Session 1: Plant pest impacts - a common set of metrics

SESSION 1: STRENGTHENING BORDER BIOSECURITY

Plant pest impacts:a common set of metrics

Kylie Ireland

biosecurity built on science

Plant pest impacts:a common set of metrics

Kylie Ireland

Postdoctoral Fellow

Plant Biosecurity Cooperative Research Centre

Pierce’s disease

Sudden Oak Death

Asian Gypsy Moth

Huanglongbing

Texas root rot

Oriental Fruit Fly

Plum curculio

False codling moth

Peach X disease

Brown rot

Verticillium wilt

Asian citrus psyllid

Vegetable leaf miner

European canker

Guava rust (exotic strain)

Cotton aphid

Tomato leaf miner

Tarnished plant bug

Apple maggot

Blackline

Tomato ringspot virusJapanese beetle

Brown marmorated stink bug


Predicting High Impact Pests

What is most likely THE next big pest?

Identify priority pathways & pest traits

Support effective resource allocation

Pathways & Risk Assessment Framework for High-Impact Species (PRAFHIS)

High Impact?


What is Impact?

# ?

% ?

Proportion?

Ratio ?

Impacts / Consequences / Effects

Small -> Medium -> Large

Minor -> Major (5%) -> Massive

Low -> Moderate -> High

Important

Severe

Serious

Extreme

Nationally Significant / National Interest


Plant-production specific

- Socio-economic, trade & market driven

Measurable metrics

Independent of biological/pathway characteristics

Cross taxa

- Pathogens & Insects +…

Spatio-temporal variability

- Past, current & potential

Alien & native

A common set of metrics


Flexible – in development & application

Transparent

Harmonising

Easy to use

Integration with new & existing tools

- ACERA – Prioritising Plant Pests

- DAWR – Risk-Return Resource Allocation (RRRA) model

- ABARES – NEBRA classification

End-user needs


Plant protection

Economic assessment parameters

- Cook et al.

Risk assessment guidance

- IPPC, EPPO, DAWR, MPI….

Policy practitioner discussions

- AU & NZ

Score amalgamation

- Holt et al.

Integrating academic advances

Environmental Impact

Blackburn et al. 2014A unified classification of alien species based on the magnitude of their environmental impacts

Hawkins et al. 2015Framework and guidelines for implementing the proposed IUCN Environmental Impact Classification for Alien Taxa (EICAT)

Class. Framework

Uncertainty

Score amalgamation


20 Metrics – 18 “Measurable”

Primary response

Investment

Yield loss

Success

Mid to long term response

Economic injury level

Control costs

Yield reduction

*Feas. of Management

Cultivar loss

Cultivar recovery

Spatio-temporal

Distribution

Maximum area affected

Frequency

*Reversibility

Market-driven

*Host crop value

*Market access

Alternate market avail.

Area freedom loss

Treatments

Price discount

Quality loss


MetricMin. Conc.

(MC = 0)Minor

(MN = 1)Moderate (MO = 2)

Major (MR = 3)

Massive (MV = 4)

Market-driven

Host crop value (% total plant industry)

≤ 0.01 % >0.01 - 0.1 % > 0.1 - 1 % > 1 – 10 % > 10 %

Market access change (loss/change of market share)

No change Minor

< 5 %

Moderate

> 5 - 20 %

Major

> 20 - 50 %

All Major

> 50 %

e.g. Rhizoctonia sp. Karnal bunt, wheat, AU/NZ *potential

Fruit flies, hort, AU/NZ

“Disruptor” Metrics & Classes

0

0


“Disruptor” Metrics & Classes

MetricMin. Conc.

(MC = 0)Minor

(MN = 1)Moderate (MO = 2)

Major (MR = 3)

Massive (MV = 4)

Spatio-temporal

Reversibility Temporary, ≤ 1 year

Temporary, > 1 - 5 years

Temporary, > 5 -15 years

Ongoing - NOexcl. alt. cropping

Ongoing - YESexcl. alt. cropping

e.g. Citrus canker,QLD, 2004-9

Foc TR4 (Panama), banana, global

Bacterial wilt, hort., global

Mid to long term management

Feasibility of management *readily avail. &cost-effective

Not required Rarely requires targeted control

Existing approaches adequate

Barriers to uptake and adoption

Cannot using existing

approaches

e.g. Rhizoctonia spp., multiple crops,

global

Fusarium head blight, wheat, AU

Current rust strains, wheat, AU

Med. Fly, hort., WA

Myrtle rust, hort& forestry?, AU


SNAPSHOT!

Pest event details:- Pest identity

- Host(s)

- Location

- Time period

- Assessor(s)

- Notes

Data deficient

Not applicable

Data Sheet = TRANSPARENCY

Everett et al. 2011Australasian Plant Dis. Notes (2011) 6:67–71

Event details HIGH (0.705; DD = 0.00; MEDIUM) ^Pest: Kiwifruit canker; Pseudomonas syringae pv. actinidiae (Psa) (Bacteria) – ExoticHost(s): KiwifruitLocation: New Zealand

Time period:

2010-2015

Assessor(s): Joy Tyson, David Logan, Lisa Jamieson – Plant and Food Research New ZealandNotes: This assessment focuses on the primary response periodMetric Class* Decision notes ScoreDisruptor 0.625Crop value MR 245 M, 2-3% 3Management MR 3Market access MN Immediate loss of access to all countries for

Actinidia nursery stock from New Zealand.Psa was already present in major growing regions of Italy, France, China and Chile

1

Reversibility MR Impact ongoing 3Spatiotemporal 0.938Distribution MV 4Max. area MV 4Frequency MV 4Reversibility MR Disruptor 3Market-driven 0.458Crop value MR Disruptor 3Market access MO Disruptor 2

Alt. market MO ? Capture initial closing markets 2

Area freedom MV 4

Treatments MO More change needed initially? 2

Price discount MC 0Quality loss MC 0

Primary response 0.917Investment MV Containment measures. Destruction of heavily

infected vines.Large investment in research.

4

Yield lossMR

? Expect more loss as gold pushed out. Likely higher than this in those first two years

3

Success

MV

MPI and the kiwifruit industry tried to contain Psato the incursion site/area (Te Puke); these containment measures failed. Spread to all growing regions by 2012

4

Mid to long-term management 0.750EIL N/A -

Control costsN/A

Removal of heavily infected vines. Large amounts of copper applied.

-

Yield reduc. N/A -

Management MR Disruptor 3Cv loss MR 3


Discrimination- Spatial

- Temporal

- High/low impact

Future work- Further testing

Spatio-temporal scales

Expand taxa/systems- e.g. weeds, animal prod.

- Scoring Weighting, decision making- DCME (Liu & Cook)

Conditional probabilities

Thresholds….

Event details

Pest Pseudomonas syringae pv. actinidiae., Psa (Bacteria)

Host(s)Actinidia deliciosa, Green kiwifruit, less susceptible;

A. chinensis ‘Hort16A’, Gold kiwifruit, highly susceptible

Location North Island, New Zealand

Time period 2010-2012 2010-2015

Impact class (score) High (0.705) High (0.674)

Uncertainty (DD) 0.00 0.05

Confidence Medium Medium

Disruptor 0.625 0.625

Crop value 3 3

Management 3 3

Market access 1 1

Reversibility 3 3

Spatiotemporal 0.938 0.938

Distribution 4 4

Max. area 4 4

Frequency 4 4

*Reversibility 3 3

Market-driven 0.458 0.396

*Crop value 3 3

*Market access 2 1

Alt. market 2 1

Area freedom 4 4

Treatments 2 1

Price discount 0 0

Quality loss 0 0

Primary response 0.917 0.750

Investment 4 3

Yield loss 3 2

Success 4 4

Mid to long-term management 0.750 0.750

EIL N/A DD

Control costs N/A 2

Yield reduction N/A 4

*Management 3 3

Cv loss 3 3

Cv recovery 3 3

Validation?

Everett et al. 2011Australasian Plant Dis. Notes (2011) 6:67–71


What next….? Please, get involved!

Petra Kuhne

rt

Metric system w’shops- Validate & improve

PRAFHIS- Analysis of predictors

of high impact pests

- Risk assessment framework

End-users engage!


For more information, or to join the PRAFHIS email list, please email [email protected]

Please, get involved! End users….Engage!

Science

Session 1: Plant pest impacts - a common set of metrics