Structural diversity is a key driver of above-ground biomass in tropical forests

BackgroundA gamut of abiotic and biotic factors is related to the amount of above-ground biomass (AGB) produced in ecosystems. Some factors have direct and others indirect relationships with AGB. Detailed analyses in tropical forests are few but much needed for better understanding the potential impacts of global change drivers and for mitigating impacts.AimsHere, we examined the relationship between AGB and different predictor variables and quantitatively evaluated their relative importance in lowland to lower montane deciduous and lower montane - montane evergreen forest types. We hypothesised that the relationship between AGB and climate, topography, structural diversity, species diversity (alpha and beta) and phylogenetic diversity would differ between the two forest types.MethodsWe inventoried trees from 114 plots (each 0.1 ha) and used partial least square structural equation modelling to test the direct and indirect relationship between AGB and the predictor variables.ResultsWe found that structural diversity variables, stem density and tree girth, were significantly and positively related to AGB in both forest types, displaying a stronger relationship in montane evergreen forests (w = 0.65 for density and 0.89 for tree girth). In the deciduous forest, alpha and phylogenetic diversity were also important factors, whereas beta and phylogenetic diversity were important in the evergreen forest. The effects of topography and climate varied between forest types, with elevation and precipitation being related to AGB directly and indirectly through their relationship with structural diversity.ConclusionOur results suggest that structural diversity is a key driver of tropical forest biomass, both directly and indirectly. This fundamental understanding can aid in the predictive efforts of biodiversity conservation and forest management.

Automated summary

This study examines the relationship between above-ground biomass (AGB) and various predictor variables in different forest types, and evaluates their relative importance. Structural diversity is found to be a key driver of AGB in tropical forests.