RESEARCH ARTICLE Estimating landscape resistance to dispersal Tabitha Graves • Richard B. Chandler • J. Andrew Royle • Paul Beier • Katherine C. Kendall Received: 16 December 2013 / Accepted: 10 June 2014 / Published online: 16 July 2014 Ó Springer Science+Business Media Dordrecht (outside the USA) 2014 Abstract Dispersal is an inherently spatial process that can be affected by habitat conditions in sites encountered by dispersers. Understanding landscape resistance to dispersal is important in connectivity studies and reserve design, but most existing methods use resistance functions with cost parameters that are subjectively chosen by the investigator. We develop an analytic approach allowing for direct estimation of resistance parameters that folds least cost path methods typically used in simulation approaches into a formal statistical model of dispersal distributions. The core of our model is a frequency distribution of dispersal distances expressed as least cost distance rather than Euclidean distance, and which includes terms for feature-specific costs to dispersal and sex (or other traits) of the disperser. The model requires only origin and settlement locations for multiple individ- uals, such as might be obtained from mark–recapture studies or parentage analyses, and maps of the relevant habitat features. To evaluate whether the model can estimate parameters correctly, we fit our model to data from simulated dispersers in three kinds of landscapes (in which resistance of environmental variables was categorical, continuous with a patchy configuration, or continuous in a trend pattern). We found maximum likelihood estimators of resistance and individual trait parameters to be approximately unbiased with moderate sample sizes. We applied the model to a small grizzly bear dataset to demonstrate how this approach could be used when the primary interest is in the prediction of costs and found that estimates were consistent with expectations based on bear ecology. Our method has important practical applications for testing hypotheses about dispersal ecology and can be used to inform connectivity planning efforts, via the resistance estimates and confidence intervals, which can be used to create a data-driven resistance surface. Keywords Animal movement  Connectivity  Cost distance  Corridor  Dispersal  Least cost path  Movement  Landscape permeability Electronic supplementary material The online version of this article (doi:10.1007/s10980-014-0056-5) contains supple- mentary material, which is available to authorized users. T. Graves  P. Beier Northern Arizona University, P.O. Box 15018, Flagstaff, AZ 86011, USA T. Graves Colorado State University, 201 JVK Wagar, Fort Collins, CO 80523, USA T. Graves (&)  K. C. Kendall U.S. Geological Survey Northern Rocky Mountain Science Center, Glacier Field Station, Glacier National Park, West Glacier, MT 59936, USA e-mail: tgraves@usgs.gov R. B. Chandler  J. A. Royle U.S. Geological Survey Patuxent Wildlife Research Center, 12100 Beech Forest Road, Laurel, MD 20708, USA 123 Landscape Ecol (2014) 29:1201–1211 DOI 10.1007/s10980-014-0056-5