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China's ecosystem service value in 1992-2018: Pattern and anthropogenic driving factors detection using Bayesian spatiotemporal hierarchy model.
Yang, Renfei; Ren, Fu; Xu, Wenxuan; Ma, Xiangyuan; Zhang, Hongwei; He, Wenwen.
Affiliation
  • Yang R; School of Resource and Environmental Science, Wuhan University, Wuhan, 430079, China. Electronic address: youngfly@whu.edu.cn.
  • Ren F; School of Resource and Environmental Science, Wuhan University, Wuhan, 430079, China; Key Laboratory of GIS, Ministry of Education, Wuhan University, Wuhan, 430079, China. Electronic address: renfu@whu.edu.cn.
  • Xu W; School of Geographic and Oceanographic Sciences, Nanjing University, Nanjing, 210023, China. Electronic address: wenshinexu@foxmail.com.
  • Ma X; School of Resource and Environmental Science, Wuhan University, Wuhan, 430079, China. Electronic address: maxiangyuan@whu.edu.cn.
  • Zhang H; Electronic Information School, Wuhan University, Wuhan, 430079, China. Electronic address: zhanghongwei@whu.edu.cn.
  • He W; School of Resource and Environmental Science, Wuhan University, Wuhan, 430079, China. Electronic address: hewenwen@whu.edu.cn.
J Environ Manage ; 302(Pt B): 114089, 2022 Jan 15.
Article in En | MEDLINE | ID: mdl-34775337
Maintaining ecosystem services (ESs) and reducing ecosystem degradation are important goals for achieving sustainable development. However, under the influence of various anthropogenic factors, the total ecosystem service value (ESV) of China continues to decline, and the detailed processes involved in this decline are unclear. In this paper, a new long-term annual land cover dataset (the Climate Change Initiative Land Cover or CCI-LC dataset) with a spatial resolution of 300 m was employed to estimate the ESV of China, and Bayesian spatiotemporal hierarchy models were built to examine the detailed patterns and anthropogenic driving factors. From 1992 to 2018, the total ESV of China fluctuated and decreased from 3265.3 to 3253.29 billion US$ at an average rate of 0.55 billion US$ per year. Furthermore, the model revealed the spatiotemporal variations in the ESV pattern, and simultaneously detected the influences of 9 variables related to economic factors, population, infrastructure, energy, agriculture and ecological restoration, providing a convenient and effective method for ESV spatiotemporal analysis. The results enrich our understanding of the detailed spatiotemporal variation and anthropogenic driving factors underlying the declining ESV in China. These findings have substantial guiding implications for adjusting ecological regulation policies.
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Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Ecosystem / Conservation of Natural Resources Type of study: Diagnostic_studies / Prognostic_studies Country/Region as subject: Asia Language: En Journal: J Environ Manage Year: 2022 Type: Article

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Ecosystem / Conservation of Natural Resources Type of study: Diagnostic_studies / Prognostic_studies Country/Region as subject: Asia Language: En Journal: J Environ Manage Year: 2022 Type: Article