Identifying the Endangered Area: Risk Mapping for Pest Risk Analysis

1. Identifying the Endangered Area: Risk Mapping for Pest Risk Analysis Richard Baker Central 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

2. 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

3. 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

4. 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

5. 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

6. Sudan bollworm - Geographical Distribution Sudan bollworm Diparopsis watersi CABI. 2005. Crop Protection Compendium. http://www.cabicompendium.org/cpc

7. World Climate Classification http://www.fao.org/WAICENT/FAOINFO/SUSTDEV/EIdirect/climate/EIsp0054.htm

8. Sudan bollworm and world climate classification Cotton and world climate classification CABI. 2005. Crop Protection Compendium. http://www.cabicompendium.org/cpc

9. 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.

10. 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.

11. Geographic Data in a Geographical Information System (GIS) • Stored in layers • Data layers can be manipulated, analysed and displayed in many ways

12. 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

13. 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

14. 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)

15. 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

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

17. Diabrotica virgifera virgifera distribution in Europe predicted by CLIMEXwith 1931-1960 mean climatic data from 285 weather stations

18. 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)

19. 5 km2 cells with accumulated temperature > 670 = 34 http://www.metoffice.com/research/hadleycentre/obsdata/ukcip/

20. 5 km2 cells with accumulated temperature > 670 = 4852 http://www.metoffice.com/research/hadleycentre/obsdata/ukcip/

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

22. 5 km2 cells with accumulated temperature > 670 = 2333

23. Effect of Climate Change on the Area suitable for Diabrotica virgifera virgifera establishment 1995: 5 km2 cells with accumulated temperature > 670 = 4852 UKCIP02: 5 km2 cells with accumulated temperature > 670 = 5137 http://www.metoffice.com/research/hadleycentre/obsdata/ukcip/

24. Maize area in England (‘000 ha) 1980-2004 http://www.defra.gov.uk/esg/work_htm/publications/cs/farmstats_web/default.htm

25. 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

26. 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.

27. 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”