
Fauchald K, Jumars PA (1979) The diet of worms: a study of polychaete feeding guilds. Oceanography Mar Biol Ann Rev 17:193-284
Fay FH (1974) The role of ice in the ecology of marine mammals of the Bering Sea. In: Hood DW, Kelly EJ (eds) Oceanography of the Bering Sea, Book 2. University of Alaska Fairbanks, Inst. Mar. Sci. Occas. , Fairbanks, Alaska
Fay FH (1982) Ecology and biology of the pacific walrus, odobenus rosmarus divergens Illiger. North American Fauna 74:1-279
Fedorov VV, Chereshnev IA, Nazarkin MV, Shestakov AV, Volobuev VV (2003) Catalog of marine and freswater fishes of the northern part of the Sea of Okhotsk. Dalnauka, Vladivostok
Fedoseev GA (1984) Present status of the population of walruses (Odobenus rosmarus) in the eastern Arctic and Bearing Sea. In: Rodin VE, Perlov AS, Berzin AA, Gavrilov NS, Shevchenko NS, Fadeev NS, Kucheriavenko EB (eds) Marine mammals of the far East, Pacific Fisheries Research Center, Vladivostok, RF
Ferguson SH, Stirling I, McLoughlin P (2005) Climate change and ringed seal (phoca hispida) recruitment in western Hudson Bay. Marine Mammal Sci 21:121-135
Finley KJ, Bradstreet MSW, Miller GW (1990) Summer feeding ecology of harp seals (Phoca groenlandica) in relation to arctic cod (Boreogadus saida) in the Canadian high arctic. Polar Biol 10:609-618
Finley KJ, Evans CR (1983) Summer diet of the bearded seal (Erignathus barbatus) in the Canadian High Arctic. Arctic 36
Fischer JB, Larned WW (2004) Summer distribution of marine birds in the western Beaufort Sea. Arctic 57
Fissel D, Cross W, Howland K (2013) An Ecological and oceanographic assessment of the Beaufort Sea region: evaluation of the risks associated with ballast water exchange. DFO Can. Sci. Advis. Sec. Res.
Forest A, Galindo V, Darnis G, Pineault S, Lalande C, Tremblay JE, Fortier L (2010) Carbon biomass, elemental ratios (C:N) and stable isotopic composition ( 13C, 15N) of dominant calanoid copepods during the winter-to-summer transition in the Amundsen Gulf (Arctic Ocean). Journal of Plankton Research 33:161-178
96
Forest A, Stemmann L, Picheral M, Burdorf L, Robert D, Fortier L, Babin M (2012) Size distribution of particles and zooplankton across the shelf-basin system in southeast Beaufort Sea: combined results from an Underwater Vision Profiler and vertical net tows. Biogeosciences 9:1301-1320
Forsyth A (1985) Mammals of the Canadian wild. Camden House Publishing Limited Fraker MA (1980) Status and harvest of the Mackenzie stock of white whales (Delphinapterus leucas).
Rep Int Whaling Comm 30:451-458 Fraker MA, Bockstoce J (1980) Summer distribution of bowhead whales in the eastern Beaufort Sea. Mar
Fish Rev:57-64 Fraker MA, Gordon CD, McDonald JW, Ford JKB, Cambers G (1979) White whale (Delphinapterus leucas)
distribution and abundance and the relationship to physical and chemical characteristics of the Mackenzie Estuary. . Fisheries and Marine Service Technical Report
Fratt DB, Dearborn JH (1984) Feeding biology of the Antarctic brittle star Ophionotus victoriae (Echinodermata: Ophiuroidea). Polar Biol 3:127-139
Fredrickson LH, Heitmeyer ME (1991) Life history strategies and habitat needs of the Northern Pintail. Waterfowl Management Handbook, Book 13.1.3, United States Geological Survey
Frost KJ (1985) The ringed seal (Phoca hispida). In: Burns JJ, Frost KJ, Lowry LF (eds) Marine Mammals Species Accounts. Alaska Department Fish and Game, Juneau, AK
Frost KJ (1999) Harvest report: Statewide summary for western Alaska beluga stocks, 1994-1998. Alaska beluga whale committee report 99-4, Fairbanks, AK
Frost KJ (2003) Harvest report: statewide summary for the western Alaska Beluga stocks, 1998-2002. Alaska Beluga Whale Committee Report 03-2
Frost KJ, Karpovich S (2008) Gray whale. Alaska Department of Fish and Game Frost KJ, Lowry LF (1981) Foods and trophic relationships of cetaceans in the Bering Sea. In: Hood DW,
Calder JA (eds) The eastern Bering Sea shelf: oceanography and resources, Book 2. University of Washington Press, Seattle, WA
Frost KJ, Lowry LF (1983) Demersal fishes and invertebrates trawled in the Northeastern Chukchi and western Beaufort Seas, 1976-77. U.S. Department of Commerce, National Oceanic and Atmospheric Administration, National Marine Fisheries Service
Frost KJ, Lowry LF (1984) Trophic relationships of vertebrate consumers in the Alaskan Beaufort Sea. In: Barnes PW, Schell DM, Reimnitz E (eds) The Alaskan Beaufort Sea - Ecosystems and Environments. Academic Press, Inc., New York, NY
Frost KJ, Lowry LF, Pendleton G, Nute HR (2002) Monitoring distribution and abundance of ringed seals in the northern Alaska. Final report from the Alaska Department of Fish and Game, Juneau, AK, for US Minerals Management Service, Anchorage, AK
Frost KJ, Lowry LF, Pendleton G, Nute HR (2004) Factors affecting the observed densities of ringed seals, Phoca hispida, in the Alaskan Beaufort Sea, 1996-99. Arctic 57
Frost KJ, Suydam R (2010) Subsistence harvest of beluga or white whales (Delphinapterus leucas) in northern and western Alaska, 1987-2006. Journal of Cetacean Research and Management 11:293-299
Fuller AS, George JC (1997) Evaluation of subsistence harvest data for the North Slope Borough 1993 census for eight North Slope villages: for the calendar year 1992. Barrow: North Slope Borough, Department of Wildlife Management
Fuller WA (1955) The inconnu (Stenodus leucichthys mackenziei) in Great Slave Lake and adjoining waters. J Fish Res Bd Can 12:768-780
George JC, Moulton L, Johnson M (2009) A field guide to the common fishes of the North Slope of Alaska. North Slope Borough, Department of Wildlife
George JC, Zeh J, Suydam R, Clark C (2002) Population size of the Bering-Chukchi-Beaufort Seas stock of bowhead whales, Balaena mysticetus, based on the 2001 census off point Barrow, Alaska.
97
George JCC, Zeh J, Suydam R, Clark C (2004) Abundance and population trend (1978-2001) of western Arctic bowhead whales surveyed near Barrow, Alaska. Marine Mammal Sci 20:755-773
Ghan D, Sprules WG (1993) Diet, prey selection, and growth of larval and juvenile burbot Lota lota (L.). Journal of Fish Biology 42:47-64
Gilbert JR, Fedoseev G, Seagars D, Razlivalov E, Lachugin A (1992) Aerial census of Pacific walrus. United States Fish and Wildlife Service, Anchorage, AK
Givens GH, Edmondson SL, George JC, Suydam R, Charif RA, Rahaman A, Hawthorne D, Tudor B, DeLong RA, Clark CW (2013) Estimate of the 2011 abundance of the Bering-Chukchi-Beaufort Seas bowhead whale population. Presented to the 65th International Whaling Commission
Gjøsæter H (1998) The population biology and exploitation of capelin ( Mallotus villosus ) in the barents sea. Sarsia 83:453-496
Gleason JS, Rode KD (2009) Polar bear distribution and habitat association reflect long-term changes in fall sea ice conditions in the Alaskan Beaufort Sea. Arctic 62
Gol'tsev VN (1971) Feeding of the harbor seal. Ecologiya 52:62-70 Gormezano LJ, Rockwell RF (2013a) Dietary composition and spatial patterns of polar bear foraging on
land in western Hudson Bay. BMC Ecol 13:51 Gormezano LJ, Rockwell RF (2013b) What to eat now? Shifts in polar bear diet during the ice-free season
in western Hudson Bay. Ecol Evol:n/a-n/a Gosselin M, Levasseur M, Wheeler PA, Horner RA, Booth BC (1997) New measurements of
phytoplankton and ice algal production in the Arctic Ocean. Deep Sea Research Part II: Topical Studies in Oceanography 44:1623-1644
Grainger EH (1979) Primary production in Frobisher Bay, Arctic Canada. In: Dunbar MJ (ed) Primary production mechanisms. Cambridge University Press, Programme 20
Gurevich VS (1980) Worldwide distribution and migration patterns of the white whale (beluga), Delphinapterus leucas. Rep Int Whal Comm 30:465-480
Haberman KL, Ross RM, Quetin LB (2003) Diet of the Antarctic krill (Euphausia superba Dana): II. Selective grazing in mixed phytoplankton assemblages. Journal of Experimental Marine Biology and Ecology 283:97-113
Haddock SHD (2007) Comparative feeding behavior of planktonic ctenophores. Integrative and Comparative Biology 47:847-853
Haldorson L, Craig P (1984) Life History and Ecology of a Pacific-Arctic Population of Rainbow Smelt in Coastal Waters of the Beaufort Sea. Transactions of the American Fisheries Society 113:33-38
Hammill MO, Smith TG (1989) Factors affecting the distribution and abundance of ringed seal structures in Barrow Strait, Northwest Territories. Can J Zool 67:2212-2219
Harwood LA, Auld JC, Joynt A, Moore SE (2010) Distribution of bowhead whales in the SE Beaufort Sea during late summer, 2007-2009. DFO Can Sci Advis Sec Res Doc 2009/111:iv + 22
Harwood LA, Iacozza J, Auld JC, Norton P, Loseto L (2014) Belugas in the Mackenzie River estuary, NT, Canada: Habitat use and hot spots in the Tarium Niryutait Marine Protected Area. Ocean & Coastal Management 100:128-138
Harwood LA, Innes S, Norton P, Kingsley MCS (1996) Distribution and abundance of beluga whales in the Mackenzie estuary, southeast Beaufort Sea, and west Amundsen Gulf during late July 1992. Journal canadien des sciences halieutiques et aquatiques 53:2262-2273
Harwood LA, Norton P, Day B, Hall PA (2002) The harvest of beluga whales in Canada’s western Arctic: Hunter-based monitoring of the size and composition of the catch. Arctic 55
Harwood LA, Pokiak F, Larsen-Walker J (2008) Assessment of the subsistence fishery and biological data for the Arctic cisco in Tuktoyaktuk Harbour, NT, Canada, 1997-1999. Canadian Manuscript Report of Fisheries and Aquatic Sciences. Central and Arctic Region Fisheries and Oceans Canada
98
Harwood LA, Smith TG (2002) Whales of the Inuvialuit Settlement region in Canada's Western Arctic: An overview and outlook. Arctic 55
Harwood LA, Smith TG, Auld JC (2012) Fall migration of ringed seals (Phoca hispida) through the Beaufort and Chukchi Seas, 2001–02. Arctic 65
Harwood LA, Smith TG, George JC, Sandstrom SJ, Walkusz W, Divoky GJ (2015) Change in the Beaufort Sea ecosystem: Diverging trends in body condition and/or production in five marine vertebrate species. Progress in Oceanography 136:263-273
Hawkins AJS, Smith RFM, Bayne BL, Héral M (1996) Novel observations underlying the fast growth of suspension-feeding shellfish in turbid environments:Mytilus edulis. Marine Ecology Progress Series 131:179-190
Hazard KW (1988) Beluga whale, Delphinapterus leucas. In: Lentfer JW (ed) Selected marine mammals of Alaska Species accounts with research and management recommendations. Marine Mammal Commission, Washington, D. C.
Heath W, Thomas D (1984) The impact of gravel dredging on benthos near Banks Island, Northwest Territories, 1981 and 1983. Technical Report, Calgary, Alberta
Hedeholm R, Grønkjær P, Rysgaard S (2012) Feeding ecology of capelin (Mallotus villosus Müller) in West Greenland waters. Polar Biol 35:1533-1543
Hills S, Gilbert JR (1994) Detecting Pacific walrus population trends with aerial surveys: a review. Transactions North American Wildlife and Natural Resource Conference
Hipfner JM, Galbraith M (2013) Spatial and temporal variation in the diet of the Pacific sand lance Ammodytes hexapterus in waters off the coast of British Columbia, Canada. Journal of Fish Biology 83:1094-1111
Hobson KA, Welch HE (1992) Determination of trophic relationships within a high Arctic marine food web using δ13C and δ15N analysis. Marine Ecology Progress Series 84:9-18
Hoekstra PF, O'Hara TM, Fisk AT, Borgå K, Solomon KR, Muir DCG (2003) Trophic transfer of persistent organochlorine contaminants (OCs) within an Arctic marine food web from the southern Beaufort–Chukchi Seas. Environmental Pollution 124:509-522
Holst M, Stirling I, Hobson KA (2001) Diet of ringed seals (Phoca hispida) on the east and west sides of the north water polynya, northern Baffin Bay. Marine Mammal Sci 17:888-908
Homer R (1980) Beaufort Sea plankton studies. Environmental Assessment of the Alaskan Continental Shelf, Final Report of Principal Investigators. Bureau of Land Management, U.S. Department of Interior, and National Oceanic and Atmospheric Administration, Office of Marine Pollution Assessment, U.S. Department of Commerce, Boulder, CO
Homer R, Schrader GC (1981) Beaufort Sea plankton studies: winter-spring studies in Stefansson Sound off Narwhal Island. Environmental Assessment of the Alaskan Continental Shelf, Final Report of Principal Investigators. Bureau of Land Management, U.S. Department of Interior, and National Oceanic and Atmospheric Administration, Office of Marine Pollution Assessment, U.S. Department of Commerce, Boulder, CO
Hopky GE, Lawrence MJ, Chiperzak DB (1994a) Data on the meio-and macrobenthos, and related bottom sediment from Tuktoyaktuk Harbour and Mason Bay, N.W.T., March, 1985 to 1988. Canadian Data Report of Fisheries and Aquatic Sciences 939:297
Hopky GE, Lawrence MJ, Chiperzak DB (1994b) NOGAP B2; Zooplankton data from the Canadian Beaufort Sea shelf, 1984 and 1985. Canadian Data Report of Fisheries and Aquatic Sciences 922:iv + 164
Hopky GE, Lawrence MJ, Chiperzak DB (1994c) NOGAP B2; Zooplankton Data from the Canadian Beaufort Sea Shelf, 1987 and 1988. Canadian Data Report of Fisheries and Aquatic Sciences 912:219
99
Hopky GE, Lawrence MJ, Chiperzak DB, Region A (1994d) NOGAP B2; Zooplankton Data from the Canadian Beaufort Sea Shelf, 1986. Canadian Data Report of Fisheries and Aquatic Sciences 923:225
Hornby CA, Hoover C, Iacozza J, Barber DG, Loseto LL (2016) Spring conditions and habitat use of beluga whales (Delphinapterus leucas) during arrival to the Mackenzie River Estuary. Polar Biol
Horner R, Murphy D (1985) Species composition and abundance of zooplankton in the nearshore Beaufort Sea in winter-spring. Arctic 38
Horner R, Schrader GC (1982) Relative contributions of ice algae, phytoplankton, and benthic microalgae to primary production in nearshore regions of the Beaufort Sea. Arctic 35
Houston J (1990) Status of the Fourhorn Sculpin, Mvoxocephalus quadricornis, in Canada. Canadian Field-Naturalist 104:7-13
Howell KL, Pond DW, Billett DSM, Tyler PA (2003) Feeding ecology of deep-sea seastars (Echinodermata: Asteroidea): a fatty-acid biomarker approach. Marine Ecology Progress Series 255:193-206
Hrabik TR, Magnuson JJ, McLain AS (1998) Predicting the effects of rainbow smelt on native fishes in small lakes: evidence from long-term research on two lakes. Journal canadien des sciences halieutiques et aquatiques 55:1364-1371
Hsiao SIC (1980) Quantitative composition, distribution, community structure and standing stock of sea ice microalgae in the Canadian Arctic. Arctic 33
Hsiao SIC, Foy MG, Kittle DW (1977) Standing stock, community structure, species composition, distribution, and primary production of natural populations of phytoplankton in the southern Beaufort Sea. Can J Bot 55:685-694
Huelsbeck DR (1988) Whaling in the pre-contact economy of the central northwest coast. Arctic Anthropology 25:1-15
Hulley PA (1990) Myctophidae. In: Quero JC, Hureau JC, Karrer C, Post A, Saldanha L (eds) Check-list of the fishes of the eastern tropical Atlantic (CLOFETA), Book 1. JNICT, Lisbon; SEI; Paris; and UNESCO, Paris
Hunter CM, Caswell H, Runge MC, Regehr EV, Amstrup SC, Stirling I (2007) Polar bears in the southern Beaufort Sea II: Demography and population growth in relation to sea ice conditions. Administrative Report. US Geological Survey
Ice-Seal-Committee (2014) The subsistence harvest of ice seals in Alaska – a compilation of existing information, 1960-2012. A report of the Ice Seal Committee
Iles DT, Peterson SL, Gormezano LJ, Koons DN, Rockwell RF (2013) Terrestrial predation by polar bears: not just a wild goose chase. Polar Biol 36:1373-1379
Irvine JR, Macdonald RW, Brown RJ, Godbout L, Reist JD, Carmack EC (2009) Salmon in the Arctic and how they avoid lethal low temperatures. North Pacific Anadromous Fish Commission Bulletin 5:39-50
Johnson A, Burns J, Dusenberry W, Jones R (1982) Aerial survey of Pacific walrus, 1980. United States Fish and Wildlife Service, Denver Wildlife Research Center, Anchorage, AK
Johnson SW, Neff AD, Thedinga JF, Lindeberg MR, Maselko JM (2012) Atlas of nearshore fishes of Alaska: A synthesis of marine surveys from 1998 to 2011. U.S. Department of Commerce
Johnson SW, Thedinga JF, Neff AD (2009) Invasion by saffron cod Eleginus gracilis into nearshore habitats of Prince William Sound, Alaska, USA. Marine Ecology Progress Series 389:203-212
Johnson SW, Thedinga JF, Neff AD, Hoffman CA (2010) Fish fauna in nearshore waters of a barrier island in the western Beaufort Sea, Alaska. U.S. Department of Commerce, National Oceanic and Atmospheric Administration, National Marine Fisheries Service, Alaska Fisheries Science Center
Joint-Secretariat (2003) Inuvialuit harvest study, data methods report 1988-1997. Joint Secretariat, Inuvik, NWT
100
Juul-Pedersen T, Michel C, Gosselin M, Seuthe L (2008) Seasonal changes in the sinking export of particulate material under first-year sea ice on the Mackenzie Shelf (western Canadian Arctic). Marine Ecology Progress Series 353:13-25
Kang SH, Hang JS, Lee S, Chung KH, Kim D, Park MG (2001) Antarctic phytoplankton assemblages in the marginal ice zone of the northwestern Weddell Sea. Journal of Plankton Research 23:333-352
Karasiuk DJ, Birch GJ, Slaney TL, McPhail JD (1993) Aquatic resources of Northern Yukon National Park. In: analysis NYNPrda (ed) Canadian Parks Service, Book RM Report 93-01/NP. Natural Resource Conservation Section, Canadian Parks Service, Prairie and Northern Region, Winnipeg
Kelly BP (1988) Ringed seal, Phoca hispida. In: Lentfer JW (ed) Selected marine mammals of Alaska: Species accounts with research and management recommendations. Marine Mammal Commission, Washington, D. C.
Kelly BP, Badajos OH, Kunnasranta M, Moran JR, Martinez-Bakker M, Wartzok D, Boveng P (2010) Seasonal home ranges and fidelity to breeding sites among ringed seals. Polar Biol 33:1095-1109
King JE (1983) Seals of the World, London Kingsley MCS (1984) The abundance of ringed seals in the Beaufort Sea and Amundsen Gulf, 1983. Book
1778. Canadian Manuscript Report of Fisheries and Aquatic Sciences Kishigami N (2013) Aboriginal subsistence whaling in Barrow, Alaska. Senri Ethnological Studies 84:101-
120 Kleinenberg SE, Yablokov AV, Tarasevich MN, Belkovich BM (1964) Beluga (Delphinapterus leucas):
Investigation of the species. Book 1923. Translated from Russian in 1969 by Israel Program for Scientific Translations, Jerusalem
Kogl DR (1971) Monitoring and evaluation of Arctic waters with emphasis on the North Slope drainages: Colville River study. Book 12. Alaska Department of Fish and Game, Federal Aid for Fisheries Restoration
Koski WR, George JC, Sheffield G, Galginaitis MS (2005) Subsistence harvests of bowhead whales (Balaena mysticetus) at Kaktovik, Alaska (1973-2000). Journal of Cetacean Research and Management 7:33-37
Koski WR, Miller GW (2009) Habitat use by different size classes of bowhead whales in the Central Beaufort Sea during late summer and autumn. Arctic 62
Kottelat M, Freyhof J (2007) Handbook of European freshwater fishes. Publications Kottelat, Cornol and Freyhof, Berlin
Kovacs KM (2002) Bearded Seal (Erignathus barbatus). In: Perrin WF, Würsig B, Thewissen JGW (eds) The Encyclopedia of Marine Mammals. Academic Press, San Diego
Lacho G (1986) Analysis of Arctic cod stomach contents from the Beaufort Shelf, July and September, 1984. Canadian Data Report of Fisheries and Aquatic Sciences No 614. Central and Arctic Region, Department of Fisheries and Oceans
Lacho G (1991) Stomach content analyses of fishes from Tuktoyaktuk Harbour, NWT, 1981. Canadian Data Report of Fisheries and Aquatic Sciences No 853. Central and Arctic Region, Department of Fisheries and Oceans
Lee SH, Schell DM, McDonald TL, Richardson WJ (2005) Regional and seasonal feeding by bowhead whales Balaena mysticetus as indicated by stable isotope ratios. Marine Ecology Progress Series 285:271-287
Leonardsson K, Bengtsson Å, Linnér J (1988) Size-selective predation by fourhorn sculpin, Myoxocephalus quadricornis (L.) (Pisces) on Mesidotea entomon (L.) (Crustacea, Isopoda). Hydrobiologia 164:213-220
Lischka S, Knickmeier K, Hagen W (2001) Mesozooplankton assemblages in the shallow Arctic Laptev Sea in summer 1993 and autumn 1995. Polar Biology 24:186-199
101
Llinás L, Pickart RS, Mathis JT, Smith SL (2008) The effects of eddy transport on zooplankton biomass and community composition in the western Arctic. University of Miami,
Logerwell E, Rand K (2010) Beaufort Sea marine fish monitoring 2008: pilot survey and test of hypotheses (final report). Alaska Fisheries Science Center, NOAA National Marine Fisheries Service, Prepared for Minerals Management Service, U.S. Department of the Interior
LOMA (2005) Marine ecosystem overview of the Beaufort Sea Large Ocean Management Area (LOMA). North/South Consultants Inc., Inuvialuit Cultural Resource Centre
Loo L-O, Rosenberg R (1989) Bivalve suspension-feeding dynamics and benthic-pelagic coupling in an eutrophicated marine bay. Journal of Experimental Marine Biology and Ecology 130:253-276
Loseto LL, Stern GA, Connelly TL, Deibel D, Gemmill B, Prokopowicz A, Fortier L, Ferguson SH (2009) Summer diet of beluga whales inferred by fatty acid analysis of the eastern Beaufort Sea food web. Journal of Experimental Marine Biology and Ecology 374:12-18
Lowry LF (1985) The belukha whale (Delphinapterus leucas). In: Burns JJ, Frost KJ, Lowry LF (eds) Marine mammal species accounts, Book 7. Alaska Department of Fish and Game, Technical Bulletin
Lowry LF, Burkanov VN, Frost KJ, Simpkins MA, Springer A, DeMaster DP, Suydam R (2000) Habitat use and habitat selection by spotted seals (Phoca largha) in the Bering Sea. Canadian Journal of Zoology 78:1959-1971
Lowry LF, Burns JJ, Frost KJ (1989) Recent harvests of belukha whales, Delphinapterus leucas, in western and northern Alaska and their potential impact on provisional management stocks. Rep Int Whal Comm 39:335-339
Lowry LF, Frost KJ, Burns JJ (1980) Feeding of bearded seals in the Bering and Chukchi Seas and trophic interaction with Pacific walruses. Arctic 33
Lowry LF, Frost KJ, Burns JJ (1987) Food of ringed seals and bowhead whales near Point Barrow Alaska. The Canadian Field Naturalist 92:67-70
Lowry LF, Frost KJ, Seaman GA (1985) Investigations of Beluhka whales in coastal waters of western and northern Alaska. III. Food habits.
Lowry LF, Sheffield G, George JC (2004) Bowhead whale feeding in the Alaskan Beaufort Sea, based on stomach contents analysis. Journal of Cetacean Research Management 6:215-223
Lunn NJ, Schliebe S, Born EW (2002) Polar Bears: Proceedings of the 13th Working Meeting of the IUCN/SSC Polar Bear Specialist Group, Nuuk, Greenland. In: Lunn NJ, Schliebe S, Born EW (eds). IUCN, Gland, Switzerland and Cambridge, UK
MacCracken JG (2012) Pacific Walrus and climate change: observations and predictions. Ecol Evol 2:2072-2090
Macdonald RW, Wong CS, Erickson PE (1987) The distribution of nutrients in the southeastern Beaufort Sea: Implications for water circulation and primary production. J Geophys Res 92:2939
Majewski AR, Reist JD, Sareault JE (2006) Fish catch data from offshore sites in the Mackenzie River Estuary and Beaufort Sea during the open water season, August 2004 aboard the CCGS Nahidik. Book 2771. Canadian Manuscript Report of Fisheries and Aquatic Sciences
Matheke GEM, Horner R (1974) Primary productivity of the benthic microalga in the Chukchi Sea near Barrow, Alaska. Journal of Fisheries Research Board of Canada 31:1779-1786
McClintock JB (1994) Trophic biology of Antarctic shallow-water echinoderms. Marine Ecology Progress Series 111:191-202
McLaren IA (1958) The biology of the ringed seal (Phoca hispida Schreber) in the eastern Canadian Arctic. Bulletin of the Fisheries Research Board of Canada 118
McLaughlin F, Carmack E, Brien MO, Bacle J, Gatien G, Tuele D, White L, Moody G, Balsom A, Corkum M (2009) Physical and chemical data from the Beaufort Sea and western Canadian Arctic archipelago, September 2 to 16, 2000. Canadian Data Report of Hydrography and Ocean Sciences 180
102
Mecklenburg CW, Mecklenburg TA, Thorsteinson LK (2002) Fishes of Alaska. American Fisheries Society, Bethesda, MD
Meuter FJ, Reist JD, Majewski AR, Sawatzky CD, Christiansen JS, Hedges KJ, Coad BW, Karamushko OV, Lauth RR, Lynghammar A, MacPhee SA, Mecklenburg CW (2013) Marine fishes of the Arctic. Arctic Report Card
Mikhail MY, Welch HE (1989) Biology of Greenland cod, Gadus ogac, at Saqvaqjuac, northwest coast of Hudson Bay. Environ Biol Fish 26:49-62
Moore SE, George JCC, Sheffield G, Bacon J, Ashjian CJ (2010) Bowhead whale distribution and feeding near Barrow, Alaska, in late summer 2005–06. Arctic 63
Moore SE, Reeves RR (1993) Distribution and movement. In: Burns JJ, Montague JJ, Cowles CJ (eds) The bowhead whale, Book Special Publication No. 2. Society for Marine Mammalogy
Morin R, Dodson JJ, Power G (1981) The migrations of anadromous cisco (Coregonus artedii) and lake whitefish (C . clupeaformis) in estuaries of eastern James Bay. Can J Zool 59:1600-1607
Morrow JE (1980) The freshwater fishes of Alaska. University of. B.C. Animal Resources Ecology Library Muus B, Salomonsen F, Vibe C (1990) Grønlands fauna (Fisk, Fugle, Pattedyr). Gyldendalske Boghandel,
Nordisk Forlag A/S København:464 NAEC (2015) Proposed polar bear critical habitat: Polar bear den locations (USGS 1910-2007). North
Alaska Environmental Center NAMMCO (2005) The beluga whale. The North Atlantic Marine Mammal Commission Nelson CH, Phillips RL, McRea J, Jr., Barber JH, Jr., McLaughlin MW, Chin JL (1994) Gray whale and pacific
walrus benthic feeding grounds and sea floor interaction in the Chukchi Sea. United States Geological Survey, Technical Report for Minerals Management Service
NG (2015) Canvasback (Aythya valisineria). National Geographic, Animals, Birds Nikol'skii GV (1961) Special Ichthyology Moscow, 1954. Translated from the Russian by J. I. Lengy and Z.
Krauthamer, Israel Program for Scientific Translations, Vol 43. Cambridge University Press (CUP), Jerusalem
NOAA (2013) Gray whale (Eschrichtius robustus): Eastern North Pacific Stock. National Oceanic and Atmospheric Administration stock assessment report
Noel LE, Johnson SR, O'Doherty GM, Butcher MK (2005) Common eider (Somateria mollissima v-nigrum) nest cover and depredation on central Alaskan Beaufort Sea barrier islands. Arctic 58:129-136
Norcross BL, Hardy S, Hopcroft R, Iken K, Majewski AR, Wedemeyer K (2017) Beaufort Sea transboundary (US-Canada) fish, lower trophic and food web survey 2012-2014 final results.
Norcross BL, Raborn SW, Holladay BA, Gallaway BJ, Crawford ST, Priest JT, Edenfield LE, Meyer R (2013) Northeastern Chukchi Sea demersal fishes and associated environmental characteristics, 2009–2010. Continental Shelf Research 67:77-95
Ognetov GN (1981) Studies on the ecology and taxonomy of the white whale (Delphinapterus leucas Pall. 1776) inhabiting the Soviet Arctic. Rep Int Whaling Commn 31:515-520
Orejas C, Gili J, López-González P, Arntz W (2001) Feeding strategies and diet composition of four Antarctic cnidarian species. Polar Biology 24:620-627
Orlova EL, Rudneva GB, Renaud PE, Eiane K, Savinov V, Yurko AS (2010) Climate impacts on feeding and condition of capelin Mallotus villosus in the Barents Sea: Evidence and mechanisms from a data set spanning 30 years. Aquat Biol
Ornithology CLo (2015a) All About Birds: Green-winged teal. Accessed 28-June-2015. https://www.allaboutbirds.org/guide/Green-winged_Teal/lifehistory
Ornithology CLo (2015b) All About Birds: Northern shoveler. Accessed 28-June-2015. https://www.allaboutbirds.org/guide/Northern_Shoveler/lifehistory
Ornithology CLo (2015c) All About Birds: Snowy owl. Accessed 28-June-2015. https://www.allaboutbirds.org/guide/Snowy_Owl/lifehistory
103
Outridge PM, Hobson KA, Savelle J (2009) Long-term changes of mercury levels in ringed seal (Phoca hispida) from Amundsen Gulf, and beluga (Delphinapterus leucas) from the Beaufort Sea, western Canadian Arctic. Science of The Total Environment 407:6044-6051
Paetkau D, Amstrup SC, Born EW, Calvert W, Derocher AE, Garner GW, Messier F, Stirling I, Taylor MK, Wiig O, Strobeck C (1999) Genetic structure of the world's polar bear populations. Molecular Ecology 8:1571-1584
Page LM, Burr BM (1991) A field guide to freshwater fishes of North America north of Mexico. Houghton Mifflin Company, Boston, MA
Patterson A (1974) Subsistence harvests in five native regions. Joint Federal-State Land Use Planning Commission for Alaska, Anchorage, Alaska
Pauly D, Christensen V (1995) Primary production required to sustain global fisheries. Nature 374:255-257
Peacock E, Derocher AE, Lunn NJ, Obbard ME (2010) Polar Bear Ecology and Management in Hudson Bay in the Face of Climate Change. A Little Less Arctic. Springer Science + Business Media
Peck LS, Barnes DKA, Willmott J (2005) Responses to extreme seasonality in food supply: diet plasticity in Antarctic brachiopods. Marine Biology 147:453-463
Pedersen S (1990) Assessment of the 1988-89 Kaktovik subsistence fishery. Internal report to US Fish and Wildlife Service under Cooperative agreement No 14-16-0007-88-7744. Subsistence Division, Alaska Department of Fish and Game, Anchorage, Alaska
Piepenburg D, Archambault P, Ambrose WG, Blanchard AL, Bluhm BA, Carroll ML, Conlan KE, Cusson M, Feder HM, Grebmeier JM, Jewett SC, Lévesque M, Petryashev VV, Sejr MK, Sirenko BI, Włodarska-Kowalczuk M (2010) Towards a pan-Arctic inventory of the species diversity of the macro- and megabenthic fauna of the Arctic shelf seas. Mar Biodiv 41:51-70
Pirtle JL, Meuter FJ (2011) Beaufort Sea fish and their trophic linkages: literature search and synthesis. School of Fisheries and Ocean Sciences report prepared for the Bureau of Ocean Energy Management, Regulation and Enforcement
Pomerleau C, Ferguson SH, Walkusz W (2010) Stomach contents of bowhead whales (Balaena mysticetus) from four locations in the Canadian Arctic. Polar Biol 34:615-620
Porsild AE (1945) Mammals of the Mackenzie Delta. The Canadian Field-Naturalist 59:4-22 Powell AN, Phillips L, Rexstad EA, Taylor EJ (2005) Importance of the Alaskan Beaufort Sea to king eiders
(Somateria spectabilis). Purcell JE (1991) A review of cnidarians and ctenophores feeding on competitors in the plankton.
Hydrobiologia 216-217:335-342 Purcell JE, Sturdevant MV (2001) Prey selection and dietary overlap among zooplanktivorous jellyfish
and juvenile fishes in Prince William Sound, Alaska. Marine Ecology Progress Series 210:67-83 Quakenbush LT, Citta JJ, Crawford J (2011) Biology of the bearded seal (Erignathus barbatus) in Alaska,
1961-2009. National Marine Fisheries Service Quakenbush LT, Citta JJ, George JC, Heide-Jørgensen MP, Small RJ, Brower H, Harwood LA, Adams B,
Brower L, Tagarook G, Pokiak C, Pokiak J (2012) Seasonal movements of the Bering-Chukchi-Beaufort stock of bowhead whales: 2006–2011 satellite telemetry results. International Whaling Commission Science Report
Quakenbush LT, Small RJ, Citta JJ (2010) Satellite tracking of Western Arctic bowhead whales. Unpublished report submitted to the Bureau of Ocean Energy Management, Regulation and Enforcement
Rand KM, Logerwell EA (2010) The first demersal trawl survey of benthic fish and invertebrates in the Beaufort Sea since the late 1970s. Polar Biol 34:475-488
Reeves RR (2002) The origins and character of 'aboriginal subsistence' whaling: a global review. Mammal Review 32:71-106
104
Regehr E, Amstrup S, Stirling I (2006) Polar Bear Population Status in the southern Beaufort Sea. U.S. Geological Survey
Richard P (2002) Beluga. Fisheries and Oceans Canada Richard PR, Martin AR, Orr JR (2001) Summer and autumn movements of belugas of the eastern
Beaufort Sea stock. Arctic 54 Riedel A, Michel C, Gosselin M, LeBlanc B (2007) Enrichment of nutrients, exopolymeric substances and
microorganisms in newly formed sea ice on the Mackenzie shelf. Marine Ecology Progress Series 342:55-67
Riedel A, Michel C, Gosselin M, LeBlanc B (2008) Winter–spring dynamics in sea-ice carbon cycling in the coastal Arctic Ocean. Journal of Marine Systems 74:918-932
Rugh DJ, Fraker MA (1981) Gray whale (Eschrichtius robustus) sightings in eastern Beaufort Sea. Arctic 34
Rugh DJ, Shelden KEW, Withrow DE (1995) Spotted seal sightings in Alaska 1992-93: Final Report. Annual report to the MMPA Assessment Program, Office of Protected Resources, NMFS, NOAA, 1335 East-West Highway, Silver Spring, MD 20910
Sauriau P-G, Kang C-K (2000) Stable isotope evidence of benthic microalgae-based growth and secondary production in the suspension feeder Cerastoderma edule (Mollusca, Bivalvia) in the Marennes-Oléron Bay. Island, Ocean and Deep-Sea Biology. Springer Science + Business Media
Schell DM, Saupe SM, Haubenstock N (1989) Bowhead whale (Balaena mysticetus) growth and feeding as estimated by δ13C techniques. Mar Biol 103:433-443
Schell DM, Ziemann PJ, Parrish DM, Dunton KH, Brown EJ (1982) Foodweb and nutrient dynamics in nearshore Alaska Beaufort Sea waters. Final Report, Outer Continental Shelf Environmental Assessment Program. Institute of Water Resources, University of Alaska
Schliebe S, Rode KD, Gleason JS, Wilder J, Proffitt K, Evans TJ, Miller S (2008) Effects of sea ice extent and food availability on spatial and temporal distribution of polar bears during the fall open-water period in the Southern Beaufort Sea. Polar Biol 31:999-1010
Schmidt DR, McMillan RO, Gallaway BJ (1983) Nearshore fish survey in the western Beaufort Sea Harrison Bay to Elson Lagoon. Final Report, Outer Continental Shelf Environmental Assessment Program, Research Unit 631
Schweder T, Sadykova D, Rugh D, Koski W (2010) Population estimates from aerial photographic surveys of naturally and variably marked bowhead whales. Journal of Agricultural, Biological, and Environmental Statistics 15:1-19
Scott C, Falk-Petersen S, Gulliksen B, Lønne O-J, Sargent J (2001) Lipid indicators of the diet of the sympagic amphipod Gammarus wilkitzkii in the Marginal Ice Zone and in open waters of Svalbard (Arctic). Polar Biology 24:572-576
Scott WB, Scott MG (1988) Atlantic fishes of Canada. Canadian Bulletin of Fisheries and Aquatic Sciences 219:731
Secretariat J (2015) Inuvialuit and Nanuq: A polar bear traditional knowledge study. Joint Secretariat, Inuvialuit Settlement Region
Sergeant DE (1973) Biology of white whales (Delphinapterus leucas) in western Hudson Bay. J Fish Res Bd Can 30:1065-1090
Sergeeva VM, Sukhanova IN, Flint MV, Pautova LA, Grebmeier JM, Cooper LW (2010) Phytoplankton community in the Western Arctic in July–August 2003. Oceanology 50:184-197
Seymour J, Horstmann-Dehn L, Wooller MJ (2014) Inter-annual variability in the proportional contribution of higher trophic levels to the diet of Pacific walruses. Polar Biol 37:597-609
Shaughnessy PD, Fay FH (1977) A review of the taxonomy and nomenclature of North Pacific harbour seals. Journal of Zoology 182:385-419
105
Sheffield G, Fay FH, Feder H, Kelly BP (2001) Laboratory digestion of prey and interpretation of walrus stomach contents. Marine Mammal Sci 17:310-330
Sheffield G, Grebmeier JM (2009) Pacific walrus (Odobenus rosmarus divergens): Differential prey digestion and diet. Marine Mammal Science 25:761-777
Shelden KEW (1994) Beluga whales (Delphinapterus leucas) in Cook Inlet - A review. In: Withrow DE, Shelden KEW, Rugh DJ (eds) Beluga whale (Delphinapterus leucas) distribution and abundance in Cook Inlet, summer 1993. Annual report to the MMPA Assessment Program, Office of Protected Resources, NMFS, NOAA, 1335 East-West Highway, Silver Spring, MD 20910
Sherr EB, Sherr BF, Hartz AJ (2009) Microzooplankton grazing impact in the Western Arctic Ocean. Deep Sea Research Part II: Topical Studies in Oceanography 56:1264-1273
Simpkins MA, Hiruki-Raring LM, Sheffield G, Grebmeier JM, Bengtson JL (2003) Habitat selection by ice-associated pinnipeds near St. Lawrence Island, Alaska in March 2001. Polar Biology 26:577-586
Smith TG (1981) Notes on the bearded seal, Erignathus barbatus, in the Canadian Arctic. Canadian Technical Report of Fisheries and Aquatic Sciences 102:58
Smith TG (1987) The ringed seal, Phoca hispida, of the Canadian Western Arctic. Canadian Bulletin of Fisheries and Aquatic Sciences 216
Smith TG, Martin AR (1994) Distribution and Movements of Belugas, Delphinapterus leucas, in the Canadian High Arctic. Can J Fish Aquat Sci 51:1653-1663
Speckman SG, Chernook VI, Burn DM, Udevitz MS, Kochnev AA, Vasilev A, Jay CV, Lisovsky A, Fischbach AS, Benter RB (2010) Results and evaluation of a survey to estimate Pacific walrus population size, 20061. Marine Mammal Science 27:514-553
Stephenson SA (2004) Harvest studies in the Inuvialuit Settlement Region, Northwest Territories, Canada: 1999 and 2001-2003. Canadian Manuscript Report of Fisheries and Aquatic Sciences 2700:41
Stewart DB (2006) Update COSEWIC status report bearded seal Erignathus barbatus (Erxleben, 1777). Committee on the Status of Endangered Wildlife in Canada, Technical Report July
Stewart DB, Mochnacz NJ, Reist JD, Carmichael TJ, Sawatzky CD (2007) Fish diets and food webs in the Northwest Territories : Arctic grayling (Thymallus arcticus) Book 2796. Canadian Manuscript Report of Fisheries and Aquatic Sciences
Stirling I (1974) An overwintering walrus in the Beaufort Sea. Murrelet 55:40-41 Stirling I (2002) Polar bears and seals in the eastern Beaufort Sea and Amundsen Gulf: A synthesis of
population trends and ecological relationships over three decades. Arctic 55 Stirling I, Archibald R, DeMaster D (1975) The distribution and abundance of seals in the eastern
Beaufort Sea. Department of the Environment, Victoria, B.C. Stirling I, Archibald WR, DeMaster D (1977) Distribution and abundance of seals in the eastern Beaufort
Sea. J Fish Res Bd Can 34:976-988 Stirling I, Kingsley M, Calvert W (1982) The distribution and abundance of seals in the eastern Beaufort
Sea, 1974‐79. Environment Canada, Canadian Wildlife Service, Edmonton, Canada Stirling I, McDonald TL, Richardson ES, Regehr EV, Amstrup SC (2011) Polar bear population status in the
northern Beaufort Sea, Canada, 1971–2006. Ecological Applications 21:859-876 Stirling I, Parkinson CL (2006) Possible effects of climate warming on selected populations of polar bears
(Ursus maritimus) in the Canadian Arctic. Arctic 59:261-275 Stirling I, Richardson E, Thiemann GW, Derocher AE (2008) Unusual predation attempts of polar bears on
ringed seals in the southern Beaufort Sea : Possible significance of changing spring ice conditions. Arctic 61:14-22
Strong T (1989) eported harvests of narwhal, beluga and walrus in the Northwest Territories, 1948–1987. Canadian Data Report of Fisheries and Aquatic Sciences, Book 734. Department of Fisheries and Oceans, Winnipeg: Western Region
106
Süfke L, Piepenburg D, von Dorrien CF (1998) Body size, sex ratio and diet composition of Arctogadus glacialis (Peters, 1874) (Pisces: Gadidae) in the Northeast Water Polynya (Greenland). Polar Biology 20:357-363
Sukhanova IN, Flint MV, Pautova LA, Stockwell DA, Grebmeier JM, Sergeeva VM (2009) Phytoplankton of the western Arctic in the spring and summer of 2002: Structure and seasonal changes. Deep Sea Research Part II: Topical Studies in Oceanography 56:1223-1236
Sullivan BK, Reeve MR (1982) Comparison of estimates of the predatory impact of ctenophores by two independent techniques. Marine Biology 68:61-65
Suydam RS, George JC (2004) Subsistence harvest of bowhead whales (Balaena mysticetus) by Alaska Eskimos, 1974 to 2003. Report to the International Whaling Commission
Suydam RS, George JC (2012) Preliminary analysis of subsistence harvest data concerning bowhead whales (Balaena mysticetus) taken by Alaska Natives, 1974 – 2011. Report to the International Whaling Commission
Suydam RS, George JC, Hanns C, Sheffield G (2005) Subsistence harvest of bowhead whales (Balaena mysticetus) by Alaska Eskimos during 2004. Report to the International Whaling Commission
Suydam RS, George JC, Hanns C, Sheffield G (2006) Subsistence harvest of bowhead whales (Balaena mysticetus) by Alaska Eskimos during 2005. Report to the International Whaling Commission
Suydam RS, George JC, Person B, Hanns C, Sheffield G (2011) Subsistence harvest of bowhead whales (Balaena mysticetus) by Alaskan Eskimos during 2010. Presented to the International Whaling Commission Scientific Committee
Suydam RS, George JC, Rosa C, Person B, Hanns C, Sheffield G (2010) Subsistence harvest of bowhead whales (Balaena mysticetus) by Alaskan Eskimos during 2009. Unpublished report submitted to the International Whaling Commission
Suydam RS, George JC, Rosa C, Person B, Hanns C, Sheffield G, Bacon JJ (2007) Subsistence harvest of bowhead whales (Balaena mysticetus) by Alaska Eskimos during 2006. Report to the International Whaling Commission
Suydam RS, George JC, Rosa C, Person B, Hanns C, Sheffield G, Bacon JJ (2008) Subsistence harvest of bowhead whales (Balaena mysticetus) by Alaskan Eskimos during 2007. Unpublished Report to the International Whaling Commission
Suydam RS, George JC, Rosa C, Person B, Hanns C, Sheffield G, Bacon JJ (2009) Subsistence harvest of bowhead whales (Balaena mysticetus) by Alaskan Eskimos during 2008. Unpublished report submitted tot he International Whaling Commission
Thorsteinson LK, Jarvela LE, Hale DA (1991) Arctic fish habitat use investigations: nearshore studies in the Alaskan Beaufort Sea, summer 1990. National Oceanic and Atmospheric Administration
Tokranov AM (2007) Distribution and some biological features of the Pacific sand lance Ammodytes hexapterus (Ammodytidae) in waters off Kamchatka in the Sea of Okhotsk. J Ichthyol 47:288-295
Trites AW, Pauly D (1998) Estimating mean body masses of marine mammals from maximum body lengths. Can J Zool 76:886-896
Udevitz MS, Gilbert JR, Fedoseev GA (2001) Comparison of methods used to estimate numbers of walruses on sea ice. Marine Mammal Sci 17:601-616
Vanderklift MA, Ponsard S (2003) Sources of variation in consumer-diet ?15N enrichment: a meta-analysis. Oecologia 136:169-182
Vilhjálmsson H (2002) Capelin (Mallotus villosus) in the Iceland–East Greenland–Jan Mayen ecosystem. ICES Journal of Marine Science 59:870-883
Vladykov VD (1946) Études sur les mammifères aquatiques. IV. Dép. Pêch. Pro. Qué. Wacasey JW (1975) Biological productivity of the southern Beaufort Sea: zoobenthic studies. Arctic
Biological Station, Beaufort Sea Project
107
Wacasey JW, Atkinson EG, Derick L, Weinstein A (1977) Zoobenthos data from the southern Beaufort Sea 1971-1975.
Wade PR, Angliss R (1997) Guidelines for assessing marine mammal stocks: report of the GAMMS workshop April 3-5, 1996, Seattle, Washington. U.S. Department of Commerce
Wailes GH (1936) Food of Clupea pallasii in Southern British Columbia Waters. Journal of the Biological Board of Canada 1:477-486
Walker RJ, Andersen DB, Brown L (1988) Community profile database catalog, Volume 3. Arctic and Interior Alaska Regions, Alaska Department of Fish and Game Division of Subsistence, Anchorage, Alaska
Walkusz W, Paulić JE, Kwaśniewski S, Williams WJ, Wong S, Papst MH (2010) Distribution, diversity and biomass of summer zooplankton from the coastal Canadian Beaufort Sea. Polar Biology 33:321-335
Walkusz W, Paulic JE, Williams WJ, Kwasniewski S, Papst MH (2011) Distribution and diet of larval and juvenile Arctic cod (Boreogadus saida) in the shallow Canadian Beaufort Sea. Journal of Marine Systems 84:78-84
Walkusz W, Paulie JE, Papst MH, Kwaśniewski S, Chiba S, Crawford RE (2008) Zooplankton and ichtyoplankton data collected from the Chukchi and Beaufort Seas during the R/V Mirai Cruise, September 2002. Central and Arctic Region Canadina Data Report of Fisheries and Aquatic Sciences
Watts PD, Draper BA (1986) Note on the Behavior of Beluga Whales Feeding on Capelin. Arctic and Alpine Research 18:439
Weaver PA (1991) The 1987 beluga (Delphinapterus leucas) harvest in the Mackenzie River Estuary, NWT. Book 2097. Canadian Manuscript Report of Fisheries and Aquatic Sciences, Winnipeg: Central and Arctic Region
Welch HE, Crawford RE, Hop H (1993) Occurrence of Arctic cod (Boreogadus saida) schools and their vulnerability to predation in the Canadian high arctic. Arctic 46
Whitehouse GA (2013) Preliminary mass-balance food web model of the Eastern Chukchi Sea. NOAA Technical Memorandum
Whitehouse GA, Aydin KY (2016) Trophic structure of the Eastern Chukchi Sea: An updated mass balance food web model. NOAA Technical Memorandum
Wiig Ø, Born E, Garner EW (1995) Polar bears: Proceedings of the 11th working meeting of the WCN/SSC Polar Bear Specialist Group. lUCN, Gland, Switzerland and Cambridge, UK
Wilce RT, Dunton KH (2014) The Boulder Patch (North Alaska, Beaufort Sea) and its benthic algal flora. Arctic 67:43
Wolfe RJ, Utermohle CJ (2000) Wild food consumption rate estimates for rural Alaska populations. Alaska Department of Fish and Game, Division Subsistence
Zeh JE, Punt AE (2005) Updated 1978-2001 abundance estimates and their correlations for the Bering-Chukchi-Beaufort Seas stock of bowhead whales. Journal of Cetacean Research and Management 7:169-175
Zeh JE, Raftery AE (1996) Population assessment methods for the bowhead whale, Balaena mysticetus, and 1994 bowhead assessment results.
