Journal
ECOLOGICAL APPLICATIONS
Volume 23, Issue 4, Pages 864-878Publisher
WILEY
DOI: 10.1890/12-0979.1
Keywords
American pika; Bayesian hierarchical model; climate change; conservation; national parks; occupancy; Ochotona princeps; place-based contingencies; presence-absence; sign surveys; turnover
Categories
Funding
- National Park Service Climate Change Response Program
- U.S. Geological Survey Park-Oriented Biological Support (POBS) Program [G11AC20397]
- Division Of Environmental Biology
- Direct For Biological Sciences [1027341] Funding Source: National Science Foundation
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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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