Multi-criteria decision analysis to select metrics for design and monitoring of sustainable ecosystem restorations

Abstract

Convertino, M.; Baker, K.M.; Vogel, J.T.; Lu, C.; Suedel, B.; and Linkov, I., "Multi-criteria decision analysis to select metrics for design and monitoring of sustainable ecosystem restorations" (2013). US Army Research. 190 The selection of metrics for ecosystem restoration programs is critical for improving the quality and utility of design and monitoring programs, informing adaptive management actions, and characterizing project success. The metrics selection process, that in practice is left to the subjective judgment of stakeholders, is often complex and should simultaneously take into account monitoring data, environmental models, socio-economic considerations, and stakeholder interests. With limited funding, it is often very difficult to balance the importance of multiple metrics, often competing, intended to measure different environmental, social, and economic aspects of the system. To help restoration planners and practitioners develop the most useful and informative design and monitoring programs, we propose the use of multi-criteria decision analysis (MCDA) methods, broadly defined, to select optimal ecosystem restoration metric sets. In this paper, we apply and compare two MCDA methods, multi-attribute utility theory (MAUT), and probabilistic multi-criteria acceptability analysis (ProMAA), for a hypothetical river restoration case study involving multiple stakeholders with competing interests. Overall, the MCDA results in a systematic, quantitative, and transparent evaluation and comparison of potential metrics that provides planners and practitioners with a clear basis for selecting the optimal set of metrics to evaluate restoration alternatives and to inform restoration design and monitoring. In our case study, the two MCDA 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 criterion, it is most likely the best option for projects with highly uncertain data and significant stakeholder involvement. Despite the increase in complexity in the metrics selection process, MCDA improves upon the current, commonlyused ad-hoc decision practice based on consultations with stakeholders by applying and presenting quantitative aggregation of data and judgment, thereby increasing the effectiveness of environmental design and monitoring and the transparency of decision making in restoration projects.

Evaluating Stream Restoration Projects: What Do We Learn from Monitoring?

“…Areal metrics do not distinguish high quality habitat (or habitat critically needed for a given species and life stage) from lower quality habitat (or habitat that was not critically needed by important species). The Corps has also undertaken efforts to develop more sophisticated metrics of restoration, developed to evaluate the likely benefits of ecosystem restoration and tradeoffs between economic and environmental benefits [10][11][12][13].…”

The Stability of Revegetated Ecosystems in Sandy Areas: An Assessment and Prediction Index

“…Thus, one may easily apply the AHP to select promising technologies, and it provides a simple method for making decisions or performing environmental impact assessments [30][31][32]. However, relatively few studies have assessed the application of AHP to ecosystem stability [27,33,34], especially in revegetated desert areas.…”

Design of optimal ecosystem monitoring networks: hotspot detection and biodiversity patterns

“…Species richness is affected by management for which species richness itself is a component on which management decisions are taken. For instance, species richness is monitored for understanding species distribution and community assembly, and for the pre/post evaluation of ecosystem restoration (Convertino et al 2013). Species richness provides a service and in this perspective it is definable as ''ecosystem service'' as well.…”