Uncovering the drivers of host-associated microbiota with joint species distribution modeling

In addition to the processes structuring free-living communities, host-associated microbiota are directly or indirectly shaped by the host. Therefore, microbiota data have a hierarchical structure where samples are nested under one or several variables representing host-specific factors, often spanning multiple levels of biological organization. Current statistical methods do not accommodate this hierarchical data structure, and therefore cannot explicitly account for the effect of the host in structuring the microbiota. We introduce a novel extension of joint species distribution models (JSDMs) which can straightforwardly accommodate and discern between effects such as host phylogeny and traits, recorded covariates like diet and collection sites, among other ecological processes. Our proposed methodology includes powerful yet familiar outputs seen in community ecology overall, including: (i) model-based ordination to visualize and quantify the main patterns in the data; (ii) variance partitioning to asses how influential the included host-specific factors are in structuring the microbiota; and (iii) co-occurrence networks to visualize microbe-to-microbe associations.