Beth Purse, Dan Chapman and Louise Barwell (CEH)

1. Beth Purse beth@ceh.ac.uk
WP3 Team: Dan Chapman, Louise Barwell, Ana Perez‐Sierra,
Beatrice Henricot, Mariella Marzano, Michael Dunn,
David Cooke, Sarah Green
Phytothreats:
WP 3 overview

2. WP3 objectives –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)

3. WP3 Team and roles
Beatrice Henricot
PATHOGEN TRAITS,
EPIDEMIOLOGY AND
OCCURRENCE DATA
Mariella Marzano
Mike Dunn
SCOPING
KNOWLEDGE GAPS
TOURISM, TRADE &
BIOSECURITY
Beth Purse
Dan Chapman Louise Barwell
RISK MODELLING
OCCURRENCE DATA
ENVIRONMENTAL DATA
Ana Perez‐Sierra
Anna Harris, Sarah Green
David Cooke (JHI)

4. Talk Outline: Progress, future plans, impact
• WP3.1 Risk of introduction (Dan, Louise)
• Novel methods for linking introduction to trade networks
• Country‐level occurrence and new trade data, potential links between
Phytophthora traits and introduction
• WP3.2 Risk of establishment and spread (Louise)
• Site‐level Phytophthora occurrence data
• Target Phytophthora species for niche analyses
• Environmental drivers of Phytophthora occurrence?
• Global Phytophthora trait database
• Analysis of links between global impact of Phytophthoras and traits
• Phytophthoras threatening key UK forestry species
• WP3.3 Scoping knowledge gaps in pathways (Mike, Beth, Mariella)
• Assessing risk of introduction from tourists visiting gardens in the UK
• Ensuring policy impact of WP3: co-development of tools (Beth)
• Milestones and plan for next 12 months (Beth)

5. WP3.1
Risk of introduction
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)

6. WP3.1 - Risk of introduction
Aims:
• Identify the most important trade and recreational pathways
linking Phytophthora source regions to the UK
• Model introduction risk based on transport networks, source
and destination characteristics and traits
• Test links between introduction risk and traits
Agricultural trade
flows into Europe

7. Global country-level database of occurrence/arrival of
Phytophthoras
• 5838 country-level records
• 1208 Species x country combinations
• Year of arrival (first record)
• Invasion status
WP3.1 - Risk of introduction

8. WP3.1 – National occurrence database
recording effort?

9. Focal commodities
• Horticultural
• Agricultural
• Forestry
WP3.1 - Risk of introduction
Horticultural trade volumes ($bn) in 2010

10. Trade networks and plant pest invasions
422 non-native plant pests
(invertebrates, pathogens, plants)
invading Europe + Mediterranean
Global trade network connectivity:
• Which commodity networks?
• Species presence in import sources
• Other characteristics of import
sources, e.g. climate similarity,
economic status
Chapman, Purse et al (in press) Global trade networks determine the
distribution of invasive non-native species. GEB

11. Best-fitting model for invasion
Connectivity through
multiple trade pathways +
climate matching
Relative invasion source risk

12. Plan for WP3.1
Collate trade-networks data
Adapt methodology to incorporate traits, environmental
characteristics and trade connectivity
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)

13. Plan for WP3.1
Collate trade-networks data
Adapt methodology to incorporate traits, environmental
characteristics and trade connectivity
Estimate arrival risk to the UK (different species and trade
scenarios)
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)

14. WP3.2
Risk of establishment and
spread
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)

15. Niche models: potential global impact, establishment and spread in UK
Burgess, T.I., Scott, J.K., McDougall, K.L., Stukely, M.J.C., Crane, C., Dunstan, W.A., Brigg, F., Andjic, V., White, D.,
Rudman, T., Arentz, F., Ota, N. & Hardy, G.E.S.J. (2016) Current and projected global distribution of Phytophthora
cinnamomi , one of the world’s worst plant pathogens. Global Change Biology
• Matching past
patterns in
occurrence with
environmental
data
• E.g. over 15000
presences from
11 countries
• 5 CLIMEX
meteorological
variables

16. • 8067 records (excluding UK data)
• 81 species
• 38 countries
• Recording effort?
Site-level database

17. Decimal lat long Species Detection probabilitySpatial precision
• quantify uncertainty
• geo‐reference localities
• translate coordinates
Locations
• synonyms
• species complexes
Species IDs
Molecular ID method
• sensitivity
• Specificity
• changes over
time
• quantify sampling
intensity
Sampling protocol
Site‐level distribution database: data cleaning
Recording
effort
!
Taxonomic
uncertainty
!
Duplication
!
Positional
uncertainty
!

18. Site-level database
Recording over time – how does ID methodology
affect our species detectability?
What are the key species identification methods that
have been used? How should we categorise these?
Relative reliability/specificity of these methods?
Do they pick up individual species or whole
communities?
When / how widely has each method been used?

19. Culture collections Citizen Science Projects
Governmental bodies
Global distribution databases
Global Phytophthora distribution: data sources
Published records
Diagnostic laboratories Sequence data repositoriesConsultants
Researchers
Agricultural
• 67 records
• 9 species
Forest / forestry
• 953 records
• 58 species
Nursery / ornamental
• 407 records
• 24 species

20. Site-level database
# records by species
Why are we not picking up many records in the
agricultural sector?
Different surveillance processes to forest sector?
Key sources of data to fill gaps?

21. Species selection
Criteria 1: Known / potential impacts on UK forestry species
Exclude:
• species known
only from
water/soil
• species with only
non-woody hosts
• Non-relevant
woody hosts: e.g.
Eucalyptus spp.
Crossover species
Risk maps
(Absent from UK)
Model validation
(Present in UK)
N = 24N = 30

22. Species selection
Criteria 2: spanning a broad range of traits

23. Species selection – UK species
Criteria 3: fine-grain data-availability

24. Criteria 1: Known / potential impacts on UK forestry species
Criteria 3: fine-grain data-availability
Criteria 4: include WP4 species
- P. foliorum
- P. obscura
- P. europaea
Criteria 5: taxonomic uncertainty?
Species selection – UK species
Criteria 2: spanning a broad range of traits

25. Global Phytophthora distribution
Data awaited
• Canada
• US data
• Southern
hemisphere
• Europe
Key contact or
sources of data
to fill
geographical
gaps?

26. WP3.1 & WP3.2
A global Phytophthora trait
database
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)

27. • 177 species
• 15 traits
• completed December 2016
• WoS / Google Scholar alerts
Phytophthora trait database

28. • long-term persistence in soil, leaf-
litter and plant tissue
Ecological traits: presence of survival structures
Oospore
Chlamydospore

29. • “Deciduous” sporangia facilitate aerial and water dispersal
Ecological traits: dispersal structures

30. • Heterothallic (two compatible mating types required)
• Homothallic (a single mating type)
Ecological traits: mating system

31. Ecological traits
• Temperate climate-matching
(growth optima 15-20°C?)

32. P. austrocedri on juniper
• Species limited to
one or two hosts
spread less than
species with wide
host ranges
• This doesn’t seem
to hold for P.
austrocedri versus
P. kernoviae
Ecological traits affecting arrival and establishment
P. kernoviae on Rhododendron, beech, Vaccinium

33. New fields
• Global impact metrics
• Genome size and contiguous counts (n = 22)
• Coded information for analyses
Phytophthora trait database

34. • The future of the database
• A parallel trait database in NZ / Australia
Phytophthora trait database
Peter Scott Treena Burgess Giles Hardy Nari Williams

35. Trait-based analysis of Phytophthora impacts
Hypotheses
• Traits associated with
- survival
- persistence
- reproduction
- spread
• 77 species

36. Trait‐based analysis of Phytophthora impacts
**
***
Dimension 1
Dimension 2

37. Phytophthoras on UK forestry hosts
• > 60 UK forestry species
• Widely grown now (or in the future)

38. Phytophthoras on UK forest hosts

39. WP3.3
Horizon scanning for
knowledge gaps
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)

40. 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
• Map relevant supply chains
- internet purchases
- literature review
- nursery partners
- EPPO
• Tourism and recreational spread
- tourism agents / travel companies
- map international
• What are people bringing into the UK?

41. Kew Gardens (1.8m visitors)
RHS: Garden Wisley (1.1m)
Eden Project (1m)
RBGE (860k)
Chatsworth House (640k)
Westonbirt Arboretum (520k)
Alnwick Gardens (270k)
(ALVA, 2016 figures)
‐ Focus in areas with known
pathogen problems
‐ Collect information on where
visitors come from and the
timing of their visits
‐ Interviews with site managers
about their pest/disease
concerns and management
‐ Replicate for other types of site
e.g. National Trust attractions
31m people visit Britain each year
One third visit a park or garden
(VisitBritain)
Assessing pathways e.g. Garden visitors

42. Ensure policy impact of tools produced in WP3
• Aim to co-develop decision support tools that arise from our
analyses with potential beneficiaries
• E.g. UK Plant Health Risk Register
• Who might benefit from a trade tool, niche maps,
pathogen or source country rankings and how?
• Who can we contact now to ensure outputs fit for purpose
by different groups of beneficiaries?

43. Milestones: Plan for next 12 months
• Finalise and disseminate trait database, analyse trait “space” and
groups, define focal species (December 2016)
• Finalise global occurrence and environmental databases
• Test of trade models and niche modelling approaches
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)

44. A thank you to our funders
and all those who have kindly
shared their data
Judit Kovacs (University of West Hungary, Hungary)
Frans Arentz (Consultant, Papua New Guinea)
Richard O’Hanlon (Department of Agriculture, Food and the Marine, Ireland)
Jozsef Bakonyi (Plant Protection Institute, Hungarian Academy of Sciences,
Hungary)
George Tziros (Hellenic Agricultural Organization, Greece)
Jan Nechwetal (Institute for Plant Protection, Germany)
Karel Černý (Silva Tarouca Research Institute for Landscape and
Ornamental Gardening)
Alina Greslebin (National University of Patagonia San Juan Bosco)
Sophie Schmitz (Walloon Agricultural Research Centre (CRA-W), Belgium)
Richard Gottsberger (AGES, Vienna)
Acknowledgements