Key points are not available for this paper at this time.
Forest Ecological Security (FES) is an essential component of ecological security and plays an important role in national security. In this study, the Delphi method was used to construct a multi-index comprehensive evaluation system, and indicators were weighted using the entropy weight method. Based on data from 31 provinces, this study evaluated the status of FES in China from 1994 to 2018 and identified the influencing factors of FES. The results showed that indicators such as forest stock volume per unit land area, forest coverage rate, population density, and population per unit forest area contributed the most to the evaluation indicator system. Forest quantity and quality, as well as population pressure, were especially important factors affecting FES. In terms of spatial distribution, FES varied greatly between regions and the developments were unbalanced. Provinces in the northeast, southern and southwest forest regions, such as Jilin, Heilongjiang, Fujian, Jiangxi, Yunnan, etc., had better FES due to their rich forest resources. The provinces in northwest China (Xinjiang, Qinghai, Gansu, and Ningxia) and north China (Shanxi, Hebei, Beijing, and Tianjin) had worse FES than other provinces. With the reference of temporal variation, the national average FES increased from 0.543 (1994–1998) to 0.593 (2014–2018). Furthermore, 51.6% of the provinces (Hainan, Fujian, Heilongjiang, Beijing, etc.) had continuous upward trends in their evaluation value of FES (VFES) during the study period, while the other provinces (Inner Mongolia, Shanghai, Shandong, etc.) exhibited fluctuating VFES. In general, the VFES of all provinces increased during the whole study period, and the average level of FES improved significantly, which indicated that China’s FES situation has shown continued improvement.
Building similarity graph...
Analyzing shared references across papers
Loading...
Xuan Gao
Guangyu Wang
John L. Innes
Global Ecology and Conservation
University of British Columbia
Institute of Geographic Sciences and Natural Resources Research
Beijing Forestry University
Building similarity graph...
Analyzing shared references across papers
Loading...
Gao et al. (Tue,) studied this question.
synapsesocial.com/papers/6a0fe981fa36b6e053fd0547 — DOI: https://doi.org/10.1016/j.gecco.2021.e01821