Implications of indicator aggregation methods for global change vulnerability reduction efforts

Composite indices are used to assess and prioritize mitigation and adaptation strategies for addressing the impacts of global environmental change. We evaluate different aggregation tools for creating these indices and their potential effects on mitigation and adaptation efforts. We assess the association of each aggregation tool with different types of trade-offs, risk strategies, and the resulting spatial and statistical distribution of their composite scores. Four aggregation tools are investigated (Weighted Linear Combination, WLC; Ordered Weighted Average, OWA; Data Envelopment Analysis, DEA; Compromise Programming, CP) using an example of vulnerability to flooding in the eastern United States. The choice of aggregation tool affects vulnerability outcomes, decision risk strategies, and the prioritization of vulnerability reduction strategies. DEA produces the highest vulnerability scores, representing a risk averse strategy associated with pessimistic outcomes. WLC implies a neutral and fixed risk strategy. CP produces a range of outcomes from neutral (equivalent to the WLC) to pessimistic, depending on its parameters. OWA offers the highest flexibility to adjust the levels of trade-off and risk strategy, producing a range of vulnerability outcomes, from optimistic to pessimistic. The units of analysis, when prioritized across the different aggregation tools, are more consistent for the top ranked units. However, the differences in rank become substantial as the selection threshold score decreases. To obtain better informed vulnerability reduction strategies, we recommend to (i) address how trade-off and decision risk are embedded in the aggregation tool chosen, and (ii) evaluate their effect in the prioritization of mitigation and adaptation strategies being considered