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In Subarctic and Arctic environments, daily patterns of activity and space-use are strongly influenced by interplay between seasonal abiotic factors and the corresponding responses of the biotic environment. Here we combined accelerometry with GPS telemetry of Canada lynx (Lynx canadensis (Kerr, 1792), n=12) in northern Alaska to test the hypotheses that lynx activity would peak during twilight throughout the year, coinciding with activity of their preferred prey, and that individuals with larger home ranges would have greater spatial displacement and expend more energy on movement. Lynx activity occurred throughout the 24h day and peaked during twilight, but variation among individuals was high and diel rhythms were sometimes only detectable using the finer resolution accelerometer data. Surprisingly, home range size was not correlated with movement costs estimated via acceleration, but step length and acceleration were correlated in a positive curvilinear fashion. However, step length was sometimes disproportionately lower than predicted by acceleration. Such intervals of high activity with low spatial displacement were often followed by periods of rest, suggesting they may be indicative of hunting in a restricted patch of habitat. We conclude that accelerometers can provide additional information to supplement GPS data, providing a more complete picture of animal behavior. 

Cyclical population dynamics are a common phenomenon in populations worldwide, yet the spatial organization of these cycles remains poorly understood. In this study, we investigated the spatial form and timing of a population collapse from 2018 to 2022 in Canada lynx (Lynx canadensis) across the northwest boreal forest. We analyzed survival, reproduction, and dispersal data from 143 individual global positioning system (GPS) collared lynx from populations across five study sites spanning interior Alaska to determine whether lynx displayed characteristics of a population wave following a concurrent wave in snowshoe hare (Lepus americanus) abundance. Reproductive rates declined across the study sites; however, site-level reproduction declined first in our easternmost study sites, supporting the idea of a population wave. Despite a clear increase in percent of dispersing lynx, there was no evidence of directional bias in dispersal following a hare population wave. Analysis did show increasingly poor survival for lynx dispersing to the east compared to combined resident and westward dispersal. This pattern is consistent with a survival-mediated population wave in lynx as the driver of the theorized population wave. The combination of these factors supports the idea of a hierarchical response to snowshoe hare population declines with a drop in lynx reproduction followed by increased dispersal, and finally reduced survival. All of this evidence is consistent with the expected characteristics of a population undergoing a traveling wave and supports the hypothesis that lynx presence may facilitate and mirror the underlying wave patterns in snowshoe hare. 

Climate warming can cause arthropods to express plastic and/or evolved changes in morphology. Previous studies have demonstrated that body sizes of Arctic butterflies are influenced by the temperatures experienced as larvae. To investigate whether this was occurring among Alaskan butterflies, we analyzed temporal trends in the wing sizes of three Holarctic species,Colias hecla,Boloria charicleaandBoloria freija, using museum specimens collected in Arctic tundra regions of Alaska between 1971 and 1995. Wing length was compared to accumulated growing degree days (GDD) during both the spring of the year collected and the previous year's summer during the normal period of larval development. We used mixed‐effects models to test if spring and summer temperatures affected adult morphology. Results show that for every 1°C increase in average seasonal temperature, wingspans decreased between 0.7 and 5 mm, withB. freijathe most strongly affected. Our results suggest that the morphological sensitivity of Arctic butterflies to warming is the outcome of interactions between life‐history traits and regional climate, with all species sensitive to warming the summer before the flight year as well as warming the spring of the flight year.Boloria freija, which overwinters as late instar larvae that do not feed before pupation the following spring, was particularly strongly affected by summer warming. 

Abstract Recent empirical studies have quantified correlation between survival and recovery by estimating these parameters as correlated random effects with hierarchical Bayesian multivariate models fit to tag‐recovery data. In these applications, increasingly negative correlation between survival and recovery has been interpreted as evidence for increasingly additive harvest mortality. The power of these hierarchal models to detect nonzero correlations has rarely been evaluated, and these few studies have not focused on tag‐recovery data, which is a common data type. We assessed the power of multivariate hierarchical models to detect negative correlation between annual survival and recovery. Using three priors for multivariate normal distributions, we fit hierarchical effects models to a mallard (Anas platyrhychos) tag‐recovery data set and to simulated data with sample sizes corresponding to different levels of monitoring intensity. We also demonstrate more robust summary statistics for tag‐recovery data sets than total individuals tagged. Different priors led to substantially different estimates of correlation from the mallard data. Our power analysis of simulated data indicated most prior distribution and sample size combinations could not estimate strongly negative correlation with useful precision or accuracy. Many correlation estimates spanned the available parameter space (−1,1) and underestimated the magnitude of negative correlation. Only one prior combined with our most intensive monitoring scenario provided reliable results. Underestimating the magnitude of correlation coincided with overestimating the variability of annual survival, but not annual recovery. The inadequacy of prior distributions and sample size combinations previously assumed adequate for obtaining robust inference from tag‐recovery data represents a concern in the application of Bayesian hierarchical models to tag‐recovery data. Our analysis approach provides a means for examining prior influence and sample size on hierarchical models fit to capture–recapture data while emphasizing transferability of results between empirical and simulation studies. 

Burrowing species rely on subterranean and subnivean sites to fulfill important life-history and behavioral processes, including predator avoidance, thermoregulation, resting, and reproduction. For these species, burrow architecture can affect the quality and success of such processes, since characteristics like tunnel width and chamber depth influence access by predators, thermal insulation, and energy spent digging. Wolverines (Gulo gulo) living in Arctic tundra environments dig burrows in snow during winter for resting sites and reproductive dens, but there are few published descriptions of such burrows. We visited 114 resting burrows and describe associated architectural characteristics and non-snow structure. Additionally, we describe characteristics of 15 reproductive den sites that we visited during winter and summer. Although many resting burrows were solely excavated in snow, most incorporated terrain structures including cliffs, talus, river shelf ice, thermokarst caves, and stream cutbanks. Burrows typically consisted of a single tunnel leading to a single chamber, though some burrows had multiple entrances, branching tunnels, or both. Tunnels in resting burrows were shorter than those in reproductive dens, and resting chambers were typically located at the deepest part of the burrow. Reproductive dens were associated with snowdrift-forming terrain features such as streambeds, cutbanks on lake edges, thermokarst caves, and boulders. Understanding such characteristics of Arctic wolverine resting and reproductive structures is critical for assessing anthropogenic impacts as snowpack undergoes climate-driven shifts. 

Abstract Background Migrations in temperate systems typically have two migratory phases, spring and autumn, and many migratory ungulates track the pulse of spring vegetation growth during a synchronized spring migration. In contrast, autumn migrations are generally less synchronous and the cues driving them remain understudied. Our goal was to identify the cues that migrants use in deciding when to initiate migration and how this is updated while en route . Methods We analyzed autumn migrations of Arctic barren-ground caribou ( Rangifer tarandus ) as a series of persistent and directional movements and assessed the influence of a suite of environmental factors. We fitted a dynamic-parameter movement model at the individual-level and estimated annual population-level parameters for weather covariates on 389 individual-seasons across 9 years. Results Our results revealed strong, consistent effects of decreasing temperature and increasing snow depth on migratory movements, indicating that caribou continuously update their migratory decision based on dynamic environmental conditions. This suggests that individuals pace migration along gradients of these environmental variables. Whereas temperature and snow appeared to be the most consistent cues for migration, we also found interannual variability in the effect of wind, NDVI, and barometric pressure. The dispersed distribution of individuals in autumn resulted in diverse environmental conditions experienced by individual caribou and thus pronounced variability in migratory patterns. Conclusions By analyzing autumn migration as a continuous process across the entire migration period, we found that caribou migration was largely related to temperature and snow conditions experienced throughout the journey. This mechanism of pacing autumn migration based on indicators of the approaching winter is analogous to the more widely researched mechanism of spring migration, when many migrants pace migration with a resource wave. Such a similarity in mechanisms highlights the different environmental stimuli to which migrants have adapted their movements throughout their annual cycle. These insights have implications for how long-distance migratory patterns may change as the Arctic climate continues to warm. 

A distinguishing characteristic of many migratory animals is their annual return to distinct calving (birthing) areas in the spring, yet the navigational mechanisms employed during migration that result in this pattern are poorly understood. Effective conservation of these species requires reliable delineation of such areas, quantifying the factors that influence their selection, and understanding the underlying mechanisms resulting in use of calving areas. We used barren-ground caribou ( Rangifer tarandus granti ) as a study species and identified calving sites of the Western Arctic Herd in Alaska using GPS collar data from 2010–2017. We assessed variability in calving areas by comparing spatial delineations across all combinations of years. To understand calving area selection at a landscape scale, we performed a resource selection analysis comparing calving sites to available locations across the herd’s range and incorporated time-varying, remotely sensed metrics of vegetation quality and quantity. We found that whereas calving areas varied from year to year, this annual variation was centered on an area of recurring attraction consistent with previous studies covering the last six decades. Calving sites were characterized by high-quality forage at the average time of calving, but not peak calving that year, and by a narrow range of distinct physiographic factors. Each year, calving sites were located on areas of above-average conditions based on our predictive model. Our findings indicate that the pattern of spring migration for pregnant females was to migrate to areas that consistently provide high-quality forage when averaged across years, and then upon arriving at this calving ground, refine selection using their perception of annually varying conditions that are driven by environmental stochasticity. We suggest that the well-documented and widespread pattern of fidelity to calving grounds by caribou is supportive of a navigational mechanism based on spatial memory at a broad scale to optimize foraging and energy acquisition at a critical life-history stage. The extent to which migrants depend on memory to reach their spring destinations has implications for the adaptability of populations to changing climate and human impacts.