Application Of Threshold Concepts In Natural Resource Decision Making

Application of Threshold Concepts in Natural Resource Decision Making

Application of Threshold Concepts in Natural Resource Decision Making

Natural resource managers face a complex decision-making environment characterized by the potential occurrence of rapid and abrupt ecological change. These abrupt changes are poorly accommodated by traditional natural resource planning and decision-making processes. As recognition of threshold processes has increased, contemporary models of ecological systems have been modified to better represent a broader range of ecological system dynamics. Key conceptual advances associated with the ideas of non-linear responses, the existence of multiple ecological stable states and critical thresholds are more likely the rule than the exception in ecological systems. Once an ecological threshold is crossed, the ecosystem in question is not likely to return to its previous state. There are many examples and a general consensus that climatic disruptions will drive now stable systems across ecological thresholds. This book provides professional resource managers with a broad general decision framework that illustrates the utility of including ecological threshold concepts in natural resource management. It gives an entry into the literature in this rapidly evolving concept, with descriptions and discussion of the promising statistical approaches for threshold detection and demonstrations of the utility of the threshold framework via a series of case studies.

The Science and Management of Uncertainty

Uncertainty can take many forms, can be represented in many ways, and can have important implications in decision-making and policy development. This book provides a rigorous scientific framework for dealing with uncertainty in real-world situations, and provides a comprehensive study of concepts, measurements, and applications of uncertainty in ecological modeling and natural resource management. The focus of this book is on the kinds and implications of uncertainty in environmental modeling and management, with practical guidelines and examples for successful modeling and risk analysis in the face of uncertain conditions and incomplete information. Provided is a clear classification of uncertainty; methods for measuring, modeling, and communicating uncertainty; practical guidelines for capturing and representing expert knowledge and judgment; explanations of the role of uncertainty in decision-making; a guideline to avoiding logical fallacies when dealing with uncertainty; and several example cases of real-world ecological modeling and risk analysis to illustrate the concepts and approaches. Case topics provide examples of structured decision-making, statistical modeling, and related topics. A summary provides practical next steps that the reader can take in analyzing and interpreting uncertainty in real-world situations. Also provided is a glossary and a suite of references.