Hybrid MCDA Methods to Integrate Multiple Ecosystem Services in Forest Management Planning: A Critical Review

Multi-criteria decision analysis (MCDA) is a decision aid frequently used in the field of forest management planning. It includes the evaluation of multiple criteria such as the production of timber and non-timber forest products and tangible as well as intangible values of ecosystem services (ES)....

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Veröffentlicht in:Environmental management (New York) 2015-08, Vol.56 (2), p.373-388
Hauptverfasser: Uhde, Britta, Andreas Hahn, W., Griess, Verena C., Knoke, Thomas
Format: Artikel
Sprache:eng
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Zusammenfassung:Multi-criteria decision analysis (MCDA) is a decision aid frequently used in the field of forest management planning. It includes the evaluation of multiple criteria such as the production of timber and non-timber forest products and tangible as well as intangible values of ecosystem services (ES). Hence, it is beneficial compared to those methods that take a purely financial perspective. Accordingly, MCDA methods are increasingly popular in the wide field of sustainability assessment. Hybrid approaches allow aggregating MCDA and, potentially, other decision-making techniques to make use of their individual benefits and leading to a more holistic view of the actual consequences that come with certain decisions. This review is providing a comprehensive overview of hybrid approaches that are used in forest management planning. Today, the scientific world is facing increasing challenges regarding the evaluation of ES and the trade-offs between them, for example between provisioning and regulating services. As the preferences of multiple stakeholders are essential to improve the decision process in multi-purpose forestry, participatory and hybrid approaches turn out to be of particular importance. Accordingly, hybrid methods show great potential for becoming most relevant in future decision making. Based on the review presented here, the development of models for the use in planning processes should focus on participatory modeling and the consideration of uncertainty regarding available information.
ISSN:0364-152X
1432-1009
DOI:10.1007/s00267-015-0503-3