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Modelling the potential spread of Solenopsis invicta Buren (Hymenoptera: Formicidae) (red imported fire ant) in Australia

Scanlan, J.C. and Vanderwoude, C. (2006) Modelling the potential spread of Solenopsis invicta Buren (Hymenoptera: Formicidae) (red imported fire ant) in Australia. Australian Journal of Entomology, 45 (1). pp. 1-9.

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Article Link(s): http://dx.doi.org/10.1111/j.1440-6055.2006.00517.x

Publisher URL: http://www3.interscience.wiley.com/cgi-bin/home

Abstract

Quantifying the potential spread and density of an invading organism enables decision-makers to determine the most appropriate response to incursions. We present two linked models that estimate the spread of Solenopsis invicta Buren (red imported fire ant) in Australia based on limited data gathered after its discovery in Brisbane in 2001. A stochastic cellular automaton determines spread within a location (100 km by 100 km) and this is coupled with a model that simulates human-mediated movement of S. invicta to new locations. In the absence of any control measures, the models predict that S. invicta could cover 763 000–4 066 000 km2 by the year 2035 and be found at 200 separate locations around Australia by 2017–2027, depending on the rate of spread. These estimated rates of expansion (assuming no control efforts were in place) are higher than those experienced in the USA in the 1940s during the early invasion phases in that country. Active control efforts and quarantine controls in the USA (including a concerted eradication attempt in the 1960s) may have slowed spread. Further, milder winters, the presence of the polygynous social form, increased trade and human mobility in Australia in 2000s compared with the USA in 1940s could contribute to faster range expansion.

Item Type:Article
Corporate Creators:Biosecurity Queensland
Additional Information:© Blackwell Publishing Ltd.
Keywords:Cellular automaton; Solenopsis invicta; transition probability.
Subjects:Science > Zoology > Invertebrates > Insects
Science > Invasive Species > Animals
Science > Statistics > Simulation modelling
Deposited On:17 Feb 2009 06:59
Last Modified:09 Jun 2011 02:58

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