メヒナコウモリ）の飛翔空間別の音声特徴を音声ラ
１）W i l s o n , D . E . a n d M i t t e r m e i e r , R . A . 2019 .
イブラリーに加えることができれば，種判別可能な
Handbook of the Mammals of the World. Vol.9.
対象種も増えるだろう．
今後，地域ごとに一定の録音条件下での音声ライ
ブラリーとともにモデル音声数を増やすことで，分
Bats. Lynx Editions. 1008 pp.
２）Jones, G., Jacobs, D. S., Kunz, T. H., Willig, M. R
a n d R a c e y , P . A . 2009 . C a r p e n o c t e m : T h e
12
信州大学農学部 AFC 報告 第21号 （2023）
importance of bats as bioindicators. Endangered
com/about–ultrasound–detectors>（2020年11月２
Species Research. 8: 93–115.
日確認）
３）Altringham, J. D. 1996. Bats: Biology and Behavior.
Oxford University Press, 262 pp.
４）船越公威．2020．コウモリ学－適応と進化．東京
大学出版会，299pp．
18）J o n e s , G . 1999 . S c a l i n g o f e c h o l o c a t i o n c a l l
parameters in bats. The Journal of Experimental
Biology. 202: 3359-3367.
19）Papadatou, E., Butlin, R. K. and Altringham, J. D.
５）Kunz, T. H., T. Orrez, E. B., Bauer, D., Lobova, T.
2008. Identification of bat species in Greece from
and Fleming, T. H. 2011. Ecosystem services
their echolocation calls. Acta Chiropterologica. 10:
provided by bats. Annals of the New York
127-143
Academy of Sciences. 1223: 1-38.
20）P a r s o n s , S . a n d J o n e s , G . 2000 . A c o u s t i c
６）Seltzer, C. E., Ndangalasi, H. J. and Cordeiro, N. J.
identification of twelve species of echolocating bat
2013. Seed dispersal in the dark: shedding light on
by discriminant function analysis and artificial
the role of fruit bats in Africa. Bio Tropica.
neural networks. Journal of Experimental Biology.
45: 450-456.
203: 2641-2565.
７）Thavry, H., Cappelle, J., Bumrungsri, S., Thona, L.
21）Rodríguez, S. P. and Simonetti, J. A. 2013. Acoustic
and Furey, N. M. 2017. The diet of the cave nectar
identification of four species of bats (Order
bat (Eonyctaris spelae Dobson) suggests it
Chiroptera) in central Chile. The International
p o l l i n a te s e c o lo g ic a lly s ig n if ic a n t p la n t s i n
Journal of Animal Sound and its Recording. 22:
southern Cambodia. Zoological Studies. 56: 1-17.
165-172.
８）Boyles, J., Cryan, P. M., Mcracken, G. F. and Kunz,
22）S k o w r o n s k i , M . D . a n d F e n t o n , M . B . 2009 .
T . H . 2011 . E c o n o m i c i m p o r t a n c e o f b a t s i n
Detecting Bat calls ： an Analysis of Automated
agriculture. Science. 332: 41-42.
Methods. Actachiroptelogic. 11: 191-203.
９）IUCN. 2020. The IUCN Red list of threatened
23）Barataud, M. 2015. Acoustic Ecology of European
species. <https://www.iucnredlist.org/ja/>（2020
Bats. Species Identification, Study of their
年10月１日確認）
Habitats and Foraging Behavior. Biotope, Muséum
10）Mickleburgh, S. P., Hutson, A. M. and Racey, P. A.
2002. A review of the global conservation status of
bats. Oryx. 36: 18-24.
national d'Histoire naturelle, Paris (Inventaires et
biodiversite series). 352 pp.
24）Fukui, D., Agetsuma, N. and Hill, A. 2004. Acoustic
11）Racy, P. A. and Entwistle, A. C. 2003. Conservation
identification of bat (Mammalia ： Chiroptera)
ecology of bats. In (Kunz, T. H. and Fenton, M. B.
inhabiting forests of southern Hokkaido, Japan:
eds.) Bat Ecology. The University of Chicago
Potential for conservation monitoring. Zoological
Press, pp. 680-743.
12）長野県．2004．長野県版レッドデータブック～長
Science. 21: 947-955.
25）増田圭祐・松井孝典・福井 大・福井健一・町村 野県の絶滅のおそれのある野生生物～動物編．長
尚．2017．機械学習法を用いたエコロケーション
野県環境部自然保護課，321 pp．
によるコウモリの種判別．哺乳類科学．57：19-33
13）長野県．2015．長野県版レッドリスト～長野県の
26）船越公威．2010．九州産食虫性コウモリ類の超音
絶滅のおそれのある野生動植物～動物編．長野県
波音声による種判別の試み． 哺乳類科学．50：
環境部自然保護課，234 pp．
14）山本輝正・佐藤顕義・勝田節子．2008．長野県に
おけるコヤマコウモリ Nyctalus furvus とクビワコ
ウモリ Eptesicus Japonensis の採集記録．哺乳類科
学48：277-280．
15）庫本 正．1972．秋吉台産コウモリ類の生態およ
び系統動物学的研究． 秋吉台科学博物館報告．
８：7–119．
16）環境省．2020．環境省レッドリスト2020．<http://
www.env.go.jp/press/107905.html>（ 2020 年 ９ 月
21日確認）
17）Pettersson Elektronik AB. 2020. How does an
ultrasound detector work? <https://batsound.
165-175．
27）クビワコウモリを守る会．2019．クビワコウモリ
カウント調査報告．NEWS LETTER．49：３．
28）辻 明子・小柳恭二．2003．長野県佐久市周辺に
おけるヤマコウモリ生活史（予報）
．日本哺乳類学
会2003年度大会要旨集：237．
29）気象庁．2020．過去の気象データ検索．<https://
www.jma.go.jp/jma/index.html>（2020年10月24日
確認）
30）W i l d l i f e A c o u st i c s. 2018 . S o n g M e t e r S M 4 –
Bioacoustics Recorder: User Guide. Wildlife
Acoustics, Inc., Massachusetts, USA. <http://
media.nhbs.com>（2020年８月３日確認）
音声解析によるコウモリ類調査
13
31）Ohdachi, D. S., Ishibashi, Y., Iwasa, M. A., Fukui, D.
2016. Acoustic identification of Mexican bats
and Saitoh,T. 2015. The Wild Mammals of Japan.
based on taxonomic and ecological constraints on
Second Edition. SHOUKADOH Book Sellers and
call design. Methods in Ecology and Evolution. 7:
the Mammal Society of Japan. 506 pp.
1082-1091.
32）佐藤雅彦・村山良子・佐藤理恵・前田喜四雄・浅
43）小松茉利奈・家根橋圭祐・安井さち子・上條隆志．
川満彦 . 2019．北海道からコヤマコウモリの初記
2016．東信地域におけるクビワコウモリ Eptesicus
録．利尻研究．38：85-90．
japonensis 及びノレンコウモリ Myotis bobinus の捕
33）J o n e s , G . , V a u g h a n , N . a n d P a r s o n s , S . 2000 .
Acoustic identification of bats from directly
獲記録．筑波大学農林技術研究報告．４：9-13．
44）近藤憲久・福井 大・倉野飛史・黒澤春樹．2012．
sampled and time–expanded recordings of
北海道網走郡大空町で確認されたヒメヒナコウモ
vocalizations. Acta Chiropterologica. 2: 155-170.
リの出産哺育コロニー．哺乳類科学．52：63-70．
34）Jones, G. 1995. Flight performance, echolocation
45）吉倉智子・渡邊真澄・安井さち子．2011．栃木県
and foraging behavior in noctule bats Nyctalus
におけるコヤマコウモリ Nyctalus furvus の初記録
noctule. Journal of Zoology. 237: 303-312.
と音声構造． 栃木県立博物館研究紀要．28：45-
35）Preatoni, D. G., Nodari, M., Chirichella, R., Tosi, G.,
49．
Wavters, L. and Martinoli, A. 2005. Identifying
46）安藤誠也・前田喜四雄．2021．島根県におけるヒ
bats from time–expanded recording of search
メヒナコウモリ Vespertilio murius linaeus，1758
calls: Comparing classification methods. The
の初確認．島根県立三瓶自然館研究報告．19：39-
Journal of Wildlife Management. 69: 1601-1614.
42．
36）Biscardi, S., Orprecio, J., Fenton, M. B., Tsoar, A.
47）重昆達也・大沢夕志・大沢啓子・峰下 耕・清水
and Ratcliffe, J. M. 2004. Data, sample sizes and
孝頼・向山 満．2013．群馬県の新幹線高架橋で
statistics affect the recognition of species of bats
見つかったヒナコウモリ Vespertilio sinensis の出
by their echolocation calls. Acta Chiropterologica.
産哺育コロニーおよび冬季集団．群馬県立自然史
6: 347-363.
博物館研究報告．17：131-146．
37）Brizke, E. R., Dudhamp, J. E., Murray, K. L.,
48）Sano, A. 2000. Postnatal growth and development
Swalhart, R. K. and Robbins, L. W. 2011. Acoustic
of thermos regulative ability in the Japanese
identification of bats on the eastern United
greater horseshoe bat, Rhinolophus
States ： Comparison of parametric and
ferrumequinum nippon, related to maternal care.
nonparametoric methods. The Journal of Wildlife
Mammal Study. 25: 1-15.
Management. 75: 660-667.
38）Robert, D.R., Szwczak, J. M., Jones, G. and Parsons,
S. 2009. Classification of echolocation calls from 14
49）立神雅宣・柳川 久．2007．北海道帯広市近郊に
おけるヤマコウモリの採餌活動．日本哺乳類学会
2007年度大会プログラム講演要旨集：153．
species of bat by support vector machines and
50）Brown, P. E. and Rainey, W. E. 2018. Bats of the
ensembles of neural networks. Algorithms. 2: 907-
California Channel Islands: New Records with
924.
New Methods. Western North American
39）Kofoky, A. F., Randrianandrianina, F., Russ, J.,
Raharinanteaina, I., Cardiff, S. G., Jenkins, R. K. B.
and Racey, P. A. 2009. Forest bats of Madagascar:
Results of acoustic surveys. Acta Chiropterogica.
11: 375-392.
40）A r m i t a g e , D . W . a n d O b e r , H . K . 2010 . A
comparison of supervised learning techniques in
the classification of bat echolocation calls.
Ecological Informatics. 5: 465-473.
41）山本輝正．2019．Python による機械学習を用いた
コウモリ類の音声による種判別の試み．コウモリ
通信．24：25-31．
42）Zamora-Gutierrez, V., Lopez-Gonzalez, C., Cristina,
M., Fenton, M. B., Jones, G., Kalko, E. K. V.,
Puechmaille, S. J., Stathopoulos, V. and Jones, K. E.
Naturalist. 78: 474-495.
14
信州大学農学部 AFC 報告 第21号 （2023）
Rare high-altitude flying bat distribution survey and their reliability based on acoustic
analysis
Kyoji KOYANAGI＊，＊＊＊・Akiko TAKII＊＊・Shigeyuki IZUMIYAMA＊＊
Shinshu University Graduate School of Science and Technology
Shinshu University Institute of Mountain Science
＊＊
Asian Bat Research Institute
＊＊＊
Summary
There are nineteen bat species distributed in Nagano prefecture, and thirteen species were recorded in
Nagano RED LIST. But, up until now we have few research to assess rare distribution. To assess the
distribution of three endangered high-altitude flying bat species (Nyctalus aviator, Vespertilio sinensis, and
Eptesicus japonensis), we conducted acoustic analysis using time expansion bat detector in Nagano
Prefecture, Japan. We attempted to discriminate species by comparing search-phase calls (model calls) of
bats emerging from their roosts in Saku City and Matsumoto City, and examined the reliability of these
species identifications. We recorded 1,078 echolocation calls across thirty-seven sites. We used cluster
analysis to assess significant differences between species. We detected N. aviator at ten locations, V.
sinensis at seven locations, and E. japonensis at seven locations. The classification accuracy using canonical
discriminant analysis and machine learning were >90%. These results suggest that it is possible to assess
the distribution of rare three bat species using acoustic analysis with high accuracy.
Key words: acoustic analysis, Chiroptera, distribution research, species identification, Nagano prefecture
...
論文の公開元へ
