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Acoustic Species Identification of Korean Myotis Bats (Chiroptera: Vespertilionidae)

  • Yoon, Kwang Bae (Division of Forest Science, College of Forest and Environmental Sciences, Kangwon National University) ;
  • Rahman, M. Mafizur (Division of Forest Science, College of Forest and Environmental Sciences, Kangwon National University) ;
  • Park, Yung Chul (Division of Forest Science, College of Forest and Environmental Sciences, Kangwon National University)
  • 투고 : 2015.11.09
  • 심사 : 2015.11.14
  • 발행 : 2016.02.28

초록

We investigated structure and intensity of 267 echolocation calls that were collected from the five Korean Myotis species (M. nettereri, M. petax, M. ikonnikovi, M. macrodactylus and M. formosus). All the Myotis species produced typical FM call pattern with similar echolocation call shapes and outer shapes, producing steep, downward frequency-modulated calls. A pulse has two harmonies, which consist of the first harmony with wider bandwidth and the second harmony with narrower bandwidth. The PF of the first harmony is higher than that of the second harmony. The typical FM call structure, with two harmonies and wide bandwidth, might be highly related to fast flying and wide screening in the dense forests. In classification of the echolocation calls by DFA, most of calls from the five species could be well correctly classified. All calls of M. nettereri (100% of 17 calls), M. formosus (95.5% of 22 calls) and M. ikonnikovi (85.7% of 70 calls) could be well discriminated from those of the other species, whereas calls of M. petax and M. macrodactylus could be discriminated by 70.4% of 98 calls and 76.7% of 60 calls, respectively. Our results indicate that the five Korean Myotis species can be well identified by the echolocation calls with high correct classification by DFA.

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참고문헌

  1. Bates P, Csorba G, Bumringsri S, Kingston T, Francis C, Rosell- Ambal G, Tabaranza B, Heaney L, Molur S, Srinivasulu C. 2008. Myotis muricola. The IUCN Red List of Threatened Species 2008: e.T14183A4416858. (Downloaded on 07 October 2015).
  2. Fukui D, Agetsuma N, Hill DA. 2004. Acoustic identification of eight species of bat (mammalia: chiroptera) inhabiting forests of southern hokkaido, Japan: potential for conservation monitoring. Zoolog Sci 21: 947-955. https://doi.org/10.2108/zsj.21.947
  3. Jiang T, Sun K, Chou C, Zhang Z, Feng J. 2010. First record of Myotis flavus (Chiroptera: Vespertilionidae) from mainland China and a reassessment of its taxonomic status. Zootaxa 2414: 41-51.
  4. Kingston T, Jones G, Akbar Z, Kunz TH. 1999. Echolocation signal design in Kerivoulinae and Murininae (Chiroptera: Vespertilionidae) from Malaysia. J Zool Lond 249: 359-374. https://doi.org/10.1111/j.1469-7998.1999.tb00771.x
  5. Krusic RA, Neefus CD. 1996. Habitat associations of bat species in the White Mountain National Forest. In: Bats and forest symposium, October 19-21, 1995. (Barclay RMR, Brigham RM, eds). Research Branch, British Columbia Ministry of Forestry, Victoria, BC. pp 185-198.
  6. Lundy M, Teeling EC, Boston ESM, Scott DD, Buckley DJ, Prodohl PA, Marnell F, Montgomery WI. 2011. The shape of sound: Elliptic Fourier Descriptors (EFD) discriminate the echolocation calls of Myotis bats (M.daubentonii, M. nattereri and M. mystacinus). Bioacoustics 20: 101-116. https://doi.org/10.1080/09524622.2011.9753638
  7. Luo JH, Ou W, Liu Y, Wang J, Wang L, Feng J. 2012. Plasticity in echolocation calls of Myotis macrodactylus (Chiroptera: Vespertilionidae): implications for acoustic identification. Acta Theriol 57: 137-143. https://doi.org/10.1007/s13364-011-0062-9
  8. Murray KL, Britzke ER, Hadley BM, Robbins LW. 1999. Surveying bat communities: a comparison between mist nets and the Anabat II bat detector system. Acta Chiropterol 1: 105-112.
  9. Parsons S, Boonman AJ, Obrist MK. 2000. Advantages and disadvantages of techniques for transforming and analyzing chiropteran echolocation calls. J Mammal 81: 927-938. https://doi.org/10.1644/1545-1542(2000)081<0927:AADOTF>2.0.CO;2
  10. Parsons S, Jones G. 2000. Acoustic identification of twelve species of echolocating bat by discriminant function analysis and artificial neural networks. J Exp Biol 203: 2641-2656.
  11. Pettersson L. 1999. Time expansion ultrasound detectors. In: Proceedings of the 3rd European Bat Detector Workshop (Harbusch C, ed). Musee national d'histoire naturelle, Luxembourg, pp 21-34, 141 pp.
  12. Russo D, Jones G, Arlettaz R. 2007. Echolocation and passive listening by foraging mouse-eared bats Myotis myotis and M. blythii. J Exp Biol 210: 166-176. https://doi.org/10.1242/jeb.02644
  13. Russo D, Jones G. 2002. Identification of twenty-two bat species (Mammalia: Chiroptera) from Italy by analysis of time-expanded recordings of echolocation calls. J Zool Lond 258: 91-103. https://doi.org/10.1017/S0952836902001231
  14. Russo D, Jones, G, Mucedda M. 2001. Influence of age, sex and body size on echolocation calls of Mediterranean (Rhinolophus euryale) and Mehely's (Rhinolophus mehelyi) horseshoe bats (Chiroptera: Rhinolophidae). Mammalia 65: 429-436.
  15. Vaughan N, Jones G, Harris S. 1997. Identification of British bat species by multivariate analysis of echolocation parameters. Bioacoustics 7: 189-207. https://doi.org/10.1080/09524622.1997.9753331
  16. Veselka N, McGuire LP, Dzal YA, Hooton LA, Fenton MB. 2013. Spatial variation in the echolocation calls of the little brown bat (Myotis lucifugus). Can J Zoolog 91: 795-801. https://doi.org/10.1139/cjz-2013-0094
  17. Zingg PE. 1990. Akustische Artidentikation von Fledermausen (Mammalia: Chiroptera) in der Schweiz. Rev Suisse Zool 97: 263-294. https://doi.org/10.5962/bhl.part.92388