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.

Variation in body size across populations of brown bears (Ursus arctos) is largely a function of the availability and quality of nutritional resources while plasticity within populations reflects utilized niche width with implications for population resiliency. We assessed skull size, body length, and lean mass of adult female and male brown bears in four Alaskan study areas that differed in climate, primary food resources, population density, and harvest regime. Full body‐frame size, as evidenced by asymptotic skull size and body length, was achieved by 8–14 years of age across populations and sexes. Lean body mass of both sexes continued to increase throughout their life. Differences between populations existed for all morphological measures in both sexes, bears in ecosystems with abundant salmon were generally larger. Within all populations, broad variation was seen in body size measures of adults with females displaying roughly a 2‐fold difference in lean mass and males showing a 3‐ to 4‐fold difference. The high level of intraspecific variation seen across and within populations suggests the presence of multiple life‐history strategies and niche variation relative to resource partitioning, risk tolerance or aversion, and competition. Furthermore, this level of variation indicates broad potential to adapt to changes within a given ecosystem and across the species’ range.

Winters are limiting for many terrestrial animals due to energy deficits brought on by resource scarcity and the increased metabolic costs of thermoregulation and traveling through snow. A better understanding of how animals respond to snow conditions is needed to predict the impacts of climate change on wildlife. We compared the performance of remotely sensed and modeled snow products as predictors of winter movements at multiple spatial and temporal scales using a data set of 20,544 locations from 30 GPS-collared Dall sheep (Ovis dalli dalli) in Lake Clark National Park and Preserve, Alaska, USA from 2005 to 2008. We used daily 500-m MODIS normalized difference snow index (NDSI), and multi-resolution snow depth and density outputs from a snowpack evolution model (SnowModel), as covariates in step selection functions. We predicted that modeled snow depth would perform best across all scales of selection due to more informative spatiotemporal variation and relevance to animal movement. Our results indicated that adding any of the evaluated snow metrics substantially improved model performance and helped characterize winter Dall sheep movements. As expected, SnowModel-simulated snow depth outperformed NDSI at fine-to-moderate scales of selection (step scales < 112 h). At the finest scale, Dall sheep selected for snow depths below mean chest height (<54 cm) when in low-density snows (100 kg/m ), which may have facilitated access to ground forage and reduced energy expenditure while traveling. However, sheep selected for higher snow densities (>300 kg/m ) at snow depths above chest height, which likely further reduced energy expenditure by limiting hoof penetration in deeper snows. At moderate-to-coarse scales (112-896 h step scales), however, NDSI was the best-performing snow covariate. Thus, the use of publicly available, remotely sensed, snow cover products can substantially improve models of animal movement, particularly in cases where movement distances exceed the MODIS 500-m grid threshold. However, remote sensing products may require substantial data thinning due to cloud cover, potentially limiting its power in cases where complex models are necessary. Snowpack evolution models such as SnowModel offer users increased flexibility at the expense of added complexity, but can provide critical insights into fine-scale responses to rapidly changing snow properties.

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Changes in climate are driving widespread landscape changes in northern ecosystems, altering the size and distribution of wildlife populations over multi‐decadal time scales. Extreme weather events are also expected to become more common over time, affecting a variety of species, and mountain ungulates may be particularly susceptible because they occupy habitats with particularly harsh winter weather conditions. To explore the impacts of weather conditions and adverse weather events as population drivers, we surveyed Dall's sheep throughout their latitudinal range in Alaska and assessed lamb production and population trend in relation to end of the continuous snow season (CSS) as a measure of spring onset. In 2013, spring onset was extraordinarily late, providing an opportunity to directly assess the impacts of variability in weather on sheep population dynamics. We hypothesized that the timing of the end of the CSS would have greater impacts in arctic areas where conditions are presumably most limiting. We found that lamb production was negatively related to the annual timing of the end of the CSS and was near 0 in arctic areas in 2013. The 2013 event was also associated with ~40–70% declines in overall sheep numbers in arctic areas, indicating adult survival was also impacted. Overall, our results suggest that expected increases in adverse weather events may have direct, lasting impacts on mountain ungulate populations and that these impacts can be expected to be most extreme for populations occurring at northern range limits where growing season conditions are most restricted.