Land Use Change Forcing Data Undermine the Modeling of China's Greening Efforts
Abstract China has made extensive afforestation efforts over the past 40 years. However, ecosystem models simulate only modest vegetation enhancement, creating a significant disparity between documented reforestation efforts and model‐based simulations. This fundamental mismatch remains largely unex...
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| Format: | Article |
| Language: | English |
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Wiley
2025-03-01
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| Series: | Geophysical Research Letters |
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| Online Access: | https://doi.org/10.1029/2024GL113403 |
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| _version_ | 1850187592291581952 |
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| author | Ziyu Wang Weiqing Zhao Sen Cao Pengjun Zhao Yuhang Luo Dajing Li Ziyun Sun Zaichun Zhu |
| author_facet | Ziyu Wang Weiqing Zhao Sen Cao Pengjun Zhao Yuhang Luo Dajing Li Ziyun Sun Zaichun Zhu |
| author_sort | Ziyu Wang |
| collection | DOAJ |
| description | Abstract China has made extensive afforestation efforts over the past 40 years. However, ecosystem models simulate only modest vegetation enhancement, creating a significant disparity between documented reforestation efforts and model‐based simulations. This fundamental mismatch remains largely unexplored. Here, we conducted a comprehensive analysis using diverse observation data to identify the determinant within Dynamic Global Vegetation Models (DGVMs) that underestimates vegetation growth in China. By developing a high‐resolution forest cover change data set, we found that LUH2‐GCB, the common land use input for DGVMs, causes models to underestimate afforestation. With a neighborhood comparison analysis, we quantitively demonstrated the predominant role of underestimated afforestation in lowering leaf area index (LAI) trends. Overall, DGVMs underestimated China's afforestation area by an average of 26.88%, leading to a 29.46% underestimation in LAI increase. Our findings confirm a significant greening trend in China and highlight the need for improved land use data representation in DGVMs. |
| format | Article |
| id | doaj-art-050aa75925fb478f96b83ee6b1122ac2 |
| institution | OA Journals |
| issn | 0094-8276 1944-8007 |
| language | English |
| publishDate | 2025-03-01 |
| publisher | Wiley |
| record_format | Article |
| series | Geophysical Research Letters |
| spelling | doaj-art-050aa75925fb478f96b83ee6b1122ac22025-08-20T02:16:05ZengWileyGeophysical Research Letters0094-82761944-80072025-03-01525n/an/a10.1029/2024GL113403Land Use Change Forcing Data Undermine the Modeling of China's Greening EffortsZiyu Wang0Weiqing Zhao1Sen Cao2Pengjun Zhao3Yuhang Luo4Dajing Li5Ziyun Sun6Zaichun Zhu7School of Urban Planning and Design Shenzhen Graduate School Peking University Shenzhen ChinaSchool of Urban Planning and Design Shenzhen Graduate School Peking University Shenzhen ChinaSchool of Urban Planning and Design Shenzhen Graduate School Peking University Shenzhen ChinaSchool of Urban Planning and Design Shenzhen Graduate School Peking University Shenzhen ChinaSchool of Urban Planning and Design Shenzhen Graduate School Peking University Shenzhen ChinaSchool of Urban Planning and Design Shenzhen Graduate School Peking University Shenzhen ChinaSchool of Urban Planning and Design Shenzhen Graduate School Peking University Shenzhen ChinaSchool of Urban Planning and Design Shenzhen Graduate School Peking University Shenzhen ChinaAbstract China has made extensive afforestation efforts over the past 40 years. However, ecosystem models simulate only modest vegetation enhancement, creating a significant disparity between documented reforestation efforts and model‐based simulations. This fundamental mismatch remains largely unexplored. Here, we conducted a comprehensive analysis using diverse observation data to identify the determinant within Dynamic Global Vegetation Models (DGVMs) that underestimates vegetation growth in China. By developing a high‐resolution forest cover change data set, we found that LUH2‐GCB, the common land use input for DGVMs, causes models to underestimate afforestation. With a neighborhood comparison analysis, we quantitively demonstrated the predominant role of underestimated afforestation in lowering leaf area index (LAI) trends. Overall, DGVMs underestimated China's afforestation area by an average of 26.88%, leading to a 29.46% underestimation in LAI increase. Our findings confirm a significant greening trend in China and highlight the need for improved land use data representation in DGVMs.https://doi.org/10.1029/2024GL113403ecosystem modelsforest cover changeLUH2‐GCBplant functional typesleaf area index |
| spellingShingle | Ziyu Wang Weiqing Zhao Sen Cao Pengjun Zhao Yuhang Luo Dajing Li Ziyun Sun Zaichun Zhu Land Use Change Forcing Data Undermine the Modeling of China's Greening Efforts Geophysical Research Letters ecosystem models forest cover change LUH2‐GCB plant functional types leaf area index |
| title | Land Use Change Forcing Data Undermine the Modeling of China's Greening Efforts |
| title_full | Land Use Change Forcing Data Undermine the Modeling of China's Greening Efforts |
| title_fullStr | Land Use Change Forcing Data Undermine the Modeling of China's Greening Efforts |
| title_full_unstemmed | Land Use Change Forcing Data Undermine the Modeling of China's Greening Efforts |
| title_short | Land Use Change Forcing Data Undermine the Modeling of China's Greening Efforts |
| title_sort | land use change forcing data undermine the modeling of china s greening efforts |
| topic | ecosystem models forest cover change LUH2‐GCB plant functional types leaf area index |
| url | https://doi.org/10.1029/2024GL113403 |
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