Coupling coordination degree spatial analysis and driving factor between socio-economic and eco-environment in northern China

• Published in: Ecological indicators Vol. 135; p. 108555
• Main Authors: Li, Liang, Fan, Zhang, Feng, Wu, Yuxin, Chen, Keyu, Qin
• Format: Journal Article
• Language: English
• Published: Elsevier Ltd 01-02-2022; Elsevier
• Subjects: Coupling coordination degree; Ecological environment; Economic development; Geographical detector; Spatial autocorrelation; Coupling coordination degree; Geographical detector; Spatial autocorrelation; Economic development; Ecological environment
• ISSN: 1470-160X; 1872-7034
• DOI: 10.1016/j.ecolind.2022.108555

•Eco-economy coupling coordination (CCD) index at county level in was evaluated.•Obvious spatial agglomeration of eco-economy CCD index in north China was found.•The driving factors of eco-economy CCD index was studied by geodetector.•Terrain has the greatest influence on eco-economic coupling, then is transportation.
Coordinating ecological and socioeconomic development is the only way to achieve regional sustainability. In this paper, the total output value of ecosystem services was selected to evaluate the ecological environment, and socioeconomic indicators were selected to evaluate socioeconomic development. The coupling coordination degree (CCD) between the ecological environment and economy of counties in northern China was evaluated by combining an entropy method and a coupling coordination model. Spatial autocorrelation and a geographical detector model were used to reveal the spatial agglomeration characteristics and factors that influence the coordination degree of the ecological–economic system in northern China. Results showed that, in 2019, most counties were in the ecological–economic transition development stage. Among them, 321 counties had a CCD index between 0.4 and 0.5 (basic coordination stage); 209 counties had a CCD index between 0.5 and 0.6 (primary coordination stage); and 77 counties had a CCD index between 0.6 and 0.8 (moderate coordination stage). The global Moran’s I was 0.349, indicating that there was spatial agglomeration of ecological–economic coupling coordination at a county level. Low-low clusters were mainly found in the central and eastern central part of the study area, and high–high clusters were mainly found in northern Hebei province, Shandong peninsula, and northern Henan province. The factors that influenced the CCD index, ordered from the largest to the smallest, were landscape, terrain, traffic, and climate factors. The interactions between driving factors showed nonlinear and bilinear enhancement. The findings show that the coordination of socioeconomic and ecological development in northern China can be further improved. Relevant policies should emphasize the local ecological advantages, promote the transformation to ecological industrialization, and encourage ecologically and economically balanced development.