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  • 1
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    In:  Supplement to: Convertino, Matteo; Baker, Kelsie; Lu, Connie; Vogel, John T; Suedel, Burton; Linkov, Igor (2013): Use of multi-criteria decision analysis to guide metrics selection for ecosystem restorations. Ecological Indicators, 26, 76-86, https://doi.org/10.1016/j.ecolind.2012.10.005
    Publication Date: 2023-01-13
    Description: The selection of metrics for ecosystem restoration programs is critical for improving the quality of monitoring programs and characterizing project success. Moreover it is oftentimes very difficult to balance the importance of multiple ecological, social, and economical metrics. Metric selection process is a complex and must simultaneously take into account monitoring data, environmental models, socio-economic considerations, and stakeholder interests. We propose multicriteria decision analysis (MCDA) methods, broadly defined, for the selection of optimal sets of metrics to enhance evaluation of ecosystem restoration alternatives. Two MCDA methods, a multiattribute utility analysis (MAUT), and a probabilistic multicriteria acceptability analysis (ProMAA), are applied and compared for a hypothetical case study of a river restoration involving multiple stakeholders. Overall, the MCDA results in a systematic, unbiased, and transparent solution, informing restoration alternatives evaluation. The two methods provide comparable results in terms of selected metrics. However, because ProMAA can consider probability distributions for weights and utility values of metrics for each criteria, it is suggested as the best option if data uncertainty is high. Despite the increase in complexity in the metric selection process, MCDA improves upon the current ad-hoc decision practice based on the consultations with stakeholders and experts, and encourages transparent and quantitative aggregation of data and judgement, increasing the transparency of decision making in restoration projects. We believe that MCDA can enhance the overall sustainability of ecosystem by enhancing both ecological and societal needs.
    Type: Dataset
    Format: application/zip, 3.2 MBytes
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  • 2
    Publication Date: 2011-09-28
    Print ISSN: 0013-936X
    Electronic ISSN: 1520-5851
    Topics: Chemistry and Pharmacology , Energy, Environment Protection, Nuclear Power Engineering
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