Journal
BIOLOGICAL CONSERVATION
Volume 117, Issue 2, Pages 143-150Publisher
ELSEVIER SCI LTD
DOI: 10.1016/S0006-3207(03)00288-X
Keywords
geographic information system; habitat model; akaike information criterion; logistic regression; Antechinus minimus
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In recent years, predictive habitat distribution models, derived by combining multivariate statistical analyses with Geographic Information System (GIS) technology, have been recognised for their utility in conservation planning. The size and spatial arrangement of suitable habitat can influence the long-term persistence of some faunal species. In southwestern Victoria, Australia, populations of the rare swamp antechinus (Antechinus minimus maritimus) are threatened by further fragmentation of suitable habitat. In the current study, a spatially explicit habitat suitability model was developed for A. minimus that incorporated a measure of vegetation structure. Models were generated using logistic regression with species presence or absence as the dependent variable and landscape variables, extracted from both GIS data layers and multi-spectral digital imagery, as the predictors. The most parsimonious model, based on the Akaike Information Criterion, was spatially extrapolated in the GIS. Probability of species presence was used as an index of habitat suitability. A negative association between A. minimus presence and both elevation and habitat complexity was evidenced, suggesting a preference for relatively low altitudes and a vegetation structure of low vertical complexity. The predictive performance of the selected model was shown to be high (91 %), indicating a good fit of the model to the data. The proportion of the study area predicted as suitable habitat for A. minimus (Probability of occurrence greater than or equal to0.5) was 11.7%. Habitat suitability maps not only provide baseline information about the spatial arrangement of potentially suitable habitat for a species, but they also help to refine the search for other populations, making them an important conservation tool. (C) 2003 Elsevier Ltd. All rights reserved.
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