Cloth: 978-0-226-81832-0 | Paper: 978-0-226-81834-4 | Electronic: 978-0-226-81833-7
DOI: 10.7208/chicago/9780226818337.001.0001
ABOUT THIS BOOK
An essential guide to quantitative research methods in ecology and conservation biology, accessible for even the most math-averse student or professional.Quantitative research techniques have become increasingly important in ecology and conservation biology, but the sheer breadth of methods that must be understood—from population modeling and probabilistic thinking to modern statistics, simulation, and data science—and a lack of computational or mathematics training have hindered quantitative literacy in these fields. In this book, ecologist Justin Kitzes addresses those challenges for students and practicing scientists alike.
Requiring only basic algebra and the ability to use a spreadsheet, Handbook of Quantitative Ecology is designed to provide a practical, intuitive, and integrated introduction to widely used quantitative methods. Kitzes builds each chapter around a specific ecological problem and arrives, step by step, at a general principle through the process of solving that problem. Grouped into five broad categories—difference equations, probability, matrix models, likelihood statistics, and other numerical methods—the book introduces basic concepts, starting with exponential and logistic growth, and helps readers to understand the field’s more advanced subjects, such as bootstrapping, stochastic optimization, and cellular automata. Complete with online solutions to all numerical problems, Kitzes’s Handbook of Quantitative Ecology is an ideal coursebook for both undergraduate and graduate students of ecology, as well as a useful and necessary resource for mathematically out-of-practice scientists.
AUTHOR BIOGRAPHY
Justin Kitzes is assistant professor of biological sciences at the University of Pittsburgh. He is coeditor of The Practice of Reproducible Research:Case Studies and Lessons from the Data-Intensive Sciences.REVIEWS
TABLE OF CONTENTS
Introduction
Part I. Change over Time
1. Introducing Difference Equations
2. Duckweed on a Pond: Exponential Growth
3. Throwing Shade I: Logistic Growth
4. Throwing Shade II: Lotka-Volterra Competition
5. Rabies Removal: SIR Models
Part II. Understanding Uncertainty
6. Introducing Probability
7. A Bird in the Cam I: Single-Variable Probability
8. A Bird in the Cam II: Two-Variable Probability
9. Picking Ticks: Bayes’s Rule
10. Rabbit Rates: Probability Distributions
Part III. Modeling Multiple States
11. Introducing Matrix Models
12. Imagine All the Beetles: Age-Structured Models
13. The Road to Succession: Transition Matrices
14. A Pair of Populations: Absorption
15. Fish Finders: Diffusion
Part IV. Explaining Data
16. Introducing Statistics
17. Seedling Counts I: Maximum Likelihood
18. Seedling Counts II: Model Selection
19. Flattened Frogs I: Generalized Linear Models
20. Flattened Frogs II: Hypothesis Testing
Part V. Expanding the Toolbox
21. Other Techniques
22. Bird Islands: Graphical Thinking
23. Max Plant Institute: Optimization
24. Bears with Me: Stochastic Simulation
25. Natives in the Neighborhood: Cellular Automata
References
Index