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

Abstract

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 above-ground 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 above-ground 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.

Structural and taxonomic diversity predict above‐ground biomass better than functional measures of maximum height in mixed‐species forests

“…Which ones of taxonomic diversity (species richness), structural diversity and functional metrics of Hmax are the main drivers of AGB? In line with previous studies (Luo et al, 2019;Aponte et al, 2020;Godlee et al, 2021), we predicted that CWMHmax and structural diversity attributes would have stronger effects on AGB than species richness and functional diversity (range and divergence) of Hmax.…”

“…We asked the following research questions: Which ones of taxonomic diversity (species richness), structural diversity and functional metrics of Hmax are the main drivers of AGB? In line with previous studies (Luo et al, 2019; Aponte et al, 2020; Godlee et al, 2021), we predicted that CWMHmax and structural diversity attributes would have stronger effects on AGB than species richness and functional diversity (range and divergence) of Hmax. How do structural diversity attributes and functional metrics of Hmax mediate the effects of species richness and environmental factors on AGB? Because we expected that structural diversity would better reflect local environmental influence than functional trait‐based metrics, we hypothesized that structural diversity would mediate the effects of species richness and environmental conditions on AGB better than functional metrics of Hmax. …”

Scale‐dependent diversity–biomass relationships can be driven by tree mycorrhizal association and soil fertility

“…Overall, the SEM results suggested that at small spatial scales (0.01 and 0.04 ha), the number of trees should be more important than mycorrhizal dominance in driving both tree diversity and AGB (Figure 3) and, hence, driving the positive DBR (Chisholm et al, 2013). This is partly because each individual positively contributes to total AGB, and abundance may promote diversity via a statistical or sampling effect at the scales where a tree community is far from being saturated by species (Appendix S1: Figure S9a; Fung et al, 2020; Godlee et al, 2021). Actually, many previously described mechanisms (e.g., complementarity and selection effect) that can drive positive BEF relationships mainly work at small spatial scales (Luo et al, 2019).…”

Evaluating the productivity of ancient Pu’er tea trees (Camellia sinensis var. assamica): a multivariate modeling approach

“…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.…”

“…Many studies have characterized 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 multi-sourced 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.…”