Weather conditions during hunting season affect the number of harvested roe deer (Capreolus capreolus)

Snow depth influences harvest of a boreal ungulate more than socio-economic factors: Implications for food security in a changing climate

Climate change may affect the ability of hunters to harvest wildlife and, hence, threaten food security of local people. However, few studies have investigated the relative influence of environmental conditions on wildlife harvest rates. We harnessed a 24-year dataset of harvest dates for a boreal ungulate in a region where climate change is having pronounced impacts on snow depth, precipitation, and temperatures to investigate the effect of weather on harvest rates. We used generalized linear models and a model selection framework to examine the influence of weather covariates (snow depth, mean daily temperature, precipitation) and socio-economic factors (gasoline and red meat prices, employment rates, and moose [Alces americanus] harvest) on harvest rates of bison (Bison bison) in Yukon, Canada, at two temporal scales: annual and daily. At an annual scale, snow depth was the only covariate that was important in explaining bison harvest. No socioeconomic variables improved our model beyond the null. At the daily scale, snow depth and mean daily temperature influenced bison harvest rates, with a 1 SD increase resulting in a 14 % and 9 % increase in daily harvest rates, respectively. Increased snow depth facilitates ease of travel in remote, roadless areas by snowmobile to locate bison and truncates movements of bison, resulting in increased harvest rates. Decreased snow depth due to climate change will impact hunter access to boreal ungulates and food security for northern people. More broadly, our data suggests that in some socioecological systems, environmental covariates have a greater influence on wildlife harvest rates than socioeconomic factors and need to be considered in future studies to better understand and predict harvest rates.

Modelling the Relative Abundance of Roe Deer (Capreolus capreolus L.) along a Climate and Land-Use Gradient

European roe deer (Capreolus capreolus L.) are important given their economic, recreational and ecological value. However, uncontrolled roe deer numbers can result in negative impacts on forest regeneration and agricultural crops, disease transmission and occurrences of deer-vehicle collisions. Information on the abundance and distribution is needed for effective management. We combined distance sampling (DS) of roe deer dung pellet groups with multiple variables to develop a density surface model (DSM) in the federal state of Bavaria in south-eastern Germany. We used the estimates of pellet group density as a proxy for roe deer relative abundance. We extrapolated our best DSM, conducted a quantitative evaluation and contrasted relative abundance along climate and land-use gradients. Relative abundance of roe deer was influenced by a combination of habitat type, climate and wildlife management variables, which differed between seasons and which reflected changes in food and shelter availability. At the landscape scale, the highest abundance was observed in agriculture-dominated areas and the lowest in urban areas. Higher abundance was also observed in areas with intermediate temperatures compared to the warmest areas. Our results provide information on possible future changes in the distribution of relative abundance due to changes in climate and land-use.