Targeting Payments for Ecosystem Services Through Geographically Weighted Regression

Payments for ecosystem services (PES) represent a growing share of conservation efforts. To make the most of limited budgets, these programs must target participants and regions most likely to produce the greatest environmental gains while improving (or at least not reducing) economic wellbeing; however, limited monitoring and unquantified results make it difficult to improve these programs’ efficiency and effectiveness. Although several studies have investigated demographic and economic covariates related to households’ participation in PES, few have explored how these characteristics influence ecological outcomes. Furthermore, there is an inherent assumption that program success, and the social and environmental factors that moderate it, are consistent across a region of interest. This study, conducted at Fanjingshan National Nature Reserve in southwestern China, uses geographically weighted regression, Landsat-derived vegetation index, and household survey data to explore how demographic and livelihood characteristics may cause PES results to vary across households, and how the impacts of these factors may vary in magnitude and direction across the study area. Results illustrate differences between the most willing participants and the most ecologically effective participants. Results also highlight the value of spatially differentiated participant selection to maximize gains and avoid counterproductive outcomes, especially amid inconsistent access to economic opportunities