Soil microbes are well known to affect plants by playing significant roles in nutrient and energy cycling. There is growing understanding of the full range of interactions and context-dependency of plant-soil microbe relationships. Modern genomics has further expanded our access to the microbial world, and the boom in microbial data requires strong theoretical frameworks for interpretation. Mathematical models that are tightly linked to data will allow us to scale up from individual plant-microbe interactions to plant growth, species coexistence and community-level trait and spatial distributions. I present two examples of mathematical models that incorporate plant-soil microbiome interactions and expand our understanding of plant communities and their response to management.

First, I present a new phenomenological model of plant-soil microbiome interaction in which the soil microbiome is represented along a one-dimensional axis (derived from multidimensional scaling or other dimensionality-reduction methods). I show how the outcomes of the dynamics of two plant populations shift dramatically when plants and soil microbiome interact reciprocally. Second, I describe a simple plant-nutrient model that exhibits hysteresis. Incorporating the soil microbiome, which mediates plant-nutrient interactions, leads to a new type of stable branch that I call “precariously stable”. Together, these models demonstrate the significance of plant-soil microbiome interactions in plant population and community dynamics.