Abstract
How to measure the overall level of regional social economy, resources, and environment and how to grasp the coordinated development between them has become a hot issue. In this paper, the driving force-pressure-state-response (DPSR) model is used to build an ecological security index (ESI) system to measure the overall ecological security level of social economy, resources, and environment. In addition, dynamic nonlinear auto regressive (NAR) neural network is used to predict the ESI level to achieve the purpose of early warning. First, the results show that the weight of the employment rate, the proportion of students in colleges, and the per capita consumption level are relatively high, which play an important role for the ecological security level of Shaanxi Province. Second, Xi’an City has been the best level in ecological security level, the ecological security of Southwest Shaanxi is relatively good, which is related to its economic development and comparative advantage geographical conditions, while the ecological security level of Weinan and Shangluo are poor. Third, the ESI of most cities in Shaanxi Province is maintained at grade III. The ESI in Shaanxi has an upward trend from 2000 to 2006; however, the trend of this increase has not been maintained, and nearly half of the cities in Shaanxi have slightly decreased the ecological security level. Four, the ESI of Xi’an and Hanzhong will remain at a high level in the future, while the ecological security situation of Shangluo, Weinan, and Yulin probably become very poor in the next years.
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This research was funded by the National Natural Science Foundation of China, grant number 71773091; Special Fund for Scientific Research of Forestry Commonwealth Industry, grant number 201504424.
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Shuai Chen: methodology, software, writing-original draft, writing-review& editing, investigation, validation. Shunbo Yao: conceptualization, supervision, funding acquisition.
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Chen, S., Yao, S. Evaluation and dynamic prediction of ecological security from the perspective of sustainable development: a case study of Shaanxi Province, China. Environ Sci Pollut Res 29, 42331–42346 (2022). https://doi.org/10.1007/s11356-022-19812-9
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DOI: https://doi.org/10.1007/s11356-022-19812-9