Understanding trade-offs and synergies of ecosystem services to support the decision-making in the Beijing–Tianjin–Hebei region

Abstract

Understanding ecosystem service trade-offs and synergies is the foundation to achieve the efficient management of the ecosystem and improve human well-being. However, the current research involving the driving mechanism of ecosystem service relationship formation is still limited. In this paper, a semi-quantitative model named Bayesian belief networks is introduced to simulate ecological processes, which links the potential influencing factors with the ecosystem service supply. The purpose of this paper is to help understand the ecosystem service relationship and provide management decision-making reference. Taking the Beijing–Tianjin–Hebei region as a study area, four ecosystem services (habitat quality, carbon storage, water yield, and soil retention services) were quantified and mapped in 2015. Based on a created Bayesian belief network simulating the ecosystem service supply, the sensitivity analysis was used to identify the key factors affecting the ecosystem service supply. Besides, the relationship between ecosystem services was identified and the driving mechanism was analyzed through the Bayesian probabilistic inference. The main conclusions demonstrate the following. (1) The spatial heterogeneity of the ecosystem service supply in the Beijing–Tianjin–Hebei region is relatively strong. (2) The key factors affecting ecosystem services are the land use type, vegetation coverage, precipitation, slope, evapotranspiration, and population density. (3) Habitat quality, carbon storage, and soil retention services synergize one another, and there are trade-offs between water yield service and habitat quality, carbon storage, and soil retention services, respectively. (4) Among the land use type, vegetation coverage, slope, and population density, the land use type has the most important impact on ecosystem service trade-offs. As a practice of combining Bayesian belief networks and ecosystem services, this study can contribute to a research method of ecosystem service relationships and references for the management decision-making on maximizing the overall benefits of ecosystem services.