Phytophthora ramorum, the causal agent of sudden oak death and ramorum blight, is known to exist as three distinct clonal lineages which can only be distinguished by performing molecular marker-based analyses. However, in the recent literature there exists no consensus on naming of these lineages. Here we propose a system for naming clonal lineages of P. ramorum based on a consensus established by the P. ramorum research community. Clonal lineages are named with a two letter identifier for the continent on which they were first found (e.g., NA = North America; EU = Europe) followed by a number indicating order of appearance. Clonal lineages known to date are designated NA1 (mating type: A2; distribution: North America; environment: forest and nurseries), NA2 (A2; North America; nurseries), and EU1 (predominantly A1, rarely A2; Europe and North America; nurseries and gardens). It is expected that novel lineages or new variants within the existing three clonal lineages could in time emerge.
Chestnut blight, caused by Cryphonectria parasitica, was identified in Devon, UK, in December 2016. Intensive surveys detected the disease at further sites in Devon (seven), Berkshire (one), Dorset (one), Derbyshire (four) and a cluster of eight sites in southeast London. Over 570 survey samples were tested, and 227 were positive for C. parasitica by isolation and real-time PCR. A total of 227 isolates were tested for mating type, and 197 screened for vegetative compatibility group (VCG) and compared with VCGs known from mainland Europe. The same isolates were also screened for the presence of Cryphonectria hypovirus 1 (CHV-1). Eleven VCGs were identified within the UK population. Five corresponded to already known European VCGs but six were unique. The European VCGs mainly came from the Devon, Dorset, Berkshire and Derbyshire disease outbreaks, whilst unique VCGs were almost exclusively from the southeast London cluster. Both mating types were detected, but only one mating type was present at each site, with the exception of a single Devon site. Perithecia of C. parasitica were never observed at any site. CHV-1 was found in seven isolates from three different locations and was always subtype-I, which has limited hypovirulence. Therefore, although CHV-1 is associated with C. parasitica at some outbreaks, it probably has limited impact on virulence. The diversity of VCGs and their distribution at outbreak sites, together with findings of CHV-1, suggests C. parasitica has been introduced to the UK multiple times over at least two decades through international plant trade.
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.
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