Spatiotemporal variation characteristics of ecosystem health and its driving mechanism in the mountains of southwest China
文献类型：期刊论文
| 作者 | Xiao, Zuolin1,2; Liu, Rui2; Gao, Yanghua1; Yang, Qingyuan3; Chen, Jilong4
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| 刊名 | JOURNAL OF CLEANER PRODUCTION
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| 出版日期 | 2022-04-15 |
| 卷号 | 345页码:11 |
| 关键词 | Ecosystem health Spatiotemporal variation Driving mechanism Migrant population |
| ISSN号 | 0959-6526 |
| DOI | 10.1016/j.jclepro.2022.131138 |
| 通讯作者 | Gao, Yanghua(gaoyanghua@sina.com) |
| 英文摘要 | A deeper understanding of the spatiotemporal variation characteristics of ecosystem health and its driving mechanism are important for ecosystem management and restoration. Under the complex environment in the southwestern mountainous area of China, various natural and anthropogenic factors interact with each other, complicating the mechanism driving ecosystem health. Quantitatively exploring the interaction among driving factors is challengeable but worthwhile. Based on the pressure-state-response (PSR) framework, the ecosystem health value of the study area was computed for the years of 2000 and 2018 at the grid scale. A geographical detector model was adopted to explore the factors driving ecosystem health change. We found that, compared to the year of 2000, there was an improvement in ecosystem health in 2018. The most significant improvement occurred in ample rural areas scattered in remote mountain areas. Nevertheless, there were grids experiencing ecosystem health deterioration. The appearance of a "deterioration ring " surrounding the metropolis region was the typical representative. Among the 10 selected driving factors, in-migrant population, out-migrant population, population density, elevation, and slope were found to be the most important factors. There were obvious impact thresholds of elevation, slope, distance to towns and distance to road on ecosystem health change. The out -migrant population in rural areas strongly promoted the local ecosystem health improvement by alleviating the pressure of human activity. In contrast, the in-migrant population presented the opposite effects on ecosystem health. All driving factors produced enhanced effects on the ecosystem health change through interaction effects. The largest enhanced effects occurred between the migrant population (in-and out-migrant) and the other eight driving factors. Our findings emphasize the key role of migrant population in ecosystem health change, which has not been considered in previous studies. |
| 资助项目 | Chongqing Research Program of Basic Research and Frontier Technology[cstc2019jcyj-msxmX0515] ; China Postdoctoral Science Foundation[2019M653830XB] ; National Natural Science Foundation of China[42001388] ; National Natural Science Foundation of China[41771460] ; Youth Innovation Promotion Association, China[2018417] |
| WOS研究方向 | Science & Technology - Other Topics ; Engineering ; Environmental Sciences & Ecology |
| 语种 | 英语 |
| WOS记录号 | WOS:000784418200005 |
| 出版者 | ELSEVIER SCI LTD |
| 源URL | [http://119.78.100.138/handle/2HOD01W0/15865]  |
| 专题 | 中国科学院重庆绿色智能技术研究院 |
| 通讯作者 | Gao, Yanghua |
| 作者单位 | 1.Chongqing Inst Meteorol Sci, Chongqing 401147, Peoples R China 2.Chongqing Normal Univ, Chongqing Key Lab GIS Applicat Res, Chongqing 401331, Peoples R China 3.Southwest Univ, Sch Geog Sci, Chongqing 400715, Peoples R China 4.Chinese Acad Sci, Chongqing Inst Green & Intelligent Technol, Chongqing 401122, Peoples R China |
| 推荐引用方式 GB/T 7714 | Xiao, Zuolin,Liu, Rui,Gao, Yanghua,et al. Spatiotemporal variation characteristics of ecosystem health and its driving mechanism in the mountains of southwest China[J]. JOURNAL OF CLEANER PRODUCTION,2022,345:11. |
| APA | Xiao, Zuolin,Liu, Rui,Gao, Yanghua,Yang, Qingyuan,&Chen, Jilong.(2022).Spatiotemporal variation characteristics of ecosystem health and its driving mechanism in the mountains of southwest China.JOURNAL OF CLEANER PRODUCTION,345,11. |
| MLA | Xiao, Zuolin,et al."Spatiotemporal variation characteristics of ecosystem health and its driving mechanism in the mountains of southwest China".JOURNAL OF CLEANER PRODUCTION 345(2022):11. |
入库方式： OAI收割
来源：重庆绿色智能技术研究院
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