CROSS-VALIDATING MULTIPLE POPULATION ESTIMATION TECHNIQUES FOR COLUMBIAN BLACK-TAILED DEER (ODOCOILEUS HEMIONUS COLUMBIANUS).
Janelle A. Dorcy; University of California, Berkeley; 738 Canterbury Avenue, Livermore, CA, 94550; (925) 963-5726; janelle.dorcy@gmail.com; Alex McInturff, Kaitlyn M. Gaynor, Brett J. Furnas, Justin S. Brashares
Black-tailed deer (Odocoileus hemionus) are an ecologically and economically important species throughout the Western US. Deer population estimates derived from harvest data and visual counts have historically provided uncertain results, hindering management. In collaboration with the California Department of Fish and Wildlife, we aim to improve methods of population estimation for Columbian black-tailed deer (Odocoileus hemionus columbianus). We conduct fieldwork at the University of California Hopland Research and Extension Center in Mendocino County, where decades of research have made the deer population one of the most-well studied in the nation. We are now cross-validating and integrating population estimation methods using multiple data sources. A grid of 37 Reconyx HyperFire cameras, operating continuously since June 2016, provides data for N-mixture models and buck-doe and adult-fawn ratios. We are also using genetic mark-recapture methods from fecal pellets, using a novel, cost-effective, and efficient method of collection and are comparing two spatially variable study designs. Finally, we deployed GPS collars on 43 does and 7 bucks, which are providing information on home range size to parameterize statistical models of population estimation. Ultimately, integrated modeling using camera, genetic, and movement data will inform more precise population estimates. [This project is a student work-in-progress.]
Poster Session