Postdoctoral Fellow University of Missouri, CA, United States
Plants are entangled in a wide variety of interactions with soil microorganisms, which can give rise to complex non-linear feedbacks that have important implications for a variety of processes including invasion, succession, and species coexistence. Much of our understanding of these processes comes from experimental work on grassland species that are relatively easy to manipulate, posing a considerable challenge towards a more general understanding of how soil microbes shape plant communities in nature. However, recent insights into belowground strategies of plants present an opportunity for developing a general and predictive framework for plant-soil microbe interactions on the basis of root functional traits, which are increasingly becoming available for a wide range of plant species. Here I will present a trait-based framework for microbial effects on plant species interactions, which generates predictions of coexistence outcomes among plants on the basis of their belowground strategies. In this framework, microbial effects on conspecific and heterospecific plant hosts arise as a function of host traits along two axes: one reflecting plants' strategies along a mycorrhizal collaboration gradient, and the other reflecting plants' investment in defense against soil pathogens.
Model analysis reveals that when there is more host-specificity in plant-pathogen than in plant-mutualist interactions, plant species’ trait along the mycorrhizal collaboration gradient, as well as inter-specific trait differences on this axis, are stronger drivers of plant fitness differences than stabilization. Conversely, model analyses predict that pathogen defense traits are stronger drivers of stabilization than fitness differences. These predictions are largely borne out by the results of a meta-analyses on the strength of stabilization and fitness differences with four traits that determine species’ positions along the mycorrhizal collaboration gradient and root economics spectrum as predictors (root diameter, root tissue density, specific root length, and root N concentration; n = 141 species pairs with complete trait matrix, n = 198 pairs with imputed traits). In particular, the meta-analysis indicates that mycorrhizal collaboration traits are significant predictors of fitness differences (p < .01) but not of stabilization. Using model selection (AIC scores), we also find that accounting for multiple belowground trait dimensions improves predictions of plant coexistence outcomes. This work highlights the value of integrating theory and data for generating broadly applicable predictions of microbial effects on plant growth.