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Habitat Suitability and Distribution Models

With Applications in R

Antoine Guisan, Wilfried Thuiller, Niklaus. E. Zimmermann

Buch (Taschenbuch, Englisch)
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Beschreibung

This book introduces key stages of niche-based habitat suitability model building, evaluation and prediction, featuring examples using R.

Produktdetails

Einband Taschenbuch
Seitenzahl 514
Erscheinungsdatum 28.09.2018
Sprache Englisch
ISBN 978-0-521-75836-9
Verlag Cambridge University Press
Maße (L/B/H) 22.9/15.2/2.7 cm
Gewicht 736 g
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  • Bilder
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  • Inhaltsverzeichnis
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  • Foreword; Preface; Acknowledgements; Authors' contributions; Introduction; 1. General content of the book; Part I. Overview, Principles, Theory and Assumptions behind Habitat Suitability Modeling: 2. Overview of the HSM modeling procedure; 3. What drives species distributions?; 4. From niche to distribution: basic modeling principles and applications; 5. Assumptions behind HSMs; Part II. Data Acquisition, Sampling Design and Spatial Scales: 6. Environmental predictors " issues of processing and selection; 7. Species data " issues of acquisition and design; 8. Ecological scales " issues of resolution and extent; Part III. Modeling Approaches and Model Calibration: 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 modeling averaging; Part IV. Evaluating Models: Errors and Uncertainty: 15. Measuring model accuracy: which metrics to use?; 16. Assessing model performance: which data to use?; Part V. Predictions in Space and Time: 17. Projecting models in space and time; Part VI. Data and Tools Used in this Book, with Developed Case Studies: 18. Datasets and tools used for the examples in this book; 19. The biomod2 modeling package examples; Part VII. Conclusions and Future Perspectives: 20. Conclusions and future perspectives in habitat suitability modeling; Glossary and definitions of terms and concepts; References; Index.