Although climate acts as a fundamental constraint on the distribution of organisms, understanding how this relationship between climate and distribution varies over a species' range is critical for addressing the potential impacts of accelerated climate change on biodiversity. Bioclimatic niche models provide compelling evidence that many species will experience range shifts under scenarios of global change, yet these broad, macroecological perspectives lack specificity at local scales, where unique combinations of environment, biota, and history conspire against generalizations. We explored how these idiosyncrasies of place affect the climate-distribution relationship of the American pika (Ochotona princeps) by replicating intensive field surveys across bioclimatic gradients in eight U.S. national parks. At macroecological scales, the importance of climate as a constraint on pika distribution appears unequivocal; forecasts suggest that the species' range will contract sharply in coming decades. However, the species persists outside of its modeled bioclimatic envelope in many locations, fueling uncertainty and debate over its conservation status. Using a Bayesian hierarchical approach, we modeled variation in local patterns of pika distribution along topographic position, vegetation cover, elevation, temperature, and precipitation gradients in each park landscape. We also accounted for annual turnover in site occupancy probabilities. Topographic position and vegetation cover influenced occurrence in all parks. After accounting for these factors, pika occurrence varied widely among parks along bioclimatic gradients. Precipitation by itself was not a particularly influential predictor. However, measures of heat stress appeared most influential in the driest parks, suggesting an interaction between the strength of climate effects and the position of parks along precipitation gradients. The combination of high elevation, cold temperatures, and high precipitation lowered occurrence probabilities in some parks, suggesting an upper elevational limit for pikas in some environments. Our results demonstrate that the idiosyncrasies of place influence both the nature and strength of the climate-distribution relationship for the American pika. Fine-grained, but geographically extensive, studies replicated across multiple landscapes offer insights important to assessing the impacts of climate change that otherwise may be masked at macroecological scales. The hierarchical approach to modeling provides a coherent conceptual and technical framework for gaining these insights.

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Ecological niche theory holds that species distributions are shaped by a large and complex suite of interacting factors. Species distribution models (SDMs) are increasingly used to describe species' niches and predict the effects of future environmental change, including climate change. Currently, SDMs often fail to capture the complexity of species' niches, resulting in predictions that are generally limited to climate-occupancy interactions. Here, we explore the potential impact of climate change on the American pika using a replicated place-based approach that incorporates climate, gene flow, habitat configuration, and microhabitat complexity into SDMs. Using contemporary presence-absence data from occupancy surveys, genetic data to infer connectivity between habitat patches, and 21 environmental niche variables, we built separate SDMs for pika populations inhabiting eight US National Park Service units representing the habitat and climatic breadth of the species across the western United States. We then predicted occurrence probability under current (1981-2010) and three future time periods (out to 2100). Occurrence probabilities and the relative importance of predictor variables varied widely among study areas, revealing important local-scale differences in the realized niche of the American pika. This variation resulted in diverse and - in some cases - highly divergent future potential occupancy patterns for pikas, ranging from complete extirpation in some study areas to stable occupancy patterns in others. Habitat composition and connectivity, which are rarely incorporated in SDM projections, were influential in predicting pika occupancy in all study areas and frequently outranked climate variables. Our findings illustrate the importance of a place-based approach to species distribution modeling that includes fine-scale factors when assessing current and future climate impacts on species' distributions, especially when predictions are intended to manage and conserve species of concern within individual protected areas.

Strategic conservation efforts for cryptic species, especially bats, are hindered by limited understanding of distribution and population trends. Integrating long‐term encounter surveys with multi‐season occupancy models provides a solution whereby inferences about changing occupancy probabilities and latent changes in abundance can be supported. When harnessed to a Bayesian inferential paradigm, this modeling framework offers flexibility for conservation programs that need to update prior model‐based understanding about at‐risk species with new data. This scenario is exemplified by a bat monitoring program in the Pacific Northwestern United States in which results from 8 years of surveys from 2003 to 2010 require updating with new data from 2016 to 2018. The new data were collected after the arrival of bat white‐nose syndrome and expansion of wind power generation, stressors expected to cause population declines in at least two vulnerable species, little brown bat (Myotis lucifugus) and the hoary bat (Lasiurus cinereus). We used multi‐season occupancy models with empirically informed prior distributions drawn from previous occupancy results (2003–2010) to assess evidence of contemporary decline in these two species. Empirically informed priors provided the bridge across the two monitoring periods and increased precision of parameter posterior distributions, but did not alter inferences relative to use of vague priors. We found evidence of region‐wide summertime decline for the hoary bat (trueλ^ = 0.86 ± 0.10) since 2010, but no evidence of decline for the little brown bat (trueλ^ = 1.1 ± 0.10). White‐nose syndrome was documented in the region in 2016 and may not yet have caused regional impact to the little brown bat. However, our discovery of hoary bat decline is consistent with the hypothesis that the longer duration and greater geographic extent of the wind energy stressor (collision and barotrauma) have impacted the species. These hypotheses can be evaluated and updated over time within our framework of pre–post impact monitoring and modeling. Our approach provides the foundation for a strategic evidence‐based conservation system and contributes to a growing preponderance of evidence from multiple lines of inquiry that bat species are declining.