Evolutionary history shapes grassland productivity through opposing effects on complementarity and selection.

Phylogenetic diversity (PD), the evolutionary history of the organisms comprising a community, is increasingly recognized as an important driver of ecosystem function. However, biodiversity-ecosystem function experiments have rarely included PD as an a priori treatment. Thus, PD's effects in existing experiments are often confounded by covarying differences in species richness and functional trait diversity (FD). Here we report an experimental demonstration of strong PD effects on grassland primary productivity that are independent of FD, which was separately manipulated, and species richness, which was planted uniformly high to mimic diverse natural grasslands. Partitioning diversity effects demonstrated that higher PD increased complementarity (niche partitioning and/or facilitation) but lowered selection effects (probability of sampling highly productive species). Specifically, for every 5% increase in PD, complementarity increased by 26% on average (±8% SE), while selection effects decreased more modestly (8 ± 16%). PD also shaped productivity through clade-level effects on functional traits, that is, trait values associated with particular plant families. This clade effect was most pronounced in the Asteraceae (sunflower family), which, in tallgrass prairies, generally comprises tall, high-biomass species with low phylogenetic distinctiveness. FD also reduced selection effects but did not alter complementarity. Our results show that PD, independent of richness and FD, mediates ecosystem function through contrasting effects on complementarity and selection. This adds to growing evidence that consideration of phylogenetic dimensions of biodiversity can advance ecological understanding and inform conservation and restoration.

Application of remote sensing technology to estimate productivity and assess phylogenetic heritability.

PREMISE: Measuring plant productivity is critical to understanding complex community interactions. Many traditional methods for estimating productivity, such as direct measurements of biomass and cover, are resource intensive, and remote sensing techniques are emerging as viable alternatives. METHODS: We explore drone-based remote sensing tools to estimate productivity in a tallgrass prairie restoration experiment and evaluate their ability to predict direct measures of productivity. We apply these various productivity measures to trace the evolution of plant productivity and the traits underlying it. RESULTS: The correlation between remote sensing data and direct measurements of productivity varies depending on vegetation diversity, but the volume of vegetation estimated from drone-based photogrammetry is among the best predictors of biomass and cover regardless of community composition. The commonly used normalized difference vegetation index (NDVI) is a less accurate predictor of biomass and cover than other equally accessible vegetation indices. We found that the traits most strongly correlated with productivity have lower phylogenetic signal, reflecting the fact that high productivity is convergent across the phylogeny of prairie species. This history of trait convergence connects phylogenetic diversity to plant community assembly and succession. DISCUSSION: Our study demonstrates (1) the importance of considering phylogenetic diversity when setting management goals in a threatened North American grassland ecosystem and (2) the utility of remote sensing as a complement to ground measurements of grassland productivity for both applied and fundamental questions.