Analysing shipping networks as a pathway for invasive species Dean Paini Research Scientist, CSIRO biosecurity built on science Cooperative Research Centre for National Plant Biosecurity
Phil Lester
KW Bridges
David Mudge
Susan Ellis, Bugwood.org
GH Rodda, US Geological Museum
Craig G Morley
biosecurity built on science
Potential vector
biosecurity built on science
biosecurity built on science
biosecurity built on science
biosecurity built on science
biosecurity built on science
Previous analyses
Kaluza et al 2010 biosecurity built on science
Shipping network data set 2002-2007 - All ships arriving into an Australian port - Previous ten ports - Container ships
Deterministic model - Arrival likelihood on ships - Two parameters Likelihood of infection/infestation Likelihood of survival biosecurity built on science
Likelihood of infection
Anyone got any ideas???? 0.001 to 0.000001 1/thousand to 1/million A ship arriving to a port = 0.0001
biosecurity built on science
Likelihood of survival Anyone got anymore ideas???? Survival per day 0.8 to 0.99 A ship travelling to Australia = 0.9/day 3 days travel = 0.9x0.9x0.9 = 0.729
biosecurity built on science
A E D
4 days
2 days 4 days 3 days Infection at port D = 0.0001
B
C
Survival to Australia = 0.96 = 0.53 Arrival likelihood = 0.0001 x 0.53 = 0.000053 Arrival likelihood = 0.000039 Arrival likelihood = 0.000059
2 days
Infected port Non-infected port
Australia
biosecurity built on science
Invasion likelihood  Arrival likelihood x establishment likelihood  Establishment likelihood (SOM analysis) - Paini et al 2010 J Applied Ecology - Paini et al 2010 Nature Communications - Paini et al 2011 PLoS ONE
biosecurity built on science
A E D
4 days
2 days 4 days
B
3 days Arrival likelihood = 0.000053
C
Establishment likelihood = 0.75 Invasion likelihood = 0.000040
2 days
Non-infected port
Invasion likelihood = 0.000029 Invasion likelihood = 0.000044
Infected port
Australia
Overall invasion likelihood = 0.00011 biosecurity built on science
Invasion likelihood  564 insect pest species (CABI CPC)  For all Australian ports
biosecurity built on science
Rank 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30
Species names Xylosandrus compactus Agrotis segetum Trichoplusia ni Pinnaspis strachani Liriomyza trifolii Diaphorina citri Sesamia inferens Orthezia insignis Leucinodes orbonalis Oryctes rhinoceros Toxoptera odinae Aleurocanthus woglumi Aphis fabae Dialeurodes citri Aproaerema modicella Liriomyza huidobrensis Sitobion avenae Chromatomyia horticola Acherontia styx Brachycaudus helichrysi Hadula trifolii Pelopidas mathias Stephanitis typica Lymantria dispar Sinoxylon conigerum Aulacophora lewisii Chilo infuscatellus Philaenus spumarius Chilo auricilius Dicladispa armigera
Invasion likelihood 0.7886 0.7512 0.6277 0.5825 0.5697 0.5674 0.5496 0.5495 0.5050 0.4860 0.4842 0.4623 0.4574 0.4551 0.4402 0.4075 0.3897 0.3894 0.3860 0.3803 0.3798 0.3402 0.3387 0.3371 0.3288 0.3085 0.3051 0.3040 0.3026 0.2927
biosecurity built on science
Rank 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23
Species names Xylosandrus compactus Agrotis segetum Trichoplusia ni Pinnaspis strachani Liriomyza trifolii Diaphorina citri Sesamia inferens Orthezia insignis Leucinodes orbonalis Oryctes rhinoceros Toxoptera odinae Aleurocanthus woglumi Aphis fabae Dialeurodes citri Aproaerema modicella Liriomyza huidobrensis Sitobion avenae Chromatomyia horticola Acherontia styx Brachycaudus helichrysi Hadula trifolii Pelopidas mathias Stephanitis typica
Invasion likelihood 0.7886 0.7512 0.6277 0.5825 0.5697 0.5674 0.5496 0.5495 0.5050 0.4860 0.4842 0.4623 0.4574 0.4551 0.4402 0.4075 0.3897 0.3894 0.3860 0.3803 0.3798 0.3402 0.3387
24 Lymantria dispar
0.3371
25 26 27 28 29 30
0.3288 0.3085 0.3051 0.3040 0.3026 0.2927
Sinoxylon conigerum Aulacophora lewisii Chilo infuscatellus Philaenus spumarius Chilo auricilius Dicladispa armigera
Asian gypsy moth
biosecurity built on science
Lymantria dispar (Asian gypsy moth) rank 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22
Australian Port invasion likelihood Melbourne 0.032973 Botany Bay 0.005405 Fremantle 0.003222 Brisbane 0.000627 Dampier 0.000045 Sydney 0.000037 Adelaide 0.000016 Geraldton 0.000011 Port Hedland 0.000011 Launceston 0.000007 Hastings 0.000006 Burnie 0.000004 Gove 0.000003 Portland 0.000003 Darwin 0.000003 Geelong 0.000002 Port Kembla 0.000002 Port Alma 0.000002 Gladstone 0.000001 Newcastle 2.96E-07 Esperance 0 Townsville 0
Asian gypsy moth
biosecurity built on science
AGM - Melbourne rank 1 2 3 4 5 6 7 8 9 10
last port of call Hong Kong (CHN) Kaohsiung (TWN) Chiwan (CHN) Shekou (CHN) Ningbo (CHN) Tauranga (NZL) La Spezia (ITA) Damietta (EGY) Auckland (NZL) Shanghai (CHN)
invasion likelihood 0.01021 0.01000 0.00199 0.00159 0.00155 0.00133 0.00110 0.00097 0.00090 0.00072
Asian gypsy moth
biosecurity built on science
Sensitivity Varied infection and survival likelihoods Infection - 0.001, 0.0001, 0.00001, 0.000001
Survival (per day) - 0.8, 0.85, 0.9, 0.95, 0.99
20 different combinations Compared a list across all combinations (190 comparisons) Spearman rank correlation biosecurity built on science
Sensitivity >95% comparisons significant (p=0.05) Mean correlation coefficient ≈ 0.95
biosecurity built on science
Conlcusions Resilient to variations in infection and survival likelihood Optimise port inspection protocols (risk return) Analysis of incoming ships in ‘real time’ AMSA vessel tracking system biosecurity built on science
Further work Validate model with interception data Test for yearly variations Incorporate seasonal aspect Expand analysis to all ship types Distinguish between species and ship type Incorporate into AMSA’s vessel tracking system Real time analysis of all incoming ships
biosecurity built on science
Thank you  For more information, please email Dean.Paini@csiro.au
biosecurity built on science