School of Atmospheric Sciences, Guangdong Province Data Center of Terrestrial and Marine Ecosystems Carbon Cycle, Sun Yat-sen University, Zhuhai, Guangdong, 510245, China.
International Research Center of Big Data for Sustainable Development Goals, Beijing, 100094, China.
Sci Data. 2024 Nov 5;11(1):1194. doi: 10.1038/s41597-024-04045-x.
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 (R) of 0.78. The county-level validation showed an averaged R 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 CH emissions, as well as contributing to grassland management.
放牧是草原的一种重要人为干扰，影响着草原的功能和组成，从而影响碳预算和温室气体排放。然而，由于缺乏长期的高分辨率放牧强度数据（即单位面积的牲畜数量），对放牧影响的准确评估受到限制。本研究利用普查牲畜数据和基于卫星的植被指数，开发了中国西部七个牧区 1980 年至 2022 年的首个长期高分辨率放牧强度（LHGI）数据集。该 LHGI 数据集有效地捕捉了放牧强度的空间变化，在 73 个地点进行的验证显示，相关系数（R）为 0.78。县级验证显示，1980 年至 2022 年的平均 R 值为 0.73±0.03。该数据集是估算草地碳循环和牲畜系统 CH 排放的重要资源，同时也为草地管理做出了贡献。
