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Open AccessArticle

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

1
Forest Research Center, School of Agriculture, University of Lisbon, Tapada da Ajuda, 1349-017 Lisboa, Portugal
2
Corvallis Forestry Sciences Laboratory, Pacific Northwest Research Station, US Department of Agriculture, Forest Service, 3200 SW Jefferson Way, Corvallis, OR 97331, USA
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Department of Fruit Science, Viticulture, Horticulture and Landscape Architecture, University of Novi Sad, Faculty of Agriculture, Trg Dositeja Obradovića 8, 21000 Novi Sad, Serbia
4
InfoHarvest, Inc., Seattle, WA 98165, USA
*
Author to whom correspondence should be addressed.
Academic Editor: Isabella De Meo
Forests 2021, 12(4), 399; https://doi.org/10.3390/f12040399
Received: 6 March 2021 / Revised: 24 March 2021 / Accepted: 25 March 2021 / Published: 28 March 2021
(This article belongs to the Section Forest Economics, Policy, and Social Science)
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. View Full-Text
Keywords: forest management planning; ecosystem services; cognitive mapping; AHP; SMART; Delphi; participatory planning forest management planning; ecosystem services; cognitive mapping; AHP; SMART; Delphi; participatory planning
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MDPI and ACS Style

Marques, M.; Reynolds, K.M.; Marto, M.; Lakicevic, M.; Caldas, C.; Murphy, P.J.; Borges, J.G. Multicriteria Decision Analysis and Group Decision-Making to Select Stand-Level Forest Management Models and Support Landscape-Level Collaborative Planning. Forests 2021, 12, 399. https://doi.org/10.3390/f12040399

AMA Style

Marques M, Reynolds KM, Marto M, Lakicevic M, Caldas C, Murphy PJ, Borges JG. Multicriteria Decision Analysis and Group Decision-Making to Select Stand-Level Forest Management Models and Support Landscape-Level Collaborative Planning. Forests. 2021; 12(4):399. https://doi.org/10.3390/f12040399

Chicago/Turabian Style

Marques, Marlene; Reynolds, Keith M.; Marto, Marco; Lakicevic, Milena; Caldas, Carlos; Murphy, Philip J.; Borges, José G. 2021. "Multicriteria Decision Analysis and Group Decision-Making to Select Stand-Level Forest Management Models and Support Landscape-Level Collaborative Planning" Forests 12, no. 4: 399. https://doi.org/10.3390/f12040399

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