Evolutionary trait‐based approaches for predicting future global impacts of plant pathogens in the genus Phytophthora. Issue 4 (23rd December 2020) - Barwell, Louise J.
Abstract: Plant pathogens are introduced to new geographical regions ever more frequently as global connectivity increases. Predicting the threat they pose to plant health can be difficult without in‐depth knowledge of behaviour, distribution and spread. Here, we evaluate the potential for using biological traits and phylogeny to predict global threats from emerging pathogens. We use a species‐level trait database and phylogeny for 179 Phytophthora species: oomycete pathogens impacting natural, agricultural, horticultural and forestry settings. We compile host and distribution reports for Phytophthora species across 178 countries and evaluate the power of traits, phylogeny and time since description (reflecting species‐level knowledge) to explain and predict their international transport, maximum latitude and host breadth using Bayesian phylogenetic generalised linear mixed models. In the best‐performing models, traits, phylogeny and time since description together explained up to 90%, 97% and 87% of variance in number of countries reached, latitudinal limits and host range, respectively. Traits and phylogeny together explained up to 26%, 41% and 34% of variance in the number of countries reached, maximum latitude and host plant families affected, respectively, but time since description had the strongest effect. Root‐attacking species were reported in more countries, and on more host plant families than foliar‐attacking species. Host generalist pathogens had thicker‐walled resting structures (stress‐tolerant oospores) and faster growth rates at their optima. Cold‐tolerant species are reported in more countries and at higher latitudes, though more accurate interspecific empirical data are needed to confirm this finding. Policy implications . We evaluate the potential of an evolutionary trait‐based framework to support horizon‐scanning approaches for identifying pathogens with greater potential for global‐scale impacts. Potential future threats from Phytophthora include Phytophthora x heterohybrida, P. lactucae, P. glovera, P. x incrassata, P. amnicola and P. aquimorbida, which are recently described, possibly under‐reported species, with similar traits and/or phylogenetic proximity to other high‐impact species. Priority traits to measure for emerging species may be thermal minima, oospore wall index and growth rate at optimum temperature. Trait‐based horizon‐scanning approaches would benefit from the development of international and cross‐sectoral collaborations to deliver centralised databases incorporating pathogen distributions, traits and phylogeny. Abstract : We evaluate the potential of an evolutionary trait‐based framework to support horizon‐scanning approaches for identifying pathogens with greater potential for global‐scale impacts. Potential future threats from Phytophthora include Phytophthora x heterohybrida, P. lactucae, P. glovera, P. x incrassata, P. amnicola and P. aquimorbida, which are recently described, possibly under‐reported species, with similar traits and/or phylogenetic proximity to other high‐impact species. Priority traits to measure for emerging species may be thermal minima, oospore wall index and growth rate at optimum temperature. Trait‐based horizon‐scanning approaches would benefit from the development of international and cross‐sectoral collaborations to deliver centralised databases incorporating pathogen distributions, traits and phylogeny.