Modeling and predicting species occurrence using broad-scale environmental variables: an example with butterflies of the Great Basin
Article Abstract:
The development of predictive models for the occurrence of resident butterflies in the central Great Basin of western North America as a function of easily quantified environmental variables using the Bayesian logistic regression is studied. The results show that the Bayesian-logistic model of species occurrence is more useful than conventional logistic models.
Publication Name: Conservation Biology
Subject: Zoology and wildlife conservation
ISSN: 0888-8892
Year: 2001
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Validation tests of predicitve models of butterfly occurrence based on environmental variables
Article Abstract:
Research has been conducted on butterfly occurrence. The authors have developed the predictive models of this occurrence which is based on environmental variables, and they describe the models.
Publication Name: Conservation Biology
Subject: Zoology and wildlife conservation
ISSN: 0888-8892
Year: 2003
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Using Indicator Species to Predict Species Richness of Multiple Taxonomic Groups
Article Abstract:
A Bayesian approach and genetic algorithms are used to delineate combined and individual species richness for avian and butterfly populations.
Publication Name: Conservation Biology
Subject: Zoology and wildlife conservation
ISSN: 0888-8892
Year: 2005
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