The Arctic is entering a new ecological state, with alarming consequences for humanity. Animal-borne sensors offer a window into these changes. Although substantial animal tracking data from the Arctic and subarctic exist, most are difficult to discover and access. Here, we present the new Arctic Animal Movement Archive (AAMA), a growing collection of more than 200 standardized terrestrial and marine animal tracking studies from 1991 to the present. The AAMA supports public data discovery, preserves fundamental baseline data for the future, and facilitates efficient, collaborative data analysis. With AAMA-based case studies, we document climatic influences on the migration phenology of eagles, geographic differences in the adaptive response of caribou reproductive phenology to climate change, and species-specific changes in terrestrial mammal movement rates in response to increasing temperature.

Kubelka et al. (Reports, 9 November 2018, p. 680) claim that climate change has disrupted patterns of nest predation in shorebirds. They report that predation rates have increased since the 1950s, especially in the Arctic. We describe methodological problems with their analyses and argue that there is no solid statistical support for their claims.

Conservation status and management priorities are often informed by population trends. Trend estimates can be derived from population surveys or models, but both methods are associated with sources of uncertainty. Many Arctic-breeding shorebirds are thought to be declining based on migration and/or overwintering population surveys, but data are lacking to estimate the trends of some shorebird species. In addition, for most species, little is known about the stage(s) at which population bottlenecks occur, such as breeding vs. nonbreeding periods. We used previously published and unpublished estimates of vital rates to develop the first large-scale population models for 6 species of Arctic-breeding shorebirds in North America, including separate estimates for 3 subspecies of Dunlin. We used the models to estimate population trends and identify life stages at which population growth may be limited. Our model for the arcticola subspecies of Dunlin agreed with previously published information that the subspecies is severely declining. Our results also linked the decline to the subspecies’ low annual adult survival rate, thus potentially implicating factors during the nonbreeding period in the East Asian–Australasian Flyway. However, our trend estimates for all species showed high uncertainty, highlighting the need for more accurate and precise estimates of vital rates. Of the vital rates, annual adult survival had the strongest influence on population trend in all taxa. Improving the accuracy, precision, and spatial and temporal coverage of estimates of vital rates, especially annual adult survival, would improve demographic model-based estimates of population trends and help direct management to regions or seasons where birds are subject to higher mortality.

No abstract

Long-distance migrants are under strong selection to arrive on their breeding grounds at a time that maximizes fitness. Many arctic birds start nesting shortly after snow recedes from their breeding sites and timing of snowmelt can vary substantially over the breeding range of widespread species. We tested the hypothesis that migration schedules of individuals co-occurring at the same non-breeding areas are adapted to average local environmental conditions encountered at their specific and distant Arctic breeding locations. We predicted that timing of breeding site availability (measured here as the average snow-free date) should explain individual variation in departure time from shared non-breeding areas. We tested our prediction by tracking American Golden-Plovers (Pluvialis dominica) nesting across the North-American Arctic. These plovers use a non-breeding (wintering) area in South America and share a spring stopover area in the nearctic temperate grasslands, located >1,800 km away from their nesting locations. As plovers co-occur at the same non-breeding areas but use breeding sites segregated by latitude and longitude, we could disentangle the potential confounding effects of migration distance and timing of breeding site availability on individual migration schedule. As predicted, departure date of individuals stopping-over in sympatry was positively related to the average snow-free date at their respective breeding location, which was also related to individual onset of incubation. Departure date from the shared stopover area was not explained by the distance between the stopover and the breeding location, nor by the stopover duration of individuals. This strongly suggests that plover migration schedule is adapted to and driven by the timing of breeding site availability per se. The proximate mechanism underlying the variable migration schedule of individuals is unknown and may result from genetic differences or individual learning. Temperatures are currently changing at different speeds across the Arctic and this likely generates substantial heterogeneity in the strength of selection pressure on migratory schedule of arctic birds migrating sympatrically.