Ecology, vol. 87, issue 6 (2006) pp. 1458-1464
See, stats, and : https : / / www . researchgate . net / publication / 6917793 GIS - BASED SPECIES ' HABITAT Article DOI : 10 . 1890 / 0012 - 9658 (2006) 87 [ 1458 : GNMFMS ] 2 . 0 . CO ; 2 : PubMed CITATIONS 97 READS 365 3 , including : John . Rotenberry University 132 , 853 SEE Kristine University , Riverside 8 SEE All . Rotenberry . The . All - text and , letting . 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 D 2 (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 .
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