Analysis and Management of Animal Populations

The goal of this important volume is to link management, evaluation, and conservation to modeling, estimation, and decision-making methods. Four major sections review these methods and applications in science-based conservation. Part I provides a methodological framework for quantifying and modeling field observations, with special emphasis on sampling design and analysis. Part II is a comprehensive framework for dynamic modeling of populations, with examples from familiar organisms and ecosystems. Part III addresses the estimation of population attributes with sampling data, focusing specifically on the use of count data to estimate population parameters. Part IV explains decision analysis and optimal management of populations.

Preface. Part I: Framework for Modeling, Estimation, and Management of Animal Populations Introduction to Population Ecology. Scientific Process in Animal Ecology. Models and the Investigation of Populations. Estimation and Hypothesis Testing in Animal Ecology. Survey Sampling and the Estimation of Population Parameters. Design of Experiments in Animal Ecology. Part II: Dynamic Modeling of Animal Populations Principles of Model Development and Assessment. Traditional Models of Population Dynamics. Model Identification with Time Series Data. Stochastic Processes in Population Models. The Use of Models in Conservation and Management. Part III: Estimation Methods for Animal Populations Estimating Abundance Based on Counts. Estimating Abundance with Distance-Based Methods. Estimating Abundance for Closed Populations with Capture-Recapture Methods. Estimation of Demographic Parameters. Estimation of Survival Rates with Band Recoveries. Estimating Survival, Movement, and Other State Transitions with Mark-Recapture Methods. Estimating Abundance and Recruitment for Open Populations with Mark-Recapture Methods. Combining Closed and Open Mark-Recapture Models: The Robust Design. Estimation of Community Parameters. Part IV: Decision Analysis for Animal Populations Optimal Decision Making in Population Biology. Traditional Approaches to Optimal Decision Analysis. Modern Approaches to Optimal Decision Analysis. Uncertainty, Learning, and Decision Analysis. Case Study: Management of the Sport Harvest of North American Waterfowl. Appendix A: Conditional Probability and Bayes' Theorem. Appendix B: Matrix Algebra. Appendix C: Differential Equations. Appendix D: Difference Equations. Appendix E: Some Probability Distributions and Their Properties. Appendix F: Methods for Estimating Statistical Variation. Appendix G: Computer Software for Population and Community Estimation. Appendix H: The Mathematics of Optimization References. Index.