Global Grassland Biomass Allocation Dataset – Created by Wu et al., 2025

Global Grassland Biomass Allocation Dataset (AGB, BGB, RS)This dataset provides global gridded estimates of aboveground biomass (AGB), belowground biomass (BGB), and root-to-shoot ratio (RS) in grassland ecosystems at a spatial resolution of <b>0.05°</b>.Biomass data were compiled from <b>2,406 field observations</b> across <b>545 sites worldwide</b>, collected from open-access repositories (e.g., ORNL DAAC) and peer-reviewed literature (1980–2024). Climatic, edaphic, topographic, and vegetation trait variables were extracted from widely used global datasets, including <b>WorldClim, HWSD, MODIS/GLASS, and global leaf trait databases</b>, yielding a total of 36 explanatory variables.We applied an <b>Extreme Gradient Boosting (XGBoost)</b> machine learning framework to integrate these multi-source drivers and predict global grassland biomass allocation. Model training and validation employed ten-fold cross-validation and multiple accuracy metrics (MSE, RMSE, MAE, R²), ensuring robust predictive performance.The final product includes:Global gridded maps of <b>AGB, BGB, and RS</b> at 0.05° resolutionSpatially explicit patterns of biomass allocation across diverse grassland biomesA benchmark dataset for <b>ecosystem modeling, carbon cycling studies, biodiversity conservation, and climate change assessments</b><b>Coverage:</b> Global grasslands<br><b>Period:</b> Contemporary baseline (1980–2024 integrated)<br><b>Format:</b> NetCDF (0.05° resolution grids)<br><b>Applications:</b> Carbon cycle modeling, Earth system model evaluation, grassland management, and climate change mitigation research