Predicting mammal species richness and distributions: testing the effectiveness of satellite-derived land cover data
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Mapping species richness and distributions is an important aspect of conservation and land use planning, but the time and cost of producing maps from field surveys is prohibitive. It is useful, therefore, if mappable environmental variables, from a readily accessible source, can be used as surrogates for species attributes. We evaluated the power of satellite-derived land cover information, from the Land Cover Map of Great Britain, to predict species richness and occurrences of terrestrial mammals in one hundred 10×10 km quadrats, from four regions of Britain. The predictive power of the land cover data was relatively poor – with a few exceptions, land cover explained less than half of the variation in mammal species richness and occurrence in regression models. Predictive power was considerably stronger when regions were analyzed separately than when analyzed together, and best fitting models varied between regions and between mammal taxa. Predictive power was also affected (positively or negatively depending on taxon) when PCA-ordinated land cover variables were used as predictors. The predictive strength of the land cover data was probably limited mostly by the high proportion of British mammal species with geographic distributions changing rapidly and independently of land cover (and hence the non-saturation of preferred habitats), and to a lesser extent by shortcomings in the mammal and land cover data, and the influence of landscape factors other than land cover on mammal distributions. The results suggest that regional stratification is essential when attempting to predict species richness and distributions, even across relatively limited areas such as Great Britain. We conclude that caution is necessary in using results from environmental information systems such as this as a basis for conservation and land use planning decisions.
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- Predicting mammal species richness and distributions: testing the effectiveness of satellite-derived land cover data
Volume 14, Issue 5 , pp 423-435
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- Kluwer Academic Publishers
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- associative models
- biodiversity mapping
- land cover
- species richness
- Industry Sectors
- Author Affiliations
- 1. Wildlife Conservation Research Unit, Department of Zoology, University of Oxford, South Parks Road, Oxford , OX1 3PS, , UK
- 2. Centre for Land Use & Water Resources Research, The University, Newcastle upon Tyne , NE1 7RU, , UK