title: GIS-based niche modeling for mapping species' habitat.
abstract: Ecological "niche modeling" using presence-only locality data and large-scale environmental variables provides a powerful tool for identifying and mapping suitable habitat for species over large spatial extents. We describe a niche modeling approach that identifies a minimum (rather than an optimum) set of basic habitat requirements for a species, based on the assumption that constant environmental relationships in a species' distribution (i.e., variables that maintain a consistent value where the species occurs) are most likely to be associated with limiting factors. Environmental variables that take on a wide range of values where a species occurs are less informative because they do not limit a species' distribution, at least over the range of variation sampled. This approach is operationalized by partitioning Mahalanobis D2 (standardized difference between values of a set of environmental variables for any point and mean values for those same variables calculated from all points at which a species was detected) into independent components. The smallest of these components represents the linear combination of variables with minimum variance; increasingly larger components represent larger variances and are increasingly less limiting. We illustrate this approach using the California Gnatcatcher (Polioptila californica Brewster) and provide SAS code to implement it.
authors.affiliation: Department of Biology and Center for Conservation Biology, University of California, Riverside 92521, USA. john.rotenberry@ucr.edu
authors.forename: John T
authors.initials: JT
authors.lastname: Rotenberry
authors.forename: Kristine L
authors.initials: KL
authors.lastname: Preston
authors.forename: Steven T
authors.initials: ST
authors.lastname: Knick
mesh_terms: D000818:Animals; D002140:California; D017753:Ecosystem; D008954:Models, Biological; D046109:Passeriformes / Q000502:physiology*