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Cooperative Research Centre for National Plant Biosecurity Final Report CRC10001 Early warning of pre-emergent emergency plant pest threats Authors Dean Paini, Susan Worner and David Cook 4 February, 2010 1 © Cooperative Research Centre for National Plant Biosecurity All rights reserved Project Leader contact details: Name: David Cook Address: CSIRO Entomology, Clunies Ross St, Acton, ACT 2601 Phone: +61 2 6246 4093 Fax: +61 2 6246 4000 Email: [email protected] CRCNPB contact details: Cooperative Research Centre for National Plant Biosecurity LPO Box 5012 Bruce ACT 5012 Phone: +61 (0)2 6201 2882 Fax: +61 (0)2 6201 5067 Email: [email protected] Web: www.crcplantbiosecurity.com.au 2 Table of contents 1. Executive Summary ....................................................................................... 8 2. Aims and objectives ..................................................................................... 10 3. Key findings ................................................................................................ 11 3.1. The SOM analysis .................................................................................... 11 3.2. Analysis of world wide data ....................................................................... 13 3.3. Analysis of Australian data ........................................................................ 21 3.4. Comparison with expert stakeholder opinion ............................................... 25 3.5. SOM sensitivity ....................................................................................... 27 3.6. SOM accuracy ......................................................................................... 36 3.7. US case study ......................................................................................... 49 3.8. SOMs and climate change ......................................................................... 56 4. Implications for stakeholders ........................................................................ 58 4.1. What have the SOMs told us? .................................................................... 58 4.2. How might the SOMs be used in its current form? ........................................ 58 4.3. What testing remains to be done? .............................................................. 59 4.4. How might the SOMs be used in future? ..................................................... 59 5. Recommendations ....................................................................................... 60 6. Abbreviations/glossary ................................................................................. 63 7. Plain English website summary ..................................................................... 63 8. Appendix .................................................................................................... 65 9. References ............................................................................................... 170 3 Tables Table 1. Top 100 risk list for insect pests from the SOM analysis. Lines indicate the three risk categories utilised in the data analysis (see Section 3.5). For a full list see Appendix, Table 12. ....... 14 Table 2. Regions in the same BMU as Australia and its states and territory, and the regions associated with the neurons that were most often clustered with the Australian BMU. For details of the cluster analyses see Appendix, Table 13. For the full list of neurons and associated regions see Appendix, Table 14. .............................................................................................................................. 15 Table 3. Species similarity indices between Australia and closely clustered regions. ....................... 18 Table 4. The top 20 countries exporting goods into Australia based on the mean monthly percentage of total imports for 2007 (extracted from ABS, 2008). ................................................................ 19 Table 5. List of 58 of the world’s most invasive insect pests (Global Invasive Species Database - http://www.issg.org/database) classified as either crop or forest pests or not. Of those that are crop or forest pests, those that were present in the CABI CPC (CABI, 2003) are also indicated. .............. 20 Table 6. List of the insect pest families requested from states and territory to be submitted to the Australian Plant Pest Database. ............................................................................................... 22 Table 7. A confusion matrix comparing the classification into 3 levels of likelihood of establishment by the SOM analysis and Plant Health Australia (PHA) (http://www.planthealthaustralia.com.au/site/Industry_Biosecurity_Plan_Mainpage.asp)................ 26 Table 8. Risk categories used by (a) Biosecurity Australia (Biosecurity Australia, 2001) and (b) the three categories used in this analysis. ...................................................................................... 29 Table 9. Error rates present in the CABI CPC for 58 countries. Error rates were calculated using data was extracted from Import Risk Assessments generated by the Australian Government’s Department of Agriculture, Forestry, and Fisheries (http://www.daff.gov.au/ba/ira/final-plant). ........................ 30 Table 10. Spearman’s rank correlations comparing the original list generated by SOM with lists generated from altered data. ................................................................................................... 33 Table 11. Weighting for the random selection of invasibility indices for regions in the virtual world. 38 Table 12. The full risk list for insect pest species absent from Australia. ...................................... 66 Table 13. The neurons clustered with Australia and its states and territory in cluster analyses using seven different clustering algorithms. For a full list of the regions associated with these neurons see 72 Table 14. Full list of neurons and associated regions. ................................................................ 73 Table 15. NSW insect pest top 200 risk list generated from SOM analysis of Australian distributional data. * Species with the same risk index were ranked in alphabetical order................................. 78 Table 16. VIC insect pest top 200 risk list generated from SOM analysis of Australian distributional data. * Species with the same risk index were ranked in alphabetical order................................. 81 Table 17. TAS insect pest top 200 risk list generated from SOM analysis of Australian distributional data. * Species with the same risk index were ranked in alphabetical order................................. 84 Table 18. QLD insect pest top 200 risk list generated from SOM analysis of Australian distributional data. * Species with the same risk index were ranked in alphabetical order................................. 87 Table 19. NT insect pest top 200 risk list generated from SOM analysis of Australian distributional data. * Species with the same risk index were ranked in alphabetical order................................. 90 Table 20. SA insect pest top 200 risk list generated from SOM analysis of Australian distributional data. * Species with the same risk index were ranked in alphabetical order................................. 93 Table 21. WA insect pest top 200 risk list generated from SOM analysis of Australian distributional data. * Species with the same risk index were ranked in alphabetical order................................. 96 Table 22. NSW fungal pathogens top 200 risk list generated from SOM analysis of Australian distributional data. * Species with the same risk index were ranked in alphabetical order. ............ 99 Table 23. VIC fungal pathogens top 200 risk list generated from SOM analysis of Australian distributional data. * Species with the same risk index were ranked in alphabetical order. ........... 101 Table 24. TAS fungal pathogens top 200 risk list generated from SOM analysis of Australian distributional data. * Species with the same risk index were ranked in alphabetical order. ........... 103 4 Table 25. QLD fungal pathogens top 200 risk list generated from SOM analysis of Australian distributional data. * Species with the same risk index were ranked in alphabetical order. ........... 106 Table 26. NT fungal pathogens top 200 risk list generated from SOM analysis of Australian distributional data. * Species with the same risk index were ranked in alphabetical order. ........... 109 Table 27. SA fungal pathogens top 200 risk list generated from SOM analysis of Australian distributional data. * Species with the same risk index were ranked in alphabetical order. ........... 112 Table 28. WA fungal pathogens top 200 risk list generated from SOM analysis of Australian distributional data. * Species with the same risk index were ranked in alphabetical order. ........... 115 Table 29. NSW bacterial pathogens risk list generated from SOM analysis of Australian distributional data. * Species with the same risk index were ranked in alphabetical order................................ 118 Table 30. NT bacterial pathogens risk list generated from SOM analysis of Australian distributional data. * Species with the same risk index were ranked in alphabetical order................................ 119 Table 31. QLD bacterial pathogens risk list generated from SOM analysis of Australian distributional data. * Species with the same risk index were ranked in alphabetical order...............................
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