Role of correlation and statistical distribution for multi-objective conservation investment

A growing body of literature suggests a need to incorporate both correlation- and distribution-related information into conservation investment decisions with multiple benefits. This study identifies optimal spatial targets and their budget distributions of payments for ecosystem services (PES), as well as the tradeoff relationships under multiple-objective scenarios of maximizing forest-based carbon sequestration, maximizing forest-dependent biodiversity, and maximizing economic impact. Specifically, this study investigates how the spatial targets, their budget distributions, and tradeoff relationships are affected by correlations among multiple objectives and their statistical distributions in terms of return on investment (ROI) by focusing on 231 counties in the eight states of the Central and Southern Appalachian Region of the United States. This study finds that (1) negative correlations between economic impact ROI and ROI associated with ecosystem service and biodiversity are explained by higher economic multipliers in urban areas than in rural areas, (2) the amount of compromise needed for carbon or biodiversity for a marginal gain of economic impact is relatively low, and (3) the greater the weight on the objective of maximizing economic impact—whose ROI on average stochastically dominants the ROIs of the other two objectives (i.e., ROIs of maximizing carbon and biodiversity)—the smaller the number of counties optimally targeted for funding. The finding suggests that assigning positive weight to an objective that encourages positive economic impact as a new objective in the design of existing PES programs makes sense. The revision of the PES design needs to be undertaken carefully to avoid unintended consequences such as a large distribution of the funding budget going to urban areas and a small number of target areas, both of which may raise potential distributional equity concerns