Spatiotemporal changes of ecosystem health and the impact of its driving factors on the Loess Plateau in China
The Loess Plateau is renowned for its fragile ecosystem, and understanding the changes and driving impacts of ecosystem health (EH) is crucial for formulating environmental protection policies for the region. Soil erosion, as a key limiting factor of the region’s ecosystem, must be considered when e...
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| Format: | Article |
| Language: | English |
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Elsevier
2025-01-01
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| Series: | Ecological Indicators |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S1470160X24014778 |
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| author | Xuepeng Zhang Taixia Wu Qiqi Du Ninglei Ouyang Wei Nie Yang Liu Peng Gou Guangchao Li |
| author_facet | Xuepeng Zhang Taixia Wu Qiqi Du Ninglei Ouyang Wei Nie Yang Liu Peng Gou Guangchao Li |
| author_sort | Xuepeng Zhang |
| collection | DOAJ |
| description | The Loess Plateau is renowned for its fragile ecosystem, and understanding the changes and driving impacts of ecosystem health (EH) is crucial for formulating environmental protection policies for the region. Soil erosion, as a key limiting factor of the region’s ecosystem, must be considered when evaluating EH in this area. Based on this idea, a new framework for assessing EH is proposed. The efficient machine learning model (light gradient boosting machine model) and the variable explanation model (SHapley Additive exPlanation model) are combined to quantify the functional relationships between various driving factors and EH, thereby exploring the impacts of climatic factors, socioeconomic development (SED), and ecological restoration projects (ERP) on EH. The study found that: (1) From 1995 to 2020, EH in the Loess Plateau increased from 0.42 to 0.58, and the forms of spatial clustering changed. Moreover, there are significant differences in the speed and patterns of EH improvement in different regions, especially after 2010. (2) The importance of precipitation (PRE), SED, ERP, and temperature (TEM) is 33 %, 26 %, 24 %, and 17 %, respectively. The driving impacts exhibit non-monotonic polynomial relationships of third, fourth, second, and fourth degrees, indicating that the mechanisms through which EH is influenced by these factors can change. (3) Counties with higher response to PRE (>0.32) are mainly located in the central region. Counties with higher response to SED (>0.30) are primarily in areas with higher population and urbanization. Counties with higher response to ERP (>0.36) are mainly in the eastern region. Counties with higher response to TEM (>0.26) are primarily in the southern and western regions. The results of this paper provide new insights for EH research in areas with fragile ecosystems and are of significant importance for the ecological civilization construction of the Loess Plateau. |
| format | Article |
| id | doaj-art-1b74f8fbd0bc4d4c9cd295579392dc7e |
| institution | Kabale University |
| issn | 1470-160X |
| language | English |
| publishDate | 2025-01-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Ecological Indicators |
| spelling | doaj-art-1b74f8fbd0bc4d4c9cd295579392dc7e2025-01-31T05:10:31ZengElsevierEcological Indicators1470-160X2025-01-01170113020Spatiotemporal changes of ecosystem health and the impact of its driving factors on the Loess Plateau in ChinaXuepeng Zhang0Taixia Wu1Qiqi Du2Ninglei Ouyang3Wei Nie4Yang Liu5Peng Gou6Guangchao Li7School of Earth Sciences and Engineering, Hohai University, Nanjing 211100, China; College of Information Engineering, Jiaxing Nanhu University, 314001 Jiaxing, Zhejiang, China; Research Center of Big Data Technology, Nanhu Laboratory, Jiaxing 314000, ChinaSchool of Earth Sciences and Engineering, Hohai University, Nanjing 211100, China; Corresponding authors.College of Information Engineering, Jiaxing Nanhu University, 314001 Jiaxing, Zhejiang, China; Corresponding authors.School of Earth Sciences and Engineering, Hohai University, Nanjing 211100, ChinaResearch Center of Big Data Technology, Nanhu Laboratory, Jiaxing 314000, ChinaResearch Center of Big Data Technology, Nanhu Laboratory, Jiaxing 314000, ChinaResearch Center of Big Data Technology, Nanhu Laboratory, Jiaxing 314000, ChinaSchool of Tourism, Henan Normal University, Xinxiang 453007, ChinaThe Loess Plateau is renowned for its fragile ecosystem, and understanding the changes and driving impacts of ecosystem health (EH) is crucial for formulating environmental protection policies for the region. Soil erosion, as a key limiting factor of the region’s ecosystem, must be considered when evaluating EH in this area. Based on this idea, a new framework for assessing EH is proposed. The efficient machine learning model (light gradient boosting machine model) and the variable explanation model (SHapley Additive exPlanation model) are combined to quantify the functional relationships between various driving factors and EH, thereby exploring the impacts of climatic factors, socioeconomic development (SED), and ecological restoration projects (ERP) on EH. The study found that: (1) From 1995 to 2020, EH in the Loess Plateau increased from 0.42 to 0.58, and the forms of spatial clustering changed. Moreover, there are significant differences in the speed and patterns of EH improvement in different regions, especially after 2010. (2) The importance of precipitation (PRE), SED, ERP, and temperature (TEM) is 33 %, 26 %, 24 %, and 17 %, respectively. The driving impacts exhibit non-monotonic polynomial relationships of third, fourth, second, and fourth degrees, indicating that the mechanisms through which EH is influenced by these factors can change. (3) Counties with higher response to PRE (>0.32) are mainly located in the central region. Counties with higher response to SED (>0.30) are primarily in areas with higher population and urbanization. Counties with higher response to ERP (>0.36) are mainly in the eastern region. Counties with higher response to TEM (>0.26) are primarily in the southern and western regions. The results of this paper provide new insights for EH research in areas with fragile ecosystems and are of significant importance for the ecological civilization construction of the Loess Plateau.http://www.sciencedirect.com/science/article/pii/S1470160X24014778Loess PlateauEcosystem healthSpatiotemporal changesDriving factorsSoil erosion |
| spellingShingle | Xuepeng Zhang Taixia Wu Qiqi Du Ninglei Ouyang Wei Nie Yang Liu Peng Gou Guangchao Li Spatiotemporal changes of ecosystem health and the impact of its driving factors on the Loess Plateau in China Ecological Indicators Loess Plateau Ecosystem health Spatiotemporal changes Driving factors Soil erosion |
| title | Spatiotemporal changes of ecosystem health and the impact of its driving factors on the Loess Plateau in China |
| title_full | Spatiotemporal changes of ecosystem health and the impact of its driving factors on the Loess Plateau in China |
| title_fullStr | Spatiotemporal changes of ecosystem health and the impact of its driving factors on the Loess Plateau in China |
| title_full_unstemmed | Spatiotemporal changes of ecosystem health and the impact of its driving factors on the Loess Plateau in China |
| title_short | Spatiotemporal changes of ecosystem health and the impact of its driving factors on the Loess Plateau in China |
| title_sort | spatiotemporal changes of ecosystem health and the impact of its driving factors on the loess plateau in china |
| topic | Loess Plateau Ecosystem health Spatiotemporal changes Driving factors Soil erosion |
| url | http://www.sciencedirect.com/science/article/pii/S1470160X24014778 |
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