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Decision Making in Natural Resource Management: A Structured, Adaptive Approach

ISBN: 978-0-470-67175-7

April 2013

Wiley-Blackwell

474 pages

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Description

This book is intended for use by natural resource managers and scientists, and students in the fields of natural resource management, ecology, and conservation biology, who are confronted with complex and difficult decision making problems. The book takes readers through the process of developing a structured approach to decision making, by firstly deconstructing decisions into component parts, which are each fully analyzed and then reassembled to form a working decision model.  The book integrates common-sense ideas about problem definitions, such as the need for decisions to be driven by explicit objectives, with sophisticated approaches for modeling decision influence and incorporating feedback from monitoring programs into decision making via adaptive management. Numerous worked examples are provided for illustration, along with detailed case studies illustrating the authors’ experience in applying structured approaches. There is also a series of detailed technical appendices.  An accompanying website provides computer code and data used in the worked examples.

Additional resources for this book can be found at: www.wiley.com/go/conroy/naturalresourcemanagement.

About the Author
Michael J. Conroy is a Senior Research Scientist in the Warnell School of Forestry and Natural Resources at the University of Georgia. He has over thirty years experience in applications of quantitative approaches to solving problems in natural resource management and is the author of three previous books.  He teaches and runs workshops in modeling, statistical estimation, and structured decision making for undergraduate and graduate students and professionals both in the US and internationally.

James T. Peterson is the Assistant Unit Leader and Associate Professor for the USGS Oregon Cooperative Fish and Wildlife Research Unit at Oregon State University. He has been developing and teaching courses in applied quantitative decision making to undergraduate and graduate students and professionals in natural resource and related disciplines for more than a decade.