Differentiated factors drive the spatial heterogeneity of ecosystem services in Xinjiang Autonomous Region, China
Exploring the driving factors of changing ecosystem services is critical for supply capacity maintaining and ecological management zoning. Xinjiang of Northwest China, is considered one of the most fragile ecological environment areas. However, studies on how ecosystem services’ driving forces respo...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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Frontiers Media S.A.
2023-03-01
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| Series: | Frontiers in Ecology and Evolution |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/fevo.2023.1168313/full |
| _version_ | 1797859052332515328 |
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| author | Zhiru Zhang Zhiru Zhang Huawei Wan Shilei Peng Lin Huang |
| author_facet | Zhiru Zhang Zhiru Zhang Huawei Wan Shilei Peng Lin Huang |
| author_sort | Zhiru Zhang |
| collection | DOAJ |
| description | Exploring the driving factors of changing ecosystem services is critical for supply capacity maintaining and ecological management zoning. Xinjiang of Northwest China, is considered one of the most fragile ecological environment areas. However, studies on how ecosystem services’ driving forces respond to the environmental conditions of Xinjiang are still insufficient, especially in sub–regions with considerable spatial heterogeneity. Based on 106 counties across Xinjiang, we employed models of the Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) and Revised Wind Erosion Equation (RWEQ) to quantify four essential ecosystem services (carbon storage, habitat quality, and sand fixation and water yield). Then, we investigated the spatial distribution of four ecosystem services and drivers at the county scale in 2020 by using multi–scale geographically weighted regression (MGWR). The results showed that the spatial distribution of ecosystem services is higher in the north and lower in the south, and hotspots and high–value ecosystem services areas were consistent. Precipitation, temperature, and fractional vegetation cover were the dominant factors influencing the four ecosystem services. Therefore, regulating climate and increasing vegetation will maximize the improvement of regional ecosystem services in Xinjiang. Significant differences exist in the counties of the type, intensity, and direction of ecosystem services drivers. The correlation between carbon storage, habitat quality and fractional vegetation cover was more robust stronger in the south. Water yield was more closely related to fractional vegetation cover in southern Xinjiang. Under different ecological and social conditions, the impact of driving forces on ecosystem services showed different changing trends. Three suggestions for improving ecosystem services management were proposed based on our results. The comparative analysis of the driving factors of county ecosystem services in this study will help to formulate differentiated ecological protection policies and promote a sustainable supply of ecosystem services in Xinjiang. In the future, it is necessary to strengthen the long-term monitoring and evaluation of ecosystem services and the research on the interaction of multiple drivers. |
| first_indexed | 2024-04-09T21:23:15Z |
| format | Article |
| id | doaj.art-ee93a69b74c64278a4255257466f92d9 |
| institution | Directory Open Access Journal |
| issn | 2296-701X |
| language | English |
| last_indexed | 2024-04-09T21:23:15Z |
| publishDate | 2023-03-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Ecology and Evolution |
| spelling | doaj.art-ee93a69b74c64278a4255257466f92d92023-03-28T04:37:17ZengFrontiers Media S.A.Frontiers in Ecology and Evolution2296-701X2023-03-011110.3389/fevo.2023.11683131168313Differentiated factors drive the spatial heterogeneity of ecosystem services in Xinjiang Autonomous Region, ChinaZhiru Zhang0Zhiru Zhang1Huawei Wan2Shilei Peng3Lin Huang4Chinese Research Academy of Environmental Sciences, Beijing, ChinaCenter for Satellite Application on Ecology and Environment, Ministry of Ecology and Environment, Beijing, ChinaCenter for Satellite Application on Ecology and Environment, Ministry of Ecology and Environment, Beijing, ChinaInstitute of Subtropical Agriculture, Chinese Academy of Sciences, Beijing, Hunan, ChinaInstitute of Geographic Sciences and Natural Resources Research, Beijing, ChinaExploring the driving factors of changing ecosystem services is critical for supply capacity maintaining and ecological management zoning. Xinjiang of Northwest China, is considered one of the most fragile ecological environment areas. However, studies on how ecosystem services’ driving forces respond to the environmental conditions of Xinjiang are still insufficient, especially in sub–regions with considerable spatial heterogeneity. Based on 106 counties across Xinjiang, we employed models of the Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) and Revised Wind Erosion Equation (RWEQ) to quantify four essential ecosystem services (carbon storage, habitat quality, and sand fixation and water yield). Then, we investigated the spatial distribution of four ecosystem services and drivers at the county scale in 2020 by using multi–scale geographically weighted regression (MGWR). The results showed that the spatial distribution of ecosystem services is higher in the north and lower in the south, and hotspots and high–value ecosystem services areas were consistent. Precipitation, temperature, and fractional vegetation cover were the dominant factors influencing the four ecosystem services. Therefore, regulating climate and increasing vegetation will maximize the improvement of regional ecosystem services in Xinjiang. Significant differences exist in the counties of the type, intensity, and direction of ecosystem services drivers. The correlation between carbon storage, habitat quality and fractional vegetation cover was more robust stronger in the south. Water yield was more closely related to fractional vegetation cover in southern Xinjiang. Under different ecological and social conditions, the impact of driving forces on ecosystem services showed different changing trends. Three suggestions for improving ecosystem services management were proposed based on our results. The comparative analysis of the driving factors of county ecosystem services in this study will help to formulate differentiated ecological protection policies and promote a sustainable supply of ecosystem services in Xinjiang. In the future, it is necessary to strengthen the long-term monitoring and evaluation of ecosystem services and the research on the interaction of multiple drivers.https://www.frontiersin.org/articles/10.3389/fevo.2023.1168313/fullecosystem servicesspatial patterndriving factorsremote sensingInVEST modelmulti–scale geographically weighted regression (MGWR) |
| spellingShingle | Zhiru Zhang Zhiru Zhang Huawei Wan Shilei Peng Lin Huang Differentiated factors drive the spatial heterogeneity of ecosystem services in Xinjiang Autonomous Region, China Frontiers in Ecology and Evolution ecosystem services spatial pattern driving factors remote sensing InVEST model multi–scale geographically weighted regression (MGWR) |
| title | Differentiated factors drive the spatial heterogeneity of ecosystem services in Xinjiang Autonomous Region, China |
| title_full | Differentiated factors drive the spatial heterogeneity of ecosystem services in Xinjiang Autonomous Region, China |
| title_fullStr | Differentiated factors drive the spatial heterogeneity of ecosystem services in Xinjiang Autonomous Region, China |
| title_full_unstemmed | Differentiated factors drive the spatial heterogeneity of ecosystem services in Xinjiang Autonomous Region, China |
| title_short | Differentiated factors drive the spatial heterogeneity of ecosystem services in Xinjiang Autonomous Region, China |
| title_sort | differentiated factors drive the spatial heterogeneity of ecosystem services in xinjiang autonomous region china |
| topic | ecosystem services spatial pattern driving factors remote sensing InVEST model multi–scale geographically weighted regression (MGWR) |
| url | https://www.frontiersin.org/articles/10.3389/fevo.2023.1168313/full |
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