Open access

Ecosystem structure and function of the North Water Polynya

Publication: Arctic Science
14 August 2024

Abstract

The North Water Polynya is one of the most productive Arctic regions on Earth, sustaining the world's northernmost Inuit communities for millennia. The polynya is a large and persistent region of open water surrounded by sea ice and exhibits high primary productivity, is a biodiversity hotspot, and is a key habitat and migration corridor for Arctic species. Many aspects of the ecosystem structure and the role of resident species in the North Water Polynya remain uncertain. To shed light on these, we developed the first representation of the North Water Polynya food web using the Ecopath modelling framework. Modelled trophic flows indicated that pelagic and benthic communities were primarily connected by Age 1+ Arctic cod (Boreogadus saida), walrus (Odobenus rosmarus), and ringed seal (Pusa hispida). Large copepods, Age 1+ Arctic cod, and bivalves were key prey species. Overall productivity in the North Water Polynya was higher compared to Western Baffin Bay and Western Greenland, corroborating expectations of relatively high productivity within the polynya. This model provides a baseline description of the North Water Polynya ecosystem structure and function prior to future climate-driven food web changes and the emergence of large-scale commercial fisheries.

1. Introduction

Polynyas are large open water areas surrounded by sea ice in polar oceans that provide important grounds for feeding, mating, spawning, and over-wintering for many Arctic species (Stirling 1980; Barber et al. 2001). The North Water Polynya (Kalaallisut: Pikialasorsuaq; Inuktitut: Sarvarjuaq), located in northern Baffin Bay (Fig. 1), is the largest and most biologically productive polynya north of the Arctic Circle. For millennia, it has sustained the world's northernmost Inuit communities and several key Arctic species, including Arctic cod (Boreogadus saida), beluga whales (Delphinapterus leucas), narwhals (Monodon monoceros), Atlantic walrus (Odobenus rosmarus), and polar bears (Ursus maritmus) (Ribeiro et al. 2021; Buchart et al. 2022).
Fig. 1.
Fig. 1. Overview of the study area, representing the maximum, open water extent of the North Water Polynya. Base map created with Natural Earth (www.naturalearthdata.com).
As is the case for other Arctic ecosystems, many aspects about ecosystem structure, food web dynamics, and the role of resident species in the North Water Polynya remain uncertain. In addition, recent observations suggest that the North Water Polynya ecosystem is already being negatively impacted by climate change (Niemi et al. 2019; Ribeiro et al. 2021). Warmer waters are causing the annual ice bridge that blocks ice transport farther south and contributes to creation of the polynya in the Nares Strait (narrow channel between Greenland and Ellesmere Island) to form later and more inconsistently (Moore et al. 2021). Without a stable ice bridge, ice transport down the channel into the area of the North Water Polynya increases and prevents or delays the annual formation of the polynya (Moore et al. 2021). If this trend continues, the role of the polynya as an early food basket for migratory and resident species could be diminished. Assessing the current food web dynamics of the North Water Polynya ecosystem is thus critical to evaluate ecosystem resilience and potential repercussions for surrounding Inuit communities in a rapidly changing climate.
Inuit communities in the northern Baffin Bay region in both Canada and Greenland (Fig. 1) depend on the North Water Polynya for their livelihoods and for cultural and spiritual well-being (Pikialasorsuaq Commission 2017). The high biodiversity provides a critical hunting ground for marine mammals, fish, and sea birds, which in turn provide resources for food, clothing, and tools (Pikialasorsuaq Commission 2017). In addition, the ice bridge north of the polynya is considered the earliest migration route between Canada and Greenland, as it provides an access route for transportation (Pikialasorsuaq Commission 2017). While the Inuit relationship to the North Water Polynya is threatened by climate change, it also exhibits increasing exploitation potential of resources such as oil and gas (Pikialasorsuaq Commission 2017; Tai et al. 2019).
Marine ecosystem models are tools that can be used to assess ecosystem dynamics and evaluate responses to changing environmental conditions (Colléter et al. 2015; Bryndum-Buchholz et al. 2019; Lotze et al. 2019). Over the past two decades, ecosystem models have been developed for various Arctic coastal and shelf ecosystems, including West Greenland (Pedersen and Zeller 2001), Western Baffin Bay (Pedro et al. 2023), Beaufort Sea shelf (Hoover et al. 2013a, 2021; Sora et al. 2022), Lancaster Sound region (Mohammed 2007), and Eastern Chukchi Sea (Whitehouse et al. 2014), using the Ecopath with Ecosim (EwE) modelling framework (Christensen et al. 2005). EwE models describe ecosystem structure and function, and can be used as a baseline for future refinement and applications. Applications include (i) review and summarize scientific knowledge available and identify data gaps (e.g., Pedersen and Zeller 2001; Whitehouse et al. 2014; Pedro et al. 2023); (ii) describe ecological dynamics to support marine conservation efforts (e.g., Hoover et al. 2013b; Sora et al. 2022); and (iii) produce ecological indicators to assess ecosystem-wide impacts of climate change and harvesting.
Here, we describe the first ecosystem model using the EwE framework to explore food web relationships within the North Water Polynya representing the spring to fall period. The necessary data gathering of life histories and feeding ecology for this model highlighted data gaps and uncertainties for further ecosystem studies and model development.

2. Materials and methods

2.1. The North Water Polynya ecosystem

The North Water Polynya is in northern Baffin Bay, between Ellesmere Island (Canada) and northwest Greenland, connected to Lancaster Sound and Jones Sound in the west, to Kane Basin and the Lincoln Sea in the north, and to central Baffin Bay in the south (Fig. 1). The average depth of the North Water Polynya is 300 m and ranges from 170 to 600 m (Bâcle 2000; Tremblay and Smith 2007). The polynya ecosystem is strongly influenced by season, availability of light, ice breakup, period of open water, and timing of the spring phytoplankton bloom (Hornby et al. 2021). A detailed description of the current understanding of the North Water Polynya ecosystem is given in Hornby et al. (2021) and in the International North Water Polynya Study (e.g., Klein et al. 2002; Ringuette et al. 2002; Tremblay et al. 2002).
The North Water Polynya is one of the most productive Arctic ecosystems (Klein et al. 2002), partly due to the early onset of open water conditions that extends the light exposure of primary producers, leading to an early spring bloom (Lewis et al. 1996; Tremblay et al. 2006). The energy provided by the spring bloom largely accumulates in surface waters, where it is intensely grazed upon by herbivorous zooplankton (e.g., Calanus hyperboreus). It is estimated that only 27% of the particulate primary production during a spring bloom leaves the upper 50 m, of which 1%–7% reaches the benthos, depending on the water depth (Tremblay et al. 2006). Lower trophic level (TL) prey, such as Arctic cod and other meso-zooplankton, play a key role in transferring energy to higher TLs such as seabirds and marine mammals (Hobson et al. 2002).
Defining the exact extent of the North Water Polynya can be challenging due to its dynamic boundaries. Sea-ice melting in the North Water Polynya starts with the return of daylight in the spring in the southeast—due to the influence of the warmer West Greenland Current—and progresses northwest. By May, extensive open water occurs throughout the region (Barber et al. 2001; Barber and Massom 2007), reaching its maximum extent by late June or early July (Dunbar 1969; Barber et al. 2001; Pikialasorsuaq Commission 2017). The North Water Polynya continues to expand until it eventually merges with open water northward from Davis Strait, dissolving the North Water Polynya, and creating a largely open ocean by August (Barber et al. 2001; Preußer et al. 2015). To capture the period of polynya formation, full open water extent, and dissolvement of the polynya, the model represents the time frame from April to October. The study area boundary ranges from 76°–78.5°N to 80.5°–65°W, covering the area of the North Water Polynya, with a size of ∼85 000 km2, representing the peak observed extension of the polynya in 2000 (Moshøj 2015).

2.2. Food web model

EwE version 6.6.8 modelling software was used for ecosystem model development (Walters et al. 1997; Christensen and Walters 2004). Ecopath models are a time-static, mass-balanced “snapshot” of biomass in an ecosystem, represented by functional groups that are linked by feeding interactions for a specific time period. To ensure that the total energy flow between functional groups is balanced, energy production of lower TLs must be able to support the energy demands of higher TLs (Christensen and Walters 2004). Functional groups of the food web are characterized by production and consumption rates and are connected through feeding interactions (eq. 1).
(1)
where Bi = biomass of functional group i; P/B = production per unit of biomass of the functional group i; (Q/B)j = consumption per unit of biomass of the predator j of biomass Bj; DCij = proportion of prey i in the diet of predator j; Yi = exports from the system as fishery catches; Ei = net migration; and EEi = ecotrophic efficiency (the fraction of total production of one functional group that is consumed by other groups) of the functional group i. Losses of energy intake or consumption for each functional group are represented by eq. 2.
(2)
where (R/B)j = respiration rate per unit of biomass and (U/Q)j = fraction of food consumption that is not assimilated. Consumer functional groups are balanced energetically such that consumption for each trophic group is the sum of production, respiration, and unassimilated food (Walters et al. 1997; Christensen and Walters 2004). At least three of the four basic parameters (P/B, Q/B, B, and EE) in the two equations, as well as diet compositions and fisheries catch (and migration if known) must be input directly, while ideally, EE is estimated, as no procedure exists for its field estimation. The model is considered balanced when the EE for each group is between 0 and 1 indicating that there is enough production from prey to support predator consumption. In cases where B, P/B, or Q/B are unknown, EE can be input, forcing the model to estimate the other key parameters (Christensen et al. 2005; Heymans et al. 2016). We considered the model balanced when EE < 1 for all functional groups after passing the pre-balance (PREBAL) diagnostics (Table 3).

2.3. Data sources

EwE classifies the uncertainty in input parameters by a qualitative grading of data quality, referred to as a pedigree (Christensen et al. 2005). To use input parameters with the highest pedigree (Table A1), we defined the model period from 2005 to 2007 based on the following rationale: (i) there are limited data and reports prior and to this time for the ecosystem components considered in this model. Quantitative sampling of species abundance, life history, and distribution in a remote, Arctic region is challenging and historically inconsistent or scarce (Hornby et al. 2021). An overview of data limitations for the marine species found in the North Water Polynya can be found in Hornby et al. (2021). (ii) The 2005–2007 period was chosen as it had the most observations directly available (see Section 2.4). This time period also provides a baseline for comparisons of ecosystem structure and functioning of the North Water Polynya in the future. Therefore, our model is a representation of the average system during this time, for the months April–October. The data pedigree index evaluates overall uncertainty in input parameters of an ecosystem model and gives insight on how much we know about the ecosystem and where uncertainties lie (See Tables A1 and A2 for pedigree classification and index for the model; Christensen et al. 2005).

2.4. Functional groups

We used 20 functional groups to characterize the food web, which were parameterized using qualitative and quantitative studies from the North Water Polynya or other Arctic regions if local data were not available (Tables 1 and A3). Selection of functional groups included species of interest in terms of role in Inuit subsistence and the polynya ecosystem. Where available, biomass (B) was estimated from survey reports and peer-reviewed research for the North Water Polynya. Production to biomass ratios (P/B) values were either calculated using total morality rates (natural mortality rate (M) + fisheries mortality rate (F)) or derived via the life-history tool in FishBase (www.fishbase.org), which combines mortality, parameters of the Bertalanffy growth function, and mean temperature to calculate M (Palomares and Pauly 1998). M estimates were taken from published literature for the North Water Polynya or other Arctic ecosystems. F, if not explicitly available in the literature, was calculated as catch over biomass, based on reported subsistence catches from Canada and Greenland. Consumption to biomass ratios (Q/B) were largely obtained for North Water Polynya taxa when available. In the absence of information from the North Water Polynya, we used estimates of values from the literature or other Ecopath models that were most appropriate to be used for North Water Polynya ecosystem or from other Arctic regions. A diet matrix (Table 2) was constructed based on published diet studies for North Water Polynya taxa, when available. In the absence of diet studies from the North Water Polynya, we used estimates of values from the literature that were the most appropriate to be used for North Water Polynya or similar Arctic species. Details on data sources for each parameter and functional group are in Table A3.
Table 1.
Table 1. Initial parameter estimates before model balancing for North Water Polynya Ecopath model.
Table 2.
Table 2. Diet matrix for the North Water Polynya Ecopath model.
Marine mammals—marine mammals were represented in five functional groups: polar bear, beluga, narwhal, walrus, and ringed seal. Data for the relevant populations or subpopulations were obtained from empirical studies and other Arctic Ecopath models (Tables 1 and A4). Based on the assumption that all marine mammals inhabited the North Water Polynya throughout the model period. To calculate biomass (B), the number of individuals was multiplied by the average weight per individual and divided by the total model area (tonnes/km2). For polar bears, B estimates were based on an average population size of 90 bears (2005–2007) from the Kane Basin subpopulation, which was similar to the estimate of 60 bears for the North Water Polynya based on aerial spring surveys in 2009 and 2010 (Heide-Jørgensen et al. 2013). P/B was calculated using M estimates for the Baffin Bay subpopulation and F for the Kane Basin subpopulation, derived from aerial or capture–recapture data provided by Canadian and Greenland government agencies (York et al. 2016). Q/B estimates for polar bears were derived from an Ecopath model for the Western Baffin Bay (Pedro et al. 2023). B estimates for beluga were based on aerial observations in the spring of 2008–2010, as direct observations for the North Water Polynya were available only for that timeframe. Similarly, B estimates for narwhal relied on aerial observations in the spring of 2009, 2010, and 2014. P/B for belugas considered M from the Beaufort Sea Shelf Ecopath model (Hoover et al. 2021) and F based on North Atlantic Marine Mammal Commission (NAMMCO) catch statistics (NAMMCO 2016). Due to a lack of data for narwhal in the North Water Polynya, we let Ecopath estimate P/B, based on our calculated B, and Q/B and EE estimates from the Western Baffin Bay Ecopath model (Pedro et al. 2023). F for narwhal was based on the annual reported catches for the municipality of Qaanaaq referenced in Heide-Jørgensen et al. (2013). B estimates for walrus were based on aerial survey counts integrated in a Bayesian assessment model (Witting and Born 2005). P/B was calculated accounting for M and F. M of 0.02 year−1 was taken from Witting and Born (2014), who used Bayesian statistical models to calculate M for western Greenland walrus populations, including Baffin Bay and the North Water region. Overall, natural mortality in walruses is considered low, due to low productivity and high longevity (∼40 years) (NAMMCO 2016). F was based on NAMMCO catch statistics, reflecting regional catches by Inughuit walrus hunting for food and walrus ivory (Born 2017; NAMMCO 2018). Q/B estimates for walrus were estimated by an Ecopath model for the Western Baffin Bay (Pedro et al. 2023). B estimates for ringed seal were based on a population model for Baffin Bay and associated waters (Kane Basin, Jones Sound, eastern Lancaster sound, Ungava Bay, and eastern Hudson Strait). Because no direct estimates for the North Water Polynya exist, the population size for the fraction of the study area was calculated, assuming an even distribution in the region. P/B was calculated accounting for M and F. M estimates were derived from an Ecopath model for the Beaufort Sea Shelf (Hoover et al. 2021). F was based on NAMMCO catch statistics (NAMMCO 2016). Q/B estimates for ringed seal was derived from an Ecopath model for the Beaufort Sea Shelf (Hoover et al. 2021).
Seabirds—little auk (Alle alle) represents seabirds in the model. Little auk is a key species in the North Water Polynya ecosystem, exhibiting the largest colony on Earth on the eastern side of the North Water Polynya (Karnovsky and Hunt 2002; Wojczulanis-Jakubas et al. 2022). In future model iterations, additional bird species could be added, such as Ivory Gull (Pagophila eburnea), Thick-billed Murre (Uria lomvia), and Black-legged Kittiwake (Rissa tridactyla). B for little auk was calculated based on population estimates of 66 million birds from aerial video recordings and aerial photographs in the Thule area (eastern North Water Polynya. P/B and Q/B were based on the Ecopath model for the Newfoundland and Labrador Shelf ecosystem (Tam and Bundy 2019). Annual mean harvest between 1998 and 2013 ranged between 7772 and 75 712 birds (Mosbech et al. 2018). To calculate F, we calculated annual mean harvest of 33 971 birds.
Fish—there is limited data on relative abundance of fish, spatial distributions, of most marine life histories, spatial connectivity, and seasonal migrations in the North Water Polynya (Hornby et al. 2021). Fish were divided into two functional groups—Age 1 + Arctic cod (Arctic cod inhabiting waters <100 m representing their benthic–pelagic life stage; Geoffroy et al. 2016) and other fish. We assumed that the other fish group contained fish that are present within the North Water Polynya with different feeding ecology than that of Arctic cod and may represent a food source to higher TLs in the North Water Polynya, including Greenland halibut (Reinhardtius hippoglossoides), Arctic eelpout (Lycodes reticulatus), snailfish (Liparis spp.), and Thorny skate (Amblyraja radiata) (Hornby et al. 2021). B for Arctic cod (Age 1+) was based on biomass estimates from hydroacoustic surveys in the North Water Polynya for 2005–2007 (Herbig et al. 2023). P/B was calculated accounting form M and F. M was derived from the FishBase life-history tool. F was set to 0.0001 year−1 as directed, commercial, and subsistence fisheries for this species are negligible (Steiner et al. 2019; Geoffroy et al. 2023). Q/B was derived from the FishBase life-history tool. For the other fish group, we let Ecopath estimate B by setting EE to 0.85. Because the biomass for this group was unknown during model creation, an assumed EE value of 0.85 indicated that 85% of fish in this group is consumed within the system (Christensen et al. 2005). This assumption is reasonable for a group set to include pelagic, demersal, and benthic species with various predation vulnerabilities (Table A7). P/B and Q/B was derived from published literature values, that make ecological sense for assumed species in this group (Table A3).
Benthic invertebrates—for the benthic invertebrate community, species were aggregated into four functional groups: arthropods, bivalves, echinoderms, and worms. These represent species that are abundant in the North Water Polynya, such as clams, scallops, crabs, polychaetas, and sea stars (Roy et al. 2015a, 2015b; Mäkelä et al. 2017). B estimates for each invertebrate group were provided by the Archambault lab (Pers. comm.) and literature based on trawl surveys in the North Water Polynya in 2013–2015. Therefore, B for all benthic invertebrate groups assumes that the respective biomass does not vary substantially over time. P/B and Q/B for each group were based on other Arctic marine ecosystem models (Table A3), as life-history parameters for the benthic invertebrate groups within the study area were not available.
Zooplankton and ichthyoplankton—copepods are the most important group of zooplankton by biomass in the North Water Polynya (Ringuette et al. 2002). Herbivorous, omnivorous, and carnivorous copepods are all present in the North Water (Hornby et al. 2021). Gelatinous zooplankton are also present in the North Water Polynya and have higher grazing rates than copepods later in summer but were not included due to data limitations (Deibel et al. 2017). Hence, our model represents one hypothesis of how the ecosystem may be structured and provides a basis for future hypothesis testing, including those around gelatinous zooplankton. Zooplankton and ichthyoplankton were represented by four functional groups: large copepods (C. hyperboreus, Calanus glacialis, and Metridia longa), medium copepods (Pseudocalanus spp. and Calanus finmarchicus), other meso-zooplankton, and Arctic cod (Age 0; (Arctic cod inhabiting waters >100 m; Geoffroy et al. 2016), as a key representative for ichthyoplankton in the region. B for large and medium copepods, and other meso-zooplankton were provided by Gérald Darnis (Darnis et al. 2022; Pers. comm.). B for Arctic cod (Age 0) was based on biomass estimates from hydroacoustic and trawl surveys in the North Water Polynya for 2005–2007 (Herbig et al. 2023). P/B ratios for large and medium copepods were taken from the Canadian Beaufort Sea Shelf Ecopath model (Hoover et al. 2021).
P/B Arctic cod (Age 0) was calculated based on daily M estimates from the Chukchi Sea. Q/B for large and medium copepods was initially set to 45 year−1, to allow for a P/Q value of 0.4; EE was set to 0.95 (adapted from Hoover et al. 2021). Q/B for Arctic cod (Age 0) was set to be 105 year−1, based on values for zooplankton <2 mm (Tam and Bundy 2019), assuming a similar diet and a body size of ≤1.6 mm of the sampled Arctic cod (Age 0). We assumed no cannibalism of Arctic cod (Age 0) by Arctic cod (Age 1+) occurred, since current literature from other Arctic regions suggest it to be limited (Walkusz et al. 2013; Majewski et al. 2016). Biomass for the other meso-zooplankton group was unknown during model creation; hence, an assumed EE value of 0.85 was set to indicate that nearly all the species included are consumed within the system. The P/B and Q/B were set to 15 and 60 year−1, higher than the copepod group.
Primary Producers—primary producers are represented by two functional groups, large pelagic producers (>=5 µm) and small pelagic producers (0.7–5 µm). Dry weight biomass values for each size class were converted to wet weight using a conversion factor of 1 gC = 9 g wet weight after Pauly and Christensen (1995). The modelled period (April—October) represents the growth period of phytoplankton in the North Water Polynya (Klein et al. 2002). We did not include ice algae as a separate primary production functional group because grazing impact of ice algae is negligible in early spring and the low standing stock of sea ice meiofauna feeding on ice algae is not considered an important food source for higher TLs in the North Water Polynya (Nozais et al. 2001). B and P/B for both groups were based on biomass and productivity estimates from water samples in the North Water Polynya in Summer–Fall (2005–2007).
Detritus—detritus is represented by two functional groups, pelagic and benthic detritus. The pelagic detritus group represents detritus that is retained within the water column, primarily derived from the spring bloom (large and small pelagic producers) and is a food source for zooplankton (Hoover et al. 2021). The benthic detritus group represents detritus that sinks quickly from the water column, originating primarily from plankton and feeding by benthic invertebrates (Hoover et al. 2021). B for the two detritus groups were based on an Ecopath model for the Beaufort Sea (Hoover et al. 2021), as no estimates exist for the North Water Polynya ecosystem.

2.5. Ecological indicators, network analysis, and SURF index

To assess the ecological position of the functional groups in the North Water Polynya, we constructed a Lindeman spine analysis of trophic flows (after Lindeman 1942) and performed the mixed trophic impact analysis to assess the direct and indirect effects of changes in biomass of one group on the biomass of the other groups within the food web (Christensen et al. 2005). To estimate potential keystone species, we used the index of keystoneness developed by Valls et al. (2015). Here, a keystone species or group is defined as a species or group with a large and broad impact on the food web despite low biomass levels (Power et al. 1996; Valls et al. 2015).
We used summary statistics and network analyses (Finn's cycling index, Finn's mean path length, and mean transfer efficiency (TE)) calculated by Ecopath to get understanding of the North Water Polynya ecosystem functioning. Finn's cycling index indicates the vertical cycling of nutrients or energy in the system before leaving; Finn's mean path length represents the average length of the food chain, and mean trophic TE represents the proportion of mean energy passed between TLs in the food web (see Christensen et al. 2005; Saint-Béat et al. 2018; for details and description of individual Ecopath statistics and network indices). These tools are considered useful for comparing and differentiating ecosystems. Here, we also use these tools to compare the North Water Polynya functioning to the functioning of (i) the Baffin Bay coastal and shelf ecosystem (Pedro et al. 2023); (ii) Lancaster sound (Mohammed 2007); and (iii) Western Greenland (Pedersen and Zeller 2001). This selection was based on the assumption that these regions harbour similar functional groups and be influenced by common oceanographical processes, such as the Baffin Island current and West Greenland current.
To determine species that have a significant impact as prey in the North Water Polynya ecosystems, we calculated the SUpportive Role to Fishery ecosystems index (SURF) after Plagányi and Essington (2014) for consumers (excl. polar bear). This index specifically identifies the level of importance of prey for their predators and adjusts for the overall number of connections in the food web. SURF values closer to zero signify non-key forage species, whereas larger values signify key forage species. If the SURF index exceeds 0.001, the species is classified as a central prey within the ecosystem. The difference between the keystones index by Valls et al. (2015) and the SURF index is that the former is a metric for top-down predation, while the latter is an indicator of bottom-up energy flow.

3. Results

3.1. Model parameters

PREBAL diagnostics revealed that for some functional groups, B, P/B, and Q/B values were underestimated (below slope line; for e.g., other fish, arthropods, medium copepods, and echinoderms) or overestimated (above slope line; for e.g., Arctic cod (Age 0), other meso-zooplankton, and large pelagic producers). These values were within a range of ecologically sensible values and included in the initial model (Heymans et al. 2016). The pedigree index for biomass parameters was between 5 and 6, meaning that the input relied heavily on local samples (Table A1, A2). For the P/Q, Q/B, and diet parameters, the overall pedigree index was between 3 and 4, indicating the input relied heavily on Ecopath models from other Arctic regions, empirical relationships, general knowledge for the same group or species, or qualitative diet composition studies (Tables A1 and A2). Catch parameters had a pedigree index of 4, meaning the data were based on national statistics, indicating a relatively high precision (Tables A1 and A2).

3.2. Model balancing

To achieve mass-balance, parameter adjustments were made to the diet matrix and biomasses of polar bear, beluga, benthic invertebrates, zooplankton groups, and benthic detritus. Adjusted parameters varied between −100% and +100% from initial values (Tables A5 and A6). The largest biomass adjustments were for medium copepods (+1335.7%), followed by bivalves (+450.25%), echinoderms (+303.33%), and worms (+401.09%) (Tables A5 and A6). We considered the adjusted biomass values for the benthic groups (arthropods, bivalves, worms, and echinoderms) ecologically sound, as they are within reported benthic biomass values for the North Water Polynya (Roy et al. 2015a, 2015b; Mäkelä et al. 2017). The adjusted values for medium copepods were considered ecologically sound as they were within the range of Arctic observations and Ecopath estimates for other Arctic models (Hoover et al. 2021).

3.3. Trophic levels and flows

TLs ranged from 1 to 4.83 (Table 3; Fig. 2), with the polar bear group occupying the highest trophic position in the food web, followed by beluga (4.02) and narwhal (4.05) groups. The groups of walrus, ringed seal, little auk, Arctic cod (Age 1+), and other fish had estimated TLs between 3.07 (other fish) and 3.81 (ringed seal). Arthropods, bivalves, echinoderms, worms, zooplankton, and Arctic cod (Age 0) had TLs between 2.06 (Arctic cod Age0) and 2.48 (arthropods). Primary producers and detritus were at the bottom of the food web with TL 1. In general, these estimated TLs agreed with the range of values reported in the literature for the North Water Polynya and other Arctic ecosystems (Table A6). Trophic flows estimated by the model indicated that pelagic and benthic communities were primarily connected by Arctic cod (Age 1+), walrus, and ringed seal (Fig. 2).
Fig. 2.
Fig. 2. Flow diagram for the North Water Polynya ecosystem model. 1 = polar bear, 2 = beluga, 3 = narwhal, 4 = walrus, 5 = ringed seal, 6 = little auk, 7 = Arctic cod (Age 1+), 8 = other fish, 9 = arthropods, 10 = bivalves, 11 = echinoderms, 12 = worms, 13 = large (Lg) copepods, 14 = medium (Med) copepods, 15 = Arctic cod (Age 0), 16 = other meso-zooplankton, 17 = Lg primary producers, 18 = small (Sm) primary producers, 19 = pelagic detritus, 20 = benthic detritus. Circle size is proportional to amount of biomass. Direction of energy flow is represented by position of line with relation to circle: flows positioned on the top of a trophic group indicate biomass outgoing, while flows positioned on the side indicate entering biomass. The weight of the line indicates the amount of energy flowing between nodes. Silhouettes created by PHYLOPIC: https://tinyurl.com/5as9eu3d.
Table 3.
Table 3. Ecopath parameters used in the balanced model representing the North Water Polynya Ecopath model in 2005–2007.
The Lindeman spine analysis indicated that most of the energy flows occurred in the first two TLs. which represented 71.33% of the total system throughput (TST; Fig. 3; 34.72% and 36.61%, respectively). TL2 largely contained large copepods (23.42 t km2), other meso-zooplankton (12.20 t km2), echinoderms (12.10 t km2), and worms (13.78 t km2) (Fig. 3; Table 2), representing 44.64% of the total biomass excluding detritus. Average TE for the North Water Polynya ecosystem was 8.5%, with the highest TE betweenTL2and TL3 (11.3%; Fig. 3).
Fig. 3.
Fig. 3. Lindeman spine of trophic flows (t km2 year−1) in the North Water Polynya ecosystem for 2005–2007. Flows to detritus are recycled though the detritus (D) and primary production (P) compartment at trophic level (TL) I. P: primary producers; D: detritus; TL: trophic level; TE: trophic efficiency; TST: total system throughput.

3.4. Mixed trophic impact

The mixed trophic impact analysis (Fig. 4) revealed that, generally, most functional groups had a negative impact on themselves, reflecting intraspecific competition for resources, and a negative impact on their respective prey due to predation pressure. Other fish, worms, and Arctic cod (Age 0) had very low to no impact on other groups, likely due to their relatively low biomass or Q/B ratios. Other meso-zooplankton negatively impacted all groups, from very low (e.g., impacts on marine mammals and benthic groups) to a high impact on large copepods. Conversely, benthic detritus impacted all other functional groups positively, except the zooplankton groups. Small pelagic producers had the largest positive impact on Arctic cod (Age 0), through their large role as prey for that age group. A similar, positive impact was observed for marine mammals and little auk groups on their respective harvesting. The largest negative impact was observed for little auk affecting Arctic cod (Age 0) through predation and interspecific competition for resources, such as zooplankton.
Fig. 4.
Fig. 4. Mixed trophic impact analysis of the North Water Polynya ecosystem model in 2005−2007. Diagram shows the positive (blue) and negative (red) impact of an increase in the biomass or harvest of the impacting group on the impacted group.

3.5. Keystone functional groups

Based on the Valls et al. (2015) keystoneness index, mid to high TL species dominate top-down control of the North Water Polynya ecosystem. Little auk had the highest ranking, followed by Arctic cod (Age 1+) and arthropods (Fig. 5), indicating their role as a keystone groups. High TL predatory groups, such as polar bear, ringed seal, and narwhal, ranked between 12 and 14, while beluga was an outlier among the higher TL predators, with a group rank of 4 (Fig. 5). Large pelagic producers had the lowest rank, due to their high biomass, followed by walrus and worms (Fig. 5) with the remaining functional groups occupying midrange ranks (Fig. 5).
Fig. 5.
Fig. 5. Keystone values of functional groups by trophic level in the ecosystem of the North Water Polynya. Groups considered keystone have higher ranks, following method by Valls et al. (2015).

3.6. Summary statistics, network analysis, and SURF index

Key ecosystem properties (TST, sum of consumption, exports, production, and total biomass) of the North Water Polynya model were largely comparable to values for the Western Baffin Bay and Western Greenland models, with values estimated for the Lancaster Sound Region being consistently higher across indices (Table 4). The total biomass (excl. detritus) in the North Water Polynya was 137.75 (t km−2 year−1), which is comparable to the Ecopath models for Western Baffin Bay (123.67 t km−2 year−1) and Western Greenland (15 771 t km−2 year−1); however, much lower compared to the estimated biomass in the Lancaster Sound Region (795 t km−2 year−1). The sum of all production within the North Water Polynya was higher than for Western Baffin Bay and Western Greenland and was lower compared to the Lancaster Sound Region.
Table 4.
Table 4. Comparison of the North Water Polynya key indicators with other Arctic ecosystem models in the region.
The system omnivory index for the North Water Polynya was low, indicating a relatively high diet specialization among the individual functional groups (Table 4). This level of diet specialization was similar for the Lancaster Sound Region model, and lower in the Western Baffin Bay and Western Greenland ecosystems (Table 4). Finn's cycling index was the lowest for the North Water Polynya (41%–72% lower than other areas), signifying a shorter cycling of total biomass flowing through the ecosystem compared to the other regions (Finn 1976). As Finn's cycling index indicates the fraction of total system biomass flow recycled in the system before it leaves the system, this result suggests a comparably less stable system, in terms of the specialization and number of components (diversity) in the food web (Christensen 1995). Finn's mean path length was also lowest for the North Water Polynya, highlighting a lower ecosystem stability compared to other ecosystems (Table 4). Mean TE in the North Water Polynya was also the lowest among models (between 38% and 57%; Table 4), highlighting that the ecosystem is more productive but with less energy being transferred to higher TLs.
Total catch within the polynya was lower than estimated for the Western Baffin Bay (180% lower) and Western Greenland (192% lower). However, mean TL of catch was similar, highlighting a high TL of catch within systems of four to five TLs. The high TL of catches across the different regions is driven by subsistence harvesting of marine mammals, such as polar bear, whales, walrus, and seals (Mohammed 2007; Pedersen and Zeller 2001; Pedro et al. 2023), that is imperative for Inuit food sovereignty and security in the region (Kenny et al. 2018). The difference in total catch among the regions can be explained by contrasting fisheries. The West Greenland region is more accessible and exhibits both subsistence and large-scale commercial fishing (inshore and offshore), including lucrative fisheries for Atlantic cod, Atlantic wolffish, Greenland halibut, and northern shrimp (Pedersen and Zeller 2001). In contrast, fisheries in the North Water Polynya, Western Baffin Bay, and Lancaster Sound Region are primarily for subsistence (Mohammed 2007; Hornby et al. 2021; Pedro et al. 2023).
The SURF index was above the threshold of 0.001 that distinguishes key from non-key forage species in a food web for large copepods, Arctic cod (Age 1+), bivalves, other fish, other meso-zooplankton, medium copepods, ringed seal, arthropods, worms, and echinoderms (Fig. 6). Large copepods, Arctic cod (Age 1+), and bivalves showed values at least a magnitude higher than for the other functional groups (Fig. 6). For beluga, Arctic cod (Age 0), walrus, narwhal, and little auk, the SURF index was below the threshold (Fig. 6).
Fig. 6.
Fig. 6. SUpportive Role to Fishery ecosystems index (SURF; after Plagányi and Essington 2014) calculated for prey species in the North Water Polynya food web. SURF index calculations include consumers only; top predators and primary producers were excluded. Dashed blue line represents the threshold (0.001) above which functional groups are considered key prey species in the ecosystem.

4. Discussion

The present Ecopath model is the first description of the food web structure and function of the North Water Polynya ecosystem. Our model revealed that, notably, large copepods, Age 1+ Arctic cod, and bivalves play a key role as forage species in the North Water Polynya. The model also revealed that little auk and Age 1+ Arctic cod are keystone. Overall productivity in the North Water Polynya was higher than for regions in the Western Baffin Bay and Western Greenland, corroborating expectations of high productivity within the polynya compared to other areas in the region. We note that the present model is the first iteration in model development; as more scientific knowledge about the ecology and seasonality of key components of the North Water Polynya food web become available, the model can be updated.

4.1. The North Water Polynya food web

The modelled North Water Polynya food web matches the expected food web structure of an Arctic ecosystem, displaying the central role of a few, mid-TL species that link energy transfer between pelagic and benthic communities, indicating a wasp–waist ecosystem structure (Whitehouse et al. 2014; Murphy et al. 2016; Pedro et al. 2023). The estimated TLs for each functional group were within the range of estimates from other published estimates (Table A7). In the North Water Polynya, those species are Arctic cod (Age 1+) and the key meso-zooplankton species (C. hyperboreus, C. glacialis, and Themisto libellula) (Welch et al. 1992). Notably, because Age 1+ Arctic cod feed on smaller, lipid-rich zooplankton, and Age 1+ Arctic cod represent a key energy conduit for higher TLs, such as ringed seal, narwhal, and beluga whale, which in turn are vital prey for polar bear and target species for Inuit subsistence harvesting (Pikialasorsuaq Commission 2017).
As a keystone group, little auk had a relatively low biomass but high relative impact on other groups. This corroborates the known role of little auks in the North Water Polynya. They arrive in the region after the April phytoplankton bloom and subsequent increase in abundance of large copepods, feeding almost exclusively on copepods and Arctic cod larvae (Karnovsky et al. 2007). This pelagic, secondary production supports the largest little auk breeding colony in the world, comprising 30 million breeding pairs (Egevang et al. 2003; Wojczulanis-Jakubas et al. 2022), and is important for Inughuit food security in Northwest Greenland (Mosbech et al. 2018). Little auks are harvested between May and August to prepare traditional Kiviaq in the Thule area, which is made from whole little auk bodies sown into sealskin bags that ferment for several months (Mosbech et al. 2018).
While our results highlight the expected role of Arctic cod and copepods as key prey in the Arctic, they also highlight the role of other functional groups such as benthic invertebrates and ringed seal as prey in the North Water polynya ecosystem. The role of ringed seal as key prey in the North Water Polynya is likely related to being the main prey of polar bears (73.8%), which is corroborated by a stable isotope study of the North Water Polynya food web, suggesting that polar bears in the region mainly feed on ringed seals (Hobson et al. 2002). The role of benthic invertebrates as key prey is likely due to the dependency of walrus on bivalves (93.5%), echinoderms (4.53%), and worms (0.97%). This high dependency on benthic invertebrates is supported by high benthic biomass in the North Water Polynya (Grebmeier and Barry 2007).
Benthic invertebrates (arthropods, bivalves, worms, and echinoderms) had relatively high biomass within the region and were prey for many other groups. Despite the data limitations for benthic invertebrates in the region, this pattern is assumed ecologically sound for an Arctic polynya ecosystem, known to support rich benthic communities due to strong benthic–pelagic coupling (Grebmeier and Barry 2007). One of the main underlying processes for this pattern is the high primary productivity despite the comparably low TE in the North Water Polynya (which can be >250 g C m−2 year−1; Klein et al. 2002). The early spring bloom does not get heavily grazed by the zooplankton community, allowing new production to reach the seabed and support the benthic community (Grebmeier and Barry 2007). Later in the spring and summer, the production provided by spring bloom largely accumulates in surface waters and is intensely grazed upon by herbivorous zooplankton (e.g., C. hyperboreus), which provide energy transfer to meso-pelagic fish species and marine mammals (Tremblay et al. 2006). Our model has captured the average energy transfer; however, depending on data availability, this seasonal difference in energy transfer could be integrated in future iterations that include temporal dynamics (Christensen et al. 2005).
The characterized food web of the North Water Polynya may have already changed, as the ice bridge in Nares Strait is becoming increasingly unstable and sea ice is thinning, possibly driven by climate warming, and limiting the formation of the polynya (Vincent 2019; Buchart et al. 2022). These changes in the ice regime will increasingly impact oceanographic and biological processes within the North Water Polynya, threatening the ecosystem functioning and structure, as well as Inuit communities on both sides of the polynya (Pikialasorsuaq Commission 2017). For example, the system nurturing spring bloom in the North Water Polynya may advance, due to earlier sea ice retreat and decreasing stratification (Buchart et al. 2022). This change can amplify throughout the food web, as the corresponding grazing by lipid rich and large copepods will be mismatched temporally, leading to overall lower secondary production in the region.

4.2. Model comparison—food web structure and function

The overall high productivity in the North Water Polynya is caused by a combination of (i) low ice cover, (ii) high nutrient input form the northern and southern surface waters, and (iii) favourable wind and upwelling driven mixing events (Tremblay and Smith 2007). While estimated net primary production for the North Water Polynya was higher compared to the Western Baffin Bay and Western Greenland models, it was more than 190% lower than the Lancaster Sound Region model estimate. Two main reasons could explain this variability among estimates: (1) biomass for the two primary producer groups for North Water Polynya are underestimated, as they do not capture the early spring bloom (sampling by Ardyna et al. (2011) took place during late summer 2005, early fall 2006, and fall 2007); (2) biomass data of primary producer for the Lancaster Sound Region model dated from the 1990s and cover a full annual productivity, and includes productivity from ice algae and kelp in addition (Welch et al. 1992; Mohammed 2007).
TE in polar food webs lies between 3.4% and 25.5%, with a mean of 12% (Eddy et al. 2021). TE was slightly above average for the Western Baffin Bay model, and average for the Western Greenland model. In contrast, our TE estimate for the North Water Polynya ecosystem lies below average, suggesting that only ∼8% of primary production is transferred to the top of the food web. This is likely due to the North Water Polynya being a highly productive but less efficient, which is typical for such upwelling systems (Melling et al. 2002). Upwelling near the Greenland coast of relatively warm water prevents the North Water Polynya from freezing completely, which in turn decreases surface stratification and facilitates nutrient (or energy) transfer to the surface (Melling et al. 2002). This estimate is low, given that the polynya is considered the most productive area north of the Arctic circle that supports ample high TL species (Ribeiro et al. 2021; Buchart et al. 2022). Another mechanism that could shape this pattern could be the high seasonal variability in the primary and secondary productivity in the North Water Polynya that may not be fully realized by higher TL predators in this short time frame.
Similarly, Finn's cycling index for the North Water Polynya was 48.7%–79.5% lower compared to Western Baffin Bay and Western Greenland, respectively. Upwelling or pelagic systems, both characterizing the North Water Polynya, tend to exhibit more export and lower levels of energy recycling (Heymans et al. 2014). This may explain the low value for our estimated Finn's cycling index, compared to the other models. Moreover, this index can highlight structural differences among Ecopath models (Heymans et al. 2014). For example, the different index values could reflect the differing structural focus of the North Water Polynya model in contrast to the Western Baffin Bay model. The Western Baffin focuses on representing a microbial loop in terms of bacteria as a separate functional group, leading to higher energy cycling in the system (Pedro et al. 2023) and less export compared to the North Water Polynya model, which represents the function of a microbial loop through the detritus group.
Feeding interactions within the food web, characterized by the Omnivory index in Ecopath, in our model and the Lancaster Sound Region were comparable but a magnitude lower than estimated for Western Baffin Bay and Western Greenland. This indicates a fairly specialized diet among the consumers and relatively high potential for trophic disruptions in the North Water and Lancaster Sound region. The higher Omnivory index for the Western Baffin Bay and Western Greenland systems indicate higher flexibility in feeding relationships and relative stability of the food web. Since those regions have similar key species, a similar Omnivory index is expected. This result could be an artefact of the relatively simple model for the North Water Polynya.
Based on the keystoneness index by Valls et al. (2015), key functional groups reflected the latitudinal gradient of the different Ecopath models compared. The sub-Arctic model (Western Greenland) identified the functional groups of “Atlantic cod” and “other bottom fish” as key species, while the two Arctic models identified marine mammal predators (polar bears and killer whales) and Arctic cod as a key species in the ecosystem. However, seals and toothed whales (either as a group or as single species—killer whales and narwhals) were identified as keystone across all other Arctic Ecopath models.

4.3. Climate change impacts on function and structure of the North Water Polynya ecosystem

With ongoing climate change, structural and functional changes in the North Water Polynya food web can be expected, affecting current levels of productivity and biodiversity (Hornby et al. 2021; Anderson et al. 2023; Geoffroy et al. 2023). For example, climate-driven changes in water temperatures and sea-ice breakup timing are expected to impact the timing of the phytoplankton spring bloom and subsequent secondary production (Hornby et al. 2021). This may lead to a mismatch in predator–prey relationships, such as between the timing of Arctic cod larvae emergence and secondary productivity increase (Søreide et al. 2010). Reduced sea ice cover may facilitate the northward expansion of boreal fish species into the region, potentially intensifying competition with Arctic cod (Fossheim et al. 2015). For example, capelin, which has an unknown role in the current North Water Polynya food web (Coad and Reist 2017; Hornby et al. 2021), may increase in the region in future, competing with Arctic cod (Kyhn and Mosbech 2019). However, the impacts of future climate-driven range shifts on the North Water Polynya ecosystem and food web remains unknown. Nevertheless, it can be expected that the effects of climate change on Arctic cod cascades through the food web, as they play an essential role in maintaining biodiversity, being key prey for marine mammal predators (e.g., ringed seal and beluga whales).
Furthermore, populations of Arctic predators, such as beluga whales and ringed seals may decline due to climate-related environmental changes (Hamilton et al. 2015; O'Corry-Crowe et al. 2016). For example, the disruption in sea-ice dynamics may lead to a decline in ringed seal populations, as their habitat for resting, feeding, and whelping pupping are reduced (Hornby et al. 2021). Additionally, a changing availability of Arctic cod can cause shifts in the diets of ringed seals, with less reliance on Arctic cod and greater consumption of other available prey fish (Geoffroy et al. 2023), potentially negatively impacting their body condition (Harwood et al. 2015). However, several fish species, such as capelin, can serve as comparable substitutes for Arctic cod, as they offer similar energy content and nutritional composition (Hop and Gjøsæter 2013; Pedro et al. 2019). Finally, in a highly dynamic ecosystem like the North Water Polynya, marine mammals can serve as indicators of ecosystem change (Moore 2008); therefore, continuous, long-term monitoring of their population dynamics remains important (Yurkowski et al. 2016).

4.4. Model limitations, knowledge gaps, and uncertainties in a data-poor system

Uncertainty in many of the input parameter estimates emphasizes the knowledge gaps that persist for many groups of organisms in the Arctic Ocean. There is a general lack of knowledge of the relative abundance and spatial distribution of fish species in the North Water Polynya (Hornby et al. 2021). This is why we aggregated other fish species occurring in the North Water Polynya (e.g., Arctic char and Greenland halibut) into one group and let Ecopath estimate the biomass. Estimates of P/B and Q/B for little auk, other fish, benthic invertebrate groups, and zooplankton groups were taken from other Arctic Ecopath models due to lacking system-specific estimates, contributing to the overall low pedigree score for these groups.
Species specific habitat use and ice coverage were not parameterized in the Ecopath model since the model structure does not characterize specific behaviour or ice dynamics over time. For example, due to the early onset of the spring bloom and subsequent, early secondary production on the Eastern side of the polynya, little auk tend to limit their foraging range to the Eastern side of the polynya and expand to the entire polynya with the onset of the polynya-wide summer bloom (Karnovsky et al. 2007). In addition, ringed seals in the polynya have been observed to spend ∼90% of their time off the coast of Western Greenland and even show different diet preferences depending on the area primarily occupied (Teilmann et al. 1999; Born et al. 2004), possibly due to lighter ice conditions. While species-specific habitat use within the model area can be parameterized by defining habitat fractions, the area occupied by ringed seals is unknown. Spatio-temporal dynamics could be captured in an Ecopath with Ecospace model for the North Water Polynya if new information becomes available.

4.5. Future steps and model applications

To improve the understanding of the North Water Polynya ecosystem, additional functional groups, species, and timeframes could be integrated into the model, based on data (historical and present) from various knowledge systems (e.g., Inuit Traditional Knowledge and quantitative ecosystem survey). To understand ecosystem dynamics over time and ecosystem responses to climate change, future model iterations could explore scenarios of future ecosystem states (e.g., increasing abundances of capelin and Greenland halibut, decreasing abundance of Arctic cod and primary producers, changes in the size structure of the copepod community, and establishment of Atlantic cod and killer whales in the polynya ecosystem). Ultimately, our model contributes to an increasing number of Arctic marine ecosystem models e.g., Western Baffin Bay (Pedro et al. 2023), Beaufort Sea (Hoover et al. 2021), Western Greenland (Pedersen and Zeller 2001), and Eastern Chukchi Sea (Whitehouse et al. 2014). In the future, these models could be combined into a model ensemble to test alternate hypotheses about how high latitude ecosystems are structured and function.
At present, there are ongoing negotiations to implement a bilateral, Inuit-led marine management region, which proposes that the North Water Polynya becomes a marine protected area (MPA) (Pikialasorsuaq Commission 2017). Our model can be used to inform MPA management decisions and evaluate management strategies. For example, an EwE model was used to support management objectives of the Tarium Niryutait Marine Protected Area (TNMPA) in the Beaufort Sea Shelf (Sora et al. 2022). Model simulations highlighted discrepancies in the main management objective of the TNMPA of protecting beluga whales as the keystone species in the area compared with estimated keystone groups of the EwE model, which identified Arctic cod, arthropods, zooplankton, and herring and smelt as keystone groups (Sora et al. 2022). It was suggested that those groups would also need to be included in the TNMPA management objectives as proxies for both beluga whales and overall ecosystem health. In context of the proposed MPA in the North Water Polynya, our model could facilitate discussion on specific management targets.

5. Conclusion

Our Ecopath model illustrates the food web relationships and energy flow within the North Water Polynya ecosystem. Overall productivity in the North Water Polynya was higher than for other Arctic regions, despite low-energy TE through the food web, corroborating expectations of one of the highest Arctic productivity levels within the upwelling driven North Water Polynya. The modelled food web supported the general understanding of Arctic ecosystems in which few, forage species couple pelagic and benthic communities, such as the Arctic cod and calanoid copepods. In addition, the model supported the hypothesis of high benthic biomass in the North Water Polynya that is being sustained by an early spring bloom. The relatively high feeding specialization across the food web points towards a relatively low ecosystem resilience that is typical for high latitude systems, as well as key forage species in the ecosystem, such as adult Arctic cod and benthic invertebrates.
While many uncertainties persist concerning life history and abundance of fish and marine mammals in the region, this model presents a first step towards understanding the North Water Polynya food web. Future model iterations could include co-produced knowledge through engagement with local communities in the North Water region, such as communities from Grise Fiord on Ellesmere Island, and Siorapaluk, Qaanaaq, or Savissivik in Kalaallit Nunaat (Greenland). Knowledge co-production can improve model structure, increase the accuracy of model predictions, identify key ecosystem players, and fill in knowledge gaps, particularly in data-poor systems communities (Rosa et al. 2014; Bevilacqua et al. 2016; Bentley et al. 2019; Sánchez-Jiménez et al. 2019; Cisneros-Montemayor et al. 2020). Future hypotheses can be tested in terms of food web changes due to increasing abundance of competing prey and predatory species, to assess the implications for local subsistence fisheries and food-security and estimate the impacts of climate change. This model provides a baseline description of the North Water Polynya ecosystem structure and function prior to the emergence large-scale, commercial fisheries. These developments will challenge management of the resource access and exploitation in the North Water Polynya, which has already prompted an Inuit-led management strategy by the Pikialasorsuaq Commission in 2017. Having ecosystem models at hand that can test food web responses to different management strategies, can facilitate the implementation of management plans for a future of the North Water Polynya and its people.

Acknowledgements

ABB acknowledge funding from the MEOPAR Postdoctoral Fellowship 2021–2022 and the Ocean Frontier Institute (Module H). TDE and MG acknowledge funding from Fisheries & Oceans Canada (DFO) Atlantic Fisheries Fund and the Canadian Natural Sciences and Engineering Research Council (NSERC) Discovery Grant. Some of the data presented herein were collected by the Canadian research icebreaker CCGS Amundsen and made available by the Amundsen Science program, which was supported by the Canada Foundation for Innovation and Natural Sciences and Engineering Research Council of Canada.

References

Anderson M.A., Fisk A.T., Laing R., Noël M., Angnatok J., Kirk J., et al., 2023. Changing environmental conditions have altered the feeding ecology of two keystone Arctic marine predators. Scientific Reports, 13: 14056.
Ardyna M., Gosselin M., Michel C., Poulin M., Tremblay J.É. 2011. Environmental forcing of phytoplankton community structure and function in the Canadian High Arctic: contrasting oligotrophic and eutrophic regions. Marine Ecology Progress Series, 442: 37–57.
Barber D.G., Massom R.A. 2007. Chapter 1: role of sea ice in Arctic and Antarctic polynyas. In Polynyas windows to the world. Edited by W.O. Smith Jr., Barber D.G. Elsevier Oceanography Series 74, Amsterdam, The Netherlands. pp. 1–54.
Barber D., Marsden R., Minnett P. 2001. The International North Water (North Water) Polynya Study. Atmosphere-Ocean, 39: 163–166.
Bâcle J. 2000. The physical oceanography of waters under the North Water Polynya. Department of Atmospheric and Oceanic Sciences and the Centre for Climate and Global Change Research McGill University, Montreal (thesis).
Bentley J.W., Hines D.E., Borrett S.R., Serpetti N., Hernandez-Milian G., Fox C., et al. 2019. Combining scientific and fishers’ knowledge to co-create indicators of food web structure and function. ICES Journal of Marine Science, 76: 2218–2234.
Bevilacqua A.H.V., Carvalho A.R., Angelini R., Christensen V. 2016. More than anecdotes: Fishers’ ecological knowledge can fill gaps for ecosystem modeling. PLoS ONE, 11: e0155655.
Born E. 2017. Walrus Odobenus rosmarus. In Baffin Bay: an updated strategic environmental impact assessment of petroleum activities in the Greenland Part of Baffin Bay, 127–137, chapter 4.8.2. Edited by Boertmann D., Mosbech A. Danish Centre for Environment and Energy. Scientific Report from DCE—Danish Centre for Environment and Energy No. 218. Available from http://dce2.au.dk/pub/SR218.pdf [accessed May 16, 2024].
Born E.W., Teilmann J., Acquarone M., Riget F.F. 2004. Habitat use of ringed seals (Phoca hispida) in the North Water area (North Baffin Bay). Arctic, 129–142.
Bryndum-Buchholz A., Tittensor D.P., Blanchard J.L., Cheung W.W., Coll M., Galbraith E.D., et al. 2019. Twenty-first-century climate change impacts on marine animal biomass and ecosystem structure across ocean basins. Global Change Biology, 25: 459–472.
Buchart L., Castro de la Guardia L., Xu Y., Ridenour N., Marson J.M., Deschepper I., et al. 2022. Future climate scenarios for Northern Baffin Bay and the Pikialasorsuaq (North Water Polynya) region. Atmosphere-Ocean, 60, 102–123.
Christensen V. 1995. Ecosystem maturity—towards quantification. Ecological Modelling, 77: 3–32.
Christensen V., Walters C.J. 2004. Ecopath with Ecosim: methods, capabilities and limitations. Ecological Modelling, 172: 109–139.
Christensen V., Walters C.J., Pauly D. 2005. Ecopath with Ecosim: a user's guide,154. Fisheries Centre, University of British Columbia, Vancouver. p. 31.
Cisneros-Montemayor A.M., Zetina-Rejón M.J., Espinosa-Romero M.J., Cisneros-Mata M.A., Singh G.G., Fernández-Rivera Melo FJ. 2020. Evaluating ecosystem impacts of data-limited artisanal fisheries through ecosystem modelling and traditional fisher knowledge. Ocean & Coastal Management, 195: 105291.
Coad B., Reist J. 2017. Marine fishes of Arctic Canada. University of Toronto Press. 618 p.
Colléter M., Valls A., Guitton J., Gascuel D., Pauly D., Christensen V. 2015. Global overview of the applications of the Ecopath with Ecosim modeling approach using the EcoBase models repository.Ecological Modelling, 302: 42–53.
Darnis G., Geoffroy M., Dezutter T., Aubry C., Massicotte P., Brown T., et al. 2022. Zooplankton assemblages along the North American Arctic: ecological connectivity shaped by ocean circulation and bathymetry from the Chukchi Sea to Labrador Sea. Elementa: Science of the Anthropocene, 10: 00053.
Deibel D., Saunders P.A., Stevens C.J. 2017. Seasonal phenology of appendicularian tunicates in the North Water, northern Baffin Bay. Polar Biology, 40: 1289–1310.
Dunbar M. 1969. The geographical position of the North Water. Arctic, 22: 438–441.
Eddy T.D., Bernhardt J.R., Blanchard J.L., Cheung W.W., Colléter M., Du Pontavice H., et al. 2021. Energy flow through marine ecosystems: confronting transfer efficiency. Trends in Ecology & Evolution, 36: 76–86.
Egevang C., Boertmann D., Mosbech A., Tamstorf M.P. 2003. Estimating colony area and population size of little auks Alle alle at Northumberland Island using aerial images. Polar Biology, 26: 8–13.
Finn J.T. 1976. Measures of ecosystem structure and function derived from analysis of flows. Journal of Theoretical Biology, 56: 363–380.
Fossheim M., Primicerio R., Johannesen E., Ingvaldsen R.B., Aschan M.M., Dolgov A.V. 2015. Recent warming leads to a rapid borealization of fish communities in the Arctic. Nature Climate Change, 5: 673–677.
Geoffroy M., Majewski A., LeBlanc M., Gauthier S., Walkusz W., Reist J.D., Fortier L. 2016. Vertical segregation of age-0 and age-1+ polar cod (Boreogadus saida) over the annual cycle in the Canadian Beaufort Sea. Polar Biology, 39: 1023–1037.
Geoffroy M., Bouchard C., Flores H., Robert D., Gjøsæter H., Hoover C., et al. 2023. The circumpolar impacts of climate change and anthropogenic stressors on Arctic cod (Boreogadus saida) and its ecosystem. Elementa: Science of the Anthropocene, 11: 00097.
Grebmeier J.M., Barry J.P. 2007. Benthic processes in polynyas. In Elsevier oceanography series, 74. pp. 363–390.
Hamilton C.D., Lydersen C., Ims R.A., Kovacs K.M. 2015. Predictions replaced by facts: a keystone species' behavioural responses to declining arctic sea-ice. Biology Letter, 11: 20150803.
Harwood L.A., Smith T.G., George J.C., Sandstrom S.J., Walkusz W., Divoky G.J. 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.
Heide-Jørgensen M.P., Burt L.M., Hansen R.G., Nielsen N.H., Rasmussen M., Fossette S., Stern H. 2013. The significance of the North Water polynya to Arctic top predators. Ambio, 42: 596–610.
Herbig J., Fisher J., Bouchard C., Niemi A., LeBlanc M., Majewski A., et al. 2023. Climate and juvenile recruitment drive Arctic cod (Boreogadus saida) dynamics in two Canadian Arctic seas. Elementa: Science of the Anthropocene, 11: 00033.
Heymans J.J., Coll M., Libralato S., Morissette L., Christensen V. 2014. Global patterns in ecological indicators of marine food webs: a modelling approach. PLoS ONE, 9: e95845.
Heymans J.J., Coll M., Link J.S., Mackinson S., Steenbeek J., Walters C., Christensen V. 2016. Best practice in Ecopath with Ecosim food-web models for ecosystem-based management. Ecological Modelling, 331: 173–184.
Hobson K.A., Fisk A., Karnovsky N., Holst M., Gagnon J.M., Fortier M. 2002. A stable isotope (δ13C, δ15N) model for the North Water food web: implications for evaluating trophodynamics and the flow of energy and contaminants. Deep Sea Research Part II: Topical Studies in Oceanography, 49: 5131–5150.
Hoover C.A. 2013a. Ecosystem model indicators for the Beaufort Sea Shelf region of the Beaufort Sea. In Canadian Data Report of Fisheries and Aquatic Sciences 1249. vi +14p.
Hoover C., Pitcher T., Christensen V. 2013. 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., Walkusz W., MacPhee S., Niemi A., Majewski A., Loseto L. 2021. Canadian Beaufort Sea Shelf food web structure and changes from 1970–2012. In Canadian Data Report of Fisheries and Aquatic Sciences 1313. viii + 97p.
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.
Hornby C.A., Scharffenberg K.C., Melling H., Archambault P., Dawson K., Geoffroy M., et al. 2021. Biophysical and ecological overview of the North Water and adjacent areas. In DFO Canadian Science Advisory Secretariat Document 2021/078. v + 203p.
Karnovsky N.J., Hunt G.L. Jr. 2002. Estimation of carbon flux to dovekies (Alle alle) in the North Water. Deep Sea Research Part II: Topical Studies in Oceanography, 49: 5117–5130.
Karnovsky N., Ainley D.G., Lee P. 2007. The impact and importance of production in polynyas to top-trophic predators: three case histories. In Elsevier oceanography series, 74. pp. 391–410.
Kenny T.A., Fillion M., MacLean J., Wesche S.D., Chan H.M. 2018. Calories are cheap, nutrients are expensive–the challenge of healthy living in Arctic communities. Food Policy, 80: 39–54.
Klein B., LeBlanc B., Mei Z.P., Beret R., Michaud J., Mundy C.J., et al. 2002. Phytoplankton biomass, production and potential export in the North Water. Deep Sea Research Part II: Topical Studies in Oceanography, 49: 4983–5002.
Kyhn L.A., Mosbech A. 2019. White Paper—North Water Polynya Conference. Aarhus Universitet, Roskilde.
Lewis E.L., Ponton D., Legendre L., Leblanc B. 1996. Springtime sensible heat, nutrients and phytoplankton in the Northwater Polynya, Canadian Arctic. Continental Shelf Research, 16(14): 1775–1792.
Lindeman R.L. 1942. The trophic-dynamic aspect of ecology. Ecology, 23: 399–417.
Lotze H.K., Tittensor D.P., Bryndum-Buchholz A., Eddy T.D., Cheung W.W., Galbraith E.D., et al. 2019. Global ensemble projections reveal trophic amplification of ocean biomass declines with climate change. Proceedings of the National Academy of Sciences, 116: 12907–12912.
Majewski A.R., Walkusz W., Lynn B.R., Atchison S., Eert J., Reist J.D. 2016. Distribution and diet of demersal Arctic Cod, Boreogadus saida, in relation to habitat characteristics in the Canadian Beaufort Sea. Polar Biology, 39: 1087–1098.
Mäkelä A., Witte U., Archambault P. 2017. Benthic macroinfaunal community structure, resource utilisation and trophic relationships in two Canadian Arctic Archipelago polynyas. PLoS ONE, 12: e0183034.
Melling H., Gratton Y., Ingram G. 2001. Ocean circulation within the North Water polynya of Baffin Bay. Atmoshere-Ocean, 39: 301–325.
Kyhn  L.A., Mosbech A., (Editors). 2019. North Water Polynya Conference, Copenhagen 2017. Aarhus University, Aarhus, Denmark. 156 p.
Mosbech A., Johansen K.L., Davidson T.A., Appelt M., Grønnow B., Cuyler C., et al. 2018. On the crucial importance of a small bird: The ecosystem services of the little auk (Alle alle) population in Northwest Greenland in a long-term perspective. Ambio, 47: 226–243.
Mohammed E. 2007. A model of the Lancaster Sound Region in the 1980s. In Fisheries impacts on North Atlantic ecosystems: models and analyses. Edited by Guenette S., Christensen V., Pauly D. Fisheries Centre Research Reports, 9(4), University of British Columbia. pp. 99–110.
Moore G.W.K., Howell S.E.L., Brady M., Xu X., McNeil K. 2021. Anomalous collapses of Nares Strait ice arches leads to enhanced export of Arctic sea ice. Nature Communications, 12: 1.
Moore S.E. 2008. Marine mammals as ecosystem sentinels. Journal of Mammalogy, 89: 534–540.
Moshøj C.M. 2015. Rapid Assessment of Circum-Arctic Ecosystem Resilience (RACER). The North Water Polynya. WWF Verdensnaturfonden, Copenhagen, Denmark.
Murphy E.J., Cavanagh R.D., Drinkwater K.F., Grant S.M., Heymans J.J., Hofmann E.E., et al. 2016. Understanding the structure and functioning of polar pelagic ecosystems to predict the impacts of change. Proceedings of the Royal Society B: Biological Sciences, 283: 20161646.
NAMMCO (North Atlantic Marine Mammal Commission). 2016. Atlantic walrus [online]. Available from https://nammco.no/atlantic-walrus/  [accessed 19 July 2023].
NAMMCO. 2018. Report of the NAMMCO Scientific Working Group on Walrus, October 2018. Available from https://nammco.no/wp-content/uploads/2019/02/final-report_wwg2018_071118_corrected250619-recall-rr3-.pdf [accessed May 16, 2024].
Niemi A., Ferguson S., Hedges K., Melling H., Michel C., Ayles B., et al. 2019. State of Canada's Arctic seas. In Canadian Technical Report of Fisheries and Aquatic Sciences, 1488-5379; 3344. Fisheries and Oceans Canada. Available from https://publications.gc.ca/pub?id=9.881731&sl=0 [accessed May 16, 2024].
Nozais C., Gosselin M., Michel C., Tita G. 2001. Abundance, biomass, composition and grazing impact of the sea-ice meiofauna in the North Water, northern Baffin Bay. Marine Ecology Progress Series, 217: 235–250.
O'Corry-Crowe G., Mahoney A.R., Suydam R., Quakenbush L., Whiting A., Lowry L., Harwood L. 2016. Genetic profiling links changing sea-ice to shifting beluga whale migration patterns. Biology Letter, 12: 20160404.
Palomares M.L.D., Pauly D. 1998. Predicting food consumption of fish populations as functions of mortality, food type, morphometrics, temperature and salinity. Marine and Freshwater Research, 49: 447–453.
Pauly D., Christensen V. 1995. Primary production required to sustain global fisheries. Nature, 374: 255–257.
Pedersen S., Zeller D. 2001. A mass balance model for the West Greenland marine ecosystem. In Fisheries impacts on North Atlantic ecosystems: models and analyses. Edited by Guenette S., Christensen V., Pauly D. Fisheries Centre Research Reports, 9. University of British Columbia. pp. 111–127.
Pedro S., Fisk A.T., Ferguson S.H., Hussey N.E., Kessel S.T., McKinney M.A. 2019. Limited effects of changing prey fish communities on food quality for aquatic predators in the eastern Canadian Arctic in terms of essential fatty acids, methylmercury and selenium. Chemosphere, 214: 855–865.
Pedro S., Lemire M., Hoover C., Saint-Béat B., Janjua M.Y., Herbig J., et al. 2023. Structure and function of the western Baffin Bay coastal and shelf ecosystem. Elementa: Science of the Anthropocene, 11: 00015.
Pikialasorsuaq Commission. 2017. Pikialasorsuaq Atlas. Interactive Atlas and Planning tool. Inuit Circumpolar Council.
Plagányi É.E., Essington T.E. 2014. When the SURFs up, forage fish are key. Fisheries Research, 159: 68–74.
Power M.E., Tilman D., Estes J.A., Menge B.A., Bond W.J., Mills L.S., et al. 1996. Challenges in the quest for keystones: identifying keystone species is difficult—but essential to understanding how loss of species will affect ecosystems. Bioscience, 46: 609–620.
Preußer A., Heinemann G., Willmes S., Paul S. 2015. Multi-decadal variability of polynya characteristics and ice production in the North Water Polynya by means of passive microwave and thermal infrared satellite imagery. Remote Sensing, 7: 15844–15867.
Ribeiro S., Limoges A., Massé G., Johansen K.L., Colgan W., Weckström K., et al. 2021. Vulnerability of the North Water ecosystem to climate change. Nature communications, 12: 4475.
Ringuette M., Fortier L., Fortier M., Runge J.A., Bélanger S., Larouche P., et al. 2002. Advanced recruitment and accelerated population development in Arctic calanoid copepods of the North Water. Deep Sea Research Part II: Topical Studies in Oceanography, 49: 4927–4946.
Rosa R., Carvalho A.R., Angelini R. 2014. Integrating fishermen knowledge and scientific analysis to assess changes in fish diversity and food web structure. Ocean & Coastal Management, 102: 258–268.
Roy V., Iken K., Archambault P. 2015a. Regional variability of megabenthic community structure across the Canadian Arctic. Arctic, 68: 180–192.
Roy V., Iken K., Gosselin M., Tremblay J.É., Bélanger S., Archambault P. 2015b. Benthic food-web responses to marine biological productivity and depth across the Canadian Arctic. Deep Sea Research Part I, 102: 55–71.
Saint-Béat B., Maps F., Babin M. 2018. Unraveling the intricate dynamics of planktonic Arctic marine food webs. A sensitivity analysis of a well-documented food web model. Progress in Oceanography, 160: 167–185.
Sánchez-Jiménez A., Fujitani M., MacMillan D., Schlüter A., Wolff M. 2019. Connecting a trophic model and local ecological knowledge to improve fisheries management: the case of Gulf of Nicoya, Costa Rica. Frontiers in Marine Science, 6: 126.
Sora K.J., Wabnitz C.C., Steiner N.S., Sumaila U.R., Cheung W.W., Niemi A., et al. 2022. Evaluation of the Beaufort Sea shelf structure and function in support of the Tarium Niryutait Marine Protected Area. Arctic Science, 8: 1252–1275.
Søreide J.E., Leu E.V., Berge J., Graeve M., Falk-Petersen S.T.I.G. 2010. Timing of blooms, algal food quality and Calanus glacialis reproduction and growth in a changing Arctic. Global Change Biology, 16: 3154–3163.
Steiner N.S., Cheung W.W., Cisneros-Montemayor A.M., Drost H., Hayashida H., Hoover C., et al. 2019. Impacts of the changing ocean-sea ice system on the key forage fish Arctic cod (Boreogadus saida) and subsistence fisheries in the western Canadian Arctic—evaluating linked climate, ecosystem and economic (CEE) models. Frontiers in Marine Science, 6: 179.
Stirling I. 1980. The biological importance of polynyas in the Canadian Arctic. Arctic, 33, 303–315.
Tai T.C., Steiner N.S., Hoover C., Cheung W.W., Sumaila U.R. 2019. Evaluating present and future potential of arctic fisheries in Canada. Marine Policy, 108: 103637.
Tam J.C., Bundy A. 2019. Mass-balance models of the Newfoundland and Labrador Shelf ecosystem for 1985–1987 and 2013–2015. In Canadian Technical Report of Fisheries and Aquatic Sciences 3328. vii + 78p.
Teilmann J., Born E.W., Acquarone M. 1999. Behaviour of ringed seals tagged with satellite transmitters in the North Water polynya during fast-ice formation. Canadian Journal of Zoology, 77: 1934–1946.
Tremblay J.E., Smith W.O. Jr. 2007. Primary production and nutrient dynamics in polynyas. In Elsevier oceanography series, 74. pp. 239–269.
Tremblay J.E., Gratton Y., Fauchot J., Price N.M. 2002. Climatic and oceanic forcing of new, net, and diatom production in the North Water. Deep Sea Research Part II: Topical Studies in Oceanography, 49(22–23): 4927–4946.
Tremblay J.É., Hattori H., Michel C., Ringuette M., Mei Z.P., Lovejoy C., et al. 2006. Trophic structure and pathways of biogenic carbon flow in the eastern North Water Polynya. Progress in Oceanography, 71: 402–425.
Valls A., Coll M., Christensen V. 2015. Keystone species: toward an operational concept for marine biodiversity conservation. Ecological Monographs, 85: 29–47.
Vincent R.F. 2019. A study of the north water polynya ice arch using four decades of satellite data. Scientific Reports, 9: 20278.
Walkusz W., Majewski A., Reist J.D. 2013. Distribution and diet of the bottom dwelling Arctic cod in the Canadian Beaufort Sea. Journal of Marine Systems, 127: 65–75.
Walters C., Christensen V., Pauly D. 1997. Structuring dynamic models of exploited ecosystems from trophic mass-balance assessments. Reviews in Fish Biology and Fisheries, 7: 139.
Welch H.E., Bergmann M.A., Siferd T.D., Martin K.A., Curtis M.F., Crawford R.E., et al. 1992. Energy flow through the marine ecosystem of the Lancaster Sound region, Arctic Canada. Arctic, 343–357.
Whitehouse G.A., Aydin K., Essington T.E., Hunt G.L. 2014. A trophic mass balance model of the eastern Chukchi Sea with comparisons to other high-latitude systems. Polar Biology, 37: 911–939.
Witting L., Born E.W. 2005. An assessment of Greenland walrus populations. ICES Journal of Marine Science, 62: 266–284.
Witting L., Born E. 2014. Population dynamics of walruses in Greenland. NAMMCO Scientific Publications, 9. pp. 191–218.
Wojczulanis-Jakubas K., Jakubas D., Stempniewicz L. 2022. The Little Auk Alle alle: an ecological indicator of a changing Arctic and a model organism. Polar Biology, 45: 163–176.
York J., Dowsley M., Cornwell A., Kuc M., Taylor M. 2016. Demographic and traditional knowledge perspectives on the current status of Canadian polar bear subpopulations. Ecology and Evolution, 6: 2897–2924.
Yurkowski D.J., Ferguson S.H., Semeniuk C.A., Brown T.M., Muir D.C., Fisk A.T. 2016. Spatial and temporal variation of an ice-adapted predator's feeding ecology in a changing Arctic marine ecosystem. Oecologia, 180: 631–644.

Appendix A

Table A1.
Table A1. Pedigree of data quality (Christensen et al. 2005). B = biomass; P/B = production/biomass ratio; Q/B = consumption/biomass ratio.
Table A2.
Table A2. Data pedigree for the North Water Polynya Ecopath model with corresponding confidence intervals (%). B = biomass; P/B = production/biomass ratio; Q/B = consumption/biomass ratio. Data sources were assigned an index based on the criteria in Table A2.
Table A3.
Table A3. References for parameter estimates for the North Water Polynya Ecopath model. References listed below. B = biomass; P/B = production/biomass ratio; Q/B = consumption/biomass ratio.
Table A4.
Table A4. Overview of marine mammal populations included in the North Water Polynya study area.
Table A5.
Table A5. Magnitude of changes in parameter estimates (%) from initial unbalanced model to balanced model. B = biomass; P/B = production/biomass ratio; Q/B = consumption/biomass ratio.
Table A6.
Table A6. Percent change made to diet parameter estimates from initial unbalanced model to balanced model.
Table A7.
Table A7. Trophic levels reported for the functional groups in the North Water Polynya ecosystem and other high Arctic marine ecosystems.

References for Appendix

Ardyna M., Gosselin M., Michel C., Poulin M., Tremblay J.É. 2011. Environmental forcing of phytoplankton community structure and function in the Canadian High Arctic: contrasting oligotrophic and eutrophic regions. Marine Ecology Progress Series, 442: 37–57.
Arndt C.E., Swadling K.M. 2006. Crustacea in Arctic and Antarctic sea ice: distribution, diet and life history strategies. Advances in Marine Biology, 51: 197–315.
Arnkværn G., Daase M., Eiane K. 2005. Dynamics of coexisting Calanus finmarchicus, Calanus glacialis and Calanus hyperboreus populations in a high-Arctic fjord. Polar Biology, 28: 528–538.
Boertmann D., Mosbech A. 1998. Distribution of little auk (Alle alle) breeding colonies in Thule District, northwest Greenland. Polar Biology, 19(3): 206–210.
Born E.W., Gjertz I., Reeves R.R. 1995. Population assessment of the Atlantic walrus (Odobenus rosmarus rosmarus L.). Norsk Polarinstitutt Meddelelser, 138: 100.
Breteler K. 1995. Development of Pseudocalanus elongatus (Copepoda, Calanoida) cultured at different temperature and food conditions. Marine Ecology Progress Series, 119: 99–110.
Carey A.G. Jr., Ruff R.E. 1977. Ecological studies of the benthos in the western Beaufort Sea with special reference to bivalve molluscs. In Polar oceans. Arctic Institute of North America, Calgary. pp. 505–530.
Christensen V., Walters C.J., Pauly D. 2005. Ecopath with Ecosim: a user's guide, 154. Fisheries Centre, University of British Columbia, Vancouver. p. 31.
Craig W., Griffiths L., Haldorson L., McElderry H. 1982. Ecological studies of Arctic Cod (Boreogadus saida) in Beaufort Sea coastal waters, Alaska. Canadian Journal of Fisheries and Aquatic Sciences, 39: 395–406.
Dietz R., Born E.W., Stewart R.E.A., M.P. Heide-Jørgensen, H. Stern, F. Rigét et al. 2014. Movements of walruses (Odobenus rosmarus) between Central West Greenland and Southeast Baffin Island, 2005–2008. Vol. 9 NAMMCO Scientific Publications. pp. 53–74.
Dodson J.J., Tremblay S., Colombani F., Carscadden J.E., Lecomte F. 2007. Trans-Arctic dispersals and the evolution of a circumpolar marine fish species complex, the capelin (Mallotus villosus). Molecular Ecology, 16(23): 5030–5043.
Egevang C., Boertmann D., Mosbech A., Tamstorf M.P. 2003. Estimating colony area and population size of little auks Alle alle at Northumberland Island using aerial images. Polar Biology, 26: 8–13.
Fort J., Cherel Y., Harding A.M., Welcker J., Jakubas D., Steen H., et al. 2010. Geographic and seasonal variability in the isotopic niche of little auks. Marine Ecology Progress Series, 414: 293–302.
Harris L., Moore J.-S., Dunmall K., Evans M., Falardeau M., Gallagher C., et al. 2022. Arctic char in a rapidly changing North: Aqhaliat Report. Vol. 4. In Polar Knowledge Canada. pp. 34–57.
Heide-Jørgensen M.P., Burt L.M., Hansen R.G., Nielsen N.H., Rasmussen M., Fossette S., Stern H. 2013. The significance of the north water polynya to arctic top predators. Ambio, 42(5): 596–610.
Hirst A.G., Kiørboe T. 2002. Mortality of marine planktonic copepods: global rates and patterns. Marine Ecology Progress Series, 230: 195–209.
Hobson K.A., Welch H.E. 1992. Determination of trophic relationships within a high Arctic marine food web using δ13C and δ15N analysis. Marine Ecology Progress Series, 84, 9–18.
Hobson K.A., Fisk A., Karnovsky N., Holst M., Gagnon J.M., Fortier M. 2002. A stable isotope (δ13C, δ15N) model for the North Water food web: implications for evaluating trophodynamics and the flow of energy and contaminants. Deep Sea Research Part II: Topical Studies in Oceanography, 49(22–23): 5131–5150.
Hoekstra P.F., O'Hara T.M., Fisk a.T., Borgå K., Solomon K.R., Muir D.C.G. 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., Walkusz W., MacPhee S., Niemi A., Majewski A., Loseto L. 2021. Canadian Beaufort Sea Shelf food web structure and changes from 1970–2012. In Canadian Data Report of Fisheries and Aquatic Sciences 1313. viii + 97p.
Innes S., Lavigne D.M., Earle W.M., Kovacs K.M. 1987. Feeding rates of seals and whales. The Journal of Animal Ecology, 56, 115–130.
Jarre-Teichmann A., Brey T., Bathmann U.V, Dahm C., Dieckmann G.S., Gorny M., et al. 1997. Trophic flows in the benthic shelf community of the eastern Weddell Sea, Antarctica, In Antarctic communities: species, structure, and survival. Edited by Battaglia B., Valencia J., Walton D.W.H. Cambridge University Press, Cambridge, UK. pp. 118–134 of 464p.
Karnovsky N.J., Hunt G.L. Jr. 2002. Estimation of carbon flux to dovekies (Alle alle) in the North Water. Deep Sea Research Part II: Topical Studies in Oceanography, 49(22–23): 5117–5130.
Kelly B.P., Bengtson J.L., Boveng P.L., Cameron M.F., Dahle S.P., Jansen J.K., et al. 2010. Status review of the ringed seal (Phoca hispida). U.S. Dep. Commer., NOAA Tech. Memo. NMFS-AFSC-212. 250 pp. Available from .http://www.afsc.noaa.gov/Publications/AFSC-TM/NOAA-TM-AFSC-212.pdf [accessed May 16, 2024].
Kingsley M.C.S. 1987. The numbers of ringed seals (Phoca hispida) in Baffin Bay and associated waters. NAMMCO Scientific Publications. Vol. 1. pp. 181–196.
Kovacs K. (Editor). 2014. Circumpolar ringed seal (Pusa hispida) monitoring. Norwegian Polar Institute, Report Series 143. 45 pp. Available from https://brage.npolar.no/npolar-xmlui/bitstream/handle/11250/191472/Rapport143.pdf?sequence=1&isAllowed=y [accessed July 17, 2024]
Lacho G. 1986. Analysis of Arctic cod stomach contents from the Beaufort Shelf, July and September, 1984. Department of Fisheries and Oceans, Central and Arctic Region.
Mäkelä A., Witte U., Archambault P. 2017. Benthic macroinfaunal community structure, resource utilisation and trophic relationships in two Canadian Arctic Archipelago polynyas. PLoS ONE, 12(8): e0183034.
Mansfield A.W. 1959. The walrus in the Canadian Arctic. Fish. Res. Board Can. Arctic Unit Circ. 2. pp. 1–13.
Montevecchi W.A., Stenhouse I.J. 2002. Dovekie (Alle alle), version 2.0. In The birds of North America. Edited by Poole A. F., Gill F. B. Cornell Lab of Ornithology, Ithaca, NY.
Mosbech A., Johansen K.L., Davidson T.A., Appelt M., Grønnow B., Cuyler C., et al. 2018. On the crucial importance of a small bird: the ecosystem services of the little auk (Alle alle) population in Northwest Greenland in a long-term perspective. Ambio, 47: 226–243.
NAMMCO (North Atlantic Marine Mammal Commission). 2016. Catch database [online]. Available from https://nammco.no/catch-database/ [accessed May 16, 2024].
Ohman M.D., Wood S.N. 1995. The inevitability of mortality. ICES Journal of Marine Science, 52(3–4): 517–522.
Outridge P.M., Davis W.J., Stewart R.E.A., Born E.W. 2003. Investigation of the stock structure of Atlantic walrus (Odobenus rosmarus rosmarus) in Canada and Greenland using dental Pb isotopes derived from local geochemical environments. Arctic, 56: 82–90.
Pauly D., Christensen V. 1995. Primary production required to sustain global fisheries. Nature, 374(6519): 255–257.
Pedersen C.E., Falk K. 2001. Chick diet of dovekies Alle alle in Northwest Greenland. Polar Biology, 24: 53–58.
Pedro S., Lemire M., Hoover C., Saint-Béat B., Janjua M.Y., Herbig J., et al. 2023. Structure and function of the western Baffin Bay coastal and shelf ecosystem. Elementa: Science of the Anthropocene, 11(1): 00015.
Rosing-Asvid A., Hedeholm R., Arendt K.E., Fort J., Robertson G.J. 2013. Winter diet of the little auk (Alle alle) in the Northwest Atlantic. Polar Biology, 36: 1601–1608.
Scott W.B., Scott M.G. 1988. Atlantic fishes of Canada. In Canadian Bulletin of Fisheries and Aquatic Sciences, 219.
Tam J.C., Bundy A. 2019. Mass-balance models of the Newfoundland and Labrador Shelf ecosystem for 1985–1987 and 2013–2015. Canadian Technical Report of Fisheries and Aquatic Sciences 3328. vii + 78p.
Thiemann G.W., Iverson S.J., Stirling I. 2008. Variation in blubber fatty acid composition among marine mammals in the Canadian Arctic. Marine Mammal Science, 24(1): 91–111.
Vibe C. 1950. The marine mammals and the marine fauna in the Thule District (northwest Greenland) with observations on ice conditions in 1939–41. Medd. Grønl. 150. 154pp.
Vongraven D., Derocher A.E., Pilfold N.W., Yoccoz N.G. 2022. Polar bear harvest patterns across the Circumpolar Arctic. Frontiers in Conservation Science, 3: 3.
Witting L., Born E.W. 2005. An assessment of Greenland walrus populations. ICES Journal of Marine Science, 62: 266–284.
Witting L., Born E. 2014. Population dynamics of walruses in Greenland. NAMMCO Scientific Publications, 9. pp. 191–218.
Wojczulanis-Jakubas K., Jakubas D., Stempniewicz L. 2022. The Little Auk Alle alle: an ecological indicator of a changing Arctic and a model organism. Polar Biology, 45(2): 163–176.
York J., Dowsley M., Cornwell A., Kuc M., Taylor M. 2016. Demographic and traditional knowledge perspectives on the current status of Canadian polar bear subpopulations. Ecology and Evolution, 6: 2897–2924.

Information & Authors

Information

Published In

cover image Arctic Science
Arctic Science
Volume 10Number 3September 2024
Pages: 545 - 568

History

Received: 20 September 2023
Accepted: 13 May 2024
Accepted manuscript online: 24 May 2024
Version of record online: 14 August 2024

Data Availability Statement

Data generated during this study are available from the corresponding author upon reasonable request. The North Water Polynya Ecopath model is publicly available through the EcoBase database of EwE models: http://ecobase.ecopath.org/#docs.

Key Words

  1. North Water Polynya
  2. food web
  3. ecopath
  4. ecosystem modelling
  5. Arctic Ocean

Authors

Affiliations

Centre for Fisheries Ecosystem Research, Fisheries and Marine Institute, Memorial University, St. John's, NL, Canada
Author Contributions: Conceptualization, Data curation, Formal analysis, Investigation, Project administration, Visualization, Writing – original draft, and Writing – review & editing.
Jennifer L. Herbig
Centre for Fisheries Ecosystem Research, Fisheries and Marine Institute, Memorial University, St. John's, NL, Canada
Author Contributions: Resources, Validation, and Writing – review & editing.
Gérald Darnis
Québec-Océan, Département de Biologie, Université Laval, Quebec City, Québec, Canada
Author Contributions: Resources, Validation, and Writing – review & editing.
Maxime Geoffroy
Centre for Fisheries Ecosystem Research, Fisheries and Marine Institute, Memorial University, St. John's, NL, Canada
Department of Arctic and Marine Biology, The Arctic University of Norway, Tromsø, Norway
Author Contributions: Resources, Validation, and Writing – review & editing.
Centre for Fisheries Ecosystem Research, Fisheries and Marine Institute, Memorial University, St. John's, NL, Canada
Author Contributions: Conceptualization, Supervision, Validation, and Writing – review & editing.

Author Contributions

Conceptualization: ABB, TDE
Data curation: ABB
Formal analysis: ABB
Investigation: ABB
Project administration: ABB
Resources: JLH, GD, MG
Supervision: TDE
Validation: JLH, GD, MG, TDE
Visualization: ABB
Writing – original draft: ABB
Writing – review & editing: ABB, JLH, GD, MG, TDE

Competing Interests

The authors declare there are no competing interests.

Funding Information

Fisheries and Oceans Canada Atlantic Fisheries Fund
Marine Environmental Observation, Prediction and Response Network (MEOPAR)
Ocean Frontier Institute (Module H)

Metrics & Citations

Metrics

Other Metrics

Citations

Cite As

Export Citations

If you have the appropriate software installed, you can download article citation data to the citation manager of your choice. Simply select your manager software from the list below and click Download.

There are no citations for this item

View Options

View options

PDF

View PDF

Media

Tables

Media

Share Options

Share

Share the article link

Share on social media

Cookies Notification

We use cookies to improve your website experience. To learn about our use of cookies and how you can manage your cookie settings, please see our Cookie Policy.
×