Antoine Guisan (Switzerland Universite de Lausanne), Wilfried Thuiller, Niklaus E. Zimmermann
Habitat Suitability and Distribution Models
Antoine Guisan (Switzerland Universite de Lausanne), Wilfried Thuiller, Niklaus E. Zimmermann
Habitat Suitability and Distribution Models
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This book 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. A website at www.unil.ch/hsdm contains example codes and supporting material.
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This book 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. A website at www.unil.ch/hsdm contains example codes and supporting material.
Produktdetails
- Produktdetails
- Ecology, Biodiversity and Conservation
- Verlag: Cambridge University Press
- Seitenzahl: 514
- Erscheinungstermin: 28. September 2018
- Englisch
- Abmessung: 229mm x 152mm x 28mm
- Gewicht: 830g
- ISBN-13: 9780521758369
- ISBN-10: 052175836X
- Artikelnr.: 48378328
- Ecology, Biodiversity and Conservation
- Verlag: Cambridge University Press
- Seitenzahl: 514
- Erscheinungstermin: 28. September 2018
- Englisch
- Abmessung: 229mm x 152mm x 28mm
- Gewicht: 830g
- ISBN-13: 9780521758369
- ISBN-10: 052175836X
- Artikelnr.: 48378328
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.
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.
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.
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.
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.