Abstract
Long-term forest management planning often involves several stakeholders with conflicting objectives, creating a complex decision process. Multiple-criteria decision analysis (MCDA) presents a promising framework for finding solutions in terms of suitable trade-offs among the objectives. However, many of the MCDA methods that have been implemented in forest management planning can only be used to compare and evaluate a limited number of management plans, which increases the risk that the most suitable plan is not included in the decision process. The aim of this study is to test whether the combination of two MCDA methods can facilitate the evaluation of a large number of strategic forest management plans in a situation with multiple objectives and several stakeholders. The Analytic Hierarchy Process (AHP) was used to set weights for objectives based on stakeholder preferences and the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) was used to produce an overall ranking of alternatives. This approach was applied to a case study of the Vilhelmina municipality, northern Sweden. The results show that the combination of AHP and TOPSIS is easy to implement in participatory forest planning and takes advantage of the capacity of forest decision support systems to create a wide array of management plans. This increases the possibility that the most suitable plan for all stakeholders will be identified.
Highlights
Forest planning is more challenging than ever
TOPSIS is easy to implement in participatory forest planning and takes advantage of the capacity of forest decision support systems to create a wide array of management plans
The results from this study show that Analytic Hierarchy Process (AHP) and TOPSIS can be successfully combined for including multiple objectives in forest planning
Summary
Forest planning is more challenging than ever. This is because sustainable forest management planning decisions cannot be made from only an economic perspective but must take into account other factors such as ecological and social values [1]. In a situation where the goal is to identify the optimal forest plan, the first step is often to use decision support systems, such as Heureka [3], for generating a wide array of alternative forest management plans. These different management plans can be analyzed with respect to forest development over time and how different management options affect the outcome in terms of a range of ecosystem services. The decision makers must reflect on their own and other stakeholders’ preferences, because one specific forest plan seldom performs best in terms of all objectives. Which forest plan is best depends on how important different objectives
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