There are hundreds, perhaps thousands, of invasive species that have the potential to arrive and establish in any particular region or country. Identifying which species are more likely than others to arrive and establish is extremely difficult, yet the capacity to do so is vitally important to the biosecurity of a nation.

The aim of this project was to combine arrival likelihood with establishment likelihood to generate the invasion threat to Australia for 1,486 invasive fungal pathogens and insect pests, from all countries of the world.

Research outcomes

Arrival and establishment likelihood for Australia was estimated for 1,486 invasive insect pests and fungal plant pathogens. Arrival likelihood was estimated from the level of trade occurring between Australia and all other countries in millions of US$. Establishment likelihood was estimated by completing a SOM analysis of the worldwide distribution of the 1,486 invasive species. These two estimates were combined to generate a value for the invasion threat of all species in millions of US$. Considering all plant invasive species, China, USA and Japan poses the highest source of risk.

Research implications

Biosecurity agencies can use this information for further refinement of import risk assessments and inspection protocols. Further, the methodology presented here could be applied to any number of invasive species and the outputs generated be incorporated into any consultative process currently used to prioritise pest lists.

Acknowledgements

Thanks to CABI and Sue Worner for providing the CABI data and to Liam Thammavongsa for collating and editing the CABI and the IMF DOT data.

Risk is divided into two categories: likelihood of an event occurring and the consequence once the event has occurred. In biosecurity, the likelihood of an event (i.e. a species invading Australia) can be further divided into the likelihood of arrival, establishment and spread with entry (arrival) and establishment being the two key components. CRC10001 has been using artificial neural networks (i.e. Self Organising Maps – SOMs) to estimate likelihood of establishment. However, this only addresses only one half of the entry/establishment likelihood equation.

The second half is the likelihood of entry and in an increasingly connected world, trade and trade paths are increasing exponentially. Ships that arrive into Australia may have visited multiple ports before arriving. These complex pathways present opportunities for pests and pathogens to arrive at Australia from indirect routes. For example, the Khapra beetle incursion in Western Australia in which this beetle was found in the personal effects of a family emigrating from Scotland. These personal effects had become contaminated when transferred into a shipping container that had originated in Pakistan. This highlights the fact that simply monitoring those pathways that directly link Australia to countries in which a pest or disease is found may not significantly reduce the likelihood of an incident.

Research outcomes:

Models developed in this project, which enable the analysis of complex shipping networks, provide a significant step forward in the risk profiling of incoming ships to Australian ports. These models enable the identification of pathways of greatest threat from invasive species as well as those Australian ports most likely to receive these invasive species.

Research implications:

These models could be incorporated into the current inspection protocols and enable further refinement and prioritisations for these procedures.

Acknowledgements:

Simon Barry, Peter Caley, Paul De Barro, Tom Harwood, Greg Hood, Rieks Van Klinken, Denys Yemshanov.