Realistic trait distributions and variable assembly processes greatly influence the predicted BEF relationship in the Eurasian Steppe

Background/Question/Methods: Research across terrestrial ecosystems indicates that the functioning of ecosystems, both in terms of the fluxes of nutrients and energy, their standing stocks, as well as the services provided to humans, are reduced with lowered biodiversity. Though these general trends appear robust when examined across studies, the wide range of relationships between biodiversity and ecosystem function (BEF) found in individual studies highlights our lack of a mechanistic understanding of how biodiversity translates to function. Several factors, including the exact functional traits present with the community, the relative abundances of species, their order of addition or deletion, as well as trophic structure, among others, are expected to directly link diversity with function. Empirically examining the numerous combinations possible, however, may be unrealistic, with modeling employed to fill these gaps. Nevertheless, few modeling attempts have been made to explicitly link theory with experiments, with species-traits often distributed randomly within the community, and communities randomly assembled, though neither is likely to be true in real ecosystems. Here we take a first step towards bridging this gap, utilizing a well-studied model with a simplified structure, parameterized with field-based trait measurements known to be associated with key model parameters to explore some basic predictions. Specifically, we explore the effects of various trait-tradeoffs known to structure communities, variable species richnesses among functional groups, and several assembly processes, on the predicted BEF relationship in the Eurasian Steppe. These are then compared with initial findings from the field to validate model behavior.

Results/Conclusions: We find that variable trait structures, species numbers among functional groups, and assembly processes each affect the BEF relationship. In particular, lower costs associated with increasing one trait over another, or variable costs as suggested from global meta-analyses, lead to stronger BEF relationships owing to their greater probability for including species highly efficient at biomass accumulation. Loss of some functional groups (e.g. perennial bunchgrasses) leads to consistent declines in function while loss of others (e.g. perennial forbs) often had variable effects based on the functional groups that remained and their constituent richnesses. This general pattern of ecosystem responses to plant functional diversity loss seems corroborated by observations from our ongoing biodiversity removal field experiment, although some important specific differences exist. Our findings suggest that simple models like ours, parameterized with easily measured species trait values, can capture the essential features of complex BEF relationships, and may help generate scenarios to predict the effects of future biodiversity decline.