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

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, commonly used 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

An Inhibitive Enzyme Assay to Detect Mercury and Zinc Using Protease from Coriandrum sativum

Heavy metals pollution has become a great threat to the world. Since instrumental methods are expensive and need skilled technician, a simple and fast method is needed to determine the presence of heavy metals in the environment. In this study, an inhibitive enzyme assay for heavy metals has been developed using crude proteases from Coriandrum sativum. In this assay, casein was used as a substrate and Coomassie dye was used to denote the completion of casein hydrolysis. In the absence of inhibitors, casein was hydrolysed and the solution became brown, while in the presence of metal ions such as Hg 2+ and Zn 2+ , the hydrolysis of casein was inhibited and the solution remained blue. Both Hg 2+ and Zn 2+ exhibited one-phase binding curve with IC 50 values of 3.217 mg/L and 0.727 mg/L, respectively. The limits of detection (LOD) and limits of quantitation (LOQ) for Hg were 0.241 and 0.802 mg/L, respectively, while the LOD and LOQ for Zn were 0.228 and 0.761 mg/L, respectively. The enzyme exhibited broad pH ranges for activity. The crude proteases extracted from Coriandrum sativum showed good potential for the development of a rapid, sensitive, and economic inhibitive assay for the biomonitoring of Hg 2+ and Zn 2+ in the aquatic environments