Timothy E Link | USGS Science

USGS2025

Detection of deer at remote camera sites in relation to snow conditions

In the rain-snow transition zone of the Pacific Northwest, climate change is expected to alter the incidence of rain-on-snow and freeze-thaw events, which will change snow density and hardness dynamics. In winter, the ability of economically and ecologically important wildlife species, such as deer ( Odocoileus spp.), to efficiently move through the landscape and access forage is mediated by snow conditions. Therefore, snow properties such as density and hardness can directly affect how energetically costly it is for these animals to survive. However, little is known about whether and how ungulates use habitats based on snow density and hardness. We deployed a stratified network of remote camera stations in complex forested terrain in Latah County, Idaho, USA, to remotely measure snow depth and detect deer. We also collected snow density and hardness measurements throughout the winter. We used these data to determine the degree to which the probability of deer presence at cameras could be explained by snow conditions and air temperature. Snow depth and density had negative relationships with the probability of deer presence, while ram resistance (a proxy for snow hardness) had a marginal positive effect. We were able to estimate snow conditions important to deer in winter 2020–2021 primarily using data obtained from cameras. This provides an important proof-of-concept that can be applied at different sites and climate conditions to gain a deeper understanding of how deer are affected by snowpack properties. These methods can be used by managers to determine how ungulates are affected by snow depth, density, and hardness collectively and subsequently inform ungulate management in a changing climate.

Idaho↗

USGS2020

Long term persistence of aspen in snowdrift-dependent ecosystems

Quaking aspen (Populus tremuloides) forests throughout the western United States have experienced significant mortality in recent decades, much of which has been influenced by climate variability, especially drought. In the western portion of its range, where most precipitation arrives during winter as snowfall and summers are dry, snowdrifts that persist into the growing season provide soil moisture recharge that sustain many aspen groves that are important locations of biodiversity within the landscape. There is growing concern that reduced snowpack due to climate change may reduce the long-term persistence and productivity of aspen communities in these regions. In this study, we evaluated the potential for climate change and drought to reduce or eliminate isolated aspen communities in southwestern Idaho. We used a landscape simulation model integrated with inputs from an empirically derived biogeochemical model of growth, and a species distribution model of regeneration to forecast how changes in climate, declining snowpack, and competition with a conifer species is likely to affect aspen occupancy over the next 85-years. We found that simulated reductions in snowpack depth (and associated increases in climatic water deficit) caused a reduction in aspen persistence; aspen occupancy was reduced under all high emissions climate scenarios. Douglas-fir (Pseudotsuga menziesii) occupancy also declined under all future climates. Aspen regeneration declined over the course of all simulations, with an ensemble ratio of mortality/establishment increasing over the course of both low and high emissions climate scenarios. Climate-induced mortality of aspen clones increased in frequency under all climate scenarios and, under the most severe emissions scenarios, contributed to a substantial decline of aspen cover. Our research suggests that snowbanks will be an important determinant of long-term persistence of aspen under changing climate in the region.

Forest Ecology and Management↗