Liang Yu;Zhou Li;Wei Liu;Huakun Zho

Northwest Institute of Plateau Biology, Chinese Academy of Sciences, Xining 810001 (China;Graduate University of the Chinese Academy of Sciences, Beijing 100049 (China); Northwest Institute of Plateau Biology, Chinese Academy of Sciences, Xining 810001 (China);Northwest Institute of Plateau Biology, Chinese Academy of Sciences, Xining 810001 (China)

livestock carrying capacity;grass yield;modis;aboveground;golog;dat

Remote sensing data from the Terra Moderate-Resolution Imaging Spectroradiometer (MODIS) and geospatial data were used to estimate grass yield and livestock carrying capacity in the Tibetan Autonomous Prefecture of Golog, Qinghai, China. The MODIS-derived normalized difference vegetation index (MODIS-NDVI) data were correlated with the aboveground green biomass (AGGB) data from the aboveground harvest method. Regional regression model between the MODIS-NDVI and the common logarithm (LOG10) of the AGGB was significant (r(2) = 0.51, P < 0.001), it was, therefore, used to calculate the maximum carrying capacity in sheep-unit year per hectare. The maximum livestock carrying capacity was then adjusted to the theoretical livestock carrying capacity by the reduction factors (slope, distance to water, and soil erosion). Results indicated that the grassland conditions became worse, with lower aboveground palatable grass yield, plant height, and cover compared with the results obtained in 1981. At the same time, although the actual livestock numbers decreased, they still exceeded the proper theoretical livestock carrying capacity, and overgrazing rates ranged from 27.27% in Darlag County to 293.99% in Baima County. Integrating remote sensing and geographical information system technologies, the spatial and temporal conditions of the alpine grassland, trend, and projected stocking rates could be forecasted for decision making.