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Home > VOLUME 30 > ISSUE 2 > Article 17 Research

Braiding Inuit knowledge and Western science to understand light goose population dynamics under a changing climate

Carter, N. A., L. M. Martinez-Levasseur, V. Johnston, P. A. Smith, A. Irkok, B. Saviakjuk, L. Emiktaut, Salliq Project Management Committee, Arviat Project Management Committee, B. Chaudhary, G. Ljubicic, R. T. Alisauskas, F. Baldwin, P. B. Y. Wong, and D. A. Henri. 2025. Braiding Inuit knowledge and Western science to understand light goose population dynamics under a changing climate. Ecology and Society 30(2):17. https://doi.org/10.5751/ES-16079-300217
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  • Natalie A. CarterORCID, Natalie A. Carter
    National Wildlife Research Centre, Environment and Climate Change Canada, Ottawa, Ontario, Canada; School of Earth, Environment & Society, McMaster University, Hamilton, Ontario, Canada
  • Laura M. Martinez-LevasseurORCID, Laura M. Martinez-Levasseur
    Wildlife Research Division, Science and Technology Branch, Environment and Climate Change Canada, Montréal, Québec, Canada
  • Vicky Johnston, Vicky Johnston
    Canadian Wildlife Service, Environment and Climate Change Canada, Yellowknife, Northwest Territories, Canada
  • Paul A. SmithORCID, Paul A. Smith
    Wildlife Research Division, Science and Technology Branch, Environment and Climate Change Canada, Ottawa, Ontario, Canada
  • Aupaa Irkok, Aupaa Irkok
    Arviat, Nunavut, Canada
  • Bobbie Saviakjuk, Bobbie Saviakjuk
    Salliq, Nunavut, Canada
  • Lenny Emiktaut, Lenny Emiktaut
    Salliq, Nunavut, Canada
  • Salliq Project Management Committee, Salliq Project Management Committee
    Salliq, Nunavut, Canada
  • Arviat Project Management Committee, Arviat Project Management Committee
    Arviat, Nunavut, Canada
  • Bhavana Chaudhary, Bhavana Chaudhary
    Landscape Science & Technology Division, Science and Technology Branch, Environment and Climate Change Canada, Ottawa, Ontario, Canada
  • Gita LjubicicORCID, Gita Ljubicic
    Department of Geography and Environmental Studies, Carleton University, Ottawa, Ontario, Canada; School of Earth, Environment & Society, McMaster University, Hamilton, Ontario, Canada
  • Ray T. AlisauskasORCID, Ray T. Alisauskas
    Wildlife Research Division, Science and Technology Branch, Environment and Climate Change Canada, Saskatoon, Saskatchewan, Canada
  • Frank BaldwinORCID, Frank Baldwin
    Canadian Wildlife Service, Environment and Climate Change Canada, Winnipeg, Manitoba, Canada
  • Pamela B. Y. Wong, Pamela B. Y. Wong
    Trailmark Systems, Victoria, British Columbia, Canada
  • Dominique A. HenriORCIDDominique A. Henri
    Wildlife Research Division, Science and Technology Branch, Environment and Climate Change Canada, Montréal, Québec, Canada

The following is the established format for referencing this article:

Carter, N. A., L. M. Martinez-Levasseur, V. Johnston, P. A. Smith, A. Irkok, B. Saviakjuk, L. Emiktaut, Salliq Project Management Committee, Arviat Project Management Committee, B. Chaudhary, G. Ljubicic, R. T. Alisauskas, F. Baldwin, P. B. Y. Wong, and D. A. Henri. 2025. Braiding Inuit knowledge and Western science to understand light goose population dynamics under a changing climate. Ecology and Society 30(2):17.

https://doi.org/10.5751/ES-16079-300217

  • Introduction
  • Methods
  • Results and Discussion
  • Conclusion
  • Acknowledgments
  • Data Availability
  • Literature Cited
  • bird population dynamics; braiding knowledge systems; environmental change; Indigenous knowledge; Inuit knowledge; light geese; migratory bird sanctuary; population trends; Ross’s Goose; Snow Goose
    Braiding Inuit knowledge and Western science to understand light goose population dynamics under a changing climate
    Copyright © 2025 by the author(s). Published here under license by The Resilience Alliance. This article is under a Creative Commons Attribution 4.0 International License. You may share and adapt the work provided the original author and source are credited, you indicate whether any changes were made, and you include a link to the license. ES-2025-16079.pdf
    Research

    ABSTRACT

    Increasing abundance of Snow and Ross’s Geese (Anser caerulescens and Anser rossii; kangut and qaaraarjuk in Inuktut, respectively), referred to collectively as light geese, has caused alterations in various Canadian Arctic ecosystems. Inuit have harvested light geese for generations and hold knowledge that offers unique insights into the ecology and population dynamics of these species. By combining interviews with 40 light goose harvesters and Elders with results from aerial surveys in the Kivalliq region of Nunavut, we (1) describe changes in light goose distribution and abundance between the 1940s and the 2010s, (2) explore the effects of light geese on local ecosystems, and (3) identify factors driving these changes. Inuit observations gathered through lifetimes of land-based observations and results from aerial surveys concurred that (1) light goose numbers have increased regionally since the 1940s, and (2) light goose numbers decreased in several colonies within the Kivalliq region between the 1960s–1990s and the 2010s, including in two Migratory Bird Sanctuaries. Inuit have noted that habitat loss due to overgrazing and grubbing has pushed light geese to abandon altered habitats in favor of new breeding and foraging sites. Inuit observations also indicated that light geese have altered their migration behavior (how, when, and where they migrate and nest) in response to earlier spring snowmelt, the drying of ponds and lakes, and an increased number of predators. These conclusions add substantially to overall understanding about light geese in regions where aerial surveys are expensive and infrequent, and scientific studies are limited in geographic coverage.

    INTRODUCTION

    Every spring, Snow Geese (Anser caerulescens, Linnaeus, 1758 [kangut in Inuktut]) and Ross’s Geese (Anser rossii, Cassin, 1861 [qaaraarjuk in Inuktut]) migrate to the Canadian Arctic tundra to breed (Ryder and Alisauskas 1995). These two species, which have been managed collectively since 1978 (Moser and Duncan 2001), are commonly referred to as “light geese” (Fig. 1).

    Light goose populations, including the Midcontinent Lesser Snow Goose (A. c. caerulescens) and Ross’s Goose populations, have increased significantly since the 1970s (Abraham et al. 2005, Leafloor et al. 2012, Fox and Leafloor 2018, Alisauskas et al. 2022, Canadian Wildlife Service Waterfowl Committee 2022) (Appendix 1). This has resulted from a combination of factors, including a widespread decline in hunting pressure due to reduced numbers of hunters (Ankney 1996, Batt 1997, Jefferies et al. 2003), and the increased use of wildlife refuges and southern agricultural feeding areas by geese during winter (Batt 1997, Jefferies et al. 2003, Abraham et al. 2005). High densities of light geese have altered northern ecosystems (Alisauskas et al. 2006, Leafloor et al. 2012). Overgrazing of shoots, shoot pulling, grubbing of belowground plant parts, nest building, and trampling of vegetation has led to decreases in vegetation biomass and species diversity in the Arctic (Didiuk and Ferguson 2005, Alisauskas et al. 2006, Kellett and Alisauskas 2025), where most Midcontinent Lesser Snow Geese nest (Alisauskas et al. 2011). At the time of publication, in Canada and the United States, light geese remain designated as overabundant (NAWMP 2018, Canadian Wildlife Service Waterfowl Committee 2022).

    Due to rapid environmental change, there is a pressing need to build reliable long-term datasets on wildlife. Traditional and local ecological knowledge gathered through interviews with Indigenous harvesters living in close relationship with wildlife is a key source of information (Huntington 2011, Pardo-de-Santayana and Macía 2015). The resulting qualitative knowledge database can provide information on aspects of wildlife ecology that are not always targeted by the scientific community or are beyond the reach of traditional scientific observations, particularly for wide-ranging species living in remote environments such as the Arctic (Mallory et al. 2003, Huntington 2011, Service et al. 2014). Furthermore, the frequency and geographic scope of wildlife scientific studies are restricted by temporal, budget, and travel restrictions (Mallory et al. 2018). In comparison, Indigenous knowledge includes observations over long and more continuous time series (Martinez-Levasseur et al. 2017).

    In Inuit Nunangat (Inuit homelands in the Canadian Arctic), Inuit have lived near goose colonies for generations, and continue to harvest light geese for their meat, eggs, and plumage (Henri et al. 2020). Inuit knowledge of light geese is gained and shared through personal experience, careful observation, and oral histories (Gagnon and Berteaux 2009, Karetak et al. 2017, Ljubicic et al. 2018). Inuit knowledge includes holistic ecological perspectives that synthesize various elements of wildlife ecology and demography (Mallory et al. 2003, Gilchrist et al. 2005), reflecting a complex web of relationships between people, land, and all living beings (Karetak et al. 2017). In Canada, the inclusion of Indigenous knowledge in resource management is a legal and policy requirement (e.g., Migratory Birds Convention Act, 1994, c. 22; Species at Risk Act, 2002, c. 29). In the territory of Nunavut, Inuit knowledge must be considered equally alongside scientific knowledge in environmental governance and decision-making (Government of Nunavut 2013). The Nunavut Land Claims Agreement requires the co-management of wildlife to ensure that Inuit harvesting rights are upheld, and that Inuit knowledge is considered in decisions affecting Inuit culture, livelihoods, lands, and food security (Government of Canada and Tunngavik Federation of Nunavut 1993).

    In Inuit Nunangat, Inuit harvesting rights are protected through land claims, which extend to federally regulated Migratory Bird Sanctuaries and National Wildlife Areas (Henri et al. 2020). In Nunavut, Migratory Bird Sanctuaries and National Wildlife Areas are co-managed by Area Co-Management Committees (ACMC), which work with the federal government and local Hunters and Trappers Organizations in management decisions (Government of Canada 2014, 2016). In 2016, the Nivvialik and Irniurviit ACMC identified light goose abundance and associated impacts as a key priority, and highlighted the need and opportunity to bring together Inuit and scientific ways of knowing about light goose ecology. These joint priorities led to the creation of the Kangut Project, of which this paper is part (see https://kangut.ca; Carter et al. 2018a,b, Henri et al. 2019, 2020). In the Kivalliq region of Nunavut (our study area), light goose colonies are located near and within three Migratory Bird Sanctuaries (MBS) that are co-managed by the Nivvialik and Irniurviit ACMC: Kuugaarjuk (McConnell River), Ikattuaq (Harry Gibbons), and Qaqsauqtuuq (East Bay) (Fig. 2).

    By combining interviews of 40 light goose harvesters and Elders with results from aerial surveys in the Kivalliq region of Nunavut, we aimed to better understand (1) local light goose phenology and habitat selection, (2) changes in light goose distribution and abundance between the 1940s and 2010s, (3) the effects of increased light goose abundance on ecosystems, and (4) factors driving changes in light goose distribution.

    METHODS

    Author positionality

    Environment and Climate Change Canada (ECCC) project leads (Henri, Johnston, Carter, Smith) worked closely with the Arviat and Salliq Project Management Committees to guide all aspects of research design, implementation, analysis, and reporting (Henri et al. 2019, 2020, Carter et al. 2018a, b). First author Carter coordinated the research, co-led analysis with Martinez-Levasseur, and worked closely with community researchers (Irkok, Saviakjuk, Emiktaut) in facilitating research in Salliq and Arviat. The results and analysis we present also greatly benefited from contributions by a National Wildlife Research Centre Geomatics Research Lab cartographer (Chaudhary), ECCC ornithologists (Baldwin, Alisauskas), a cultural geographer (Ljubicic), and a technical writer (Wong). Our motivation for this project was rooted in the desire to work collaboratively, in a reciprocal relationship, to address community-identified concerns about the impacts of overabundant light goose populations. Authors Irkok, Saviakjuk, Emiktaut, and the Project Management Committees have close, personal ties within their communities of Arviat and Salliq, as well as strong connections with the land and goose colonies around their communities. Authors Carter, Johnston, Henri, Smith, and Baldwin have well-established, long-term, working relationships with Arviat and Salliq community members and organizations. These relationships provided a strong foundation for research co-design, and knowledge co-creation, according to the strengths of both Inuit knowledge and Western science. Established relationships enabled the expansion of the research team where additional support was needed, with mutual commitments to working together for the common good (Healey and Tagak 2014, Carter et al. 2025).

    Study area

    Inuit knowledge was documented in June 2017 in Arviat (61°11’ N, 94°06’ W; population 2657) and in August 2017 in Coral Harbour (Salliq in Inuktut; 64°08’ N, 89°09’ W; population 891), Nunavut, Canada (Fig. 2) (Statistics Canada 2016). These communities were selected due to (1) their proximity to three MBS, and (2) known local experience and concerns about light goose population dynamics. Both communities have a majority Inuit population (≥ 94%) (Statistics Canada 2021).

    Inuit knowledge documentation

    “Inuit Qaujimajatuqangit (IQ) embraces all aspects of traditional Inuit culture, including values, worldview, language, social organization, knowledge, life skills, perceptions and expectations” (Nunavut Department of Education 2007). While Inuit Qaujimajatuqangit was integral to and documented through the Kangut Project, we use the term Inuit knowledge because we are presenting ecological observations and inferences made from natural history observations. We conducted semi-structured individual and group interviews (see Carter et al. 2018a, b for interview questions) with 40 light goose harvesters and Elders from Arviat and Salliq (Table 1) ranging in age from their early 20s to their late 80s, thus providing direct observations that extended back to the 1940s. Audio-recorded discussions were transcribed, and thematic analysis was conducted using NVivo10 (Version 10, 2012) (Creswell 2009).

    During interviews, biogeographical information on light goose distribution (e.g., during nesting, feeding, and migration) and Inuit activities related to light geese (e.g., egg picking, hunting) were recorded using six maps (two at scale 1:250,000 for Arviat and four at scale 1:150,000 for Salliq). Light goose abundance (low, medium, high) was documented for each decade between the 1940s and the 2010s. The National Wildlife Research Centre Geomatics Research Lab digitized field maps and created the final maps using ArcMap (ESRI Inc., Redlands, California, USA). We added a spatial limit of the “range of direct observations” made by interview contributors (Martinez-Levasseur et al. 2017) by merging all polygons drawn by contributors (all observations related to light geese and shorebirds; see full project results in Carter et al. 2018a, b) and adding a 2-km buffer to the new polygon. For specific details on results validation, see Henri et al. (2020). The numbers cited (e.g., 26/40) represent the number of interview contributors who shared similar views on specific topics out of the total number of individuals who responded to the question (details in Appendix 1).

    Aerial photography used to estimate the distribution of nesting light geese

    Methods used to estimate the nesting distribution of Lesser Snow and Ross’s Geese in known colonies are described in detail in Kerbes et al. (2014). Briefly, aerial photography of nesting colonies of Lesser Snow Geese was conducted in June 2003 (Western Hudson Bay), 2004 (Southampton Island), and 2008 (Western Hudson Bay, Southampton Island). Ross’s Goose numbers were estimated at Kuugaarjuk (McConnell River) MBS using air photo and ground data (Kerbes et al. 2014). Note that the time frame of the aerial surveys corresponds to the decades 2000s–2010s of the observations mapped during interviews.

    Literature search

    A snowball and citation search approach was used to search peer reviewed and grey literature sources. First, seminal articles on light geese (e.g., Alisauskas et al. 2022; A. M. Calvert, personal observation) were mined for key references and to inform the development of a search strategy to identify relevant literature (i.e., a list of keywords). This included light goose-specific terms (e.g., light goose phenology, habitat, abundance, trend, competition, predation), and themes such as Inuit knowledge of geese/birds or the effects of environmental changes on migrating species. The search was considered complete once all references in the bibliography of all sources had been explored, and no additional sources could be found. Duplicate records were identified and removed. Forty-two sources published between 1971 and 2022, most corresponding to our study area, were retained and imported into NVivo10.

    Braiding multiple knowledge types

    We strove to braid multiple knowledge types (Kimmerer 2015, Henri et al. 2021, Giroux et al. 2024) throughout project development and implementation, as described in Henri et al. 2020. This approach to knowledge co-production (Yua et al. 2022) guided database analysis (i.e., Inuit knowledge interviews, aerial survey results, and published literature) and results interpretation. The database was analyzed using thematic analysis (i.e., coded and organized according to broad themes: light goose phenology, light goose habitat, effects of increased light goose abundance on ecosystems, changes in light goose abundance, factors driving changes in light goose distribution) associated with our Inuit knowledge interviews and aerial survey results (Creswell 2009). Each broad theme included up to three levels of subthemes (e.g., general theme: effects of increased light goose abundance on ecosystems; subtheme level 1: effects on the land and vegetation; subtheme level 2: effects resulting from foraging; subtheme level 3: foraging method). We identified common and novel themes within and across knowledge types, then compared knowledge types and identified areas that overlapped, conflicted, or were unique.

    Limitations and potential biases

    Although Project Management Committees identified community members with topical expertise (Henri et al. 2020), our results represent a partial sample of all knowledge about light geese held by Salliq and Arviat community members. Thus, additional knowledge may exist that was not documented through this study. Also, the personality and gender of visiting scientist co-facilitator (N. A. Carter, woman), and the loss of information through English/Inuktut interpretation may have influenced responses (Brook and McLachlan 2005). However, interviews were co-facilitated by local, Inuit community researchers (one man and one woman in each community), with support from Carter and expert simultaneous interpreters, to maximize interviewee comfort level and ensure interview contributors could share knowledge in the language of their choice (Henri et al. 2020). Furthermore, prior to the interviews, community researchers translated the interview guide from English into the local Inuktut dialect (Henri et al. 2020), then back into English using a method known as forward and backward translation (Bullinger et al. 1993). This approach ensured that regardless of language, questions were conceptually equivalent.

    RESULTS AND DISCUSSION

    This section is divided into four subsections corresponding to our study objectives: (1) light goose phenology and habitat selection, (2) changes in light goose distribution and abundance between the 1940s and the 2010s, (3) effects of increased light goose abundance on ecosystems, and (4) factors driving changes in light goose distribution. A table summarizing Inuit knowledge results (including more details on numbers of interview contributors and selected quotes) and Western science results is included in Appendix 1.

    Light goose nomenclature, phenology, and habitat selection

    Nomenclature

    In Salliq and Arviat, Lesser Snow and Ross’s Geese were respectively referred to in Inuktut as kanguq (singular) or kanguit (plural) and qaaraarjuk (singular) or qaaraarjuit (plural). Most interview contributors did not distinguish between Snow and Ross’s Geese, and referred to both species collectively as light geese or kanguq/kanguit. Similarly, Alisauskas (2001) reported that the two species are difficult to distinguish from a distance; thus, they have been managed collectively since 1978 (Moser and Duncan 2001). We use “light geese” (Lesser Snow and Ross’s Geese collectively) as our unit of identification and to designate the population of interest.

    Phenology

    Interview contributors observed light geese from the end of April/early May through September (Fig. 3). Four contributors reported that light geese arrive earlier compared to a few decades ago. In the 1970s and 1980s, Snow Geese arrived on the west coast of Hudson Bay between the last week of May and the first week of June (Harwood 1977, Ankney and MacInnes 1978, Ankney 1980, Kerbes et al. 1990). Contributors associated earlier migration with earlier snowmelt, as has also been observed by Inuit regarding other migrating species (Martinez-Levasseur et al. 2021). Contributors noted that light geese lay eggs at least 1 week earlier than in the past. Similarly, Rockwell et al. (2011) reported that hatching dates of Snow Geese breeding at La Pérouse Bay (Manitoba, western Hudson Bay) had advanced by approximately 1 week between the 1960s and the 2000s.

    In the 1970s–1980s, scientists observed that light goose fall migration began in mid-September in the Hudson Bay interior (Mclaren and Mclaren 1982, Richards and Gaston 2018). However, three contributors shared that today, fall migration begins in late September or early October, with light geese and goslings feeding near communities from mid-summer until migration (Fig. 3). This earlier arrival and later departure by high densities of light geese exerts added foraging pressure on the coastal tundra and biodiversity (Abraham et al. 2019; A. M. Calvert, personal observation).

    Habitat selection

    Many contributors (18/40) observed light geese nesting near food sources (vegetation), and described nesting areas as marshy and muddy, located near rivers, lakes, and ponds, and concentrated near the coast. They reported that habitats rich in water bodies (i.e., ponds, lakes, rivers) have fewer predators. One contributor and Alisauskas et al. (2009) reported that habitats rich in water bodies provide escape from terrestrial predators during the brood rearing/moulting phase. During brood rearing, light geese disperse over wide areas up to 40 km inland (Kerbes et al. 1990, Leafloor et al. 2012; A. M. Calvert, personal observation). By dispersing, light geese reduce their grazing pressure at nesting areas (Leafloor et al. 2012).

    Changes in light goose abundance between the 1940s and the 2010s

    Detailed results on light goose abundance, by study site, and specific results for Ross’s Goose abundance, are provided in Appendix 1.

    General trends

    Most contributors (27/40) reported an increase in light goose abundance along the western coast of Hudson Bay and southern Southampton Island over their lifetime (i.e., since the 1940s for the eldest). Since the 1980s on western Hudson Bay, both Inuit observations and aerial surveys (1985–2008) identified decreased local light goose numbers (Fig. S2, Appendix 1). Aerial surveys showed that over the 1985–2008 period, the population decreased by 41% from an estimated 420,000 to 246,300 birds. One Salliq contributor reported a recent decline on Southampton Island, as did scientists (Alisauskas et al. 2022). Likewise, Snow Goose declines were reported by scientists in other breeding subpopulations (e.g., Karrak Lake in Canada’s central Arctic) (Weegman et al. 2022, Alisauskas et al. 2024).

    Trends in colonies

    Interview contributors noted that the number of nesting light geese has significantly decreased in Kuugaarjuk MBS near Arviat (Fig. 2-A) and Qaqsauqtuuq MBS near Salliq (Fig. 2-C) since the 1960s and 1990s, respectively. Similarly, aerial surveys at Kuugaarjuk MBS revealed a 79% decrease in nesting birds between 1973 and 2008 (Fig. S2, Appendix 1). Scientists reported that birds have nested at Kuugaarjuk MBS since at least 1941 (MacInnes and Kerbes 1987). Surveys conducted in 1977 showed that most geese had moved elsewhere (Kerbes et al. 1990). Similarly, three contributors said that high densities of light geese nesting at Kuugaarjuk MBS resulted in overgrazed lands, which forced geese to move elsewhere in search of forage—a phenomenon also recorded by scientists, first at the end of the 1960s (Lieff 1973). The coastal salt marshes of western and southern Hudson Bay, including Kuugaarjuk MBS, are sensitive to goose foraging pressure due to their unique soil and vegetation characteristics, low diversity of organisms, and small size (A. M. Calvert, personal observation). Furthermore, in addition to local breeding colonies, the west coast of Hudson Bay is grazed by many migrating geese that stage there in spring (Abraham et al. 2005; A. M. Calvert, personal observation). Other causes, including disease outbreaks and spring droughts, could have also been involved in the decline of light geese at Kuugaarjuk (McConnell River) MBS (Kerbes et al. 1990).

    Colony-specific trends in abundance were more difficult to assess from aerial surveys of Southampton Island because the Qaqsauqtuuq and Salliq colonies were not distinguished in the counts after the colonies expanded to the point where their borders merged in 2008 (Fig. S5, Appendix 1). For both colonies combined, the total number of birds increased by 43% between 1997 (156,700) and 2008 (223,400). In the East Bay region, an extensive decline in vegetation between 1979 and 2010 (Abraham et al. 2019) was due to persistent long-term foraging by light geese, as reported by eight Salliq contributors. Two contributors reported that the number of light geese at Ikattuaq MBS (Fig. 4) was still high, and the land was less overgrazed compared to the Qaqsauqtuuq MBS colony. Aerial surveys revealed that Ikattuaq MBS, including Ell Bay, and its surrounding areas (Boas River) still had, in 2008, the largest colony of Snow Geese (644,000) on Southampton Island.

    Contributors reported that the deterioration of breeding ground habitats in some colonies might have induced the movement of birds toward their communities. Around Arviat (Fig. 5), shifts in nesting areas farther north (toward Maguse River) and south (south of McConnell River) were also reported by Kerbes et al. (2006). In 1973, the first record of 1000 nesting light geese was made using aerial surveys around Maguse River (Kerbes 1975, Kerbes et al. 2006). By 2008, the nesting population had increased to 111,500 birds (Fig. S2, Appendix 1). The Nivvialik ACMC—which has management responsibility for Kuugaarjuk MBS—has expressed interest in reviewing the MBS boundaries in response to these changes (Nivvialik Area Co-Management Committee, personal observation). On Southampton Island (Fig. 4), five contributors, as well as scientists (Abraham and Ankney 1986, Kerbes et al. 2006), reported that the Salliq colony (nearest to the community) had become established by the mid-1980s. While aerial surveys in 1997 estimated 11,900 light geese breeding at this colony (Kerbes et al. 2006), four contributors noted light geese had been nesting there only since the 2010s. Finally, recaptures indicated that light geese have emigrated from declining colonies in our study area to other Arctic colonies, especially on Baffin Island, Nunavut (Alisauskas et al. 2022). Three Salliq contributors noted that some migrating light geese observed in their area are on their way to Baffin Island.

    Effects of increased light goose abundance on ecosystems

    Effects on the land and vegetation

    Most contributors (27/40) highlighted how light geese have changed the land through removal of vegetation by grazing, grubbing, and nesting. One contributor reported that when light geese build nests, they cause a substantial impact due to the quantity of moss, lichen, grasses, and twigs used.

    Habitat and vegetation changes caused by light geese have been the focus of intensive scientific research since the 1970s (A. M. Calvert, personal observation). The main factors predicting the severity of habitat alteration by light geese are the season, foraging method (Fig. 3), and density of birds (A. M. Calvert, personal observation). In the salt marshes of coastal Hudson Bay, decades of foraging by increasing numbers of geese have led to changes such as a reduction in vegetation, exposure of underlying sediment, and changes in soil chemistry (A. M. Calvert, personal observation). Abraham et al. (2019) reported that in Qaqsauqtuuq MBS, persistent long-term cumulative foraging pressure by multiple species of geese induced significant declines in graminoids that are preferred by geese as forage, and declines in lichen and willow cover, resulting in a drastic decrease in plant species richness and diversity. One contributor, as well as Kellett and Alisauskas (2022), reported that goose-induced habitat changes are part of a long-term natural cycle wherein the land replenishes itself. Though some freshwater sites have shown signs of recovery within 5–10 years, the recovery of vegetation in salt marshes can take more than 20 years (Jefferies et al. 2006; A. M. Calvert, personal observation).

    Interview contributors mentioned light goose feces when discussing the effects of increased numbers of light geese on the land. Contrasting views included goose droppings fertilizing and replenishing soils with nutrients versus droppings contaminating the land by introducing pollutants. Bird species with longer migration distances tended to have higher pesticide levels in their feathers (Xiao et al. 2023), suggesting that migratory birds might play a role in the transport of pollutants. These findings highlight the importance of studying the levels of contaminants, including pesticides, in different organs of light geese because they are an important food source for Inuit.

    Interactions with other wildlife

    Two Arviat contributors were concerned about the decrease in other goose species (i.e., Cackling Goose [Branta hutchinsii]). However, Cackling Geese had greater nest survival inside a Ross’s Goose colony than outside it in the McConnell River area, unless surrounded by a very high density of Ross’s Goose nests (Baldwin et al. 2011; A. M. Calvert, personal observation). Around Salliq, Ross’s Geese were reported to be “invading” and “pushing out” Snow Geese. While one contributor reported no interactions between shorebirds and light geese, explaining that their habitats differed, another reported that Red Phalaropes (Phalaropus fulicarius) were no longer seen around Salliq, having moved to new areas due to light goose abundance, which has resulted in species competition for space/food.

    Scientists reported that changes in the availability of nesting material and sites, reduced food sources, and altered prey–predator dynamics might explain declines of local breeding birds (A. M. Calvert, personal observation) such as shorebirds, other goose species, and songbirds (Jefferies et al. 2003, Abraham et al. 2005, 2019, Flemming et al. 2016, 2019, 2022, Lamarre et al. 2017; A. M. Calvert, personal observation). In general, overabundant light geese have been affecting sympatric fauna through “bottom-up” effects of habitat alteration and “top-down” changes in predator–prey dynamics (A. M. Calvert, personal observation). Three contributors reported that numbers of light goose predators (i.e., polar bears, gulls, raptors, foxes) had increased since the 2000s. Increasing predation on light goose eggs and goslings by Herring Gulls (Larus argentatus) has been reported in western Hudson Bay (Sammler et al. 2008). In the same area, predation of Snow Goose nests by polar bears might result from the increasing overlap between ice-free sea conditions and the light goose breeding season (Rockwell et al. 2011, Gormezano and Rockwell 2013; A. M. Calvert, personal observation). On the other hand, the increased light goose abundance has led to a healthier fox population, as reported by an Arviat contributor. In Bylot Island MBS (Qikiqtaaluk region, Nunavut), probabilities of successful fox reproduction increased with proximity to goose colonies, especially during periods of low lemming abundance (Giroux et al. 2012, Flemming et al. 2016).

    Finally, eight contributors noted that light geese and caribou compete for food and space. A recent review of caribou diet revealed that in warmer seasons, caribou consume graminoids and berries, as do light geese (Prevett et al. 1979, Webber et al. 2022). Two contributors said that migrating caribou herds damage land used by light geese. A contributor explained that light geese defecate on the vegetation that caribou consume, which could cause caribou to become diseased. Tugend (2017) reported that during the light goose breeding season, geese and caribou share the same land, which in turn has affected both species.

    Effects on people

    Six contributors expressed frustration about light geese feeding heavily on berries (Fig. 3). Prevett et al. (1979) and Jefferies et al. (2003) indicated that 18% of the diet of Snow Geese staging in the Hudson Bay Lowland at the start of the fall migration consists of seeds and berries. Two contributors expressed concern about the negative impacts of increased goose droppings on freshwater bodies (e.g., contamination by Escherichia coli). Light goose feces contribute to changes in water chemistry, including an increase in nitrogen and phosphorus, in ponds or lakes adjacent to nesting colonies (Tugend 2017, Mariash et al. 2018; A. M. Calvert, personal observation).

    On a more positive note, 11 contributors explained that abundant light geese and eggs near their communities has reduced harvest costs and allowed families to access some goose hunting and nesting grounds on foot. Opportunities to share light geese with food-insecure households and regions, and with other Nunavut communities that do not have light goose colonies, were described by contributors as a benefit of local light goose abundance. In Salliq, beneficial impacts also included opportunities for recreational hunting, commercial harvesting and processing of light goose meat and down, and expansion of local outfitting and bird-watching businesses.

    Factors driving changes in light goose distribution

    Interview contributors (19/40) reported that habitat loss due to overgrazing has pushed light geese to abandon altered habitats in favor of intact breeding and foraging sites, as reported on the west coast of Hudson Bay in the 1970s and 1980s, and in central and eastern Arctic areas (Kerbes et al. 1990, Aubry et al. 2013, Alisauskas et al. 2022). To avoid the use of heavily degraded habitats, which results in reduced clutch size, egg size, and gosling growth, size, and survival (Abraham et al. 2005, Aubry et al. 2013; A. M. Calvert, personal observation), light geese have displayed density-dependent changes in foraging behavior and breeding site fidelity (Aubry et al. 2013, Wilson et al. 2016; A. M. Calvert, personal observation). Between 2006 and 2015, Lesser Snow Geese (typically male breeding and juvenile geese) emigrated from the degraded habitats of the central (Queen Maud Gulf) and eastern Arctic (James Bay, La Pérouse Bay, Southampton Island), mostly toward the Baffin Island subpopulation (Alisauskas et al. 2022). According to scientists, spatial adjustments by light geese appear to have had a larger influence on their distribution and regional abundance than have previous unsuccessful human attempts to liberalize harvest regulations as a way to control population growth (Alisauskas et al. 2011, 2022). This concurs with Inuit knowledge about natural cycles of population restoration reported by one contributor.

    Ten contributors described predator avoidance as influencing goose distribution. Lima (2009) similarly reported that as a response to increased predation, light geese might increase their anti-predatory behavior and vigilance, leading to chronic stress and reduced foraging. When bird breeding areas are populated with numerous predators, birds may choose to nest, abandon their nest, or forego nesting (Lima 2009). Five contributors reported that food and space competition (i.e., among goose species, other bird species, or mammals) influenced light goose distribution, and seven contributors reported that increasing human activity did (i.e., increased noise due to all-terrain vehicles, cars, trucks, and heavy equipment). Inuit in Pond Inlet (Qikiqtaaluk region, Nunavut) have also reported that disturbance from hunting activities, including noise from snowmobiles and rifles, impacted Greater Snow Goose distribution and abundance (Gagnon and Berteaux 2009). Other emerging issues, including disease (e.g., avian cholera), have the potential to affect light goose abundance and distribution (Alisauskas 2001).

    Climate change-induced phenomena were reported by 10 contributors as drivers of light goose distribution. Warmer-than-average winters and summers can result in earlier spring snowmelt and increased incidence of dried up ponds or lakes, respectively (Campbell et al. 2018), the latter of which has also increased due to isostatic rebound (Bos and Pellatt 2012). This phenomenon not only reduces the area available for suitable nesting habitats, but it also makes it more difficult for goslings to access drinking water and hydrate, particularly during abnormally warm summers (Aubry et al. 2013). Major declines in protein reserves acquired at spring staging areas, likely due to advancing springs and habitat alternation, might affect Lesser Snow Geese recruitment and thus be contributing to overall population declines (Baldwin et al. 2022, Alisauskas et al. 2024). One contributor explained that snowmelt created over-flooded grounds, causing light geese to find a drier place to nest locally or to alter their migration (i.e., how, when, and where they migrate). Arctic warming temperatures have extended the gap between light goose migration timing (and indirectly hatch timing) and seasonal peaks in vegetation quality (Aubry et al. 2013). This “mismatch” could in turn affect gosling development due to a lack of required nutrients (Aubry et al. 2013, Ross et al. 2018). As explained previously, when sea ice breakup occurs increasingly earlier, polar bear predation on light goose colonies is predicted to continue to increase (Smith et al. 2010). Scientists have reported that Ross’s Geese seem to be more resilient to environmental change, including extreme weather or degraded habitat, than Snow Geese (Baldwin et al. 2022). Ross’s Goose nests are well structured and provide more insulation for developing embryos and less exposure to inclement weather compared to Snow Goose nests (McLandress 1983, McCracken et al. 1997, Weegman et al. 2022). Furthermore, Ross’s Geese have a smaller bill size and faster pecking rate than Snow Geese, which allows Ross’s Geese to more easily graze cropped vegetation (Pezzanite 2003, Abraham et al. 2005) and acquire sufficient resources on degraded lands (Abraham et al. 2005, Alisauskas et al. 2006). Finally, it is important to note that contributors (16/40) viewed distributional or abundance changes as normal animal behavior, and not unique to light geese or situations of light goose overabundance.

    Research recommendations

    Additional participatory methods, including conducting proportional piling exercises for different time periods and within the range of direct observations of Inuit (Martinez-Levasseur et al. 2017, Tomaselli et al. 2022) could be used in the future to better understand subpopulation trends based on interviews. Knowledge gathered through interviews, which can provide information from past observations, can be combined with contemporary light goose monitoring, led by trained local Inuit, to identify potential changing trends. In the Kivalliq region, community-based monitoring projects have become essential to capture local changes in specific light goose subpopulations because aerial photographic surveys conducted by the United States Fish and Wildlife Service and the Canadian Wildlife Service were discontinued around 2010 (F. Baldwin, Canadian Wildlife Service, personal communication). Regular monitoring is difficult to maintain due to the enormous geographic extent and remoteness of Arctic nesting goose populations, and to issues associated with survey timing, coverage, and cost. Consequently, within the Kivalliq region, at the time of the study, Inuit observations were the only available source of knowledge for detecting and reporting local trends in light goose abundance and distribution. While banding of light geese occurs across several sites in the Arctic, recent work has shown that there are dramatic differences in demography of light goose populations at the regional scale due to variations in adult and juvenile survival rates and differences in probability of movement between colonies. This highlights the importance of Inuit perspectives on the local population status of light geese because such knowledge can occur at frequencies and scales that are simply not possible under current migratory bird monitoring programming. Note that bird banding resumed in 2022 through 2024 near Arviat and Coral Harbour (F. Baldwin, Canadian Wildlife Service, personal communication). Furthermore, in the Arviat region, bird banding has become part of a community-led and community-engaged project on different species of geese, including light geese, involving many co-authors (see https://straightupnorth.ca/goose-monitoring-to-restore-inuit-food-sovereignty/).

    CONCLUSION

    Braiding diverse knowledge systems generates an enriched body of evidence on light goose population dynamics under a changing climate and broadens the spectrum of solutions that can support environmental decision-making and stewardship at multiple scales. Inuit in the Kivalliq region of Nunavut, Canada hold broad and detailed knowledge related to light goose distribution, abundance, habitat effects, and interactions with co-occurring animals and people. In addition, Inuit knowledge and the knowledge produced through Western scientific methods and tools frequently provide complementary long-term, place-specific observations of light geese. Most published scientific studies of light goose phenology in the Kivalliq region date from the 1970s and 1980s; Inuit observations add to this record with an additional 40 years of observations extending to the present day. The frequency and geographic scope of light goose aerial surveys, monitoring, banding, and other scientific studies is constrained by temporal, budget, travel, and other restrictions (Mallory et al. 2018). In comparison, Inuit knowledge includes, on a local scale for areas accessible from the nearest community, observations over long and more continuous time series. An opportunity exists for Inuit communities to lead studies that address local research priorities and monitor local changes (CAFF 2021), such as light goose phenology, particularly in the context of rapid environmental change (Ross et al. 2018, Baldwin et al. 2022).

    By combining Inuit knowledge with aerial surveys and a review of the existing scientific literature, we elucidated changes in light goose distribution and abundance between the 1940s and the 2010s in the Kivalliq region of Nunavut, explored the effects of light geese on local ecosystems, and increased understanding of the factors driving these changes. Furthermore, we were able to better comprehend ways in which climate change is affecting light goose colonies (e.g., changes in timing of migration and phenology, increases in predator numbers). In the future, light goose colonies identified in this study could be further monitored through community-based monitoring programs led by local Inuit (e.g., banding programs, colony monitoring, colony observations using mobile applications such as SIKU [the Indigenous knowledge social network: https://siku.org]) (CAFF 2021). Future projects could also involve further Inuit knowledge documentation, as well as ecological data collection through Western ecological science methods. Finally, we provide a basis for Area Co-Management Committees to use Inuit knowledge in the development or update of management plans in Migratory Bird Sanctuaries. Inuit knowledge inclusion, leadership, and guidance when conducting research is fundamental to a multifaceted and holistic understanding of wildlife population dynamics, particularly in a changing Arctic.

    RESPONSES TO THIS ARTICLE

    Responses to this article are invited. If accepted for publication, your response will be hyperlinked to the article. To submit a response, follow this link. To read responses already accepted, follow this link.

    AUTHOR CONTRIBUTIONS

    Natalie A. Carter and Laura M. Martinez-Levasseur have contributed equally to this work and are recognized as co-first authors.

    ACKNOWLEDGMENTS

    First and foremost, the authors would like to acknowledge the Salliq and Arviat residents who participated in this study as interview and group discussion contributors, and generously shared their knowledge and experience about light geese in the Kivalliq region (in alphabetical order): Matthew Adams, Evano Aggark Sr., David Aglukark Sr., Peter Alareak, Louie Angalik, John Aupaq, Dino Bruce, Bobby Eetuk, Ayowna Emiktaut, Leo Ikakhik, Paul K. Irksuk, Noah Kadlak, Johnny Kataluk, Luke Kinniksie, George Kuksuk, Jimmy Main, Catherina Manik, Jacque John Mikiyungiak, Josiah Nakoolak, Lucassie Nakoolak, Marguerite Nakoolak, Pauloosie Nakoolak, Peter Nakoolak, Willie Nakoolak, Leonard Netser, Arden Nibgoarsi, Bobby Saviakjuk, Joe Saviakjuk, Mark Paniyuk, Jerry Paniuq, Danny Pee, Lizzie Pootoolik, Joe Savikataaq Sr., John Sikikauk, Melanie Tabvahtah, Timothy Taleriktok, and five contributors who wished to remain anonymous. This research was conducted as a partnership between Environment and Climate Change Canada, the Nivvialik and Irniurviit Area Co-Management Committees, and the Arviat and Aiviit Hunters and Trappers Organizations. We acknowledge the significant contribution of the Project Management Committee (PMC) members who participated in project planning and implementation: (Salliq PMC members) Noah Kadlak, Ron Ningeongan, Moses Nakoolak, Casey Paniyuk, and Tapia Jar; (Arviat PMC members) David Aglukark Sr., Angelina Suluk, and Gordy Kidlapik. We would also like to thank Shelton Nipisar (community researcher); Bobby Suluk, Angelina Suluk, Suzie Napayok-Short, and the community researchers (interpreting/translation); Natasha Hattie Ottokie, Louisa Kalai, Andrea Ishalook, Mary Issumatardjuak, Qovik Netser, Toghwemu Akande, the Kivalliq Wildlife Board, and the Nunavut Inuit Wildlife Secretariat (administrative support); Andrew Murray, Jon Pasher, and Jason Duffe from the National Wildlife Research Centre Geomatics Lab (ECCC mapping support); Matilde Tomaselli (technical support); Nickia McIvor for her beautiful illustration (Fig. 3); Richard H. Kerbes and Katherine M. Meeres (for compiling and analyzing aerial survey data of light geese; Kerbes et al. 2014); Jean-François Dufour, Hamlet of Arviat, Hamlet of Salliq, Arctic College, Sakku School, Troy Netser, and the Government of Nunavut Department of Environment (logistical support). Trailmark Systems (P. Evans, D. King, B. Keats, and J. Tews) assisted with editing earlier versions of this manuscript. The authors wish to acknowledge the financial support of Environment and Climate Change Canada, the Nunavut Wildlife Management Board, and the Nunavut General Monitoring Plan. We would like to thank the reviewers whose feedback strengthened this manuscript. This project was conducted under Nunavut Scientific Research License 0301517N-M.

    Use of Artificial Intelligence (AI) and AI-assisted Tools

    The authors of this manuscript declare that in the process of this work, no generative artificial intelligence (AI) or AI-assisted technologies were used.

    DATA AVAILABILITY

    The data and code supporting the findings of this study are available upon request to the corresponding author [DAH]. None of the data and code are publicly available because of restrictions [they contain information that could compromise the privacy of research participants]. Ethical approval for this research study was granted by the Nunavut Research Institute [Nunavut Scientific Research License 0301517N-M].

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    Corresponding author:
    Dominique Henri
    dominique.henri@ec.gc.ca
    Appendix 1
    Fig. 1
    Fig. 1. Blue (left) and white (right) morph adult Snow Geese in their Arctic breeding area (Credit: Frank Baldwin).

    Fig. 1. Blue (left) and white (right) morph adult Snow Geese in their Arctic breeding area (Credit: Frank Baldwin).

    Fig. 1
    Fig. 2
    Fig. 2. Study area. Thick black rectangles correspond to the study area in the Kivalliq region of Nunavut, Canada. Hatched areas correspond to the Migratory Bird Sanctuaries (MBS) located within our study area: (A) Kuugaarjuk (McConnell River) MBS located near the community of Arviat, and (B) Ikattuaq (Harry Gibbons) and (C) Qaqsauqtuuq (East Bay) MBS, both located on Southampton Island near the community of Salliq. Black dots outside rectangles indicate other communities. Map created using ESRI's geographic information system software ArcPro 2.8.3.

    Fig. 2. Study area. Thick black rectangles correspond to the study area in the Kivalliq region of Nunavut, Canada. Hatched areas correspond to the Migratory Bird Sanctuaries (MBS) located within our study area: (A) Kuugaarjuk (McConnell River) MBS located near the community of Arviat, and (B) Ikattuaq (Harry Gibbons) and (C) Qaqsauqtuuq (East Bay) MBS, both located on Southampton Island near the community of Salliq. Black dots outside rectangles indicate other communities. Map created using ESRI's geographic information system software ArcPro 2.8.3.

    Fig. 2
    Fig. 3
    Fig. 3. Light goose phenological calendar and the related Inuit harvesting calendar. Note that interannual variations occur. © Nickia McIvor.

    Fig. 3. Light goose phenological calendar and the related Inuit harvesting calendar. Note that interannual variations occur. © Nickia McIvor.

    Fig. 3
    Fig. 4
    Fig. 4. Distribution and temporal change in high-density areas of light geese (Snow and Ross’s Geese) in the Salliq area (southern Southampton Island) according to observations from 21 Salliq interview contributors. Each polygon represents knowledge contributed by one or more interviewees during individual and/or group interviews (therefore, darker areas indicate that many contributors made a similar spatial observation and not that higher numbers of geese were observed). Note that the areas include both nesting and brood-rearing areas, which are also used by nonbreeding geese. The boundary of the range of direct observations was obtained by merging all polygons drawn by contributors (observations made between the 1940s and the 2010s) and adding a 2-km buffer to the new polygon. Map created using ESRI’s geographic information system software ArcPro 2.8.3 (cartographic basemaps: Atlas of Canada National Scale Data 1:15,000,000; projection NAD_1983_Canada Atlas Lambert WKID 3978; data source: EPSG).

    Fig. 4. Distribution and temporal change in high-density areas of light geese (Snow and Ross’s Geese) in the Salliq area (southern Southampton Island) according to observations from 21 Salliq interview contributors. Each polygon represents knowledge contributed by one or more interviewees during individual and/or group interviews (therefore, darker areas indicate that many contributors made a similar spatial observation and not that higher numbers of geese were observed). Note that the areas include both nesting and brood-rearing areas, which are also used by nonbreeding geese. The boundary of the range of direct observations was obtained by merging all polygons drawn by contributors (observations made between the 1940s and the 2010s) and adding a 2-km buffer to the new polygon. Map created using ESRI’s geographic information system software ArcPro 2.8.3 (cartographic basemaps: Atlas of Canada National Scale Data 1:15,000,000; projection NAD_1983_Canada Atlas Lambert WKID 3978; data source: EPSG).

    Fig. 4
    Fig. 5
    Fig. 5. Distribution and temporal change in high-density areas of light geese (Snow and Ross’s Geese) in the Arviat area (western Hudson Bay) according to observations from 19 Arviat interview contributors. Each polygon represents knowledge contributed by one or more interviewees during individual and/or group interviews (therefore, darker areas indicate that many contributors made a similar spatial observation and not that higher numbers of geese were observed). Note that polygons include both nesting and brood-rearing areas, which are also used by nonbreeding geese. The boundary of the range of direct observations was obtained by merging all polygons drawn by contributors (observations made between the 1940s and the 2010s) and adding a 2-km buffer to the new polygon. Map created using ESRI’s geographic information system software ArcPro 2.8.3 (cartographic basemaps: Atlas of Canada National Scale Data 1:15,000,000; projection NAD_1983_Canada Atlas Lambert WKID 3978; data source: EPSG).

    Fig. 5. Distribution and temporal change in high-density areas of light geese (Snow and Ross’s Geese) in the Arviat area (western Hudson Bay) according to observations from 19 Arviat interview contributors. Each polygon represents knowledge contributed by one or more interviewees during individual and/or group interviews (therefore, darker areas indicate that many contributors made a similar spatial observation and not that higher numbers of geese were observed). Note that polygons include both nesting and brood-rearing areas, which are also used by nonbreeding geese. The boundary of the range of direct observations was obtained by merging all polygons drawn by contributors (observations made between the 1940s and the 2010s) and adding a 2-km buffer to the new polygon. Map created using ESRI’s geographic information system software ArcPro 2.8.3 (cartographic basemaps: Atlas of Canada National Scale Data 1:15,000,000; projection NAD_1983_Canada Atlas Lambert WKID 3978; data source: EPSG).

    Fig. 5
    Table 1
    Table 1. Numbers of light goose knowledge holders interviewed.

    Table 1. Numbers of light goose knowledge holders interviewed.

    Total Salliq Arviat
    All 40 21 19
    Women 7 4 3
    Men 33 17 16
    Individual interviews 27 17 10
    Group interviews 5 2 3
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    bird population dynamics; braiding knowledge systems; environmental change; Indigenous knowledge; Inuit knowledge; light geese; migratory bird sanctuary; population trends; Ross’s Goose; Snow Goose

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