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Environmental science (ecology, conservation, and resource management) is an increasingly quantitative field. This accessible textbook introduces quantitative ecology in a manner that aims to confront the limitations of the current literature and thereby appeal to a far wider audience.
List of contents
- About This Book
- Part I: Fundamentals of Dynamic Models
- 1: Why Do We Model?
- 2: Introduction to Population Models
- 3: Structured Population Models
- 4: Competition and Predation Models
- 5: Stochastic Population Models
- Part II: Fitting Models to Data
- 6: Why Fit Models to Data?
- 7: Random Variables and Probability
- 8: Likelihood and Its Applications
- 10: Model Selection
- 10: Bayesian Statistics
- Part III: Skills
- 11: Mathematics Refresher
- 12: Modeling in Spreadsheets
- 13: Modeling in R
- 14: Skills for Dynamic Models
- 15: Sensitivity Analysis
- 16: Skills for Fitting Models to Data
- Part IV: Putting It All Together and Next Steps
- 17: Putting It Together : Fitting a Dynamic Model
- 18: Next Steps
About the author
Timothy E. Essington is a Professor at the School of Aquatic and Fishery Sciences, University of Washington, USA. He is also Director of the Center for Quantitative Sciences and of the University of Washington's QERM Graduate Program. His research chiefly focuses on food web interactions involving fish in marine, estuarine and freshwater habitats.
Summary
Environmental science (ecology, conservation, and resource management) is an increasingly quantitative field. This accessible textbook introduces quantitative ecology in a manner that aims to confront the limitations of the current literature and thereby appeal to a far wider audience.
Additional text
Very accessibly written and clearly aimed at readers who might be predisposed to hate math but are open to a gentle presentation with plenty of real-world examples.
