Identifying the Endangered Area: Risk Mapping for Pest Risk Analysis

Richard BakerCentral Science Laboratory, York, United

Kingdom

Presented at the International Plant Health Risk Analysis Workshop, October 24-28, 2005, Niagara Falls, Canada N.B. Many slides have been deleted to restrict the file to 2mb

Outline Predicting establishment potential and mapping

endangered areas With limited resources and little information Straightforward assessments

Complex assessments Species at the edge of their range

Western corn rootworm (Diabrotica virgifera virgifera) in the UK

Colorado beetle (Leptinotarsa decemlineata) in the UK Species with complex life cycles

Karnal bunt (Tilletia indica) in Europe Sudden oak death (Phytophthora ramorum) in Europe

Some key challenges The spatial and temporal resolution of datasets Climate change Mapping economic loss

Factors determining the Probability of Establishment

Ecological Factors Suitability of the abiotic environment, e.g. climate Presence of suitable hosts, alternate hosts and vectors Availability of effective natural or artificial control

mechanisms Cultural practices

Intrinsic Factors Life cycle Reproductive strategy Genetic adaptability Minimum population needed for establishment

Factors determining the Probability of Establishment

Ecological Factors Suitability of the abiotic environment, e.g. climate Presence of suitable hosts, alternate hosts and vectors Availability of effective natural or artificial control

mechanisms Cultural practices

Intrinsic Factors Life cycle Reproductive strategy Genetic adaptability Minimum population needed for establishment

Predicting establishment with little information and few resources

Assume you always know or can infer: Pest name Pest presence/absence in the PRA area Host plant Pest origin

Assume you have access to a computer and therefore the: CABI Crop Protection Compendium Internet and search engines such as Google

Sudan bollwormDiparopsis watersi

Sudan bollworm - Geographical Distribution

CABI. 2005. Crop Protection Compendium. http://www.cabicompendium.org/cpc

World Climate Classification

http://www.fao.org/WAICENT/FAOINFO/SUSTDEV/EIdirect/climate/EIsp0054.htm

Sudan bollworm and world climate classification

Cotton and world climate classification

CABI. 2005. Crop Protection Compendium. http://www.cabicompendium.org/cpc

World Annual Accumulated Temperatures base 10ºC for 1961-1990

(Data from the Climatic Research Unit, Norwich)

Baker, R.H.A. 2002. Predicting the limits to the potential distribution of alien crop pests. In: Invasive Arthropods in Agriculture. Problems and Solutions, Hallman, G.J. & Schwalbe, C.P. (Eds). pp. 207-241. Science Publishers Inc. Enfield USA.

Areas in the World with Similar Annual Accumulated Temperatures base 10ºC and Annual Minimum

Temperatures(Data from the Climatic Research Unit, Norwich)

Baker, R.H.A. 2002. Predicting the limits to the potential distribution of alien crop pests. In: Invasive Arthropods in Agriculture. Problems and Solutions, Hallman, G.J. & Schwalbe, C.P. (Eds). pp. 207-241. Science Publishers Inc. Enfield USA.

Geographic Data in a Geographical Information System (GIS)

Stored in layers Data layers can be

manipulated, analysed and displayed in many ways

ArcView Geographical Information System (GIS)

Provides basic and advanced functions

Used widely throughout government and the industry

Powerful modular GIS (ArcGIS)

Extensions for spatial & geostatistical analysis, 3D modelling

Many contributed scripts Can be programmed in

Visual Basic

CLIMEX: a model for predicting distribution based on climate

Climate Matching Estimates distribution from known climatic

responses and geographical distribution Growth Index - the overall potential for population growth Stress Indices - the probability of survival through

unfavourable seasons Ecoclimatic Index - the overall suitability of a location for

establishment

http://www.ento.csiro.au/climex/climex.html

Diabrotica virgifera virgifera Western Corn Rootworm

Serious maize pest in northern USA and Canada

In central Europe since 1992, August 2002 arrived near Paris

Since first introduced into Europe, UK area of maize has risen markedly (now >100,000 ha/year)

Diabrotica virgifera virgifera in the UK: Predicting Establishment & Mapping the

Endangered Area

Apply CLIMEX at low temporal & spatial resolution

Enhance spatial and temporal resolution Calculate accumulated temperatures above

and below ground Look at effects of climate change

CLIMEX parameters for growth and environmental stress are estimated fromDiabrotica virgifera virgifera’s current distribution (above right) and used to generate ecoclimatic indices and a map of expected distribution in the USA (above left)

Diabrotica virgifera virgifera distribution in Europe predicted by CLIMEX with 1931-1960 mean climatic data from 285 weather

stations

Diabrotica virgifera virgifera distribution in Europe predicted by CLIMEX with 1961-1990 mean climatic data interpolated to a 0.5°

latitude/longitude grid (Climatic Research Unit, Norwich)

5 km2 cells with accumulated temperature > 670 = 34

http://www.metoffice.com/research/hadleycentre/obsdata/ukcip/

5 km2 cells with accumulated temperature > 670 = 4852

http://www.metoffice.com/research/hadleycentre/obsdata/ukcip/

http://www.defra.gov.uk/esg/work_htm/publications/cs/farmstats_web/default.htm

5 km2 cells with accumulated temperature > 670 = 2333

Effect of Climate Change on the Area suitable for Diabrotica virgifera virgifera establishment

UKCIP02: 5 km2 cells with accumulated temperature > 670 = 5137

1995: 5 km2 cells with accumulated temperature > 670 = 4852

http://www.metoffice.com/research/hadleycentre/obsdata/ukcip/

Maize area in England (‘000 ha) 1980-2004

0

20

40

60

80

100

120

1980 1985 1990 1995 2000 2005 2010

Year

'000

ha

http://www.defra.gov.uk/esg/work_htm/publications/cs/farmstats_web/default.htm

Conclusions

Risk mapping provides a powerful tool for directly analysing and displaying endangered areas

Risk mapping does not have to be complex Detailed risk mapping is particularly useful

when: Species are at the edge of their range Future impacts need to be assessed Species have complex life cycles

Risk Mapping: Key Issues to Address

Increasing the availability and accuracy of international datasets to enable risks maps to be generated for large areas, e.g. the European Union

Enhancing the spatial and temporal resolution of datasets ensuring they are compatible and relevant to the species concerned

Defining the climate baseline to represent accurately the current climate in the PRA area and predict the effects of climate change

Incorporating models of pest spread, population dynamics and impacts into risk maps, displaying the dynamic, stochastic nature of pest invasions

Including economic, environmental and social impacts in maps of endangered areas

Representing uncertainty in risk maps Using endangered area risk maps in surveillance, contingency

planning and action in emergencies.

Acknowledgements

Claire Sansford and Alan MacLeod of the CSL Pest Risk Analysis sub-team

Other colleagues in CSL Plant Health Group, PHSI and PHD

Defra GI Unit, Economics & Statistics Directorate Claire Jarvis, Geography Dept., University of

Edinburgh (now University of Leicester) Frank Ewert & John Porter (KVL, Denmark) and

Beniamino Gioli & Franco Miglietta (IATA, Florence) EU Vth Framework Project “Karnal Bunt Risks”