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”
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