AUTHOR=Robles-Fernández Ángel L. , Lira-Noriega Andrés TITLE=Combining Phylogenetic and Occurrence Information for Risk Assessment of Pest and Pathogen Interactions with Host Plants JOURNAL=Frontiers in Applied Mathematics and Statistics VOLUME=3 YEAR=2017 URL=https://www.frontiersin.org/journals/applied-mathematics-and-statistics/articles/10.3389/fams.2017.00017 DOI=10.3389/fams.2017.00017 ISSN=2297-4687 ABSTRACT=

Phytosanitary agencies conduct plant biosecurity activities, including early detection of potential introduction pathways, to improve control and eradication of pest and pathogen incursions. For such actions, analytical tools based on solid scientific knowledge regarding plant-pest or pathogen relationships for pest risk assessment are needed. Recent evidence indicating that closely related species share a higher chance of becoming infected or attacked by pests has allowed the identification of taxa with different degrees of vulnerability. Here, we use information readily available online about pest-host interactions and their geographic distributions, in combination with host phylogenetic reconstructions, to estimate a pest-host interaction (in some cases infection) index in geographic space as a more comprehensive, spatially explicit tool for risk assessment. We demonstrate this protocol using phylogenetic relationships for 20 beetle species and 235 host plant genera: first, we estimate the probability of a host sharing pests, and second, we project the index in geographic space. Overall, the predictions allow identification of the pest-host interaction type (e.g., generalist or specialist), which is largely determined by both host range and phylogenetic constraints. Furthermore, the results can be valuable in terms of identifying hotspots where pests and vulnerable hosts interact. This knowledge is useful for anticipating biological invasions or spreading of disease. We suggest that our understanding of biotic interactions will improve after combining information from multiple dimensions of biodiversity at multiple scales (e.g., phylogenetic signal and host-vector-pathogen geographic distribution).