Assessing Temporal Trade-Offs of Ecosystem Services by Production Possibility Frontiers

Abstract

Ecosystems provide multiple valuable services that play an essential role in preventing meteorological risks, combating sandy land expansion, and ensuring sustainable development in the West Liao River Basin. The trade-off among ecosystem services (ES) is inevitable because of biophysical constraints and societal preferences. The production possibility frontier (PPF) is increasingly deemed an appropriate tool for representing trade-off relationships among ES. In this study, we developed a feasible approach for estimating PPF, which includes three steps. First, the annual water yield model, the sediment delivery ratio model, the carbon storage and sequestration model, and the habitat quality model of InVEST models were used to quantify temporal changes in four key ES, including water retention, soil conservation, carbon sequestration, and habitat improvement, in five-year periods from 1990 to 2020. Second, after the standardization of ES quantities, the functional forms of PPF curves for six pairs of ES trade-offs were derived by adopting a two-term exponential function of the curve fitting tool in MATLAB. Third, the trade-off intensity for each ES pair was defined and calculated based on the distance from the mean point to the PPF curve. Compared to the existing approaches, our approach has the advantage of fitting functional forms of PPF curves, handling both positive and negative values of ES, and calculating trade-off intensities. This study has three implications. First, showing the trade-offs between ES by PPF is helpful for providing knowledge on the existence of turning points and a complex relationship between certain ES pairs, thus avoiding unintended and large-scale shifts in the provision of ES. Second, PPF curves are a useful tool for visualizing the nature of ES relationships and the changes in trade-off intensity, thus supporting decision-makers to identify optimal solutions and make land use planning that can increase the overall efficiency over multiple ES. Third, socioeconomic components should be integrated into the assessment of ES trade-offs in order to understand the influences of societal choices on and examine stakeholders’ preferences regarding efficient ES combinations.