Hostname: page-component-cd9895bd7-jkksz Total loading time: 0 Render date: 2024-12-25T18:56:03.890Z Has data issue: false hasContentIssue false
  • English
  • Français

Polyphasic approach applying artificial neural networks, molecular analysis and postabdomen morphology to West Palaearctic Tachina spp. (Diptera, Tachinidae)

Published online by Cambridge University Press:  20 October 2010

N. Muráriková ,
J. Vaňhara ,
A. Tóthová  and
J. Havel
N. Muráriková
Affiliation:
Masaryk University, Faculty of Science, Kotlářská 2, CZ-611 37 Brno, Czech Republic
J. Vaňhara*
Affiliation:
Masaryk University, Faculty of Science, Kotlářská 2, CZ-611 37 Brno, Czech Republic
A. Tóthová
Affiliation:
Masaryk University, Faculty of Science, Kotlářská 2, CZ-611 37 Brno, Czech Republic
J. Havel
Affiliation:
Masaryk University, Faculty of Science, Kotlářská 2, CZ-611 37 Brno, Czech Republic
*
*Author for correspondence Fax: +420 532 146 213 E-mail: [email protected]
Get access Rights & Permissions [Opens in a new window]

Abstract

Artificial neural networks (ANN) methodology, molecular analyses and comparative morphology of the male postabdomen were used successfully in parallel for species identification and resolution of some taxonomic problems concerning West Palaearctic species of the genus Tachina Meigen, 1803. Supervised feed-forward ANN with back-propagation of errors was applied on morphometric and qualitative characters to solve known taxonomic discrepancies. Background molecular analyses based on mitochondrial markers CO I, Cyt b, 12S and 16S rDNA and study of male postabdominal structures were published separately. All three approaches resolved taxonomic doubts with identical results in the following five cases: case 1, the four presently recognized subgenera of the genus Tachina were confirmed and the description of a new subgenus was recommended; case 2, the validity of a new boreo-alpine species (sp.n.) was confirmed; case 3, the previously supposed presence of T. casta (Rondani, 1859) in central Europe was not supported; case 4, West Palaearctic T. nupta (Rondani, 1859) was contrasted with East Palaearctic specimens from Japan, which seem to represent a valid species not conspecific with central European specimens; T. nupta needs detailed further study; case 5, T. nigrohirta (Stein, 1924) resurrected recently from synonymy with T. ursina Meigen, 1824 was confirmed as a valid species. This parallel application of three alternative methods has enabled the principle of ‘polyphasic taxonomy’ to be tested and verified using these separate results. For the first time, the value of using the ANN approach in taxonomy was justified by two non-mathematical methods (molecular and morphological).

Keywords

ANN - artificial neural networksmolecular markers CO ICyt b12S16S rDNAmale postabdomenspecies identificationpolyphasic taxonomyDipteraTachinidaeTachinaparasitoids
Type
Research Paper
Information
Bulletin of Entomological Research , Volume 101 , Issue 2 , April 2011 , pp. 165 - 175
Copyright
Copyright © Cambridge University Press 2010

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Aldrich, B.T., Magirang, E.B., Dowell, F.E. & Kambhampati, S. (2007) Identification of termite species and subspecies of the genus Zootermopsis using near-infrared reflectance spectroscopy. Journal of Insect Science 7, 18., 7 pp. Available online at http://www.insectscience.org/7.18/ (accessed March 2010).CrossRefGoogle ScholarPubMed
Bezzi, M. & Stein, P. (1907) Tachinidae (Cyclorrhapha Schizophora: Schizometopa). pp. 189–584 in Becker, T., Bezzi, M., Kertész, K. & Stein, P. (Eds) Katalog der paläarktischen Dipteren, bd. 3. Budapest, Hungary.Google Scholar
Čepelák, J. (1986) Tachinidae. pp. 278–332, 411–424 in Čepelák, J. (Ed.) Diptera Slovenska 2 (Cyclorrhapha). /Diptera of Slovakia 2/. Bratislava, Slovakia, Veda.Google Scholar
Čepelák, J. & Vaňhara, J. (1997) Tachinidae. pp. 100–106 in Chvála, M. (Ed.) Check list of Diptera (Insecta) of the Czech and Slovak Republics. Prague, CR, Karolinum, Charles University Press.Google Scholar
Chao, C., Shi, Y., Zhou, S., Chen, R., Liang, E. & Sun, X. (1998) Tachinidae. pp. 1661–2206 in Xue, W. & Chao, C. (Eds) Flies of China, vol. 2. Shenyang, China, Liaoning Science & Technology Press (in Chinese).Google Scholar
Chesmore, E.D. (2001) Application of time domain signal coding and artificial neural networks to passive acoustical identification of animals. Applied Acoustics 62, 1359–1374.CrossRefGoogle Scholar
Chesmore, E.D. (2004) Automated bioacoustic identification of species. Anais da Academia Brasileira de Cięncias 76, 435–440.Google ScholarPubMed
Colwell, R.R. (1970) Polyphasic taxonomy of the genus Vibrio: numerical taxonomy of Vibrio cholerae, Vibrio parahaemolyticus, and related Vibrio species. Journal of Bacteriology 104, 410–433.CrossRefGoogle ScholarPubMed
Deans, A.R. & Kawada, R. (2008) Alobevania, a new genus of neotropical ensign wasps (Hymenoptera: Evaniidae), with three new species: integrating taxonomy with the World Wide Web. Zootaxa 1787, 28–44.CrossRefGoogle Scholar
Do, M.T., Harp, J.M. & Norris, K.C. (1999) A test of a pattern recognition system for identification of spiders. Bulletin of Entomological Research 89, 217–224.CrossRefGoogle Scholar
Fedor, P., Malenovský, I., Vaňhara, J., Sierka, W. & Havel, J. (2008) Thrips (Thysanoptera) identification using artificial neural networks. Bulletin of Entomological Research 98, 437–447.CrossRefGoogle ScholarPubMed
Fedor, P., Vaňhara, J., Havel, J., Malenovský, I. & Spellerberg, I. (2009) Artificial intelligence in pest insect monitoring. Systematic Entomology 34, 398–400.CrossRefGoogle Scholar
Francoy, T.M., Wittmann, D., Drauschke, M., Müller, S., Steinhage, V., Bezerra-Laure, M.A.F., De Jong, D. & Gonçalves, L.S. (2008) Identification of Africanized honey bees through wing morphometrics: two fast and efficient procedures. Apidologie 39, 488–494.CrossRefGoogle Scholar
Hernández-Borges, J., Corbella-Tena, R., Rodriguez-Delgado, M.A., Garcia-Montelongo, F.J. & Havel, J. (2004) Content of aliphatic hydrocarbons in limpets (Patella) as a new way for classification of species using Artificial Neural Networks. Chemosphere 54, 1059–1069.CrossRefGoogle ScholarPubMed
Herting, B. (1984) Catalogue of Palearctic Tachinidae (Diptera). Stuttgarter Beiträge zur Naturkunde, Serie A (Biologie) 383, 1–137.Google Scholar
Herting, B. & Dely-Draskovits, Á. (1993) Tachinidae. pp. 118–458 in Soós, Á. & Papp, L. (Eds) Catalogue of Palaearctic Diptera, vol. 13. Budapest, Hungary, Hungarian Natural History Museum.Google Scholar
La Salle, J., Wheeler, Q., Jackway, P., Winterton, S., Hobern, D. & Lovell, D. (2009) Accelerating taxonomic discovery through automated character extraction. Zootaxa 2217, 43–55.CrossRefGoogle Scholar
MacLeod, N. (Ed.) (2008) Automated Taxon Identification in Systematics. Theory, Approaches and Applications. The Systematics Association, special vol. 74, Boca Raton, FL, USA, CRC Press.Google Scholar
MacLeod, N., O'Neill, M. & Walsh, S.A. (2007) A comparison between morphometric and Artificial Neural Network approaches to the automated species recognition problem in systematic. pp. 37–62 in Curry, G.B. & Humphries, C.J. (Eds) Biodiversity Databases: Techniques, Politics, and Applications. The Systematics Association, special vol. 73. Boca Raton, FL, USA, CRC Press.CrossRefGoogle Scholar
Marcondes, C.B. & Borges, P.S. (2000) Distinction of males of the Lutzomyia intermedia (Lutz & Neiva, 1912) species complex by ratios between dimensions and by an Artificial Neural Network (Diptera: Psychodidae, Phlebotominae). Memorias del Instituto de Oswaldo Cruz, Rio de Janeiro 95, 685–688.Google ScholarPubMed
Mesnil, L.P. (1966) Larvaevorinae (Tachininae). pp. 881–928 in Lindner, E. (Ed.) Die Fliegen der Palaearktischen Region 64 g. Stuttgart, Germany, Schweizerbart.Google Scholar
Mihályi, F. (1986) Fürkészlegyek – Aszkalegyek, Tachinidae – Rhinophoridae. Fauna Hungarica 161(15), 425 pp. Budapest, Hungary, Akadémiai Kiadó (in Hungarian).Google Scholar
Miller, S.E. (2007) DNA barcoding and the renaissance of taxonomy. Proceedings of the National Academy of Sciences of the USA 104, 4775–4776. Available online at http://www.pnas.org/content/104/12/4775.full (accessed March 2010).CrossRefGoogle ScholarPubMed
Moore, A. (1991) Artificial Neural Network trained to identify mosquitoes in flight. Journal of Insect Behavior 4, 391–396.CrossRefGoogle Scholar
Moore, A. & Miller, R.H. (2002) Automated identification of optically sensed aphid (Homoptera: Aphidae) wingbeat waveforms. Annals of the Entomological Society of America 95, 1–8.CrossRefGoogle Scholar
Moritz, G., Morris, D.C. & Mound, L.A. (2001) Thrips ID: Pest Thrips of the World. CD ROM. Collingwood, Australia, ACIAR, CSIRO Publishing.Google Scholar
Novotná, H., Vaňhara, J., Tóthová, A., Muráriková, N., Bejdák, P. & Rozkošný, R. (2009) Identification and taxonomy of the West Palaearctic species of Tachina Meigen (Tachinidae, Diptera) based on male terminalia and molecular analyses. Entomologica Fennica 20, 139–169.CrossRefGoogle Scholar
O'Hara, J.E., Shima, H. & Zhang, C. (2009) Annotated Catalogue of the Tachinidae (Insecta Diptera) of China. Zootaxa 2190, 1–236.Google Scholar
O'Neill, M.A. (2007) DAISY: A practical computer-based tool for semi-automated species identification. pp. 101–114 in MacLeod, N. (Ed.) Automated Taxon Identification in Systematics: Theory, Approaches and Applications. The Systematics Association, special vol. 74, Boca Raton, FL, USA, CRC Press. Available online at http://www.tumblingdice.co.uk/daisy/ (accessed March 2010).CrossRefGoogle Scholar
Platnick, N.I., Russell, K.N. & Do, M.T. (2005) SPIDA. SPecies IDentified Automatically: A neural network based automated identification system for biological species. Available online at http://research.amnh.org/invertzoo/spida/common/index.htm (accessed March 2010).Google Scholar
Russell, K.N., Do, M.T., Huff, J.C. & Platnick, N.I. (2008) Introducing SPIDA-Web: wavelets, neural networks and internet accessibility in an image-based automated identification system. pp. 131–152 in MacLeod, N. (Ed.) Automated Taxon Identification in Systematics: Theory, Approaches and Applications. The Systematics Association, special vol. 74, Boca Raton, FL, USA, CRC Press.Google Scholar
Tóthová, A., Bryja, J., Bejdák, P. & Vaňhara, J. (2006) Molecular markers used in phylogenetic studies of Diptera with a methodological overview. Dipterologica Bohemoslovaca. vol. 13. Acta Universitatis Carolinae: Biologica 50, 125–133.Google Scholar
Tóthová, A., Knoz, J., Sonnek, R., Bryja, J. & Vaňhara, J. (2008) Taxonomic problems in the subgenus Meloehelea Wirth of the genus Atrichopogon Kieffer (Diptera: Ceratopogonidae) inferred from both morphological and molecular characters. Entomologica Fennica 19, 1–12.CrossRefGoogle Scholar
Tschorsnig, H.-P. & Herting, B. (1994) Die Raupenfliegen (Diptera: Tachinidae) Mitteleuropas: Bestimmungstabellen und Angaben zur Verbreitung und Ökologie der einzelnen Arten. Stuttgarter Beiträge zur Naturkunde, Serie A, No. 506, 1–170. (English translation by Rayner, R. & Raper, C. authorized by Tschorsnig, H.-P.). Available online at http://tachinidae.org.uk/site/downloads.php (accessed March 2010).Google Scholar
Tschorsnig, H.-P., Ziegler, J. & Herting, B. (2003) Tachinid flies (Diptera: Tachinidae) from the Hautes-Alpes, France. Stuttgarter Beiträge zur Naturkunde, Serie A, No. 656, 1–62.Google Scholar
Tschorsnig, H.-P., Bergström, C., Bystrowski, C., Cerretti, P., Hubenov, Z., Raper, C., Richter, V.A., Van de Weyer, G., Vaňhara, J., Zeegers, T. & Ziegler, J. (2004) Fauna Europaea: Diptera, Tachinidae. Fauna Europaea, vers. 1.1. Available online at http://www.faunaeur.org (accessed December 2009).Google Scholar
Vandamme, P., Pot, B., Gills, M., De Vos, P., Kersters, K. & Swings, J. (1996) Polyphasic taxonomy a consensus approach to bacterial systematics. Microbiological Reviews 60, 407–438.CrossRefGoogle ScholarPubMed
Vaňhara, J. & Tschorsnig, H.-P. (2006) Tachinidae Robineau-Desvoidy 1830. in Jedlička, L., Kúdela, M. & Stloukalová, V. (Eds) Checklist of Diptera of the Czech Republic and Slovakia. Electronic, vers. 1. CD ROM edition, ISBN 80-969629-0-6, Bratislava, Slovakia, Comenius University. Available online at http://zoology.fns.uniba.sk/diptera/Titul.htm (accessed December 2009).Google Scholar
Vaňhara, J., Tschorsnig, H.-P. & Barták, M. (2004) New records of Tachinidae (Diptera) from the Czech Republic and Slovakia, with revised check-list. Studia dipterologica 10 (2003), 679–701.Google Scholar
Vaňhara, J., Muráriková, N., Malenovský, I. & Havel, J. (2007) Artificial Neural Networks for fly identification: a case study from the genera Tachina and Ectophasia (Diptera, Tachinidae). Biologia Bratislava 62, 462–469.CrossRefGoogle Scholar
Vaňhara, J., Havel, J. & Fedor, P. (2010) Artificial Neural Networks (ANN) in Entomology. pp. 9–12 in O'Hara, J. (Ed.) The Tachinid Times, vol. 21. Available online at http://www.uoguelph.ca/nadsfly/Tach/TTimes/TT23.pdf (accessed March 2010).Google Scholar
Weeks, P.J.D. & Gaston, K.J. (1997) Image analysis, neural networks, and the taxonomic impediment to biodiversity studies. Biodiversity and Conservation 6, 263–274.CrossRefGoogle Scholar
Weeks, P.J.D., Gauld, I.D., Gaston, K.J. & O'Neill, M.A. (1997) Automating the identification of insects: a new solution to an old problem. Bulletin of Entomological Research 87, 203–211.CrossRefGoogle Scholar
Ziegler, J. & Lange, C.H. (2001) Asselfliegen, Fleischfliegen und Raupenfliegen (Diptera: Rhinophoridae, Sarcophagidae, Tachinidae) aus Südtirol (Italien). Gredleriana 1, 133–170.Google Scholar
Ziegler, J. & Lange, C.H. (2006) Raupenfliegen (Diptera: Tachinidae) aus dem Nationalpark Stilfserjoch (Norditalien): Teil 2. Forest Observer 2/3, 169–204.Google Scholar
Zimin, L.S. & Kolomietz, N.G. (1984) Parasitic Diptera of the USSR fauna (Diptera, Tachinidae): The Key. 233 pp. Novosibirsk, Russia, Nauka.Google Scholar
Zimin, L.S., Zinověva, K.B. & Shtakelberg, A.A. (1970) Tachinidae (Larvaevoridae) Diptera. pp. 678–798 in Shtakelberg, A.A. & Nartshuk, E.P. (Eds) The Key to the Insects of the European Part of the USSR 5(1–2), Leningrad, Russia, Nauka (in Russian).Google Scholar