Part I provides a basic background in population and community modeling. It introduces statistical models, and familiarizes the reader with important concepts in the design of monitoring and research programs. These programs provide the essential data that guide conservation decision making. Part II covers the principal methods used to estimate abundance, occupancy, demographic parameters, and community parameters, including occupancy sampling, sample counts, distance sampling, and capture-mark-recapture (for both closed and open populations). Emphasis is placed on practical aspects of designing and implementing field studies, and the proper analysis of data. Part III introduces structured decision making and adaptive management, in which predictive models are used to inform conservation decision makers on appropriate decisions in the face of uncertaintywith the goal of reducing uncertainty through monitoring and research. A detailed case study is used to illustrate each of these themes.

Numerous worked examples and accompanying electronic material (on a website -http://www.blackwellpublishing.com/conroy - and accompanying CD) provide the details of model construction and application, and data analysis.

DR MICHAEL J. CONROY has nearly 30 years of experience in developing sampling approaches, statistical estimation methods, and modeling for a wide variety of natural resource management problems. He is the author of numerous publications in applied quantitative approaches, and is coauthor on the widely acclaimed volume by Williams et al. (2002). He is currently Adjunct Professor of Wildlife Ecology and Management at the University of Georgia, and Assistant Unit Leader of the Georgia Cooperative Fish and Wildlife Research Unit. He is literate in Spanish and has taught short courses on quantitative methods in the US, Spain, India, and Latin America.

DR JOHN P. CARROLL has been researching conservation issues relative to the Galliformes for more than 20 years. He is Chair of the World Pheasant Association/BirdLife/IUCN Species Survival Commission Partridge, Quail, and Francolin Specialist Group. He is author of numerous publications on the biology and conservation of Galliformes and the effects of agricultural practices on wildlife. He is currently Professor of Wildlife Ecology and Management in the Warnell School of Forestry and Natural Resources at the University of Georgia. He has taught short courses on ??? eld research methods and techniques in Malaysia, China, Nepal, and India.

Preface vii

Acknowledgements ix

Companion website and CD-ROM x

1 Introduction: the role of science in conservation 1

Part I Basic concepts in scientific investigations for conservation 7

2 Using models in conservation biology 9

3 Models of population dynamics 15

4 Applying population models to conservation 32

5 Basics of study design and analysis 47

Part II Conservation studies and monitoring programs 71

6 General principles of estimation 73

7 Occupancy (presenceabsence) analysis 81

8 Sample counts for abundance estimation 101

9 Distance sampling for estimating density and abundance 115

10 Capturemarkrecapture studies for estimating abundance and density 135

11 Estimation of survival from radiotelemetry, nesting success studies, and age distributions 160

12 Markrecapture for estimating survival, recruitment, abundance, and movement rates 189

13 Analysis of habitat 219

14 Estimation of species richness and other community parameters 230

Part III Integrating modeling and monitoring for conservation 251

15 Elements of conservation decision making 253

16 Accounting for uncertainty in conservation decisions 265

17 Learning and adaptive management 274

18 Case study: decision modeling and adaptive management for declining grassland birds in the southeastern USA 289

19 Summary and recommendations 303

Literature cited 307

Glossary 314

Appendix A: Statistical and modeling programs available on the worldwide web 324

Appendix B: Other internet resources 326

Appendix C: Modeling and statistical notation 328

Appendix D: Key to abundance and parameter estimation 331

Index 337