Modeling plant-microbe interactions with species distribution models

Plants interact with diverse microorganisms that play a crucial role in plant growth and development. The diversity and distribution of plant microbiota are altered by anthropogenic environmental change, leading to subsequent impacts on ecosystems. Modeling the distribution of plant-associated microbes is critical for predicting and managing future changes in microbial function, but there remain challenges and open questions when developing these models. We present a conceptual framework for process-oriented predictive modeling of the distribution of plant-associated microbiota. We first describe different approaches to incorporating host plants into modeling microbial distributions, namely by including them as static variables, nesting them within microbial distribution models or incorporating them simultaneously via joint species distribution models. Additionally, we discuss issues associated with collecting and analyzing sequencing-based microbial data, emphasizing the importance of data normalization and careful interpretation of species distribution models. We further discuss how to incorporate evolutionary history into microbial distribution modeling. Finally, we present a case study demonstrating how incorporating host information can improve the prediction of microbial distributions. This study provides insights for predicting future distributions of plant-associated microbes under climate change and plant species redistribution, which can be generalized to other host-associated microbial systems.