Monday, 12 September 2016

Multiple Criteria Decision Support Methods in Forest Management

Published Date
Volume 6 of the series Managing Forest Ecosystems pp 37-70

Title 

Multiple Criteria Decision Support Methods in Forest Management

An overview and comparative analyses
  • Author 
  • Jyrki Kangas
  • Annika Kangas

Abstract

Nowadays, forests are often managed for multiple uses. Forests are expected to produce reasonable incomes while at the same time promoting nature conservation and amenity values. There are also other characteristics that make natural resources decisionmaking situations complex. For example, group decision making and public participation are often required. To help decision makers make good choices, information and analyses are needed on the decision situation, on alternative choices of action, and on the consequences of alternative choices as well as on the preferences among these consequences. Multiple Criteria Decision Support (MCDS) methods are decision analysis tools that have been developed for dealing with all that information in order to support complex decision making with multiple objectives. In this chapter, some MCDS methods that recently have been applied to forestry or other natural resources management planning problems, and have been found to be promising, will be presented. In addition, some forestry applications are briefly described, and experiences gained using MCDS methods in forest management are discussed. Of the MCDS approaches, a closer look is taken at the Analytic Hierarchy Process, outranking methods, voting approaches, and the Stochastic Multicriteria Acceptability Analysis, because of their potentials for application. Applications for practically all MCDS methods with different qualities can be found in the field of natural resources decision support. However, no single method is best for all the decision support processes. The tool to be used should be chosen to fit the situation at hand: i.e., planning-case-wise consideration is always needed in order to build up an appropriate decision support process.

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