An integrated ecological security early-warning framework in the national nature reserve based on the gray model

Nature reserves (NRs) play a pivotal role in minimizing habitat loss and protecting wild animals and plants, which are critical for human ecological security. However, focusing only on the construction of ecological security patterns of NRs without understanding their ecological security early-warning situations and their driving factors may fail to achieve protection goals. This study constructed an ecological security early-warning framework and index system based on the Driving force-Pressure-State-Impact-Response (DPSIR) framework model. The gray model (GM) was used to predict the ecological security early-warning situation, and the Geo-detector model was applied to explore the driving factors of the ecological security early-warning system in the Baishuijiang National Nature Reserve (BNNR). The results showed that the average ecological security index (ESI) value increased from 0.2796 in 2005 to 0.3171 in 2017, with an average increase of 11.82%. The ecological security early-warning index (ESEWI) value increased from 0.3171 in 2018 to 0.3622 in 2030, which was an average increase of 12.46%. These results indicated that the ecological security situation continually improved from 2005 to 2030. By 2030, the number of towns with a “no warning” grade increased to four, the number of towns with an “extreme warning” grade was zero, and the proportion of areas with early-warnings decreased from 100% to 33%. The q values of per capita forest land areas and per capita grassland areas were both 0.9334, which indicated that environmental characteristic factors were the primary driving factors in ecological security early-warning. Our results demonstrated that the ecological security early-warning index system based on the DPSIR model and grey model can well prediction ecological security situation and provide scientific support for the ecological protection and management of NRs.