Evaluation of China’s rural resource and environmental carrying capacity based on the ZI–CI–GI framework
Year: 2025
Type: article
Abstract: • Established was a coupled RRECC model based on the ZI–CI–GI framework. • The RECC of over 90% of rural areas in China is in a stable and surplus state. • Southeastern rural areas have few constraints and high development potential. • Analyzed the key factors for enhancing RRECC. Effectively evaluating the carrying capacity of rural resources and the environment, and identifying key factors for its enhancement, are critical for rural sustainability. To meet this objective, a coupling model for rural resource and environmental carrying capacity (RRECC) was constructed using multi-source spatiotemporal data. The model incorporates the zonal division index of resources and environment (ZI), the categorization index of socioeconomic development (CI), and the grading index of population concentration (GI). Spatial autocorrelation and factor contribution analysis were employed to simulate the RRECC of China and identify key factors for enhancing this capacity. The results show that the overall carrying capacity status of China’s rural resources and environment is favorable. Out of 30,055 rural study units, 91.076% are in balance and surplus states, encompassing 90.044% of the population and 66.451% of the land. The carrying capacity exhibits a spatial pattern of higher capacity in the east and south, with significant spatial clustering. The contributions of socioeconomic development and ecological environment protection to carrying capacity are 28.018% and 27.625%, respectively. Therefore, enhancing carrying capacity requires synergistic advancement in both areas. This study advances the evaluation methods for resource and environmental carrying capacity (RECC) in rural areas, providing scientific guidance and support for the realization of the great goal of the Rural Revitalization Strategy.
Source: Ecological Indicators
Authors: Zhiyuan Ma, Xuejun Duan, Lei Wang, Yazhu Wang, Wei Yan, Haiyue Wang, Xiayi Ju
Language: English
Subfield: Water Science and Technology
Field: Environmental Science
Domain: Physical Sciences
Open Access status: gold
Estimated APC paid: $3,650
OpenAlex ID: W4407102615
