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1st ed 
Descript 
1 online resource (476 pages) 

text txt rdacontent 

computer c rdamedia 

online resource cr rdacarrier 
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Cover  Title page  Copyright page  Contents  List of boxes  Preface  Acknowledgements  Guide to using this book  Companion website  PART I.: Introduction To Decision Making  1: Introduction: Why a Structured Approach in Natural Resources?  The role of decision making in natural resource management  Common mistakes in framing decisions  Poorly stated objectives  Prescriptive decisions  Confusion of values and science  Poor use of information  What is structured decision making (SDM)?  Why should we use a structured approach to decision making?  Limitations of the structured approach to decision making  Adaptive resource management  Summary  References  2: Elements of Structured Decision Making  First steps: defining the decision problem  General procedures for structured decision making  Predictive modeling: linking decisions to objectives prospectively  Uncertainty and how it affects decision making  Type of uncertainty  Dealing with uncertainty in decision making  Summary  References  3: Identifying and Quantifying Objectives in Natural Resource Management  Identifying objectives  Identifying fundamental and means objectives  Clarifying objectives  Separating objectives from science  Barriers to creative decision making  Types of fundamental objectives  Identifying decision alternatives  Quantifying objectives  Dealing with multiple objectives  Multiattribute valuation  Utility functions  Determining weights by pricing out or indifference scores  Marginal gain  Swing weighting  Other approaches  Additional considerations  Decision, objectives, and predictive modeling  References  4: Working with Stakeholders in Natural Resource Management  Stakeholders and natural resource decision making  Why involve stakeholders?  Stakeholder analysis 

Stakeholder governance  Working with stakeholders  Characteristics of good facilitators  Getting at stakeholder values  Stakeholder meetings  The first workshop  References  Additional reading  PART II.: Tools for Decision Making and Analysis  5: Statistics and Decision Making  Basic statistical ideas and terminology  Probability  Probability distributions  Using data in statistical models for description and prediction  Why you should look at your data?  Linear models  Hierarchical models  Shrinkage estimators, sharing information  Bayesian inference  Example  Binomial likelihood with a beta prior on p  Hierarchical and random effects models  Resampling and simulation methods  Statistical significance  References  Additional reading  6: Modeling the Influence of Decisions  Structuring decisions  Influence diagrams  Frequent mistakes when structuring decisions  Defining node states  Decision trees  Solving a decision model  Conditional independence and modularity  Parameterizing decision models  Elicitation of expert judgment  Quantifying uncertainty in expert judgment  Group elicitation  The care and handling of experts  References  Additional reading  7: Identifying and Reducing Uncertainty in Decision Making  Types of uncertainty  Irreducible uncertainty  Reducible uncertainty  Effects of uncertainty on decision making  Approaches for incorporating uncertainty in decision making  Sensitivity analysis  Value of information  Imperfect information  Reducing uncertainty  Traditional approaches to reducing epistemic uncertainty  Reducing uncertainty through ARM  References  Additional reading  8: Methods for Obtaining Optimal Decisions  Overview of optimization  Factors affecting optimization  Single vs. multiple decision controls 

Unconstrained vs. constrained optimization  Static or equilibrium optimization vs. dynamic optimization  Deterministic vs. stochastic system response  Multiple attribute objectives and constrained optimization  Dynamic decisions  Optimization under uncertainty  Maximum expected values approach  Simulationoptimization  Stochastic dynamic programming  Analysis of the decision problem  Sensitivity analysis  Simulation of optimal decision impacts  Suboptimal decisions and "satisficing"  Other problems  Summary  References  PART III.: Applications  9: Case Studies  Case study 1 Adaptive Harvest Management of American Black Ducks  Background  Decision problem  Stakeholders, decision makers, and development of an SDM/ARM approach to black duck harvest management  Management objectives and decision alternatives  Model development  Incorporation of uncertainty  Evaluation of decision alternatives  Sensitivity analysis  Current status of black duck AHM  Case study 2 Management of Water Resources in the Southeastern US  Background  Decision problem  Stakeholders and decision makers  Management objectives and decision alternatives  Model development  Incorporation of uncertainty  Evaluation of decision alternatives  Sensitivity analysis  Current status of water resource management  Case study 3 Regulation of Largemouth Bass Sport Fishery in Georgia  Background and decision problem  Stakeholders and decision makers  Management objectives and decision alternatives  Model development  Incorporation of uncertainty  Evaluation of decision alternatives and sensitivity analysis  Value of information  Current status of largemouth bass management  Summary  References  10: Summary, Lessons Learned, and Recommendations  Summary  Lessons learned 

Structured decision making for Hector's Dolphin conservation  Landowner incentives for conservation of early successional habitats in Georgia  Cahaba shiner  Other lessons  References  PART IV.: Appendices  Appendix A: Probability and Distributional Relationships  Probability axioms  Conditional probability  Conditional independence  Expected value of random variables  Law of total probability  Bayes' theorem  Distribution moments  Sample moments  Additional reading  Appendix B: Common Statistical Distributions  General distribution characteristics  Distribution parameters  Distribution quantiles  Generation of random numbers  Continuous distributions  Uniform distribution  Normal distribution  Exponential distribution  Gamma distribution  Beta distribution  Distributions of quadratic forms  Discrete distributions  Discrete uniform  Bernoulli and binomial distributions  Multinomial distribution  Poisson distribution  Geometric distribution  Negative binomial distribution  Hypergeometric distribution  Reference  Additional reading  Appendix C: Methods for Statistical Estimation  General principles of estimation  Properties of estimators  Method of moments  Least squares  Maximum likelihood  Example: binomial likelihood  Bayesian approaches  Binomial likelihood with a beta prior on p  Example  posterior inference with a vague (noninformative) prior  Informative prior (I)  prior based on x successes in n initial trials  Example  posterior inference with prior from a previous study  Informative prior (II)  prior estimate of mean and variance of p  Conjugate distributions  Poisson likelihoodgamma conjugate prior  Posterior inference with a vague (noninformative) prior  Normal likelihood  normal conjugate prior 

Example  posterior inference with a vague (noninformative) prior  Monte Carlo methods for Bayesian inference  Example  Example  closed population capturerecapture  Empirical Bayes estimation  References  Appendix D: Parsimony, Prediction, and MultiModel Inference  General approaches to multimodel inference  Model plausibility  Example  Multimodel inference and model averaging  Example  AIC for least squares  Adjustment for overdispersion (quasilikelihood) for count data  Multimodel Bayesian inference  Computational approaches for Bayesian MMI  Reversible jump MCMC  Bayesian information criteria  References  Appendix E: Mathematical Approaches to Optimization  Review of general optimization principles  General statement of the optimization problem  Necessity and sufficiency conditions  Unconstrained Optimization  Classical programming  Bivariate classical programming  Example  conservation of 2 species  Multivariate classical programming  Sensitivity analysis  Nonlinear programming  Example: conservation of 2 species with inequality constraints  Linear programming  Example  Reserve design  Dynamic decision problems  Nonlinear programming  Example  The calculus of variations  Example  Pest control  Pontryagin's maximum principle  Dynamic programming  Discrete time dynamic programming  Example  Stochastic dynamic programming  Example  Harvest of a stochastically growing population  Transition matrix formulation of SDP  Example  Decision making under structural uncertainty  Reduction of structural uncertainty  Passive adaptation  Example  Passive adaptation  Active adaptation  Example  Active adaptation  Generalizations of Markov decision processes  Heuristic methods  Simulationgaming/simulationoptimization 

Genetic algorithms and machine learning 

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 commonsense 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 

Description based on publisher supplied metadata and other sources 

Electronic reproduction. Ann Arbor, Michigan : ProQuest Ebook Central, 2020. Available via World Wide Web. Access may be limited to ProQuest Ebook Central affiliated libraries 
Link 
Print version: Conroy, Michael J. Decision Making in Natural Resource Management : A Structured, Adaptive Approach
Hoboken : John Wiley & Sons, Incorporated,c2013 9780470671740

Subject 
Natural resources  Decision making


Electronic books

Alt Author 
Peterson, James T

