Species-level biomass and its change are important indicators in the measurement of the reliability of forest ecosystem structure and function. To understand the changes in species-level biomass and its linkage to climate and forest disturbances, maps of changes in species-level biomass in the Great Xing'an Mountains between 2000 and 2015 were generated by integrating Moderate Resolution Imaging Spectroradiometer (MODIS) images with forest inventory data using k-nearest neighbor distance (kNN) methods. The distribution information regarding fires, logging, and afforestation in the Great Xing'an Mountains between 2000 and 2015 were also extracted from MODIS production. The relationships between species-level biomass changes, climatic factors, and forest disturbances were explored using canonical correspondence analysis (CCA) and the random forests method. The results showed that the total aboveground biomass in the study area increased by 8.9% (0.41×10⁸ t) from 2000 to 2015. For the species-level biomass, white birch (Betula platyphylla Suk.) increased most significantly (0.40×10⁸ t), followed by pine (Pinus sylvestris var. mongolica Litv.), aspen (Populus davidiana Dode), and Mongolian oak (Quercus mongolica Fisch. ex Ledeb.). The biomass of larch (Larix gmelinii (Rupr.) Kuzen) declined the most, decreasing by 0.08×10⁸ t from 2000 to 2015. There were no obvious changes for the species-level biomass of willow (Chosenia arbutifolia (Pall.) A. Skv.) and spruce (Picea koraiensis Nakai) during these period. The areas of fire disturbance derived from MODIS products were consistent with the records in the yearbook for the Great Xing'an Mountains (R²=0.97). Fire disturbance, logging, and afforestation all significantly influenced the changes in the species-level biomass (P < 0.01). Among the three disturbance factors, fire disturbance exhibited the greatest explanatory ability for the variation in species-level biomass change based on the random forests method. However, climatic factors exhibited a relatively greater importance value than did forest disturbances. Annual temperature and precipitation explained the greatest variation in species-level biomass change among all the climatic factors and forest disturbances, and exhibited a strong positive correlation with broad-leaf species biomass and fire disturbance, but a negative correlation with total aboveground biomass (AGB), logging, and afforestation. A weak negative correlation between annual temperature and the biomass of white birch and larch was observed. Annual precipitation was positively correlated with the biomass of white birch and total AGB but negatively correlated with the biomass of larch and annual temperature. Our results indicated that climatic warming would increase the proportion of deciduous broad-leaved tree species and reduce forest ecosystem productivity in the Great Xing'an Mountains in northeast China.