Many ecological processes are profoundly influenced by abiotic factors, such as temperature and snow. However, despite strong evidence linking shifts in these ecological processes to corresponding shifts in abiotic factors driven by climate change, the mechanisms connecting population size to season-specific climate drivers are little understood. Using a 21-year dataset and a Bayesian state space model, we identified biologically informed seasonal climate covariates that influenced densities of snowshoe hares (Lepus americanus), a cold-adapted boreal herbivore. We found that snow and temperature had strong but conflicting season-dependent effects. Reduced snow duration in spring and fall and warmer summers were associated with lowered hare density, whereas warmer winters were associated with increased density. When modeled simultaneously and under two climate change scenarios, the negative effects of reduced fall and spring snow duration and warmer summers overwhelm the positive effect of warmer winters, producing projected population declines. Ultimately, the contrasting population-level impacts of climate change across seasons emphasize the critical need to examine the entire annual climate cycle to understand potential long-term population consequences of climate change.
Keywords: climate change; climate scenarios; population dynamics; population projections; snow cover; snowshoe hare; state-space model; temperature.
© 2022 The Authors. Global Change Biology published by John Wiley & Sons Ltd.