Grassland biomass spatiotemporal patterns and response to climate change in eastern Inner Mongolia based on XGBoost model estimates

Aboveground biomass (AGB) is a key index that reflects grassland health and is of great importance for grassland conservation and sustainable utilization. Many previous studies on grassland AGB were based on the analysis of the whole study period, can’t reflect the change of grassland in the short term, which was not conducive to the implementation and revision of policies. And it is still a challenge to accurately describe the response of grassland AGB to climate factors. In this study, we used four machine learning algorithms (kNN, k-nearest neighbor; RF, Random Forest; SVR, Support Vactor Regression; and XGBoost, eXtreme Gradient Boosting) to construct the estimation model of grassland AGB in eastern Inner Mongolia based on grassland AGB measurement data, MODIS(MOD13Q1) data and environmental data (climate and topography). The average distribution of grassland AGB from 2003 to 2021 was calculated based on the optimal grassland AGB estimation model. The changes of grassland AGB from 2003 to 2021 and in every five-year period during the study series were comprehensively analyzed by the Theil–Sen Median trend analysis and the Mann–Kendall test. The response of grassland AGB to climatic factors was investigated using sensitivity analysis. The results showed that (1) the XGBoost model constructed by NDVI, longitude, latitude, temperature, precipitation, elevation, slope, and aspect (NXYTPESA) is the optimal grassland AGB model (R2 = 0.87, RMSE = 14.27 g/m2). (2) The 20-year average grassland AGB in Eastern Inner Mongolia showed heterogeneous, with higher values in the northeast and lower values in the southwest. (3) The inter-annual variation fluctuated substantially, and the overall trend was increasing. Compared with other time periods, most grassland AGBs were in an increasing trend during 2008–2012 (79 %) and 2018–2021 (84 %). (4) The grassland AGB in the study area was regulated by temperature and precipitation, and the influence of precipitation was greater than that of temperature. This study provides a new method for estimating grassland AGB and its changes and a scientific basis for the sustainable development of grassland ecosystems in eastern Inner Mongolia.