A combined approach for better estimation of a species’ biosecurity risk Sunil Singh1,2,3 Supervisors: Mike Hodda1,2,3 and Gavin Ash 1,3 1Cooperative
Research Centre for National Plant Biosecurity Ecosystem Sciences 3Charles Sturt University
2CSIRO
biosecurity built on science Cooperative Research Centre for National Plant Biosecurity
Biosecurity problem Nearly 600 PPN sp. cause economic damage Losses of >$600 million/yr in Australia and $157 billion/yr worldwide Many damaging species absent from Australia Multiple pathways for entry Quarantinable sp. impact market access biosecurity built on science
Approach 1  Analysis of distribution data - 355 regions x 250 PPN species SOM Map of regional clusters
PPN SOM Distribution Analysis Dataset biosecurity built on science
Outcomes Clustering of regions with similar species assemblages Identification of “donor” regions for invasive species SOM Index = likelihood of sp. existing in a given region
biosecurity built on science
Limitations Preliminary estimate of risk Does not include a species’ impact Taxonomic and geographic bias in distribution data
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Approach 2 Criteria based assessment Expert risk estimate (0-1 probability value) E.g. Criteria: Pathways Assoc. with propagative material p ≥ 0.6 Assoc. as contaminant p<0.6 >0.3 Not directly assoc. to trade < 0.3
Weighted average Sum of (p x weight) = estimate of overall risk
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Combining 1 & 2 Example: Pine wilt nematode (B. xylophilus)
Criteria
Probability
Weight
Distribution (SOM index from 1) 0.37
0.2
Pathways
0.80
0.15
Survival adaptations
0.65
0.1
Pathogenicity
0.85
0.1
Host range
0.55
0.1
Emerging pest
0.80
0.1
Taxonomy
0.60
0.1
Pathotypes
0.50
0.05
Disease complex
0.60
0.05
Knowledge
0.45
0.05
Sum (prob. x weight)
0.62 biosecurity built on science
Examples Species
SOM Index
B. xylophilus
0.37
Combined weighted average 0.62
H. carotae
0.10
0.47
H. glycines
0.40
0.63
H. oryzae
0.47
0.52
M. chitwoodi
0.20
0.62 biosecurity built on science
Other approaches ď&#x201A;§ Detailed climatic assessment (Climex) ď&#x201A;§ Expert opinion
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Conclusion ď&#x201A;§ Combining SOM index from analysis of distribution data with a criteria based assessment can better estimate a speciesâ&#x20AC;&#x2122; risks than either of the methods alone.
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What next? Source regions fauna Detailed analysis of high risk sp. Surveillance and diagnostics
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Acknowledgements Dr Dean Paini (CSIRO) - for assistance with SOM analysis CRC National Plant Biosecurity for PhD scholarship
Thank you
ď&#x201A;§ For more information, please email sunil.singh@csiro.au ph: 02 6246 4417 biosecurity built on science