Spatial and temporal changes in ecosystem services value and analysis of driving factors in the Yangtze River Delta Region
Based on land use classification data for the Yangtze River Delta region in 2000, 2015, and 2020, this study aims to explore the spatial and temporal evolution of ecosystem services value (ESV) in the region. By analyzing the land use structure and its dynamic changes, an ESV model is constructed. F...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
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De Gruyter
2024-03-01
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| Series: | Open Geosciences |
| Subjects: | |
| Online Access: | https://doi.org/10.1515/geo-2022-0604 |
| _version_ | 1797279189249818624 |
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| author | Zhang Wei Wang Fang-Fang Shan Wei |
| author_facet | Zhang Wei Wang Fang-Fang Shan Wei |
| author_sort | Zhang Wei |
| collection | DOAJ |
| description | Based on land use classification data for the Yangtze River Delta region in 2000, 2015, and 2020, this study aims to explore the spatial and temporal evolution of ecosystem services value (ESV) in the region. By analyzing the land use structure and its dynamic changes, an ESV model is constructed. Furthermore, the study utilizes a geodetector to analyze the driving factors of ESV in the Yangtze River Delta region. The findings are as follows: (1) From 2000 to 2020, arable land was the predominant land use type in the Yangtze River Delta region. (2) The ESV in the region showed an upward trend followed by a decline from 2000 to 2020. Regulating services and supporting services have always been the core functions of ecosystem services in the region, with hydrological regulation contributing the most. (3) From a spatial perspective, there were significant differences in the spatial distribution of AESV (aggregated ecosystem services value) in the Yangtze River Delta region. The AESV changes in various cities within the region were evident, with a decreasing trend observed in most cities. (4) The sensitivity index of each land use type was less than 1, with forest land exhibiting the highest sensitivity and having the greatest impact on ESV. (5) Geodetector analysis revealed that the AESV in the Yangtze River Delta region is influenced by a combination of regional natural factors, economic factors, and social factors, and the interaction among different driving forces significantly enhances the spatial heterogeneity of AESV in the region. |
| first_indexed | 2024-03-07T16:20:46Z |
| format | Article |
| id | doaj.art-62275e0526244d11a304e67823001bc6 |
| institution | Directory Open Access Journal |
| issn | 2391-5447 |
| language | English |
| last_indexed | 2024-03-07T16:20:46Z |
| publishDate | 2024-03-01 |
| publisher | De Gruyter |
| record_format | Article |
| series | Open Geosciences |
| spelling | doaj.art-62275e0526244d11a304e67823001bc62024-03-04T07:28:51ZengDe GruyterOpen Geosciences2391-54472024-03-01161395610.1515/geo-2022-0604Spatial and temporal changes in ecosystem services value and analysis of driving factors in the Yangtze River Delta RegionZhang Wei0Wang Fang-Fang1Shan Wei2Business School, Wenzhou University, Wenzhou, ChinaBusiness School, Wenzhou University, Wenzhou, ChinaSchool of Economics and Management, Wenzhou University of Technology, Wenzhou, ChinaBased on land use classification data for the Yangtze River Delta region in 2000, 2015, and 2020, this study aims to explore the spatial and temporal evolution of ecosystem services value (ESV) in the region. By analyzing the land use structure and its dynamic changes, an ESV model is constructed. Furthermore, the study utilizes a geodetector to analyze the driving factors of ESV in the Yangtze River Delta region. The findings are as follows: (1) From 2000 to 2020, arable land was the predominant land use type in the Yangtze River Delta region. (2) The ESV in the region showed an upward trend followed by a decline from 2000 to 2020. Regulating services and supporting services have always been the core functions of ecosystem services in the region, with hydrological regulation contributing the most. (3) From a spatial perspective, there were significant differences in the spatial distribution of AESV (aggregated ecosystem services value) in the Yangtze River Delta region. The AESV changes in various cities within the region were evident, with a decreasing trend observed in most cities. (4) The sensitivity index of each land use type was less than 1, with forest land exhibiting the highest sensitivity and having the greatest impact on ESV. (5) Geodetector analysis revealed that the AESV in the Yangtze River Delta region is influenced by a combination of regional natural factors, economic factors, and social factors, and the interaction among different driving forces significantly enhances the spatial heterogeneity of AESV in the region.https://doi.org/10.1515/geo-2022-0604yangtze river deltaecosystem services valuegeodetector analysisland use change |
| spellingShingle | Zhang Wei Wang Fang-Fang Shan Wei Spatial and temporal changes in ecosystem services value and analysis of driving factors in the Yangtze River Delta Region Open Geosciences yangtze river delta ecosystem services value geodetector analysis land use change |
| title | Spatial and temporal changes in ecosystem services value and analysis of driving factors in the Yangtze River Delta Region |
| title_full | Spatial and temporal changes in ecosystem services value and analysis of driving factors in the Yangtze River Delta Region |
| title_fullStr | Spatial and temporal changes in ecosystem services value and analysis of driving factors in the Yangtze River Delta Region |
| title_full_unstemmed | Spatial and temporal changes in ecosystem services value and analysis of driving factors in the Yangtze River Delta Region |
| title_short | Spatial and temporal changes in ecosystem services value and analysis of driving factors in the Yangtze River Delta Region |
| title_sort | spatial and temporal changes in ecosystem services value and analysis of driving factors in the yangtze river delta region |
| topic | yangtze river delta ecosystem services value geodetector analysis land use change |
| url | https://doi.org/10.1515/geo-2022-0604 |
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