Forest structure and species diversity as predictors of aboveground biomass in a temperate forest of northern Mexico

Background: Understanding the biotic factors that drive aboveground biomass, including species and structural diversity, is essential for improving forest productivity and informing management under climate change. Hypotheses: We evaluated whether species diversity and structural diversity positively influence aboveground biomass in a temperate forest of northwestern Mexico, hypothesizing that structural diversity would exert a stronger and more consistent effect. Data description / Mathematical model: Aboveground biomass was estimated using species- and genus-specific allometric equations. Species diversity indices (richness, Shannon, and evenness) and structural metrics (tree density, number of diameter and height classes, and tree-size diversity indices) were calculated. Partial correlations guided variable selection, followed by linear regression relating diversity metrics to plot-level aboveground biomass. Study site and dates: The study was conducted in the El Brillante ejido, Sierra Madre Occidental, Durango, Mexico (~2,500 m elevation), using data collected in 2023 from 40 randomly distributed plots. Methods: Pearson and partial correlations evaluated bivariate and independent relationships between predictors and aboveground biomass. The final model included tree density, number of diameter classes, and the Shannon index of height classes; assumptions were verified using residual diagnostics and variance inflation factor. Results: Mean aboveground biomass was 82 Mg ha⁻¹. Species richness showed weak and non-significant relationships, whereas structural variables explained 82% of biomass variation. Conclusions: Structural diversity is a strong predictor of aboveground biomass, while species richness plays a limited role.