Title of article :
An evaluation of the predictive performance of distributional models for flora and fauna in north-east New South Wales
Author/Authors :
Pearce، نويسنده , , J. and Ferrier، نويسنده , , S. and Scotts، نويسنده , , D.، نويسنده ,
Issue Information :
روزنامه با شماره پیاپی سال 2001
Pages :
14
From page :
171
To page :
184
Abstract :
To use models of species distributions effectively in conservation planning, it is important to determine the predictive accuracy of such models. Extensive modelling of the distribution of vascular plant and vertebrate fauna species within north-east New South Wales has been undertaken by linking field survey data to environmental and geographical predictors using logistic regression. These models have been used in the development of a comprehensive and adequate reserve system within the region. We evaluate the predictive accuracy of models for 153 small reptile, arboreal marsupial, diurnal bird and vascular plant species for which independent evaluation data were available. edictive performance of each model was evaluated using the relative operating characteristic curve to measure discrimination capacity. Good discrimination ability implies that a model’s predictions provide an acceptable index of species occurrence. scrimination capacity of 89% of the models was significantly better than random, with 70% of the models providing high levels of discrimination. Predictions generated by this type of modelling therefore provide a reasonably sound basis for regional conservation planning. scrimination ability of models was highest for the less mobile biological groups, particularly the vascular plants and small reptiles. In the case of diurnal birds, poor performing models tended to be for species which occur mainly within specific habitats not well sampled by either the model development or evaluation data, highly mobile species, species that are locally nomadic or those that display very broad habitat requirements. Particular care needs to be exercised when employing models for these types of species in conservation planning.
Keywords :
Species distribution model , conservation , logistic regression , Australia. , Model validation
Journal title :
Journal of Environmental Management
Serial Year :
2001
Journal title :
Journal of Environmental Management
Record number :
1569059
Link To Document :
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