Genetic inference as a method for modelling occurrence: A viable alternative to visual surveys
Management and conservation require a comprehensive understanding of species distributions and habitat requirements. Reliable species occurrence data are critical in the face of climate change and other anthropogenic activity, but are often difficult to obtain, particularly for wide ranging species....
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Published in | Austral ecology Vol. 39; no. 8; pp. 952 - 962 |
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Main Authors | , , |
Format | Journal Article |
Language | English |
Published |
Richmond
Blackwell Publishing Ltd
01.12.2014
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Subjects | |
Online Access | Get full text |
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Summary: | Management and conservation require a comprehensive understanding of species distributions and habitat requirements. Reliable species occurrence data are critical in the face of climate change and other anthropogenic activity, but are often difficult to obtain, particularly for wide ranging species. This directly affects ecological models of occurrence and habitat suitability and, in turn, conservation and management decisions. We used generalized linear mixed‐effects models to identify ecological determinants of occurrence for four macropod species (across a region of tropical northern Australia) using a non‐invasive genetic scat approach with and without additional observation records from visual surveys. We show that genetically derived occurrence data, alone, can be used to develop informative ecological models that describe the inter‐specific habitat requirements of macropods. Furthermore, we show that genetic scat surveys of macropods are cheaper and less time consuming to conduct, and tend to provide more occurrence records (and less false absences) than visual surveys. We conclude that indirect surveys using molecular approaches have an important role to play in modelling species' occurrence, and developing future management practices and guidelines to aid species conservation. |
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Bibliography: | ARC Super Science Fellowship Appendix S1. Data sources for the predictors used to model occurrence. Appendix S2. Cost of lab work for identifying scat samples. Appendix S3. GLMM results for all M. antilopinus candidate models using molecularly determined occurrence records. Appendix S4. GLMM results for all M. agilis candidate models using molecularly determined occurrence records. Appendix S5. GLMM results for all M. robustus candidate models using molecularly determined occurrence records. Appendix S6. GLMM results for all M. giganteus candidate models using molecularly determined occurrence records. Appendix S7. GLMM results for all M. robustus and M. giganteus candidate models using occurrence data from combined identification records. ark:/67375/WNG-J3SPX8X1-X ARC Future Fellowship Australian Research Council (ARC) Discovery Project - No. DP1096427 istex:B771DEE9BFEB90EECC682453BA5A2FE979677054 ArticleID:AEC12160 ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 23 |
ISSN: | 1442-9985 1442-9993 |
DOI: | 10.1111/aec.12160 |