Publication
Direct and indirect viral associations predict coexistence in wild plant virus communities
Publisher:
Research Square Platform LLC
Date:
29-07-2021
DOI:
10.21203/RS.3.RS-741379/V1
Abstract: Integration of community ecology with disease biology is viewed as a promising avenue for uncovering determinants of pathogen ersity, and for predicting disease risks. Plant-infecting viruses represent a vastly underestimated component of bio ersity with potentially important ecological and evolutionary roles. We performed hierarchal spatial analysis of wild plant populations to characterise the ersity and coexistence structure of within-host virus communities, and their predictors. Our results show that these virus communities are characterised by single infections of few, dominating virus taxa as well as erse, non-random coinfections. Using a novel graphical modelling framework we demonstrate that after accounting for environmental heterogeneity at the level of both in idual host plants and populations, most virus co-occurrence patterns can be attributed to virus-virus associations. Moreover, we show that conditioning variables changed virus association networks especially through their indirect effects. This highlights a previously underestimated mechanism of how human-driven environmental change can influence disease risks.