Direct and indirect viral associations predict coexistence in wild plant virus communities

Viruses are a vastly underestimated component of biodiversity that occur as diverse communities across hierarchical scales from the landscape level to individual hosts. The integration of community ecology with disease biology is a powerful, novel approach that can yield unprecedented insights into the abiotic and biotic drivers of pathogen community assembly. Here, we sampled wild plant populations to characterize and analyze the diversity and co-occurrence structure of within-host virus communities and their predictors. Our results show that these virus communities are characterized by diverse, non-random coinfections. Using a novel graphical network modeling framework, we demonstrate how environmental heterogeneity influences the network of virus taxa and how the virus co-occurrence patterns can be attributed to non-random, direct statistical virus-virus associations. Moreover, we show that environmental heterogeneity changed virus association networks, especially through their indirect effects. Our results highlight a previously underestimated mechanism of how environmental variability can influence disease risks by changing associations between viruses that are conditional on their environment.