A long-term high-resolution dataset of grasslands grazing intensity in China
Abstract Grazing is a significant anthropogenic disturbance to grasslands, impacting their function and composition, and affecting carbon budgets and greenhouse gas emissions. However, accurate evaluations of grazing impacts are limited by the absence of long-term high-resolution grazing intensity d...
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Nature Portfolio
2024-11-01
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| Series: | Scientific Data |
| Online Access: | https://doi.org/10.1038/s41597-024-04045-x |
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| author | Daju Wang Qiongyan Peng Xiangqian Li Wen Zhang Xiaosheng Xia Zhangcai Qin Peiyang Ren Shunlin Liang Wenping Yuan |
| author_facet | Daju Wang Qiongyan Peng Xiangqian Li Wen Zhang Xiaosheng Xia Zhangcai Qin Peiyang Ren Shunlin Liang Wenping Yuan |
| author_sort | Daju Wang |
| collection | DOAJ |
| description | Abstract Grazing is a significant anthropogenic disturbance to grasslands, impacting their function and composition, and affecting carbon budgets and greenhouse gas emissions. However, accurate evaluations of grazing impacts are limited by the absence of long-term high-resolution grazing intensity data (i.e., the number of livestock per unit area). This study utilized census livestock data and a satellite-based vegetation index to develop the first Long-term High-resolution Grazing Intensity (LHGI) dataset of grassland in seven pastoral provinces in western China from 1980 to 2022. The LHGI dataset effectively captured spatial variations in grazing intensity, with validation at 73 sites showing a correlation coefficient (R2) of 0.78. The county-level validation showed an averaged R2 values of 0.73 ± 0.03 from 1980 to 2022. This dataset serves as a vital resource for estimating grassland carbon cycling and livestock system CH4 emissions, as well as contributing to grassland management. |
| format | Article |
| id | doaj-art-ec0dc8c2b56c499c9d0382463da67277 |
| institution | Kabale University |
| issn | 2052-4463 |
| language | English |
| publishDate | 2024-11-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Scientific Data |
| spelling | doaj-art-ec0dc8c2b56c499c9d0382463da672772024-11-10T12:06:16ZengNature PortfolioScientific Data2052-44632024-11-0111111510.1038/s41597-024-04045-xA long-term high-resolution dataset of grasslands grazing intensity in ChinaDaju Wang0Qiongyan Peng1Xiangqian Li2Wen Zhang3Xiaosheng Xia4Zhangcai Qin5Peiyang Ren6Shunlin Liang7Wenping Yuan8School of Atmospheric Sciences, Guangdong Province Data Center of Terrestrial and Marine Ecosystems Carbon Cycle, Sun Yat-sen UniversitySchool of Atmospheric Sciences, Guangdong Province Data Center of Terrestrial and Marine Ecosystems Carbon Cycle, Sun Yat-sen UniversitySchool of Atmospheric Sciences, Guangdong Province Data Center of Terrestrial and Marine Ecosystems Carbon Cycle, Sun Yat-sen UniversityState Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry (LAPC), Institute of Atmospheric Physics, Chinese Academy of SciencesSchool of Atmospheric Sciences, Guangdong Province Data Center of Terrestrial and Marine Ecosystems Carbon Cycle, Sun Yat-sen UniversitySchool of Atmospheric Sciences, Guangdong Province Data Center of Terrestrial and Marine Ecosystems Carbon Cycle, Sun Yat-sen UniversitySchool of Atmospheric Sciences, Guangdong Province Data Center of Terrestrial and Marine Ecosystems Carbon Cycle, Sun Yat-sen UniversityJockeyClub STEM Laboratory of Quantitative Remote Sensing, Department of Geography, University of Hong KongInstitute of Carbon Neutrality, Sino-French Institute for Earth System Science, College of Urban and Environmental Sciences, Peking UniversityAbstract Grazing is a significant anthropogenic disturbance to grasslands, impacting their function and composition, and affecting carbon budgets and greenhouse gas emissions. However, accurate evaluations of grazing impacts are limited by the absence of long-term high-resolution grazing intensity data (i.e., the number of livestock per unit area). This study utilized census livestock data and a satellite-based vegetation index to develop the first Long-term High-resolution Grazing Intensity (LHGI) dataset of grassland in seven pastoral provinces in western China from 1980 to 2022. The LHGI dataset effectively captured spatial variations in grazing intensity, with validation at 73 sites showing a correlation coefficient (R2) of 0.78. The county-level validation showed an averaged R2 values of 0.73 ± 0.03 from 1980 to 2022. This dataset serves as a vital resource for estimating grassland carbon cycling and livestock system CH4 emissions, as well as contributing to grassland management.https://doi.org/10.1038/s41597-024-04045-x |
| spellingShingle | Daju Wang Qiongyan Peng Xiangqian Li Wen Zhang Xiaosheng Xia Zhangcai Qin Peiyang Ren Shunlin Liang Wenping Yuan A long-term high-resolution dataset of grasslands grazing intensity in China Scientific Data |
| title | A long-term high-resolution dataset of grasslands grazing intensity in China |
| title_full | A long-term high-resolution dataset of grasslands grazing intensity in China |
| title_fullStr | A long-term high-resolution dataset of grasslands grazing intensity in China |
| title_full_unstemmed | A long-term high-resolution dataset of grasslands grazing intensity in China |
| title_short | A long-term high-resolution dataset of grasslands grazing intensity in China |
| title_sort | long term high resolution dataset of grasslands grazing intensity in china |
| url | https://doi.org/10.1038/s41597-024-04045-x |
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