A new pattern to quantitatively evaluate the value of ecosystem services in the large-scale open-pit coal mining area

Abstract

IntroductionOpen-pit coal mining could disrupt the ecosystem and lead to the loss of service values for the ecosystem through direct occupation or indirect impacts on adjacent ecosystems.MethodsIn this research, we combined a new accounting system, gross ecosystem product (GEP), with spatial–temporal analyses to quantify the ecological variation and explore its driving factors in Pingshuo, a large-scale open-pit coal mining area in China. GEP is an aggregate accounting system that can summarize the value of provisioning, regulating, and cultural ecosystem services (ES) in a single monetary metric. The spatial–temporal approaches used in our study were known as exploratory spatial data analyses and interpretable models in machine learning. Both spatial and non-spatial data, including remote sensing images, meteorological data, and official statistics, were applied in the research.ResultsThe results indicated the following: (i) From 1990 to 2020, the annual average growth rates of GEP decreased from 30.78 to 9.1%. Furthermore, the classified results of GEP revealed that the regions with rich ES quality rapidly reduced from 51.90 to 32.18%. (ii) Spatial correlation of GEP was significant, and the degree of spatial clustering was relatively high in the mining areas. Moreover, the mining areas also continually presented concentrated high-density and hot spot areas of GEP changes. (iii) The spatial–temporal effects were notable in the relationship between GEP and three socioeconomic factors, i.e., the mining effects, human activity intensity, and gross domestic product (GDP). (iv) The win–win development for both the economy and ecological environment in Pingshuo could be realized by restricting the annual growth rate of mining areas to between 4.56 and 5.03%.DiscussionThe accounting results and spatial–temporal analyses of GEP will contribute to the future regional sustainable development and ecosystem management in Pingshuo.