Habitat Suitability and Distribution Models
With Applications in R

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

Antoine Guisan (Author), Wilfried Thuiller (Author), Niklaus E. Zimmermann (Author)

9780521765138, Cambridge University Press

Hardback, published 14 September 2017

478 pages, 133 b/w illus. 8 tables
23.5 x 15.6 x 2.6 cm, 0.93 kg

This book introduces the key stages of niche-based habitat suitability model building, evaluation and prediction required for understanding and predicting future patterns of species and biodiversity. Beginning with the main theory behind ecological niches and species distributions, the book proceeds through all major steps of model building, from conceptualization and model training to model evaluation and spatio-temporal predictions. Extensive examples using R support graduate students and researchers in quantifying ecological niches and predicting species distributions with their own data, and help to address key environmental and conservation problems. Reflecting this highly active field of research, the book incorporates the latest developments from informatics and statistics, as well as using data from remote sources such as satellite imagery. A website at www.unil.ch/hsdm contains the codes and supporting material required to run the examples and teach courses.

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.

Subject Areas: Conservation of the environment [RNK], Applied ecology [RNC], Environmentalist, conservationist & Green organizations [RNB], The environment [RN], Biogeography [RGM], Biology, life sciences [PS]