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Habitat Suitability and Distribution Model 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 to quantify ecological niches and predict species distributions with their own data, and help addressing key environmental and conservation problems. Reflecting this highly active field of research, Habitat Suitability and Distribution Model 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.
Chapter 1. General content of the book
Part I. Overview, principles, theory and assumptions behind habitat suitability modelling
Chapter 2. Overview of the HSM modelling procedure
Chapter 3. What drives species distributions?
Chapter 4. From niche to distribution: basic modelling principles and applications
Chapter 5. Assumptions behind HSMs
Part II. Data acquisition, sampling design and spatial scales
Chapter 6. Environmental predictors – issues of processing and selection
Chapter 7. Species data – issues of acquisition and design
Chapter 8. Ecological scales – issues of resolution and extent
Part III. Modelling approaches and model calibration
Chapter 9. Envelopes and distance-based approaches
Chapter 10. Regression-based approaches
Chapter 11. Classification approaches and machine learning systems
Chapter 12. Boosting and bagging approaches
Chapter 13. Maximum Entropy
Chapter 14. Ensemble modelling and modelling averaging
Part IV. Evaluating models: errors and uncertainty
Chapter 15. Measuring model accuracy: which metrics to use?
Chapter 16. Assessing model performance: which data to use?
Part V. Predictions in space and time
Chapter 17. Projecting models in space and time
Part VI. Data and tools used in this book, with developed case studies
Chapter 18. Datasets and tools used for the examples in this book
Chapter 19. The biomod2 modelling package examples
Part VII. Conclusions and future perspectives
Chapter 20. Conclusions and future perspectives in habitat suitability modelling
Glossary & Definitions of terms and concepts
Methods, Approaches, Models, Techniques, Algorithms
ENM, SDM, HSM, etc.: Different names and acronyms for the same models
Environment, habitat, niche, niche-biotope duality and distribution
Technical acronyms for the most commonly used modelling techniques
Antoine Guisan is Professor at the University of 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 modelling, very high-resolution spatial modelling 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 National Center for Scientific Research, Laboratory of Alpine Ecology in Grenoble, France. Besides being a specialist in habitat suitability and distribution models, his interests include macroecology, macroevolution, conservation, biodiversity modelling 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 ETH. 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.