Habitat Suitability and Distribution Models

Antoine Guisan is Professor at the Université de Lausanne, Switzerland, where he leads the ECOSPAT Spatial Ecology group. Besides being a specialist in habitat suitability and distribution models, his interests also include ecological niche dynamics in space and time, community and multitrophic modeling, very high resolution spatial modeling in mountain environments, and applications of models to environmental decision-making and transfer of scientific knowledge to society. Wilfried Thuiller is a senior scientist at the Centre national de la recherche scientifique (CNRS), Laboratory of Alpine Ecology in Grenoble, France. Besides being a specialist in habitat suitability and distribution models, his interests include macroecology, macroevolution, conservation, biodiversity modeling with both mechanistic and phenomenological models, community ecology, functional ecology, and ecosystem functioning in alpine environments. Niklaus E. Zimmermann is a senior scientist and directorate member of the Swiss Federal Research Institute WSL, and an adjunct professor at the Swiss Federal Institute of Technology Zurich (ETH Zurich). Besides being a specialist in habitat suitability and distribution models, his interests include macroecology, macroevolution, biodiversity and community modeling using both empirical and mechanistic approaches, as well as conservation and applied biodiversity management support.

• 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.

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