4.7 Article

Multicriteria Decision Analysis and Group Decision-Making to Select Stand-Level Forest Management Models and Support Landscape-Level Collaborative Planning

Journal

FORESTS
Volume 12, Issue 4, Pages -

Publisher

MDPI
DOI: 10.3390/f12040399

Keywords

forest management planning; ecosystem services; cognitive mapping; AHP; SMART; Delphi; participatory planning

Categories

Funding

  1. European Union's Horizon 2020 Research and Innovation Programme [676754]
  2. Marie Skodowska-Curie Research and Innovation Staff Exchange (RISE) within the H2020Work Programme (H2020-MSCA-RISE2015)
  3. Portuguese Science Foundation (FCT) [PD/BD/128257/2016]
  4. Forest Research Center Project [UIDB/00239/2020]
  5. BIOECOSYS project [LISBOA-01-0145-FEDER-030391, PTDC/ASP-SIL/30391/2017]
  6. [SFRH/BD/108225/2015]
  7. H2020 Societal Challenges Programme [676754] Funding Source: H2020 Societal Challenges Programme
  8. Fundação para a Ciência e a Tecnologia [UIDB/00239/2020, PD/BD/128257/2016, PTDC/ASP-SIL/30391/2017, SFRH/BD/108225/2015] Funding Source: FCT

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The research explores the challenges and methods of forest management planning in joint collaborative management areas (ZIF) by combining multicriteria decision analysis and group decision-making process. The results show that the actors consider income and risks as the most important criteria, with consistent preferences for the sub-criteria of income, risks, and cultural services.
Forest management planning is a challenge due to the diverse criteria that need to be considered in the underlying decision-making process. This challenge becomes more complex in joint collaborative management areas (ZIF) because the decision now may involve numerous actors with diverse interests, preferences, and goals. In this research, we present an approach to identifying and quantifying the most relevant criteria that actors consider in a forest management planning process in a ZIF context, including quantifying the performance of seven alternative stand-level forest management models (FMM). Specifically, we developed a combined multicriteria decision analysis and group decision-making process by (a) building a cognitive map with the actors to identify the criteria and sub-criteria; (b) structuring the decision tree; (c) structuring a questionnaire to elicit the importance of criteria and sub-criteria in a pairwise comparison process, and to evaluate the FMM alternatives; and (d) applying a Delphi survey to gather actors' preferences. We report results from an application to a case study area, ZIF of Vale do Sousa, in North-Western Portugal. Actors assigned the highest importance to the criteria income (56.8% of all actors) and risks (21.6% of all actors) and the lowest to cultural services (27.0% of all actors). Actors agreed on their preferences for the sub-criteria of income (diversification of income sources), risks (wildfires) and cultural services (leisure and recreation activities). However, there was a poor agreement among actors on the sub-criteria of the wood demand and biodiversity criteria. For 27.0% of all actors the FMM with the highest performance was the pedunculate oak and for 43.2% of all actors the eucalypt FMM was the least preferable alternative. The findings indicate that this approach can support ZIF managers in enhancing forest management planning by improving its utility for actors and facilitating its implementation.

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