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

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 subcriteria 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 implementationinfo:eu-repo/semantics/publishedVersio

Causality and Importance of Sustainable Forestry Goals: Strategic and Tactical Assessment by DEMATEL and AHP

This paper presents the combined use of standard DEMATEL and AHP methodologies in assessing a selected set of criteria for evaluating sustainable forestry goals. Creating a decision-making framework with two participating individuals (the authors of this research) enabled the comparison of individually obtained solutions with the aggregated solutions derived by two methodologies. The use of DEMATEL enabled strategic viewing of the causality relations among criteria and a limited indication of cardinal information (weights) about their importance. Different from DEMATEL, the use of AHP is considered a control mechanism in tactical decision-making situations such as the usage of standard multi-criteria methods for solving forestry-related allocation or selection problems. AHP’s role is to derive weights of criteria in a very structured environment based on assumption that criteria are independent and only their mutual importance is relevant for further decision-making. Individual solutions and aggregation schemes for creating group solutions are compared for both methodologies. Critical analysis is given for different aspects of their combined use when treating causalities and the importance of criteria in evaluations of long-term sustainable forestry goals

Fuzzy AHP Assessment of Urban Parks Quality and Importance in Novi Sad City, Serbia

This paper proposes an AHP approach that utilizes the fuzzy extent model to prioritize five city parks based on their present quality and projected importance for Novi Sad City, the capital of Vojvodina Province, in Serbia. The study involved an expert evaluation of a set of eight criteria to identify the most relevant subset of criteria for a detailed park assessment. The park evaluation took into account uncertainties (fuzziness), the expert’s risk tolerance, and different levels of optimism and pessimism. The obtained results could serve when defining upcoming city plans and management agendas related to green areas in the city. The proposed fuzzy-based methodology can be extended to group decision-making scenarios by involving more experts and stakeholder representatives. The park weights obtained through the fuzzy AHP methodology described in this paper can aid city planners and politicians in the strategic allocation of financial, organizational, and human resources for parks

Using Analytic Hierarchy Process and Best–Worst Method in Group Evaluation of Urban Park Quality

The paper compares two multi-criteria methods, the analytic hierarchy process (AHP) and the best–worst method (BWM), in assessing criteria related to the quality of urban parks. The criteria assessed were accessibility, location, biodiversity preservation, park equipment, water elements, terrain configuration, cultural and historical value, and the presence of small architectural objects. Five decision-makers participated in the research, having expertise in urban greenery, urban forestry, environmental protection, landscape design, and cultural and historical heritage. The results of decision-makers’ evaluations were compared at individual and group levels after the application of three aggregation procedures: CRITIC, ENTROPY, and WGGM (weighted geometric mean method). Similarities in results, i.e., priorities of analyzed criteria after applying the two different decision support methods, indicated high consistency between experts during the cognitive evaluation processes. All applied aggregation schemes performed well and may be considered trustworthy in identifying the group solution. One of the conclusions is that either the AHP or the BWM can be efficiently used in evaluations of criteria for assessing the quality of urban parks if the members of a group are consistent, regardless of whether the consensus process is properly carried out before the decision-making process

Assessing impacts of sulfur deposition on aquatic ecosystems: A decision support system for the Southern Appalachians

Abstract With climate change and ongoing impacts from human development and resource extraction, US federal land management agencies are acutely concerned with managing for healthy aquatic ecosystems in the Southern Appalachian Mountain (SAM) Region. Here, we describe development of a spatial decision support application to assess the biological and ecological impacts of atmospheric S and N deposition on aquatic ecosystems of the region. We first summarize foundational published work to predict continuous maps of surface water acid neutralizing capacity (ANC) and soil base cation weathering (BCw). We use the predicted ANC and BCw maps to estimate steady‐state critical loads (CLs) of atmospheric S and N deposition. We included estimated CLs of atmospheric N to get a complete picture of CLs and potential exceedances. We then present a logic‐based decision support model for assessing effects of S and N deposition based on statistically modeled stream ANC and CL exceedance. The model is easily modified for continuous monitoring of CL exceedance patterns as new S and N deposition and ANC data become available. We present mapped model results for the SAM study area and an important subset of the region, the Great Smoky Mountains National Park. ANC modeling results revealed that predicted acid sensitivity was spatially variable, with areas of relatively low stream ANC (<50 μeq · L−1) and soil BCw (<50 meq · m−2 · year−1) predominantly found in certain critical areas. Within the Great Smoky Mountains National Park, evidence for S CL exceedance based on an ANC criterion of 50 μeq · L−1 was strong at locations where ambient S deposition was at least two times the CL. We also predicted likely impacts of CL exceedances on aquatic insect species richness and native fish abundance. Responses for insect species richness and fish impact showed variability similar to CL exceedance, with increasing impact positively correlated with elevation. Finally, we discuss ways that the decision support system can be used to prioritize management across the region