INTRODUCTION

Knowledge about the distribution and abundance of organisms is a fundamental goal of ecology (Krebs 2009). Trajectories of population abundance over time can provide an important measure of population health (Nichols and Hines 2002), which might be particularly desirable for populations in which exploitation rates by hunting are prescribed in relation to stated conservation goals (Anderson et al. 2018). Ideally, the gold standard for inference drawn about population change is based on robust and unbiased estimates of numerical abundance over time. The quality and availability of such information may relate to the effort and expense of sampling populations, and to the desired spatial scale of inference. However, alternative approaches to measuring population change may be more cost-effective. Detecting change in distribution at various spatial scales may provide a reasonable and less-expensive alternative to numerical estimates of abundance for understanding if and how populations change over time and space.

The midcontinent population of Lesser Snow Geese (Anser caerulescens caerulescens) and North American population of Ross’s Geese (Anser rossii), collectively known as “light geese,” breed in sympatric nesting colonies in Canada’s central and eastern Arctic and subarctic regions (Alisauskas et al. 2022, Jónsson et al. 2024). Both populations have shown exponential growth in abundance over the last few decades (Alisauskas et al. 2018a, b) and have been the focus of continental management efforts to reduce population size (Alisauskas et al. 2011, Leafloor et al. 2012).

Various methods have been used to infer population trajectory for light geese at different scales. For example, general inference about range-wide trajectory of midcontinent snow geese has been drawn from abundances estimated using Lincoln’s (1930) method that relies on information about absolute range-wide harvest and fraction of the population harvested using marked individuals (Alisauskas et al. 2009, 2011, 2012, Cooch et al. 2021). Counts of light geese have been used during winter to provide an alternative range-wide index of abundance, but midwinter counts of light geese have been criticized as being inconsistent and problematically biased (Eggeman and Johnson 1989, Alisauskas et al. 2011). Colony specific abundance has been estimated using aerial photography to measure colony area and nesting density of light geese in much of the breeding range, but coverage across this range is incomplete (Kerbes et al. 2014).

Herein, we document spatial dynamics in colony size of sympatric Ross’s and Lesser Snow Goose breeding colonies in the central Canadian Arctic south of Queen Maud Gulf, Nunavut. We demonstrate and propose that simply mapping spatial extent of terrestrial habitat (i.e., excluding open water within colony boundaries) used by colonial, Arctic-nesting Ross’s and Lesser Snow Geese can provide a cost-effective and tractable alternative index for reasonable inference about colony-specific population change.

METHODS

Study area

Methods described below were applied in the ~63,655 km² Ahiak-Queen Maud Gulf Migratory Bird Sanctuary (A-QMGMBS), Nunavut, comprising 10.3% offshore marine waters, 18.6% freshwater lakes and rivers, and 71.1% terrestrial habitat. In turn, terrestrial habitat comprises 28.6% hydric lowland tundra, 30.7% xeric upland tundra, and 11.8% exposed substrates, i.e., mineral or peat (Didiuk and Ferguson 2005, Environment and Climate Change Canada 2019, Alisauskas et al. 2024). This area was designated as a Migratory Bird Sanctuary in 1961 and recognized in 1982 under the Ramsar Convention as the second largest wetland of international importance. The sanctuary was established, in part, because of its importance to a rich array of migratory birds, in particular waterbirds, including the formerly rare Ross’s Goose (Alisauskas et al. 2024). This large area is especially attractive to waterfowl because of its location in a wide zone of postglacial marine transgression, extending over 230 km inland south of Queen Maud Gulf and spanning over 350 km west-east (Bird 1967). The area supports numerous lakes with islands previously favored by nesting Ross’s Geese (Kerbes 1978), and vast expanses of mesic and hygric sedge- and graminoid-dominated wetlands and tundra (Didiuk and Ferguson 2005) favored by Ross’s and Lesser Snow Goslings (Slattery and Alisauskas 2007).

Ross’s and Lesser Snow Geese at Karrak Lake

Multidecadal research on the population biology of nesting Ross’s and Lesser Snow Geese has been conducted in A-QMGMBS annually at Karrak Lake (67.25 N, 100.25 W) from 1991 to 2019 (Alisauskas et al. 2024). Each year from 1993 to 2019, we estimated nesting abundance for each of Ross’s and Snow Geese at the Karrak Lake colony, based on (i) spatial extent of terrestrial habitat within annual colony boundaries, and (ii) density of nesting geese within this spatial extent.

Nesting colony perimeter was determined each year from a helicopter flying along the boundary ~200 m above ground and mapped onto 1:250,00 scale National Topographic System maps during flight. This defined the extent of a sampling frame for measuring nesting density as referenced by the Universal Transverse Mercator (UTM Zone 14) system. Subsequently, area of terrestrial habitat, i.e., excluding water bodies, was determined with a Geographic Information System (GIS) using a digital habitat basemap classified by Didiuk and Ferguson (2005) based on 7 LANDSAT5 Thematic Mapper images spanning 1986–1992. All calculations of area for terrestrial habitat within colony boundaries (i.e., excluding open water) were made from a GIS study area that included the entirety of the A-QMGMBS with an Albers Equal Area projection (based on the Clarke 1866 ellipsoid) with first and second parallels of 62.25° and 68°, respectively, and longitude and latitude for true origin of 102° and 67.25°, respectively.

An annual sampling frame was composed of nest sampling plots restricted to terrestrial habitat, and of either 20 m (1993–1996) or 30 m (1997–2019) radius spaced either 0.5 or 1.0 km apart using easting and northing coordinates in the UTM system Zone 14. Nest sample plots were searched annually for new nests, whether active or failed, and plots were either (1) initiation plots visited every fourth day during egg-laying and every ~5 days during incubation or (2) incubation plots visited after egg-laying at least once. Complete details of separate post-stratified estimation of nesting density of Ross’s and Snow Geese are described by Alisauskas et al. (2012, 2024), but this paper is focused on aggregate abundance of both species of light geese. Thus, the essence for estimating annual abundance of light geese, T, that attempt to nest in the colony is a function of goose density D = 2∙nests/km², and terrestrial area of the colony in km², A, such that T = D ∙ A to infer combined abundance of Ross’s and Lesser Snow Goose individuals instead of nests.

Other mainland goose colonies south of Queen Maud Gulf

Annual research activities at Karrak Lake provided opportunities to visit other known colonies with a helicopter as well as to detect and document previously unknown colonies (see also Alisauskas and Boyd 1994, Kerbes et al. 2014). At such colonies, colony perimeters were mapped from a helicopter in a similar fashion to the annual mapping of Karrak Lake, but ground sampling of goose nesting densities was not conducted. However, estimates of nesting abundance for many of the colonies were available for a select number of years (1965–1967, 1976, 1982, 1988, 1998, 2005–2006) from aerial photography (Kerbes et al. 2014). In addition to flights of colony perimeters for this study (from 1993 to 2019), colony boundaries for estimating Snow and Ross’s Goose abundance from aerial photography by Kerbes et al. (2014 and references therein) were digitized and imported into the GIS study area with the same projection described above.

Lincoln’s range-wide estimate of midcontinent Lesser Snow Geese

As a comparison to time series of abundance and size of colonies in A-QMGMBS, we estimated range-wide abundance of adult midcontinent Snow Geese (see Alisauskas et al. 2009, 2011, 2022) following Lincoln’s (1930) method. Briefly, the method provides annual range-wide abundance estimates for year i, N̂_i, which are derived from estimates of absolute harvest, Ĥ_i, and harvest rate, ĥ_i, of banded birds recovered by hunters, following N̂_i = Ĥ_i/ĥ_i.

Relationship between colony size and area

We used PROC GLM in SAS (Statistical Analysis System 2023) to model variation in numerical abundance of nesting geese/colony, T, based on method of estimation, M, [aerial photography (Kerbes et al. 2014) vs ground plots (Alisauskas et al. 2024)] as a function of colony area, A, with an interaction effect between method and colony area, M*A. For the four models considered, we used an information theoretic approach for comparing model quality (Appendix 1) based on model fit and number of parameters (Burnham and Anderson 2002).

RESULTS

Between 1993 and 2019, spatial extent (including land and water) of 13 mainland colonies was determined by helicopter (Fig. 1) with special emphasis on eight colonies that were the largest and each with ≥ 10 years of mapping. All these colonies showed an initial growth phase up until 2005–2011. The largest (Colony 3 at Karrak Lake, Colony 9 on the upper Simpson River, Colony 10 east of McNaughton Lake, but also Colony 46 west of McNaughton Lake, Colony 68 near Atkinson point) had grown exponentially in coverage of terrestrial habitat to such a degree that they coalesced with or absorbed colonies that surrounded them initially (Kerbes et al. 2014; Fig. 2). During this same period of general expansion of established colonies, there was additional colonization of mainland areas in the Sanctuary, mostly along the coast of Queen Maud Gulf. Thereafter, these newly established coastal colonies found from 2000 to 2005 were ephemeral, as all had become extinct by 2019. As well, all eight of the largest major colonies that occupied mainland terrestrial habitat surrounding lakes declined in size with some of the smaller colonies approaching or also reaching extinction by 2019 (Figs. 1, 2).

The general pattern of exponential increase in terrestrial habitat occupied by colonies up to about 2010, followed by general decline was evident from the time series of available measurements (Fig. 3A); this dynamic corresponded to the range-wide estimate of numerical abundance of midcontinent Lesser Snow Geese. On the other hand, nesting densities showed an overall monotonic decline from the 1960s until 2019 (Fig. 3B); most aerial photographic estimates of density were available only until 2005–2006, while estimates from ground plots at Karrak Lake spanned 1993 to 2019, thus providing 14 years of overlap between the two methods. This decline in nesting density occurred over the entire period of general population increase in the region before about 2010 and continued to decline during the period of apparent population collapse thereafter.

Most spatiotemporal variation (91%) in colonial nesting abundance of Ross’s and Lesser Snow Geese in the region south of Queen Maud Gulf was due to variation in terrestrial habitat occupied by each nesting colony (Fig. 3C) rather than to variation in colonial nesting density (Fig. 3D). The best model had an interaction effect between methods of estimation (M, photo vs ground) and colony area, A, on colonial population estimate {T≈A+M+A*M}, although its support was equivocal compared with a model that excluded the interaction effect {T≈A+M, DAIC = 0.29}; however, exclusion of estimation method from the model, retaining only the effect of colony area {T≈A} resulted in much poorer model fit with DAIC = 5.41 Nevertheless, estimation of T from only A, regardless of estimation method (Fig. 3E), had the useful relationship T=25,518+4,601∙A with a very high r² = 0.91.

Annual rate of change in sequential annual estimates of colony area (λ_a) correlated poorly (r = 0.23) with annual rate of population change in corresponding colonies (λ_n), explaining only 5% variation in the latter (Fig. 3F); this precluded robust inference about annual numerical abundance dynamics from changes in rate of spatial spread or contraction of colonies. Nevertheless, the strong relation between nesting abundance of Ross’s or Lesser Snow Geese and amount of terrestrial habitat occupied by colonies (Fig. 3E) provided a useful qualitative metric of abundance that could be relevant for conservation monitoring.

DISCUSSION

There have been 110 nesting colonies of Ross’s and Lesser Snow Geese detected in A-QMGMS during 1965–2019, but the total number of active colonies concurrently documented during any survey until 2005–2006 never exceeded 73 (Kerbes et al. 2014). Ryder (1970) first documented 37 colonies during his original and extensive surveys in the Sanctuary from 1965 to 1967. The number of concurrently active colonies had grown to 66 by 2005–2006 (Kerbes et al. 2014). Most of these were small colonies confined to islands in lakes and showed turnover through colonization and extinction (Alisauskas and Boyd 1994, Kerbes et al. 2014), characterizing the highly dynamic nature of colonialism by these species in the central Canadian Arctic. However, during the period of overall population increase in A-QMGMBS from 1965 to ~2010, a smaller number of colonies had expanded from islands to mainland areas surrounding respective lakes, and showed very rapid, even exponential, growth in abundance of nesting light geese. By 2005–2006, four of these largest mainland colonies (3, 10, 46, 58) accounted for 95% of nesting Ross’s and Lesser Snow Geese (Kerbes et al. 2014) in the Sanctuary. An exhaustive survey of active colonies in A-QMGMBS has not been done since then, but simply mapping in this study showed that even these largest colonies (3, 10) showed evidence of population collapse consistent with findings for Colony 3 at Karrak Lake (Weegman et al. 2022, Alisauskas et al. 2024).

Weegman et al. (2022) showed that for both Ross’s and Lesser Snow Geese nesting at Karrak Lake, the inflection from population growth to decline was associated with a reduction in both the production of new geese and their eventual recruitment as breeding adults, instead of an association with any decline in adult survival. In fact, adult survival was increasing as the population was collapsing. The relevant declines in per capita production of goslings to the flight stage were associated with declining clutch size, nest success, and gosling survival until fledging (Alisauskas et al. 2024). These metrics, in turn, were associated with reduced density-dependent nutrition of breeding adults during prenesting arrival at the colony each spring (Alisauskas et al. 2024), the latter of which is important for clutch production and ability to complete incubation (Ryder 1970, Ankney and MacInnes 1978). As well, advanced phenology of snowmelt and of vegetation growth played roles in overall reduced per capita production of goslings to the flight stage through negative effects on gosling survival (Ross et al. 2017, 2018). These reductions in demographic components of recruitment were further accompanied by reduced probability of survival by juvenile geese, i.e., during the first year of life after achieving flight ability at ~6 weeks of age, and a diminished propensity to return to natal colonies as adults (Weegman et al. 2022). Reduced natal philopatry of Lesser Snow Geese marked as juveniles and breeding philopatry of those marked as adults in the Queen Maud Gulf subpopulation were among the lowest probabilities of the five subpopulations studied by Alisauskas et al. (2022). Thus, dispersal by both age classes of Lesser Snow Geese contributed to the population decline at Karrak Lake, as demonstrated by Weegman et al. (2022) and likely played a role in the dynamics of other colonies in the region. The evidently synchronized spatial dynamics of major colonies in A-QMGMBS over about two decades from 1999 to 2019 (Fig. 2) suggested that a common set of demographic drivers was responsible for those spatial changes over time (Fig. 3A), together with correlated and contemporaneous abundance dynamics (Fig. 3E) documented at Karrak Lake (Alisauskas et al. 2024).

Over the full geographic range of a population, the dynamics of abundance are governed by the rate at which mortality of adults is compensated by production and recruitment of new geese. At the subpopulation level within metapopulations, these compensations are further mediated by movements of geese through immigration or emigration to specific regional subpopulations such as at A-QMGMBS (Alisauskas et al. 2012, 2024) or even among colonies comprising such regional subpopulations (Drake and Alisauskas 2004). Such dispersal movements by Ross’s and Lesser Snow Geese in A-QMGMBS were nontrivial to their colonial population dynamics for Colony 3 at Karrak Lake (Wilson et al. 2016, Weegman et al. 2022), and at subpopulation and metapopulation scales (Alisauskas et al. 2012, 2022). Thus, demographic components driving reduced production of goslings and diminished natal and breeding philopatry by both Ross’s and Lesser Snow Geese at Karrak Lake, as well as their role behind declines in snow geese from the Queen Maud Gulf subpopulation was probably responsible for the pervasiveness of colony declines inferred in this study using the simple mapping of colony boundaries (Fig. 2). In fact, changes in colony size were strongly concordant with, for example, the abundance of Lesser Snow Geese comprising the midcontinent population overall (Fig. 3A). This suggests that subpopulation events in A-QMGMBS had an influence on the broader dynamics of the midcontinent population of Lesser Snow Geese. The exponential range-wide increase in abundance during the 1990s and 2000s estimated using Lincoln’s method (Fig. 3A) was linked to (i) the contemporaneous northwestward expansion in breeding range of midcontinent Lesser Snow Geese into the A-QMGMBS (Alisauskas et al. 2022) and surrounding areas of Canada’s central Arctic along with (ii) accelerated colonization in A-QMGMBS (Fig. 1; Alisauskas and Boyd 1994, Kerbes et al. 2014) and (iii) the rapid growth of specific mainland colonies, i.e., those not exclusively on islands in freshwater lakes (Figs. 2, 3).

Compared to estimates of population abundance for specific colonies, whether based on aerial photography or on ground plots, inferences about colony growth from simple mapping provided a seemingly reasonable inference about population change at a reduced cost. In this study, mapping was conducted by helicopter but might also be accomplished via fixed-wing aircraft that could operate from the nearest airport fuel facilities without the need to use fuel caches in A-QMGMBS, possibly reducing costs further. Nevertheless, maneuverability of helicopters may render them more suitable for this kind of work, particularly for smaller colonies. Colony boundaries for the aerial photographic method are determined from the photographs themselves taken from fixed-winged aircraft but transect flights for photographing geese to determine nesting density within the colony would not be needed. The need for detailed photointerpretation associated with the aerial photographic method can increase the time between data acquisition and reporting, e.g., 2006 to 2014 (Kerbes et al. 2014). There was evidence that aerial photographic methods slightly underestimated abundance relative to ground plots (Fig. 3C), but this is expected in some years, especially if nesting is delayed because of protracted spring melt as discussed by Alisauskas et al. (2011). Simple mapping of colonies as done herein provides a tractable and rapid qualitative evaluation of the status of individual colonies in the A-QMGMBS and likely in other areas of light goose colonial nesting. In mixed species colonies of Ross’s and Lesser Snow Geese, inference about species-specific dynamics are not possible; however, the method seems useful for providing information about potential grazing pressure and combined effects of light geese on local ecosystem change (Alisauskas et al. 2024).

Still, helicopter-based mapping may become prohibitively expensive so that other methods of remote sensing may prove useful as well. Information about colony size and associated goose densities may be acquired from high resolution satellite imagery of colonies in conjunction with counting software (LaRue et al. 2017, Chabot et al. 2018, Cruz et al 2022) to reduce time between data acquisition and reporting and avert physical presence by researchers on site. However, we note that our method can still provide information when persistent cloud cover during nesting could preclude the usefulness of satellite imagery. Population trends inferred from paleo-reconstruction based on ornithogenic proxies (Bosch et al. 2024) may have applications as well. If so, population estimates and mapped areas of the kind reported herein may provide metrics against which to apply potential environmental correlates such as limnological deposits inside colonies of stable isotopes, macronutrients or other elements to address past population growth.

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