Empirical estimation of dispersal resistance surfaces: a case study with red-cockaded woodpeckers
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Persistence of wildlife populations depends on the degree to which landscape features facilitate animal movements between isolated habitat patches. Due to limited data availability, the effect of landscape features on animal dispersal is typically estimated using expert opinion. With sufficient data, however, resistance surfaces can be estimated empirically. After modeling suitable prospecting habitat using an extensive dataset from the federally endangered red-cockaded woodpecker (Picoides borealis), we used data from over 800 prospecting events from 34 radio-tagged birds to identify the best relationship between habitat suitability and resistance surfaces. Our results demonstrated that juvenile female P. borealis prospecting for new territories beyond their natal territories preferred to traverse through forests with tall canopy and minimal midstory vegetation. The non-linear relationship between habitat suitability and resistance surfaces was the most biologically relevant transformation, which in turn identified the specific forest composition that promoted and inhibited prospecting and dispersal behavior. These results corresponded with over 60 % of dispersal events from an independent dataset of short-distance dispersal events. This new understanding of P. borealis prospecting behavior will help to identify areas necessary for maintaining habitat connectivity and to implement effective management strategies. Our approach also provides a framework to not only estimate and evaluate resistance surfaces based on species-specific responses to intervening landscape features, but also addresses an often-neglected step, selecting a biologically relevant function to transform habitat suitability model into a resistance surface.
KeywordsNatal dispersal Picoides borealis Prospecting Radio-telemetry LiDAR
We thank D. Urban, C. Song, J. Weiss for suggestions regarding study design and analyses. J. Kappes, D. Kesler, and D. Kuefler collaborated in the design and execution of the radio-telemetry field study. We would also like to thank the Sandhills Ecological Institute and Fort Bragg’s Endangered Species Branch for all their efforts in collecting and organizing the extensive monitoring data. We are grateful to the North Carolina Floodplain Mapping Program for providing LiDAR data. We thank Z. Cleveland, P. Beier and an anonymous reviewer for extremely helpful suggestions and comments. Funding for this project was provided by the U.S. Department of Defense Strategic Environmental Research and Development Program (RC-1471).
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