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Spotting the right spot: computer-aided individual identification of the threatened cerambycid beetle Rosalia alpina

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Abstract

Individual identification of animals is of paramount importance to analyze population size, dispersal, habitat preferences or behaviour. Especially for sensitive, threatened species, it is advisable to develop non-invasive recognition methods avoiding direct handling and tagging of the study subjects to be applied to procedures such as marking-recapture. Here we present an application of the I3S software for the individual recognition of the Rosalia longicorn Rosalia alpina based on the contour digitization of the spots present on the beetle’s elytra. Classification performances to individual level tested on an overall sample of 290 images (one per subject) were 94.8 (both elytra), 94.5 (right elytron) and 95.2 % (left elytron). Since I3S leaves the final decision to the operator, such high classification performances may be refined further in the final step leading to a fully reliable identification. We found that the identification performance was statistically supported and that the influence of two main error sources (contour tracing and angle under which the images were taken) was negligible. Our approach minimizes the subjectivity of a qualitative manual comparison of images and greatly reduces the time taken to visually retrieve the image of an individual especially for large photo libraries. It may be successfully used in surveys covering large areas and involving many untrained operators such as volunteers or park rangers. We propose that I3S can be applied to other insect species presenting characteristic spot patterns. To our best knowledge, this is the first study using computer-aided identification of a terrestrial arthropod.

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Acknowledgments

Thanks go to Rome Zoological Museum for allowing us to take photographs of R. alpina specimens in their collection. Alessandro Franza and Benedetta Ciaccio kindly provided us with some photographs taken in the field of live R. alpina specimens (including that used for Fig. 1). DR was partly funded by the Abruzzo Lazio and Molise National Park.

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Authors and Affiliations

  1. Laboratorio di Ecologia Applicata, Dipartimento di Agraria, Università degli Studi di Napoli Federico II, via Università 100, 80055, Portici (Napoli), Italy

    Giovanni Caci & Danilo Russo

  2. Via Simeto 12, 00198, (Roma), Italy

    Alessandro Bruno Biscaccianti

  3. Forestry and Conservation, via Botticelli 14, 03043, Cassino (Frosinone), Italy

    Luca Cistrone

  4. Laboratorio di Entomologia “Ermenegildo Tremblay”, Dipartimento di Agraria, Università degli Studi di Napoli Federico II, via Università 100, 80055, Portici (Napoli), Italy

    Luciano Bosso & Antonio Pietro Garonna

  5. School of Biological Sciences, University of Bristol, Woodland Road, Bristol, BS8 1UG, UK

    Danilo Russo

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  1. Giovanni Caci
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  2. Alessandro Bruno Biscaccianti
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  6. Danilo Russo
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Correspondence to Danilo Russo.

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Caci, G., Biscaccianti, A.B., Cistrone, L. et al. Spotting the right spot: computer-aided individual identification of the threatened cerambycid beetle Rosalia alpina . J Insect Conserv 17, 787–795 (2013). https://doi.org/10.1007/s10841-013-9561-0

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