Multi-criteria decision analysis for nature conservation: A review of 20years of applications

Multi-criteria decision analysis (MCDA) is a method to support decision-making, by exploring the balance between the pros and cons of different alternatives to accomplish a specific goal. It assists in framing decision problems, illustrating the performance of alternatives across criteria, exploring trade-offs, formulating a decision and testing its robustness. This paper provides a structured review of empirical applications of MCDA to nature conservation published in the scientific literature over the last 20years. The paper aims at taking stock of past experiences, and comparing them with best practices and common pitfalls identified in the literature, to provide recommendations for better MCDA application to conservation. The review follows the structure of a generalized MCDA process consisting of three key stages: (1) decision context and problem structuring, (2) analysis and (3) decision. The search identified 86 papers that describe MCDA applications to a range of topics, including conservation prioritization and planning; protected areas management and zoning; forest management and restoration; and mapping of biodiversity, naturalness and wilder. The results show that, concerning problem structuring, a small percentage of the reviewed MCDA engaged stakeholders other than the authors in identifying alternatives and formulating criteria (15% and 35% respectively). Concerning the analysis, criteria assessment was adequately justified by the authors (47%), at times also by involving other stakeholders (22%). Weighting was performed in almost all applications, whereas criteria aggregation was mostly based on the weighted linear combination (63%). Sensitivity analysis was largely overlooked (57%). Concerning decision, 45% of the articles provided only an overall ranking or suitability of alternatives, while 22% included additional rankings according to specific criterion, and 8% further analyses and clustering of stakeholders' preferences. The paper concludes by suggesting key elements of successful MCDA applications, including clear construction of the decision context; collaborative identification of alternatives and criteria that reflect the values at stake; adequate justification and communication of the methods for criteria assessment and weighting; reasoned choice of the criteria aggregation method, and comprehensive sensitivity analysis.