Habitat suitability and distribution models : with applications in R /
By: Guisan, A. (Antoine) [author.].
Contributor(s): Thuiller, Wilfried [author.] | Zimmermann, Niklaus E [author.].
Series: Ecology, biodiversity, and conservation: Publisher: Cambridge, United Kingdom ; New York, NY, USA : Cambridge University Press, 2017Description: xiii, 462 pages : illustrations (some color), maps (some color) ; 24 cm.Content type: text | text | still image | cartographic image Media type: unmediated | unmediated Carrier type: volume | volumeISBN: 9780521758369; 9780521758369:; 052175836X; 9780521765138; 0521765137.Subject(s): Habitat suitability index models | Ecology![](/opac-tmpl/bootstrap/images/filefind.png)
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Item type | Current library | Call number | Status | Date due | Barcode | Item holds |
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ATU Sligo Yeats Library Main Lending Collection | 333.954 GUI (Browse shelf(Opens below)) | Available | 0082640 |
Includes bibliographical references (pages 417-457) and index.
1. General content of this book -- 2. Overview of the habitat suitability modeling procedure -- 3. What drives species distributions? -- 4. From niche to distribution : basic modeling principles and applications -- 5. Assumptions behind habitat suitability models -- 6. Environmental predictors : issues of processing and selection -- 7. Species data : issues of acquisition and design -- 8. Ecological scales : issues of resolution and extent -- 9. Envelopes and distance-based approaches -- 10. Regression-based approaches -- 11. Classification approaches and machine-learning systems -- 12. Boosting and bagging approaches -- 13. Maximum entropy -- 14. Ensemble modeling and model averaging -- 15. Measuring model accuracy : which metrics to use? -- 16. Assessing model performance : which data to use? -- 17. Projecting models in space and time -- 18. Datasets and tools used for the examples in this book -- 19. The Biomod2 modeling package examples -- 20. Conclusions and future perspectives in habitat suitability modeling.
This work introduces the key stages of niche-based habitat suitability model building, evaluation and prediction. Extensive examples using R support students and researchers to quantify ecological niches and predict species distributions with their own data.