Data from: Developing allometric models to predict the individual aboveground biomass of shrubs worldwide

Aim Existing global models to predict standing woody biomass are based on trees characterized by a single principal stem, well-developed in height. However, their use in open woodlands and shrublands, characterized by multistemmed species with substantial crown development, generates a high level of uncertainty in biomass estimates. This limitation led us to i) develop global predictive models of shrub individual aboveground biomass based on simple allometric variables; ii) to compare the fit of these models with existing global biomass models; and iii) to assess whether models fit change when bioclimatic variables are considered. Location Global. Time period Present. Major taxa studied 118 species. Methods We compile a database of 3243 individuals across 49 sites distributed worldwide. Including basal diameter, height and crown diameter as predictor variables, we built potential models and compared their fit using generalized least squares. We used mixed effects models to determine if bioclimatic variables improved the accuracy of biomass models. Results Although the most important variable in terms of predictive capacity was stem basal diameter, crown diameter significantly improved the models fit, followed by height. Four models were finally chosen, with the best model combining all these variables in the same equation (R2 = 0.930, RMSE = 0.476). Selected models performed as well as established global biomass models. Including the individual bioform significantly improved the models fit. Main conclusions Basal diameter, crown diameter and height measures could be combined to provide robust AGB estimates of individual shrub species. Our study supplements well-established models developed for trees, allowing more accurate biomass estimation of multistemmed woody individuals. We further provide tools for a methodological standardization of individual biomass quantification in these species. We expect these results contribute to improve the quality of biomass estimates across ecosystems, but also to generate methodological consensus on field biomass assessments in shrubs