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.