Testing GIS-Generated Least-Cost Path Predictions forMartes pennanti(Fisher) and its Application for Identifying Mammalian Road-crossings in Northern New Hampshire

Abstract

Abstract To mitigate the unintended consequences of roads and habitat fragmentation, biologists model wildlife corridors with least-cost path (LCP) analysis of spatial data managed with geographic information systems. However, the ability of LCP models to accurately predict preferred movement corridors remains questionable. We tested the effectiveness of an LCP model constructed using literature review, expert opinion, and the relative distribution of land-cover types present at roadside observations of Martes pennanti (Fisher). The model was then used to predict road-crossing corridors of Fishers, Lynx rufus (Bobcat), and Ursus americanus (American Black Bear) within our study area in northern New Hampshire. Roadside data were collected through track surveys from 5 Dec 2005–25 May 2006. Our analysis demonstrated that least-cost modeling successfully identified roadside wildlife corridors for Fishers and Bobcats, but not for American Black Bears.