Decision Support for Participatory Forest Planning Using AHP and TOPSIS

• Published in: Forests
• Main Authors: Hilma Nilsson, Eva-Maria Nordström, Karin Öhman
• Format: Article in Journal/Newspaper
• Language: English
• Published: MDPI AG 2016
• Subjects: Analytic Hierarchy Process; forest decision support system; forest management; the Heureka system; multiple criteria decision analysis; multiple objectives; Technique for Order Preference by Similarity to Ideal Solution; Plant ecology; QK900-989; Northern Sweden
• Online Access: https://doi.org/10.3390/f7050100; https://doaj.org/article/33c64e86395840d4b3d1bda60545df2c

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.