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Structural diversity and tree density drives variation in the biodiversity‐ecosystem function relationship of woodlands and savannas

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Positive biodiversity‐ecosystem function relationships (BEFRs) have been widely documented, but it is unclear if BEFRs should be expected in disturbance‐driven systems. Disturbance may limit competition and niche differentiation, which are frequently posited to underlie BEFRs. We provide the first exploration of the relationship between tree species diversity and biomass, one measure of ecosystem function, across southern African woodlands and savannas, an ecological system rife with disturbance from fire, herbivores and humans. We used >1000 vegetation plots distributed across 10 southern African countries, and structural equation modelling, to determine the relationship between tree species diversity and aboveground woody biomass, accounting for interacting effects of resource availability, disturbance by fire, tree stem density and vegetation type. We found positive effects of tree species diversity on aboveground biomass, operating via increased structural diversity. The observed BEFR was highly dependent on organismal density, with a minimum threshold of c. 180 mature stems ha‐1. We found that water availability mainly affects biomass indirectly, via increasing species diversity. The study underlines the close association between tree diversity, ecosystem structure, environment and function in highly disturbed savannas and woodlands. We suggest that tree diversity is an under‐appreciated determinant of wooded ecosystem structure and function.
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... the relationships of plant productivity with species richness [4] and climate [5], the effects of crown attributes and stand structure on tree productivity [6], and the effects of management policies on plant productivity [7]. Most of these studies have used integrative modeling approaches to explore the relationships among variables [4,8], but few have evaluated correlations using multisourced factors (e.g., environment, plant attributes, and management) at the individual level. In addition, the difficulty of interpreting the significance of the outputs of these modeling analyses often impedes the ability to extract practical insights that could be applied to improve productivity. ...
... We used IBM SPSS AMOS 24.0 to build the integrative model, a graphic-based software to visualize correlations and regression weights among variables [32]. The structural equation modeling method applied in the software has been widely used in recent ecological modeling studies [4,8]. We built the environment suitability, tree growth, and management models and evaluated their relationships with the productivity model. ...
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