Habitat availability and gene flow influence diverging local population trajectories under scenarios of climate change: a place-based approach

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.Keywords: genetic neighborhood, species distribution modeling, functional connectivity, Random Forest, realized niche, American pika, Ochotona princeps, National Park

Winter movement behavior by swift foxes (Vulpes velox) at the northern edge of their range

Winter can be a limiting time of year for many temperate species, who must access depressed prey resources to meet energetic demands. The swift fox (Vulpes velox Say, 1823) was extirpated from Canada and Montana by 1969 but reintroduced in the 1980s to Canada, and subsequently spread into northern Montana. Swift foxes in this region are at the current northern range edge where winter conditions are harsher and persist longer than in their southern range (i.e. Colorado to Texas). We collected fine-scale locational data from swift foxes fitted with Global Positioning System collars to examine movement and resource use patterns during winter of 2016-2017 in northeastern Montana. Our results suggest that swift foxes displayed three distinct movement patterns (i.e., resting, foraging, and travelling) during the winter. Distance to road decreased relative probability of use by 39-46% per kilometer across all movement states and individuals, whereas the influence of topographic roughness and distance to crop field varied among movement states and individuals. Overall, while our findings are based on data from three individuals, our study suggests that across movement states during the critical winter season, swift foxes are likely using topography and areas near roads to increase their ability to detect predators.The accepted manuscript in pdf format is listed with the files at the bottom of this page. The presentation of the authors' names and (or) special characters in the title of the manuscript may differ slightly between what is listed on this page and what is listed in the pdf file of the accepted manuscript; that in the pdf file of the accepted manuscript is what was submitted by the author

SchwalmHabitatAvailabilityGeneAppendixS1FiguresS1-S6.pdf

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.Keywords: Random Forest, functional connectivity, species distribution modeling, genetic neighborhood, American pika, National Parks, Ochotona princeps, realized nicheKeywords: Random Forest, functional connectivity, species distribution modeling, genetic neighborhood, American pika, National Parks, Ochotona princeps, realized nich

Pika Genetic Sample Localities

One .csv file including the xy coordinates (UTM, NAD83) for each pika genetic sample used in analyses. Data was collected in the field on handheld GPS units

SchwalmHabitatAvailabilityGene.pdf

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.Keywords: species distribution modeling, Random Forest, National Parks, Ochotona princeps, functional connectivity, American pika, realized niche, genetic neighborhoodKeywords: species distribution modeling, Random Forest, National Parks, Ochotona princeps, functional connectivity, American pika, realized niche, genetic neighborhoo

Landscape Resistance Surface Raster Files

Final landscape resistance surfaces for each study site

Genetic Distance Matrices

One .csv file per study site including the genetic distances among individual pika samples. Genetic distances were calculated from individual genotypes as a principal conponents distance calculated using the ecodist package in R

Pika Habitat Patch Centroids

One .csv file per study site including the xy coordinates (UTM, NAD83) for each pika habitat patch used in network analyses. Patch IDs correspond to Patch IDs in Patch Distance Matrices files. Centroids calculated in ArcGIS10.0

Pika Habitat Patch Distances

One .csv file per study site as a 3-column matrix including resistance distances and Euclidean distances among pika habitat patches. Resistance distance was calculated from the perimeter of each patch (polygon) using an overlapping tile approach with the program Circuitscape. Patch IDs correspond to Patch IDs in the Habitat Patch Centroid files. Resistance distance was not calculated between habitat patches separated by >10km