Experiments in grassland communities have consistently indicated a strong positive relationship between plant diversity and ecosystem function. However, relatively few studies have been conducted regarding this relationship across tropical forest ecosystems. Using partial redundancy analysis (RDA) and variation partitioning, we examined how species richness, species dominance, community-weighted mean, and divergence or variation in trait values (functional divergence) explain variation in aboveground biomass in pre- and post-logging forest stands in a moist tropical forest in Ghana. As tropical forests are under a threat of biodiversity loss, it is timely to explore the role plant diversity indices play in ecosystem functioning, particularly in species-rich tropical African forests which are largely understudied.
Functional traits were better predictors of biomass storage compared with taxonomic traits. In particular, community-weighted mean of Hmax (maximum height) explained most of the variation in aboveground biomass: 29% and 20% in pre- and post-logging stands, respectively. Functional divergence was a better predictor of aboveground biomass in the post-logging stand suggesting an increase in variability of traits and a greater diversity in resource use among the dominant species as a result of the post-logging conditions. With respect to the influence of individual species on aboveground biomass, three species, Celtis zenkeri, Celtis mildbraedii, and Triplochiton scleroxylon, belonging to different ecological species guilds (non-pioneer light demander, shade bearer, pioneer, respectively), were significantly associated with aboveground biomass and varied greatly in their influence between stands (P <0.001; P <0.01; for C. zenkeri and C. mildbraedii in the pre-logging stand; P <0.001, T. scleroxylon in post-logging stand). Our results suggest that management of communities or forests for the maintenance of ecosystem functions should consider species dominance hierarchies in addition to other ecologically important factors.