Analyses
We tested whether the overall occupancy, richness, and density of shorebirds had changed over time, using Generalized Linear Models (GLMs) with time period as the main predictor of interest, region (Rasmussen, Foxe Basin) to control for any regional effects, and habitat type (upland, lowland) to control for any habitat effects. For the model of overall occupancy, we used a binomial distribution, and for the models of species richness and total density across all species, we used a negative binomial distribution to accommodate count data with many zeros.
We then tested whether species associated with warmer breeding habitats were moving into the region and species associated with colder habitats were moving out of the region. We modeled the relationship between the percent change in a species’ observed occupancy and its Species Temperature Index (STI), the long-term average temperature across the species’ breeding range (Devictor et al. 2008). Two species (Red Knot, Stilt Sandpiper) had an infinite percent growth, and are therefore excluded from the model with STI. To calculate STI, we used the breeding season occurrence maps available from Birdlife International to define the North American breeding range of each species (BirdLife International and Handbook of the Birds of the World 2020). We calculated the mean June temperature (1970-2000) for each species’ breeding range from the WorldClim 2.1 dataset, which has a 30 arc second (~1km2) resolution (Fick and Hijmans 2017). We chose to use this long-term average climate to match with the spatial temporal scale that seems relevant to the species range data described above, which is necessarily coarse. We used the mean June temperature because shorebirds arrive in the region, initiate their nests, and begin incubation in June, and temperature influences these behaviours (Meltofte et al. 2007). We clipped the mean June temperature grid to our breeding range polygons, and calculated a mean value for June temperature across the whole of each species’ breeding range. Finally, we used a linear model to test the relationship between the percent change in a species’ occupancy and its STI. The data used for these analyses is published in Anderson et al. (2022)

RESULTS

There was considerable variability in overall shorebird occupancy, richness and density between plots, therefore there was no significant difference between 1994-97 and 2019 (Table 1). The overall occupancy of breeding shorebirds per plot (all species combined) in the two study regions was 79% in 1994-97 to 81% in 2019. The mean (±SD) species richness per plot was 1.80 (±1.42) species per plot in 1994-97 and 2.10 (±1.63) species per plot in 2019 (Figure 3). The mean density (±SD) of breeding shorebirds was 55 (±60) birds/km2 in 1994-97 and 61 (±94) birds/km2 in 2019 (Figure 3).
Changes in occupancy were highly variable between species (Figure 4). Occupancy by Baird’s Sandpiper, Buff-breasted Sandpiper, Black-bellied Plover, Pectoral Sandpiper and Red Phalarope declined (Table 2). Occupancy by Ruddy Turnstone and White-rumped Sandpiper increased moderately, and occupancy by Dunlin, American Golden Plover and Semipalmated Sandpiper increased considerably. Interestingly, these same three species that increased substantially are the three species with the highest STI (Table 2). As predicted, there was a significant, positive relationship between the change in a species’ occupancy and its STI (Figure 5; Intercept = -95.49, Slope = 55.72, p = 0.01, Adjusted R² = 0.51). STI ranged from -1.3°C for Red Knot to 5.3°C for Stilt Sandpiper (Table 2).

DISCUSSION

Our results indicate shifting distributions for shorebirds in Arctic Canada at a large spatial scale, over a period of 25 years. We found occupancy varied widely across species, some increasing, some decreasing, despite the negative population trends observed for these species based on migratory data from southern Canada and the United States (Bart et al. 2012, Smith et al. 2020, Smith et al. submitted). The changes in occupancy that we observed were positively related to STI. The increases in occupancy by and Dunlin, American Golden Plover and Semipalmated Sandpiper, the warmer-breeding species, indicate that these species may be moving into these regions. Most of the colder-breeding species, namely Baird’s Sandpiper, Buff-breasted Sandpiper, Black-bellied Plover, Pectoral Sandpiper and Red Phalarope, were observed less frequently, potentially as their ranges shifted northwards.
Species distributions are shaped by complex interactions between abiotic conditions, biotic interactions, dispersal capabilities and historical events, operating at different intensities at different spatial scales (Gaston 2003). Climate is widely recognized as one of the most common, influential drivers of species distribution, through both direct and indirect effects (Grinnell 1917; Root 1988). All of the species considered here have breeding ranges centred at Arctic latitudes, but their breeding distributions nevertheless vary widely in terms of climate. Arctic-breeding shorebirds arrive to breed as the snow recedes in May and June, and their fledged young must depart before snow returns in August and September; temperature and weather during this brief window can have a profound effect on reproductive success (Meltofte et al. 2007). This may be through direct effects on incubation and chick survival during extreme events, or through indirect effects on invertebrate prey availability, the timing of snow and the vegetation community.
Climate change could also have indirect effects on shorebird distributions through its effect on biotic interactions (Blois et al. 2013). Climatic shifts appear to lengthen lemming population cycles in the Arctic, and decrease their maximum population densities (Gilg et al. 2012). This is likely to affect shorebird distributions, as the presence of lemmings provides alternative prey for Arctic foxes (Gilg and Yoccoz 2010; Léandri-Breton and Bêty 2020), reducing predation risk in shorebird nests. Climate-related northward shits of nest predator distribution could also increase nest loss through predation at higher latitudes, nest predation risk having been shown to decrease with latitude (McKinnon et al. 2010).
The status and distribution of shorebirds is undoubtedly influenced by non-climatic factors as well. The densities of Dunlin, Pectoral Sandpiper, Red Phalarope, Semipalmated Sandpiper and White-rumped Sandpiper are depressed in the vicinity of Snow Goose (Anser caerulescens ) and Ross’ Goose (Anser rossi ) colonies, for which populations and colonies have increased dramatically in the past century, in large part due to increasing agricultural food subsidies in their overwintering areas (Flemming et al. 2019). In their migration and wintering habitats, shorebird survival has been negatively affected by processes including loss of coastal habitats to development (Fernández and Lank 2008; Murray and Fuller 2015), and unsustainable hunting of some species (Watts, Reed, and Turrin 2015). Semipalmated Sanpipers have shifted their stopover habitats in response to increasing predation as raptor populations recover from critical lows, a dynamic that is likely affecting other shorebird species as well (Hope et al. 2020). Climate change during the non-breeding season also plays a role, for example through inundation of coastal habitats (Galbraith et al. 2002). Decreased survival during the non-breeding season could influence distributions on the breeding grounds if there is strong migratory connectivity between breeding and wintering sites (Iwamura et al. 2013).
All studied species, including the four species showing increasing occupancy in our two study regions, are thought to be declining in total abundance, based on surveys during migration at temperate latitudes in Canada and the US (Smith et al. submitted). These declines average around 50% over 15 years and appear to be accelerating when compared to the previous 15 years. The mismatch between the trends we observed in the eastern Arctic and the overall population trends for Semipalmated Sandpiper, Ruddy Turnstone, Dunlin, and American Golden-Plover suggest that our study regions may have been closer to the margins of these species’ ranges 25 years ago, and that climate change has shifted their distributions such that our regions are now closer to the centre of their ranges, where occupancy is assumed to be higher. For the species showing declines in occupancy, our data are likely reflecting a shift or contraction of their ranges towards the north as well as overall population declines. The inference of range shifts is stronger for the four species showing simultaneously increased occupancy in our region and overall population declines.
Given the numerous other factors and interactions influencing shorebird distributions, it is notable that we detected an apparent signal of climate change through our cross-species analysis. As climate change in the Arctic is expected to be rapid and severe, environmental changes to shorebird breeding habitats may increasingly cause additional stress in these species. Changing distributions on the Arctic breeding grounds, including local increases in occupancy and density in some cases, indicate that suitable habitat continues to exist in the Arctic for some species. However, there are limits to these species’ capacity to shift their ranges, especially for colder-breeding species, not least of which is the geographic limit imposed by the Arctic Ocean. The shift towards a warmer-breeding community of species suggests that, in addition to the pressures on shorebird species during the non-breeding periods, we should also be concerned about declining breeding habitat availability for shorebird species whose current breeding ranges are centred on higher, colder latitudes.

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FIGURES

Figure 1: Expected changes in plot occupancy as species distributions shift north in response to warming temperatures. Species are assumed to have higher occupancy in the centre of their range and lower occupancy at the edges of their range (Gaston et al. 2003; indicated in this figure by opacity of the orange and blue species ranges). Plots are surveyed within the study area outlined by the black box. The STI (mean June temperature of the range) for species 1 is 5 °C, in this case making it a colder-breeding species. At time 1, the mean temperature of the study area is also 5 °C, therefore the occupancy of species 1 is high. At time 2, the mean temperature of the study area has increased to 10 °C. Species 1 has shifted its distribution northwards. The study area is now on the southern edge of its range, and the occupancy of species 1 has declined. The STI of species 2, a warmer-breeding species, is 10 °C. At time 1 the study area is at the northern edge of its range, therefore the occupancy of species 2 at time 1 is low. At time 2, the study area is now in the centre of its range, and the occupancy of species 2 has increased.