"Scale-dependent effects of tree diversity on above- versus below-ground biomass partitioning" dataset

This dataset integrates field-measured and model-predicted data from 332,531 forest plots worldwide to facilitate the study of above- and below-ground biomass partitioning in relation to biodiversity and environmental factors.The core data were synthesized from two primary sources:<b>Root Mass Fraction (RMF):</b> Plot-level RMF values were derived from a global map of root-shoot ratio (RSR) generated by Ma et al. (2021) using random forest modeling at a 30 arcsec resolution. The original RMF calculation is based on 13,499 forest plot records.<b>Biodiversity and Productivity:</b> Tree species richness (S) and primary site productivity (P, measured as periodic annual increment in stem volume) were obtained from the Global Forest Biodiversity (GFB) initiative, which aggregates data from 777,126 permanent plots. URL - References http://science.sciencemag.org/content/354/6309/aaf8957.abstract?ijkey=RKRNpnVI10Em2&amp;keytype=ref&amp;siteid=sciTo create a unified dataset, RMF, S, and P values were extracted for coinciding locations. A spatial de-duplication process was applied using a 0.01-degree window to calculate mean values for each unique location, resulting in the final 332,531 plots.The dataset is enriched with key environmental variables to support ecological modeling:<b>Climate Data:</b> Six bioclimatic variables from WorldClim (v1.4), including mean annual temperature, temperature seasonality, mean annual precipitation, and precipitation seasonality.<b>Soil Data:</b> Eight soil properties from the Harmonized World Soil Database, including soil organic carbon, pH, texture (sand, silt), and bulk density.Each plot is classified by ecoregion (based on the WWF classification) and plot size, making it ideal for investigating scale-dependent and biome-specific ecological patterns.