Climate change and disease are threats to biodiversity that may compound and interact with one another in ways that are difficult to predict. White-nose syndrome (WNS), caused by a cold-loving fungus (Pseudogymnoascus destructans), has had devastating impacts on North American hibernating bats, and impact severity has been linked to hibernaculum microclimate conditions. As WNS spreads across the continent and climate conditions change, anticipating these stressors’ combined impacts may improve conservation outcomes for bats. We build on the recent development of winter species distribution models for five North American bat species, which used a hybrid correlative-mechanistic approach to integrate spatially explicit winter survivorship estimates from a bioenergetic model of hibernation physiology. We apply this bioenergetic model given the presence of P. destructans , including parameters capturing its climate-dependent growth as well as its climate-dependent effects on host physiology, under both current climate conditions and scenarios of future climate change. We then update species distribution models with the resulting survivorship estimates to predict changes in winter hibernacula suitability under future conditions. Exposure to P. destructans is generally projected to decrease bats’ winter occurrence probability, but in many areas, changes in climate are projected to lessen the detrimental impacts of WNS. This rescue effect is not predicted for all species or geographies and may arrive too late to benefit many hibernacula. However, our findings offer hope that proactive conservation strategies to minimize other sources of mortality could allow bat populations exposed to P. destructans to persist long enough for conditions to improve.
White-nose syndrome (WNS) has decimated hibernating bat populations across eastern and central North America for over a decade. Disease severity is driven by the interaction between bat characteristics, the cold-loving fungal agent, and the hibernation environment. While we further improve hibernation energetics models, we have yet to examine how spatial heterogeneity in host traits is linked to survival in this disease system. Here we develop predictive spatial models of body mass for the little brown myotis (Myotis lucifugus) and reassess previous definitions of the duration of hibernation of this species. Using data from published literature, public databases, local experts, and our own fieldwork, we fit a series of generalized linear models with hypothesized abiotic drivers to create distribution-wide predictions of pre-hibernation body fat and hibernation duration. Our results provide improved estimations of hibernation duration and identify a scaling relationship between body mass and body fat; this relationship allows for the first continuous estimates of pre-hibernation body mass and fat across the species’ distribution. We used these results to inform a hibernation energetic model to create spatially-varying fat use estimates for M. lucifugus. These results predict that WNS mortality of newly and soon-to-be infected M. lucifugus populations in western North America may be comparable to the substantial die-off observed in eastern and central populations.