Distribution and occupancy of wolverines on tundra, northwestern Alaska

Landscape heterogeneity buffers the impact of an extreme weather event on wildlife

Extreme weather events are becoming more frequent, with poorly known consequences for wildlife. In December 2021, an atmospheric river brought record-shattering amounts of rain and snow to interior Alaska, creating conditions expected to cause mass mortality in grazing ungulate populations that need to access ground forage. We characterized snowpack conditions following the storm and used a 36-year monitoring dataset to quantify impacts on caribou (Rangifer tarandus) and their primary predator, wolves (Canis lupus). December precipitation was 7.3 SD above the 99-year mean and 2.5-fold higher than the prior record, with a return period of 333 years. However, ice thickness within the snowpack was highly variable across vegetation types, and caribou shifted to use higher elevations that can blow free of snow. Caribou and wolf mortality rates were 1.3-1.8 SD above normal and caribou population growth rates were low but similar to recent years, indicating a surprisingly weak demographic response. These findings indicate that landscape diversity may bolster resistance of wildlife populations to short-term, potentially devastating effects of extreme weather.

Diet and landscape characteristics drive spatial patterns of mercury accumulation in a high-latitude terrestrial carnivore

Limited information exists on mercury concentrations and environmental drivers of mercury bioaccumulation in high latitude terrestrial carnivores. Spatial patterns of mercury concentrations in wolverine (Gulo gulo, n = 419) were assessed across a 1,600,000 km2 study area in relation to landscape, climate, diet and biological factors in Arctic and boreal biomes of western Canada. Hydrogen stable isotope ratios were measured in wolverine hair from a subset of 80 animals to assess the spatial scale for characterizing environmental conditions of their habitat. Habitat characteristics were determined using GIS methods and raster datasets at two scales, the collection location point and a 150 km radius buffer, which was selected based on results of a correlation analysis between hydrogen stable isotopes in precipitation and wolverine hair. Total mercury concentrations in wolverine muscle ranged >2 orders of magnitude from 0.01 to 5.72 μg/g dry weight and varied geographically, with the highest concentrations in the Northwest Territories followed by Nunavut and Yukon. Regression models at both spatial scales indicated diet (based on nitrogen stable isotope ratios) was the strongest explanatory variable of mercury concentrations in wolverine, with smaller though statistically significant contributions from landscape variables (soil organic carbon, percent cover of wet area, percent cover of perennial snow-ice) and distance to the Arctic Ocean coast. The carbon and nitrogen stable isotope ratios of wolverine muscle suggested greater mercury bioaccumulation could be associated with feeding on marine biota in coastal habitats. Landscape variables identified in the modelling may reflect habitat conditions which support enhanced methylmercury transfer to terrestrial biota. Spatially-explicit estimates of wet atmospheric deposition were positively correlated with wolverine mercury concentrations but this variable was not selected in the final regression models. These landscape patterns provide a basis for further research on underlying processes enhancing methylmercury uptake in high latitude terrestrial food webs.

Wolverines (Gulo gulo) in the Arctic: Revisiting distribution and identifying research and conservation priorities amid rapid environmental change

Wolverines (Gulo gulo) occupy most of the globe’s Arctic tundra. Given the rapidly warming climate and expanding human activity in this biome, understanding wolverine ecology, and therefore the species’ vulnerability to such changes, is increasingly important for developing research priorities and effective management strategies. Here, we review and synthesize knowledge of wolverines in the Arctic using both Western science sources and available Indigenous Knowledge (IK) to improve our understanding of wolverine ecology in the Arctic and better predict the species’ susceptibility to change. To accomplish this, we update the pan-Arctic distribution map of wolverines to account for recent observations and then discuss resulting inference and uncertainties. We use these patterns to contextualize and discuss potential underlying drivers of distribution and population dynamics, drawing upon knowledge of food habits, habitat associations, and harvest, as well as studies of wolverine ecology elsewhere. We then identify four broad areas to prioritize conservation and research efforts: (1) Monitoring trends in population abundance, demographics, and distribution and the drivers thereof, (2) Evaluating and predicting wolverines’ responses to ongoing climate change, particularly the consequences of reduced snow and sea ice, and shifts in prey availability, (3) Understanding wolverines’ response to human development, including the possible impact of wintertime over-snow travel and seismic testing to reproductive denning, as well as vulnerability to hunting and trapping associated with increased human access, and (4) Ensuring that current and future harvest are sustainable.

Spatiotemporally variable snow properties drive habitat use of an Arctic mesopredator

Climate change is rapidly altering the composition and availability of snow, with implications for snow-affected ecological processes, including reproduction, predation, habitat selection, and migration. How snowpack changes influence these ecological processes is mediated by physical snowpack properties, such as depth, density, hardness, and strength, each of which is in turn affected by climate change. Despite this, it remains difficult to obtain meaningful snow information relevant to the ecological processes of interest, precluding a mechanistic understanding of these effects. This problem is acute for species that rely on particular attributes of the subnivean space, for example depth, thermal resistance, and structural stability, for key life-history processes like reproduction, thermoregulation, and predation avoidance. We used a spatially explicit snow evolution model to investigate how habitat selection of a species that uses the subnivean space, the wolverine, is related to snow depth, snow density, and snow melt on Arctic tundra. We modeled these snow properties at a 10 m spatial and a daily temporal resolution for 3 years, and used integrated step selection analyses of GPS collar data from 21 wolverines to determine how these snow properties influenced habitat selection and movement. We found that wolverines selected deeper, denser snow, but only when it was not undergoing melt, bolstering the evidence that these snow properties are important to species that use the Arctic snowpack for subnivean resting sites and dens. We discuss the implications of these findings in the context of climate change impacts on subnivean species.