Spatiotemporal dynamics and driving mechanisms of wetlands in arid regions of Xinjiang
Wetlands in arid regions provide essential economic, cultural, and climate change mitigation services. However, studies that comprehensively consider the overall wetland dynamics of Xinjiang, a typical inland arid region, are limited. We analyzed the spatiotemporal dynamics and driving factors in we...
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Elsevier
2025-05-01
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| Series: | Ecological Indicators |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S1470160X25004157 |
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| author | Yue Ding Jianli Ding Jinjie Wang Lijing Han Jiao Wang Xiangyue Chen Xiangyu Ge |
| author_facet | Yue Ding Jianli Ding Jinjie Wang Lijing Han Jiao Wang Xiangyue Chen Xiangyu Ge |
| author_sort | Yue Ding |
| collection | DOAJ |
| description | Wetlands in arid regions provide essential economic, cultural, and climate change mitigation services. However, studies that comprehensively consider the overall wetland dynamics of Xinjiang, a typical inland arid region, are limited. We analyzed the spatiotemporal dynamics and driving factors in wetlands in Xinjiang from 1990 to 2020. Wetland maps were generated at 10-year intervals using the Google Earth Engine cloud computing platform. The complex relationships between natural environmental factors and human activities influencing wetland change were quantitatively analyzed using the partial least squares-path modeling (PLS-PM). The overall accuracy of wetland mapping exceeded 0.94, effectively classifying wetlands into five categories: water, marsh, swamp, saline wetland, and flooded flat. During the study period, the total area of wetlands increased by 1,958.58 km2. Specifically, the area of water bodies expanded by 2,988.40 km2, while the areas of marshes, saline wetlands, and flooded flats significantly decreased. PLS-PM analysis revealed that the driving factors had four direct impact paths and nine indirect impact paths on wetland changes. Notably, anthropogenic factors emerged as the primary drivers of wetland loss. The influence of topography on wetland distribution shifted from negative to positive due to interactions with climatic and soil factors. These findings not only deepen our understanding of the spatiotemporal dynamics of wetlands in arid regions but also provide a scientific basis for developing effective conservation and restoration strategies. |
| format | Article |
| id | doaj-art-a86578ab11d14817bcc3bc8bffa16f27 |
| institution | DOAJ |
| issn | 1470-160X |
| language | English |
| publishDate | 2025-05-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Ecological Indicators |
| spelling | doaj-art-a86578ab11d14817bcc3bc8bffa16f272025-08-20T03:13:49ZengElsevierEcological Indicators1470-160X2025-05-0117411348510.1016/j.ecolind.2025.113485Spatiotemporal dynamics and driving mechanisms of wetlands in arid regions of XinjiangYue Ding0Jianli Ding1Jinjie Wang2Lijing Han3Jiao Wang4Xiangyue Chen5Xiangyu Ge6College of Geography and Remote Sensing Sciences, Xinjiang University, Urumqi 830017, ChinaXinjiang Institute of Technology, Aksu 843100, China; Institute for Beautiful China, Xinjiang University, Urumqi 830017, China; Corresponding authors.College of Geography and Remote Sensing Sciences, Xinjiang University, Urumqi 830017, China; Corresponding authors.College of Geodesy and Geomatics, Shandong University of Science and Technology, Qingdao 266590, ChinaCollege of Geography and Remote Sensing Sciences, Xinjiang University, Urumqi 830017, ChinaSchool of Earth Sciences and Spatial Information Engineering, Hunan University of Science and Technology, Xiangtan 411201, ChinaCollege of Geography and Remote Sensing Sciences, Xinjiang University, Urumqi 830017, ChinaWetlands in arid regions provide essential economic, cultural, and climate change mitigation services. However, studies that comprehensively consider the overall wetland dynamics of Xinjiang, a typical inland arid region, are limited. We analyzed the spatiotemporal dynamics and driving factors in wetlands in Xinjiang from 1990 to 2020. Wetland maps were generated at 10-year intervals using the Google Earth Engine cloud computing platform. The complex relationships between natural environmental factors and human activities influencing wetland change were quantitatively analyzed using the partial least squares-path modeling (PLS-PM). The overall accuracy of wetland mapping exceeded 0.94, effectively classifying wetlands into five categories: water, marsh, swamp, saline wetland, and flooded flat. During the study period, the total area of wetlands increased by 1,958.58 km2. Specifically, the area of water bodies expanded by 2,988.40 km2, while the areas of marshes, saline wetlands, and flooded flats significantly decreased. PLS-PM analysis revealed that the driving factors had four direct impact paths and nine indirect impact paths on wetland changes. Notably, anthropogenic factors emerged as the primary drivers of wetland loss. The influence of topography on wetland distribution shifted from negative to positive due to interactions with climatic and soil factors. These findings not only deepen our understanding of the spatiotemporal dynamics of wetlands in arid regions but also provide a scientific basis for developing effective conservation and restoration strategies.http://www.sciencedirect.com/science/article/pii/S1470160X25004157Wetland classificationGoogle Earth Engine (GEE)Partial Least Squares-Path Modeling (PLS-PM)Xinjiang wetlandsRemote sensing |
| spellingShingle | Yue Ding Jianli Ding Jinjie Wang Lijing Han Jiao Wang Xiangyue Chen Xiangyu Ge Spatiotemporal dynamics and driving mechanisms of wetlands in arid regions of Xinjiang Ecological Indicators Wetland classification Google Earth Engine (GEE) Partial Least Squares-Path Modeling (PLS-PM) Xinjiang wetlands Remote sensing |
| title | Spatiotemporal dynamics and driving mechanisms of wetlands in arid regions of Xinjiang |
| title_full | Spatiotemporal dynamics and driving mechanisms of wetlands in arid regions of Xinjiang |
| title_fullStr | Spatiotemporal dynamics and driving mechanisms of wetlands in arid regions of Xinjiang |
| title_full_unstemmed | Spatiotemporal dynamics and driving mechanisms of wetlands in arid regions of Xinjiang |
| title_short | Spatiotemporal dynamics and driving mechanisms of wetlands in arid regions of Xinjiang |
| title_sort | spatiotemporal dynamics and driving mechanisms of wetlands in arid regions of xinjiang |
| topic | Wetland classification Google Earth Engine (GEE) Partial Least Squares-Path Modeling (PLS-PM) Xinjiang wetlands Remote sensing |
| url | http://www.sciencedirect.com/science/article/pii/S1470160X25004157 |
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