Pest risk analysis: tools, resources and key challenges

Dr Alan MacLeod

Pest risk analyst

United Kingdom

Typical structure of PRA

Devorshak, C. (2012) Plant Pest Risk Analysis, Concepts and Application, CAB International, Wallingford, UK 2

INITIATION

• Identity of pest

• Reason for PRA

• Identify PRA area

RISK MANAGEMENT

• Management options

(Consultation)

• Monitoring and review of measures

RISK ASSESSMENT

• Host Plants

• Geographical Distribution

(biology of the pest)

• Capable of introduction ? (entry & establishment)

• Spread & potential impact?

• Overall risk

Interpreting evidence

Gathering evidence

PRA complexity

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Type of PRA Principal Applications Assessment methods

Rapid PRA Following new interceptions, new outbreaks,

Rapid qualitative evaluation of the literature, online datasets and other evidence

Comprehensive (detailed) PRA

To justify phytosanitary measures on trade / import requirements

Detailed qualitative evaluationof the literature, online datasets and other evidence, could have quantitative aspects

Detailed analysis of particular elements of risk (e.g. focus on entry or establishment or impact or management)

To resolve major uncertainties in PRA

To defend challenges to a PRA (WTO disputes)

Detailed quantitativeassessment; could include modelling and mapping, e.g. interception data and climatic suitability, cost: benefit analysis, systems approach

Burgman et al. (2014) The Role of Pest Risk Analysis in Plant Biosecurity. In: The Handbook of Plant Biosecurity, Springer

Tools & Resource needs

• Entry: data to assess pathways

• Establishment: data for mapping

Venette et al. (2010) Pest Risk Maps for Invasive Alien Species: A Roadmap for Improvement, Bioscience 60, 349-362 4

• Spread: data for modelling

• Impacts: data for analysis

Potential distribution of Lycorma delicatulaJung et al. (2017) Journal of Asia-Pacific Biodiversity 10 (4) 532-538

Relationships between economic techniquesSoliman et al. (2010) Crop Protection 29 (6), 517-524

Robinet et al. (2012) PLoS One, 7(10), e43366

Case study: Thrips palmi

• A polyphagous pest feeding on leaves, flowers and fruit of many horticultural plants including Cucurbitaceae, Solanaceae and Orchidaceae

• Native to southern Asia. Now widespread mostly throughout tropical and sub-tropical countries

• Not established in Europe

Images from EPPO Global database http://gd.eppo.int MacLeod et al. (2004) Crop Protection 23 (7), 601-610. 5

MacLeod (2015) The relationship between biosecurity surveillance and risk analysis. In: Biosecurity surveillance: quantitative approaches, CABI 6

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1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004

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T. palmi on Thai orchids Thousands of Tonnes imported

Case study: Thrips palmi on Thai orchids

Sudden rise in interceptions of T. palmiPRA conducted, • identified Thai orchids as principle

pathwayPRA concluded:• could establish in glasshouses• could impact cucumbers, aubergines &

peppers• Consult with Thai Ministry of Agriculture• New phytosanitary measures developed

(inspections at production sites, chemical treatment of orchids)

• Trade continued

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1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004

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T. palmi on Thai orchids Thousands of Tonnes imported

Case study: Thrips palmi on Thai orchids

As a result of PRA, phytosanitary measures strengthened in 1998

MacLeod (2015) The relationship between biosecurity surveillance and risk analysis. In: Biosecurity surveillance: quantitative approaches, CABI

Case study: Acidovorax citrulli

• Bacterial pathogen of cucurbit fruit (e.g. blotches on watermelons)

• Can cause significant losses

• Assess risk to EU

• Could enter via imported seed & seedlings

• Could establish

• Most harmful when warm & humid

• Potential measures:

• seed testing

• inspect seedlings

MacLeod et al. (2012) Pest risk assessment for European Community plant health: A comparative approach with case studies. http://www.efsa.europa.eu/fr/supporting/doc/319e.pdf

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Global distribution of watermelon production (green/ yellow) with approximate occurrence of Acidovorax citrulli (ellipses)

Mechanism for combining components

• PRA method developed in EFSA project (BBN)

• Questions on entry (6), establishment (1), spread (1), consequences (2)

• Apportion degree of belief across 5 categories (VL, L, M, H, VH) (defined)

• Combine risk elements via conditional probability tables

• Perform assessment without and with measures in place

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3.06 Pest Risk

3.05 Potential Impact2.08 Overall potential for Entry

Entry: Pathway 1, Seeds Entry: Pathway 2, Seedlings

3.06 Pest Risk

3.05 Potential Impact2.08 Overall potential for Entry

Entry: Pathway 1, Seeds Entry: Pathway 2, Seedlings

Macleod et al. (2012) Pest risk assessment for European Community plant health: A comparative approach with case studies. http://www.efsa.europa.eu/fr/supporting/doc/319e.pdf

Acidovorax citrulli risk without RROs

Expressing uncertainty & assessing measures

• Method captures uncertainty

• Indicates effectiveness of measures

• seed testing & visual inspection not very effective

• Challenge to adopt method

Risk With RROs

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Comparison

Macleod et al. (2012) Pest risk assessment for European Community plant health: A comparative approach with case studies. http://www.efsa.europa.eu/fr/supporting/doc/319e.pdf

Risk element Tools & resources ChallengesEntry Customs import data Lack of data on species of plants for planting

(aggregated HS data

Establishment Species distribution models (e.g.

CLIMEX, MaxEnt)

Lack detailed pest distribution data

Pest adaptation to new environment

Responses to climate change (hosts & pests)Spread Generic models of spread (natural &

via humans)

Mixed mechanisms for spread

Lab studies to real world (e.g. flight mills)

Repeated introductions?Impact Economic tools (e.g. partial

budgeting, partial equilibrium

(supply & demand))

Quantifying all ecosystem service impacts

Impacts over time (e.g industry resilience)

Apply knowledge of pest to PRA areaPest adaptation to new hosts

Overall risk and

uncertainty

Qualitative methods (e.g. matrices)

Quantitative methods (e.g.Monte

Carlo)

Revealing uncertainty

Resources required

Management Efficacy data / trials

If multiple pests - Prioritisation

systems (lack detail)

Consistency in ALOP/ ALR

Allocation of resources to deal with multiple

pestsRisk

communication

IPPC guide

EFSA Guide

Identifying stakeholders

Common understanding of linguistic terms? 11

Challenges within the PRA process

Disconnect challenge

MacLeod & Lloyd (2020) Emerging Topics in Life Sciences 4 (5), 463–471. 12

Millennia

Centuries

Years

Months

Days

Hours

cm m km 100 km 1,000 km

Landscape evolution

Direct impacts of Invasive species

Forests develop

El Nino events

Climate change

Local land use change

Trees grow

Annual crops Where risk assessors

aim to inform

All year round crops

The scale at which much field research is performed

The disconnect between where PRA aims to inform (red), and the scale at which field data informing the analysis is often collected (green).

Tem

po

ral s

cale

Spatial scale

Challenges to the process

• PRA is reactive (Brasier, 2008) i.e. pests must be known knowns

• PRA standards cannot assess risks from unknown organisms (known unknowns) Some ‘newly escaped’ organisms were previously unknown to science before they escaped and were found to be pests

• Brockerhoff & Bulman (2014): we have a good understanding of the risks posed by many [known] pests and pathogens, experience indicates that there are many pests that are unknown,

• their behaviour in a new environment differs from that in their native range

• they are unknown to science

• Call to manage risk in a more general way to protect plant resources

• PRA focuses on genetically stable species – how to take adaptation into account (wider environmental tolerances / broaden hosts)? (e.g. de Vienne et al., 2009)

• Multiple stressors (multiple pests on same host)Brasier, 2008, Plant Pathology 57 (5), 792–808. Brockerhoff & Bulman (2014) New Zealand Journal of Forestry, 59 (2), 3-8 de Vienne et al. (2009) J of Evolutionary Biol 22, 2532-2541

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Thank you

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