The goal of this book is to make some underutilized but potentially very useful methods in experimental design and analysis available to ecologists, and to encourage better use of standard statistical techniques. Ecology has become more and more an experimental science in both basic and applied work,but experiments in the field and in the laboratory often present formidable statistical difficulties. Organized around providing solutions to ecological problems, this book offers ways to improve the statistical aspects of conducting manipulative ecological experiments, from setting them up to interpreting and reporting the results. An abundance of tools, including advanced approaches, are made available to ecologists in step-by-step examples, with computer code provided for common statistical packages. This is an essential how-to guide for the working ecologist and for graduate students preparing for research and teaching careers in the field of ecology.
Table of Contents
1. Introduction: Theories, hypotheses, and statistics 2. Exploratory data analysis and graphic display 3. ANOVA: Experiments in controlled environment 4. ANOVA and ANCOVA: Field competition experiments 5. MANOVA: Multiple response variables and multispecies interactions 6. Repeated-measures analysis: Growth and other time-dependent measures 7. Time-series intervention analysis: Unreplicated large-scale experiments 8. Nonlinear curve fitting: Predation and functional response curves 9. Multiple regression: Herbivory 10. Path analysis: Pollination 11. Population sampling and bootstrapping in complex designs: Demographic analysis 12. Failure-time analysis: Emergence, flowering, survivorship, and other waiting times 13. The bootstrap and the jackknife: Describing the precision of ecological indices 14. Spatial statistics: Analysis of field experiments 15. Mantel tests: Spatial structure in field experiments 16. Model validation: Optimal foraging theory 17. Meta-analysis: Combining the results of independent experiments