Arctic-breeding shorebirds have experienced widespread population declines in recent decades, largely driven by the loss and degradation of migratory stopover habitats, contaminants, and unsustainable harvest. These declines are occurring even though Arctic nesting grounds are relatively undisturbed by human infrastructure and fragmentation, although future infrastructure expansion poses a threat to breeding shorebirds. Additionally, climate change effects are more pronounced in the Arctic, leading to variable spring environmental conditions and the phenological advancement of key shorebird food resources. However, it is unknown how shorebirds respond to more variable environmental conditions due to climate change or to what extent human infrastructure influences shorebird movements on the breeding grounds. To address this knowledge gap, I monitored Dunlin movements using high-frequency GPS tracking devices during the pre-incubation period (i.e., the period between arrival on the breeding grounds and the first day of incubation) near the town of Utqiaġvik in northern Alaska. My overall objectives were to 1) evaluate and describe Dunlin movements and behavior states during the pre-incubation period, 2) assess the influence of snow cover and temperature on Dunlin movements, 3) identify hotspots of Dunlin occurrence across years, and 4) assess Dunlin space-use relative to human infrastructure, particularly the roads. To address objectives 1 and 2, I monitored the movements of 93 Dunlin captured during the pre-incubation period from 2021-2024, and used hidden Markov models and generalized linear mixed models to identify behavior states and assess the influence of snow cover and temperature on the movements and behaviors of male and female Dunlin. Dunlin spent >90% of the time engaged in small-scale movements (i.e., foraging, roosting, courtship). Dunlin engaged in larger transitory movements (i.e., territory scouting or moving between foraging patches) when snow cover was highest early in the season, and males engaged in more long-distance movements than females. As incubation approached, males and females adopted similar movement distances. We found limited evidence that temperature influenced Dunlin movements. To address objectives 3 and 4, I used a spatial kernel density estimator to identify areas of high use across years when Dunlin engaged in small-scale behaviors. Dunlin used primary (74 ha) and secondary (99 ha) core foraging areas along gravel roads and other developed areas where snow had been removed through regular road maintenance activities. Dunlin spent more time in these core areas and were closer to roads when snow cover was high and temperatures were low. My findings indicate that Dunlin respond strongly to annual environmental conditions and that increasing snowmelt variability caused by climate change influence Dunlin movements and behaviors prior to nesting. Dunlin also use anthropogenically-modified areas during the most physiologically challenging portion of the breeding season, likely due to the availability of food resources in these areas. My work highlights the need to evaluate the consequences, positive or negative, of shorebird use of human-modified areas as infrastructure increases and the effects of climate change in the Arctic become more pronounced in future years
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