Beth Purse, Dan Chapman Phytothreats: WP3

Overview of the programme of work for WP3

Transcript

1. Beth Purse beth@ceh.ac.uk WP3 Team: Dan Chapman, Ana Perez-Sierra, Beatrice Henricot, Mariella Marzano, Michael Dunn Phytothreats: WP 3 overview
2. Talk Outline • WP3 Objectives and approach • Team members and responsibilities • Approach • WP3.1 Risk of introduction • WP3.2 Risk of establishment and spread • WP3.3 Scoping knowledge gaps • Potential policy impact • Milestones and plan for next 12 months
3. WP3 Team and roles Ana Perez-Sierra Beatrice Henricot PATHOGEN TRAITS, EPIDEMIOLOGY AND OCCURRENCE DATA Mariella Marzano Mike Dunn SCOPING KNOWLEDGE GAPS TOURISM, TRADE & BIOSECURITY Beth Purse Dan Chapman RISK MODELS OCCURRENCE DATA
4. WP3 objective –identify and rank global Phytophthora threats to the UK WP3.1 Risk of introduction WP3.3 Horizon-scanning for emerging pathogens: scoping of knowledge gaps WP3.2 Risk of establishment and spread Trait-based frameworks to inform risk register • Identify the most important trade and recreational pathways • Link introduction risk to ecological traits • Map global environmental niches of Phytophthora species • Link establishment in Europe to social factors and ecological traits • Map risk areas in the UK • identify research priorities for horizon scanning for emerging pathogens (supply chains, tourism pathways)
5. WP3.1 - Risk of introduction Aims: • Identify the most important trade and recreational pathways linking Phytophthora source regions to the UK • Model introduction risk statistically based on position in transport networks and intersection with sources of Phytophthora • Test links between introduction risk and pathogen traits
6. Existing modelling • 422 non-native EPPO-categorised plant pests (invertebrates, pathogens, plants) • Models for presence in EPPO countries (GLMM) Probability of presence of pest p in country j ~ network connectivity for p to j + pest characteristics + destination country characteristics + (1|destination country) + (1|species) • Compare different connectivity measures, multiple networks, assignment of specie to known pathways, etc.
7. Network connectivity indices Agricultural trade Bilateral network Species presence Source country characteristics Climatic similarity GDP per capita Sum columns  index of connectivity to all sources
8. Results • Best model uses climate- weighted connectivity through multiple pathways and assignment of species to known pathways • Host breadth increases pathogen invasiveness Relative invasion source risk
9. For Phytophthora • More refined analysis: • Better temporal resolution of arrivals and spread(?) • Air transport as well as trade • More traits in the analysis • Relevant socio-economic drivers (e.g. nursery density?)
10. WP3.2 - Risk of establishment and spread Aims: • Identify known Phytophthora species worldwide with greatest capacity for establishment and spread under UK conditions • Quantify global environmental niches of Phytophthora species • Map areas of the UK landscape most at risk of invasion • Link patterns of establishment/spread in Europe to pathogen traits
11. Existing approaches to mapping pathogen niches Pattern Process Statistical models Biological models Oospore Chlamydospore Matching disease patterns with patterns in environmental drivers Applicable, given occurrence data, in absence of detailed ecological knowledge Mathematical descriptions of life cycle processes Require detailed ecological knowledge Hourly rate of infection Temperature Pr Pk Data from P. Jennings APHA
12. Particular challenges of mapping pathogen niches Potential distribution of sudden oak death pathogen Phytophthora ramorum in Oregon Vaclavik & Meentemeyer 2012 •Occurrence data may be patchy, clustered and incomplete •Species not yet spread to every where that they can persist • May capture only a small proportion of potential environmental niche •Models developed early in invasion may underestimate environmental niche •Biology may be poorly known EARLY LATE
13. Mapping pathogen niches – statistical approaches, integrating some ecology •US distribution used to predict global distribution •Eco-climatic index defined by known occurrence, tweaked by known laboratory temperature and moisture responses •But which areas of the UK are more suitable than others? •Habitat suitability also defined by other factors e.g. disturbance, host availability Global climate suitability map for Phytophthora ramorum, Ireland et al. 2013 PLoS ONE
14. Mapping pathogen niches – biological models • Temperature and humidity requirements for infection process • Hourly temperature and relative humidity for each 4km grid cell (Met Office) • Number of days suitable for Pr or Pk infection Hourly rate of infection Temperature Pr Pk Infection data from P. Jennings APHA Model funding from Scottish Government and Forestry Commission Match between onward Pr spread in England and modelled suitability (2007-2010)
15. Mapping pathogen niches – biological models • Temperature and humidity requirements for infection process • Hourly temperature and relative humidity for each 4km grid cell • Number of days suitable for Pr or Pk infection Hourly rate of infection Temperature Pr Pk Infection data from P. Jennings APHA Model funding from Scottish Government and Forestry Commission 0 50 100 150 200 250 300 2006 2008 2010 2012 2014 No. suitable days Year Scotland England Wales N. Ireland Annual variation in number of days suitable for Pr infection
16. Phytothreats approach to mapping pathogen niches • Test out approaches on well-described Phytophthoras already found in the UK (yr 1-2) • Can the UK distribution be reproduced from the global occurrence? • Evidence of niche shifts? • Environmental drivers - literature review of drivers explaining patterns in Phytophthora, different scales (yr 1) • e.g. disturbance, climatic predictors, host and landscape predictors (fragmentation, host density) • Roll out best-performing methods across 40 focal species to predict global environmental niches (yr 3) • Relate global spread and niches to traits (yr 3)
17. Relating pathogen establishment in countries in Europe to social and ecological factors • Escape from nursery and horticulture sectors • biological and social factors associated with escape e.g. GDP, human population density, forestry production • Santini et al. 2012, invasive forest pathogens more likely to establish in countries with a wider range of environments, higher human impact and international trade volumes. Rainfall influenced the diffusion rates between countries.
18. Ecological traits affecting arrival and establishment • Substrate • Host range • Disease symptoms •Survival - oospore and chlamydospore stages •Aerial spread •Oospore wall index •Temperature optima/range •Homothallic/heterothallic Oospore Chlamydospore Caducous sporangia enables dispersal in running water / wind Species limited to one or two hosts spread less than species with wide host range e.g P. austrocedri versus P. kernoviae P. austrocedrae on juniper P. kernoviae on Rhododendron, beech, Vaccinium
19. Focal species for modelling • 10-15 species already present in the UK (validate approach) • 25-30 species outside Europe that pose threats • E.g. Species listed on the UK Plant Health Risk Register Species here already Species yet to arrive • P. alni P. acerina • P. austrocedri P. pinifolia • P. fragariae P. pluvialis • P. infestans P. polonica • P. kernoviae • P. lateralis • P. pseudosyringae • P. ramorum • P. rubi • P. siskiyouensis • Species selection criteria to be decided in July following trait database collation • Span wide range of ecological traits, exclude crop pathogens(?), define by data availability
20. Mapping pathogen distributions: source data Potential global data sources on interceptions, and occurrences National level • EPPO GD (155 spp) • CABI ISC (12 spp) • GBIF (165 spp) • DAISIE (36 spp) • Europhyt (no Phytophthora?) Site to county level data • PhytophthoraDB (isolates) • Forest Phytophthoras of the World • Literature (e.g. Jung et al 2015) • Unpublished survey data (FR, APHA, other countries) • Other workpackages of Phytothreats Distribution of P. ramorum isolates in Phytophthoradb
21. WP 3.3. Horizon scanning for emerging pathogens: scoping knowledge gaps Aim: Building our understanding of patterns of movement in source country and ways in which pathogens are transferred to UK • Prioritise most likely source countries • Literature review/Discussion with nursery partners/Contact with international colleagues/EPPO to identify and map state of knowledge of relevant supply chains at national and sub-national levels. Input into WP2 Consumer survey - internet purchases • Develop our understanding of tourism and recreational spread pathways and implications for potential disease spread. Initially contact with tourism agents, travel companies and international forest and recreational organisations in source countries to map patterns of international movement (e.g. who is coming to UK & when) for recreational purposes. Any data on reason for visits? Link this to flight paths? • If possible - source available data from border security on what people are bringing into the UK
22. WP3 potential policy impact • UK Plant Health Risk Register – can we tailor models to needs of register? • Publish ecological trait database (data paper and doi) • Make collated distribution data publicly accessible • UK/global pathogen habitat /climate suitability maps • UK Plant and Animal Health Internet of Things?
23. Milestones: Plan for next 12 months • Trade and environmental data extracted for country level analysis of introduction risk. Introduction models tested on EPPO plant pathogen data • Met 6th April, devised strategy for compiling traits database (July target for initial version) • Species selection and strategy for extracting occurrence data decided in July WP3 meeting WP3 Milestones • WP3 Compile European database of country level occurrence/arrival of Phytophthoras in nursery and wider environment and associated trade and environmental data (year 1) • WP3 Compile global database of fine scale occurrence data for ~40 target Phytophthora species and associated environmental data (year 1) • WP3 Compile traits database for Phytophthora species (including all species found in Europe plus selected others worldwide) (year 2) • WP3 Complete models relating to patterns of introduction and establishment in Europe to species traits, trade pathways and local environmental conditions and global niche models for ~ 40 target Phytophthora species worldwide (year 3) • WP3 Develop policy brief for UK risk register board and other stakeholders on improved risk ranking for Phytophthoras (year 3)