GIS-based niche modeling for mapping species' habitats
Ecology
By: J.T. Rotenberry, K.L. Preston, and S. Knick
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Abstract
Ecological a??niche modelinga?? 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.
| Publication type | Article |
|---|---|
| Publication Subtype | Journal Article |
| Title | GIS-based niche modeling for mapping species' habitats |
| Series title | Ecology |
| Volume | 87 |
| Issue | 6 |
| Year Published | 2006 |
| Language | English |
| Contributing office(s) | Forest and Rangeland Ecosystem Science Center |
| Description | p. 1458-1464 |
| Larger Work Type | Article |
| Larger Work Subtype | Journal Article |
| Larger Work Title | Ecology |
| First page | 1458 |
| Last page | 1464 |
| Google Analytic Metrics | Metrics page |