Publication Date:
2011-06-10
Description:
Disease is often implicated as a factor in population declines of wildlife and plants. Understanding the characteristics that may predispose a species to infection by a particular pathogen can help direct conservation efforts. Recent declines in amphibian populations world-wide are a major conservation issue and may be caused in part by a fungal pathogen, Batrachochytrium dendrobatidis (Bd). We used Random Forest, a machine learning approach, to identify species-level characteristics that may be related to susceptibility to Bd. Our results suggest that body size at maturity, aspects of egg laying behavior, taxonomic order and family, and reliance on water are good predictors of documented infection for species in the continental United States. These results suggest that, whereas local-scale environmental variables are important to the spread of Bd, species-level characteristics may also influence susceptibility to Bd. The relationships identified in this study suggest future experimental tests, and may target species for conservation efforts. Content Type Journal Article Pages 1-10 DOI 10.1007/s10531-011-0066-4 Authors Betsy A. Bancroft, School of Forest Resources, University of Washington, Seattle, WA 98195-2100, USA Barbara A. Han, Odum School of Ecology, University of Georgia, 30602 Athens, GA, Greece Catherine L. Searle, Department of Zoology, Oregon State University, Corvallis, OR 97331, USA Lindsay M. Biga, Department of Zoology, Oregon State University, Corvallis, OR 97331, USA Deanna H. Olson, USDA Forest Service, Pacific Northwest Research Station, Corvallis, OR 97331, USA Lee B. Kats, Natural Science Division, Seaver College, Pepperdine University, Malibu, CA 90263, USA Joshua J. Lawler, School of Forest Resources, University of Washington, Seattle, WA 98195-2100, USA Andrew R. Blaustein, Department of Zoology, Oregon State University, Corvallis, OR 97331, USA Journal Biodiversity and Conservation Online ISSN 1572-9710 Print ISSN 0960-3115
Print ISSN:
0960-3115
Electronic ISSN:
1572-9710
Topics:
Biology
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