An easily overlooked but vitally important component of invasive species management is accurate identification. Picture the scene: It’s Australia, it’s a Friday afternoon, a comprehensive fire ant management strategy has been drawn up, baits have been acquisitioned and an eager team of volunteers is ready to deal with this invasive foe and escape for the weekend. There are plenty of ants around… but nobody knows if they’ve found the right ones because the pesky little critters all look so similar! Scientists in Australia believe they have a solution – a database of 3D images of known species against which 2D photographs of organisms taken and uploaded in the field are compared, giving an estimate of their likely invasive or native status.
3D Ant – by Leo Blanchette, flickr
When working with any type of organism in the field, it is important to correctly identify the species of interest before any actions are undertaken, be it for conservation, research or pest management. Nowhere is this more true than when carrying out control measures against an invasive species, where misidentification could result not only in the intended target being left unscathed, but could lead to impacts on non-target species of similar appearance. When it comes to the scale of arthropods such as ants, even those with expert skills in identification may struggle to distinguish between species in the field when armed only with a hand lens, a camera and some reference images. Even with samples and photographs taken from the field back to the lab, an expert taxonomist may be required to provide a correct identification, based on cryptic morphological characteristics. Xiaozheng Zhang and his colleagues at NICTA Queensland Laboratory, Australia, however, propose a novel solution to this problem, as reported in NewScientist. Zhang et al. suggest that by creating a database of 3D models of known insect species that are constructed in a way that allows their comparison with 2D photographs of insects, they will be able to produce software to allow the identification of these insects based on morphological traits. A key use of this could be in the identification of invasive non-native species that may otherwise be confused with natives.
The modelling process is likely to be complex – in the words of Zhang et al. “The 3D structure of the insect body is modelled from two geometric primitives, generalized cylinders and deformable ellipsoids. The primitives are fitted and warped based on both edge and medial axis constraints of the 2D image. Individualized 3D models are then built to approximate the insect structure.” For this reason the team are first working on a prototype of the system designed to identify longhorn beetles, which are relatively large, morphologically distinctive insects that should be relatively easy to model. Longhorn beetles include a number of species that are invasive in regions around the world, including the Asian longhorn beetle, Anoplophora glabripennis, which is a quarantine organism in Australia. The construction of the prototype in itself is, therefore, a valuable exercise. Based on the success of and knowledge acquired from designing the prototype, the team hopes to expand the system to detect more invasive species, with the aim to start modelling the invasive red imported fire ant (Solenopsis invicta) by next year. Ultimately this system could be expanded to identify any invasive insect and could be used by anyone with a digital camera; from the experienced taxonomist to the amateur entomologist.
Invasive Species Research Scientist
Zhang, X., Gao, Y & Caelli, T. (2010) Primitive-based 3D structure inference from a single 2D image for insect modeling: Towards an electronic field guide for insect identification. 11th International Conference on Control, Automation, Robotics and Vision. Singapore, 2010. Pp 866-871.
Zukerman, W. (2011) Online 3D insect sleuth tells friend from foe. NewScientist: Tech [online]. 29th March, 2011.
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