Positive biodiversity-productivity relationships are a predominant pattern in global forests that are based on both observational and experimental studies. Growing evidence has revealed that ecosystem productivity depends more on the functional characteristics of tree species than on their number. However, just how the extent of tree diversity effects on ecosystem productivity is influenced by functional trait variability and composition has been rarely tested both across and at given species richness levels. Here, we conducted a global meta-analysis based on 210 paired observations of tree mixtures and corresponding monocultures from 59 tree diversity experiment studies to examine how functional dispersion and community-weighted mean determine the various outcomes of tree mixture effects on productivity, for each of across and within species richness levels.
Results/Conclusions
We found that the positive effects of tree mixtures on productivity were strengthened by the increasing multidimensional functional dispersion both across, and within, two- and four-species mixtures. Moreover, the community-weighted mean of leaf nitrogen content of species mixtures enhanced the positive effects of mixtures on forest productivity overall, and within the two- and four-species mixtures. Our results revealed that the effects of tree mixtures on productivity increased with the functional dissimilarity of the leaf and wood economics traits, and the community-weighted mean of leaf nitrogen content both across and at given species richness levels. Our analysis provides mechanistic insights into the potent roles of functional trait attributes in determining the magnitude (and even directionality) of the biodiversity-ecosystem functioning relationship in forest ecosystems.