Challenges of Using Bioacoustics to Globally Monitor Bats

  • Charlotte L. Walters
  • Alanna Collen
  • Tim Lucas
  • Kim Mroz
  • Catherine A. Sayer
  • Kate E. JonesEmail author


As bats are important biodiversity indicators, monitoring their populations is becoming increasingly important to understand the impacts of global change. Bats leak information about themselves into the environment in the form of ultrasonic calls. Using these calls to globally survey bat populations may offer a more efficient alternative or addition to traditional methods for bat monitoring. We identify three of the most important challenges to the development of a global acoustic bat monitoring programme: the robust identification of acoustic signals, the ability to develop meaningful population trends from acoustic activity, and engaging a global audience to take part. We discuss the rapid progress in all three of these areas, for example, development of comprehensive call libraries, quantitative regional tools for call identification, new statistical methods to monitor trends and a resurgence of interest in the public participation in science and monitoring of nature. We also discuss the important gaps in our knowledge and where resources could be best focused to build a global programme. Specifically, tropical areas present a particular challenge: they have high species-richness; species acoustic diversity is poorly documented; call similarity of species is very high, making robust call identification more challenging; and traditionally these areas have had a lower citizen engagement in biodiversity monitoring.


Discrete Wavelet Transform Acoustic Signal Automate Speech Recognition Discriminant Function Analysis Echolocation Call 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.



We thank Michel Barataud, Roger Coles, Christian Dietz, Brock Fenton, Dai Fukui, Gareth Jones, David Jacobs, Richard Jenkins, Nancy Jennings, Elisabeth Kalko, Martin Obrist, Stuart Parsons, Sebastien Puechmaille, and Thomas Sattler for contributing calls to EchoBank, Bernd Brandt for assistance using PhyloPars, and an anonymous reviewer and editor Rick Adams for invaluable comments on a previous version of this manuscript.


  1. Aanensen DM, Huntley DM, Feil EJ, al-Own F, Spratt BG (2009) EpiCollect: linking smartphones to web applications for epidemiology, ecology and community data collection. PLoS One 4(9):e6968PubMedCrossRefGoogle Scholar
  2. Ahlen I, Baagoe H (1999) Use of ultrasound detectors for bat studies in Europe: experiences from field identification, surveys, and monitoring. Acta Chiropterol 1:137–150Google Scholar
  3. Armitage DW, Ober HK (2010) A comparison of supervised learning techniques in the classification of bat echolocation calls. Ecol Inform 5:465–473CrossRefGoogle Scholar
  4. Barclay RMR (1999) Bats are not birds: a cautionary note on using echolocation calls to identify bats: a comment. J Mammal 80:290–296CrossRefGoogle Scholar
  5. Battersby J (2010) Guidelines for surveillance and monitoring of European bats. EUROBATS Publication Series No. 5. UNEP/EUROBATS Secretariat, Bonn, GermanyGoogle Scholar
  6. Bazley EN (1976) Sound absorption in air at frequencies up to 100 kHz. NPL Acoustics Report Ac 74, National Physics LaboratoryGoogle Scholar
  7. Beyer HL (2004) Hawths analysis tools for ArcGIS.
  8. Brandes TS (2008) Feature vector selection and use with Hidden Markov Models to identify frequency-modulated bioacoustic signals amidst noise. IEEE Trans Audio Speech Lang Processing 16:1173–1180. doi: 10.1109/TASL.2008.925872 CrossRefGoogle Scholar
  9. Britzke ER, Duchamp JE, Murray KL et al (2011) Acoustic identification of bats in the eastern United States: a comparison of parametric and nonparametric methods. J Wildl Manage 75:660–667. doi: 10.1002/jwmg.68 CrossRefGoogle Scholar
  10. Brooks RT (2011) Declines in summer bat activity in central New England 4 years following the initial detection of white-nose syndrome. Biodivers Conserv 20:2537–2541. doi: 10.1007/s10531-011-9996-0 CrossRefGoogle Scholar
  11. Bruggeman J, Heringa J, Brandt BW (2009) PhyloPars: estimation of missing parameter values using phylogeny. Nucleic Acids Res 37:W179–W184. doi: 10.1093/nar/gkp370 PubMedCrossRefGoogle Scholar
  12. Buckley D, Puechmaille S, Roche N, Teeling E (2011) A critical assessment of the presence of Barbastella barbastellus and Nyctalus noctula in Ireland with a description of N. leisleri echolocation calls from Ireland. Hystrix Ital J Mammal 22:111–127. doi: 10.4404/Hystrix-22.1.4472 Google Scholar
  13. Campbell G, Gisiner RC, Helweg DA, Milette LL (2002) Acoustic identification of female Steller sea lions (Eumetopias jubatus). J Acoust Soc Am 111:2920–2928PubMedCrossRefGoogle Scholar
  14. Chesmore D (2004) Automated bioacoustic identification of species. Ann Braz Acad Sci 76:435–440Google Scholar
  15. Collen A (2012) The evolution of echolocation. PhD thesis, University College LondonGoogle Scholar
  16. Davis SB, Mermelstein P (1980) Comparison of parametric representations for monosyllabic word recognition in continuously spoken sentences. IEEE Trans Acoust 28:357–366CrossRefGoogle Scholar
  17. Doupe AJ, Kuhl PK (1999) Birdsong and human speech: common themes and mechanisms. Annu Rev Neurosci 22:567–631. doi: 10.1146/annurev.neuro.22.1.567 PubMedCrossRefGoogle Scholar
  18. Dudley H, Balashek S (1958) Automatic recognition of phonetic patterns in speech. J Acoust Soc Am 30:721–733CrossRefGoogle Scholar
  19. ESRI (2008) ArcGIS v.9.3. Redlands, CAGoogle Scholar
  20. Estrada-Villegas S, Meyer CFJ, Kalko EKV (2010) Effects of tropical forest fragmentation on aerial insectivorous bats in a land-bridge island system. Biol Conserv 143:597–608. doi: 10.1016/j.biocon.2009.11.009 CrossRefGoogle Scholar
  21. Fagerlund S (2007) Bird species recognition using support vector machines. EURASIP J Adv Signal Process 2007:1–8. doi: 10.1155/2007/38637 CrossRefGoogle Scholar
  22. Fukui D, Agetsuma N, Hill D (2004) Acoustic identification of eight species of bat (Mammalia: Chiroptera) inhabiting forests of southern Hokkaido, Japan: potential for conservation monitoring. Zool Sci 21:947–955. doi: 10.2108/zsj.21.947 PubMedCrossRefGoogle Scholar
  23. Ganchev T, Potamitis I, Fakotakis N (2007) Acoustic monitoring of singing insects. Proceedings of the 2007 IEEE international conference on acoustics, speech and signal processing – ICASSP’07. IEEE, pp 721–724Google Scholar
  24. Greenwood DD (1961) Critical bandwidth and the frequency coordinates of the basilar membrane. J Acoust Soc Am 33:1344–1356CrossRefGoogle Scholar
  25. Griffin D (1958) Listening in the dark. Yale University Press, New Haven, CTGoogle Scholar
  26. Griffin D, Galambos R (1941) The sensory basis of obstacle avoidance by flying bats. J Exp Zool 86:481–586CrossRefGoogle Scholar
  27. Griffin DR, Webster FA, Michael CR (1960) The echolocation of flying insects by bats. Anim Behav 8:141–154CrossRefGoogle Scholar
  28. Harris JG, Skowronski MD (2006) Automatic speech processing methods for bioacoustic signal analysis: a case study of cross-disciplinary acoustic research. Proceedings of the 2006 IEEE international conference on acoustics, speech and signal processing – ICASSP’06. pp 793–796Google Scholar
  29. Hayes J (2000) Assumptions and practical considerations in the design and interpretation of echolocation-monitoring studies. Acta Chiropterol 2:225–236Google Scholar
  30. Hayes J, Ober H, Sherwin R (2009) Survey and monitoring of bats. In: Kunz T, Parsons S (eds) Ecological and behavioral methods for the study of bats, 2nd edn. John Hopkins University Press, Baltimore, MD, pp 112–129Google Scholar
  31. Haysom KA (2008) Streamlining European 2010 biodiversity indicators (SEBI 2010): developing a methodology for using bats as indicator species; and testing the usability of GBIF data for use in 2010 biodiversity indicators, European environment agency technical report series. European Environment Agency, CopenhagenGoogle Scholar
  32. Heller K, Von Helversen O (1989) Resource partitioning of sonar frequency bands in rhinolophoid bats. Oecologia 80:178–186Google Scholar
  33. Hughes A, Satasook C, Bates P et al (2010) Echolocation call analysis and presence-only modelling as conservation monitoring tools for Rhinolophoid bats in Thailand. Acta Chiropterol 12:311–327CrossRefGoogle Scholar
  34. Hutchinson JMC, Waser PM (2007) Use, misuse and extensions of “ideal gas” models of animal encounter. Biol Rev 82:335–359PubMedCrossRefGoogle Scholar
  35. IUCN (2012) IUCN red list of threatened species version 2012.14.
  36. Jaberg C, Guisan A (2001) Modelling the distribution of bats in relation to landscape structure in a temperate mountain environment. J Appl Ecol 38:1169–1181CrossRefGoogle Scholar
  37. Jennings N, Parsons S, Pocock MJO (2008) Human vs. machine: identification of bat species from their echolocation calls by humans and by artificial neural networks. Can J Zool 86:371–377. doi: 10.1139/Z08-009 CrossRefGoogle Scholar
  38. Jones G, Siemers BM (2011) The communicative potential of bat echolocation pulses. J Comp Physiol A Neuroethol Sens Neural Behav Physiol 197:447–457. doi: 10.1007/s00359-010-0565-x PubMedCrossRefGoogle Scholar
  39. Jones G, Teeling E (2006) The evolution of echolocation in bats. Trends Ecol Evol 21:149–156. doi: 10.1016/j.tree.2006.01.001 PubMedCrossRefGoogle Scholar
  40. Jones G, Jacobs D, Kunz T et al (2009a) Carpe noctem: the importance of bats as bioindicators. Endanger Species Res 8:93–115. doi: 10.3354/esr00182 CrossRefGoogle Scholar
  41. Jones KE, Bielby J, Cardillo M et al (2009b) PanTHERIA: a species-level database of life history, ecology, and geography of extant and recently extinct mammals. Ecology 90:2648–2648. doi: 10.1890/08-1494.1 CrossRefGoogle Scholar
  42. Jones KE, Russ J, Bashta A-T et al (2013) Indicator bats program: a system for the global acoustic monitoring of bats. In: Collen B, Pettorelli N, Baillie JEM, Durant S (eds) Biodiversity monitoring and conservation: bridging the gaps between global commitment and local action. Wiley, London, pp 211–247. doi: 10.1002/9781118490747.ch10 CrossRefGoogle Scholar
  43. Kalko EV, Schnitzler H-U (1993) Plasticity in echolocation signals of European Pipistrelle bats in search flight: implications for habitat use and prey detection. Behav Ecol Sociobio 33:415–428. doi: 10.1007/BF00170257 CrossRefGoogle Scholar
  44. Kéry M, Royle JA, Schmid H et al (2010) Site-occupancy distribution modeling to correct population-trend estimates derived from opportunistic observations. Conserv Biol 24:1388–1397. doi: 10.1111/j.1523-1739.2010.01479.x PubMedCrossRefGoogle Scholar
  45. Kofoky A, Andriafidison D, Ratrimomanarivo F et al (2006) Habitat use, roost selection and conservation of bats in Tsingy De Bemaraha National Park, Madagascar. Biodivers Conserv 16:1039–1053. doi: 10.1007/s10531-006-9059-0 CrossRefGoogle Scholar
  46. Korine C, Kalko EK (2001) Toward a global bat-signal database. IEEE Eng Med Biol 20:81–85CrossRefGoogle Scholar
  47. Kossel M (1993) Evidence for a mechanical filter in the cochlea of the ‘constant frequency’ bats, Rhinolophus rouxi and Pteronotus parnellii. Hear Res 72:73–80CrossRefGoogle Scholar
  48. Kunz T, Brock C (1975) A comparison of mist nets and ultrasonic detectors for monitoring flight activity of bats. J Mammal 58:309–315CrossRefGoogle Scholar
  49. Kunz TH, Arnett E, Erickson W et al (2007) Ecological impacts of wind energy development on bats: questions, research needs, and hypotheses. Front Ecol Environ 5:315–324CrossRefGoogle Scholar
  50. Larsen RJ, Boegler KA, Genoways HH et al (2007) Mist netting bias, species accumulation curves, and the rediscovery of two bats on Montserrat (Lesser Antilles). Acta Chiropterol 9:423–435. doi: 10.3161/1733-5329(2007)9[423:MNBSAC]2.0.CO;2 CrossRefGoogle Scholar
  51. Lee C-H, Lee Y-K, Huang R-Z (2006) Automatic recognition of bird songs using Cepstral Coefficients. J Inform Technol Appl 1:17–23Google Scholar
  52. Limpens H (2004) Field identification: using bat detectors to identify species. In: Brigham M, Kalko EKV, Jones G et al (eds) Bat echolocation research: tools, techniques and analysis. Bat Conservation International, Austin, TX, pp 46–57Google Scholar
  53. Lundy M, Teeling E, Boston E et al (2011) The shape of sound: elliptic fourier descriptors (EFD) discriminate the echolocation calls of Myotis bats (M. daubentonii, M. nattereri & M. mystacinus). J Bioacoust 20:101–116CrossRefGoogle Scholar
  54. MacSwiney MC, Clarke FM, Racey P (2008) What you see is not what you get: the role of ultrasonic detectors in increasing inventory completeness in neotropical bat assemblages. J Appl Ecol 45:1364–1371. doi: 10.1111/j.1365-2664.2008.01531.x CrossRefGoogle Scholar
  55. Meyer CFJ, Aguiar LMS, Aguirre LF et al (2011) Accounting for detectability improves estimates of species richness in tropical bat surveys. J Appl Ecol 48:777–787. doi: 10.1111/j.1365-2664.2011.01976.x CrossRefGoogle Scholar
  56. Mirzaei G, Majid MW, Ross J, et al. (2012) The BIO-acoustic feature extraction and classification of bat echolocation calls. 2012 IEEE international conference on electro/information technology. doi: 10.1109/EIT.2012.6220700
  57. Murray SO, Mercado E, Roitblat HL (1998) The neural network classification of false killer whale (Pseudorca crassidens) vocalisations. J Acoust Soc Am 104:3626–3633PubMedCrossRefGoogle Scholar
  58. Murray K, Britzke E, Robbins L (2001) Variation in search phase calls of bats. J Mammal 82:728–737CrossRefGoogle Scholar
  59. O’Farrell MJ, Gannon WL (1999) A comparison of acoustic versus capture techniques for the inventory of bats. J Mammal 80:24–30CrossRefGoogle Scholar
  60. Obrist MK (1995) Flexible bat echolocation: the influence of individual, habitat and conspecifics on sonar signal design. Behav Ecol Sociobiol 36:207–219CrossRefGoogle Scholar
  61. Obrist MK, Boesch R, Flückiger PF (2004) Variability in echolocation call design of 26 Swiss bat species: consequences, limits and options for automated field identification with a synergetic pattern recognition approach. Mammalia 68:307–322. doi: 10.1515/mamm.2004.030 CrossRefGoogle Scholar
  62. Ochoa JG, O’Farrell MJ, Miller BW (2000) Contribution of acoustic methods to the study of insectivorous bat diversity in protected areas from northern Venezuela. Acta Chiropterol 2:171–183Google Scholar
  63. Papadatou E, Butlin RK, Altringham JD (2008) Identification of bat species in Greece from their echolocation calls. Acta Chiropterol 10:127–143. doi: 10.3161/150811008X331153 CrossRefGoogle Scholar
  64. Parmesan C (2006) Ecological and evolutionary responses to recent climate change. Annu Rev Ecol Evol Syst 37:637–669. doi: 10.1146/annurev.ecolsys.37.091305.110100 CrossRefGoogle Scholar
  65. Parsons S (2001) Identification of New Zealand bats (Chalinolobus tuberculatus and Mystacina tuberculata) in flight from analysis of echolocation calls by artificial neural networks. J Zool 253:447–456. doi: 10.1017/S0952836901000413 CrossRefGoogle Scholar
  66. Parsons S, Jones G (2000) Acoustic identification of twelve species of echolocating bat by discriminant function analysis and artificial neural networks. J Exp Biol 203:2641–2656PubMedGoogle Scholar
  67. Parsons S, Szewczak JM (2009) Detecting, recording, and analyzing the vocalizations of bats. In: Kunz TH, Parsons S (eds) Ecological and behavioral methods for the study of bats. John Hopkins University Press, Baltimore, MD, pp 91–111Google Scholar
  68. Parsons S, Boonman A, Obrist MK (2000) Advantages and disadvantages of techniques for transforming and analyzing Chiropteran echolocation calls. J Mammal 81:927–938CrossRefGoogle Scholar
  69. Patriquin K, Hogberg L, Chruszcz B, Barclay R (2003) The influence of habitat structure on the ability to detect ultrasound using bat detectors. Wildl Soc Bull 31:475–481Google Scholar
  70. Preatoni DG, Nodari M, Chirichella R et al (2005) Identifying bats from time-expanded recordings of search calls: comparing classification methods. J Wildl Manage 69:1601–1614CrossRefGoogle Scholar
  71. Puechmaille SJ, Frick WF, Kunz TH et al (2011) White-nose syndrome: is this emerging disease a threat to European bats? Trends Ecol Evol 26:573–579. doi: 10.1016/j.tree.2011.06.013 CrossRefGoogle Scholar
  72. Rebelo H, Tarroso P, Jones G (2009) Predicted impact of climate change on European bats in relation to their biogeographic patterns. Glob Change Biol 16:561–576. doi: 10.1111/j.1365-2486.2009.02021.x CrossRefGoogle Scholar
  73. Redgwell RD, Szewczak JM, Jones G, Parsons S (2009) Classification of echolocation calls from 14 species of bat by support vector machines and ensembles of neural networks. Algorithms 2:907–924. doi: 10.3390/a2030907 CrossRefGoogle Scholar
  74. Roche N, Langton S, Aughney T, Russ J (2011) A car-based monitoring method reveals new information on bat populations and distributions in Ireland. Anim Conserv 14:642–651CrossRefGoogle Scholar
  75. Rodhouse TJ, Ormsbee PC, Irvine KM, Vierling LA, Szewczak JM, Vierling KT (2012) Assessing the status and trend of bat populations across broad geographic regions with dynamic distribution models. Ecol Appl 22:1098–1113PubMedCrossRefGoogle Scholar
  76. Rowcliffe JM, Field J, Turvey S, Carbone C (2008) Estimating animal density using camera traps without the need for individual recognition. J Appl Ecol 45:1223–1236. doi: 10.1111/j.1365-2664.2008.01473.x CrossRefGoogle Scholar
  77. Roy HE, Pocock MJO, Preston CD, Roy DB, Savage J, Tweddle JC, Robinson LD (2012) Understanding citizen science & environmental monitoring. Final report on behalf of UK-EOF. NERC Centre for Ecology & Hydrology and Natural History MuseumGoogle Scholar
  78. Russo D, Jones G (2003) Use of foraging habitats by bats in a Mediterranean area determined by acoustic surveys: conservation implications. Ecography 26:197–209. doi: 10.1034/j.1600-0587.2003.03422.x CrossRefGoogle Scholar
  79. Schnitzler H-U, Moss CF, Denzinger A (2003) From spatial orientation to food acquisition in echolocating bats. Trends Ecol Evol 18:386–394. doi: 10.1016/S0169-5347(03)00185-X CrossRefGoogle Scholar
  80. Siemers BM, Beedholm K, Dietz C et al (2005) Is species identity, sex, age or individual quality conveyed by echolocation call frequency in European horseshoe bats? Acta Chiropterol 7:259–274. doi: 10.3161/1733-5329(2005)7[259:ISISAO]2.0.CO;2 CrossRefGoogle Scholar
  81. Simmons NB (2005) Order Chiroptera. In: Wilson DE, Reeder DM (eds) Mammal species of the world: a taxonomic and geographic reference. John Hopkins University Press, Baltimore, MD, pp 312–529Google Scholar
  82. Skowronski MD, Fenton MB (2008) Model-based detection of synthetic bat echolocation calls using an energy threshold detector for initialization. J Acoust Soc Am 123:2643–2650. doi: 10.1121/1.2896752 PubMedCrossRefGoogle Scholar
  83. Struebig MJ, Kingston T, Petit EJ et al (2011) Parallel declines in species and genetic diversity in tropical forest fragments. Ecol Lett 14:582–590PubMedCrossRefGoogle Scholar
  84. Thomas D, Bell G, Fenton M (1987) Variation in echolocation call frequencies recorded from North American Vespertilionid bats: a cautionary note. J Mammal 68:842–847CrossRefGoogle Scholar
  85. Trifa VM, Kirschel ANG, Taylor CE, Vallejo EE (2008) Automated species recognition of antbirds in a Mexican rainforest using hidden Markov models. J Acoust Soc Am 123:2424–2431PubMedCrossRefGoogle Scholar
  86. Tyagi H, Hegde RM, Murthy HA, Prabhakar A (2006) Automatic identification of bird calls using spectral ensemble average voice prints. Proceedings of the european signal processing conference (EUSIPCO), Italy, p 5Google Scholar
  87. Ulanovsky N, Fenton MB, Tsoar A, Korine C (2004) Dynamics of jamming avoidance in echolocating bats. Proc R Soc Lond B Biol Sci 271:1467–1475. doi: 10.1098/rspb.2004.2750 CrossRefGoogle Scholar
  88. Vaughan N, Jones G, Harris S (1997) Habitat use by bats (Chiroptera) assessed by means of a broad-band acoustic method. J Appl Ecol 34:716. doi: 10.2307/2404918 CrossRefGoogle Scholar
  89. Walsh A, Catto C, Hutson T et al (2001) The UK’s national bat monitoring programme final report. Department for Environment, Food and Rural Affairs, LondonGoogle Scholar
  90. Walters CL, Freeman R, Dietz C et al (2012) A continental-scale tool for acoustic identification of European bats. J Appl Ecol 49:1064–1074CrossRefGoogle Scholar
  91. Wickramasinghe LP, Harris S, Jones G, Vaughan N (2003) Bat activity and species richness on organic and conventional farms: impact of agricultural intensification. J Appl Ecol 40:984–993CrossRefGoogle Scholar
  92. Williams S, Wolbert S, Whidden H (2007) Evaluation of the program SCAN’R for sorting ultrasonic recordings of bat vocalisations. Proceedings of the Northeast Bat Working Group, North Branch, NJGoogle Scholar
  93. Zingg PE (1990) Akustische Artidentifikation von Fledermäusen (Mammalia: Chiroptera) in der Schweiz – acoustic species identification of bats (Mammalia, Chiroptera) in Switzerland. Rev Suisse Zool 97:263–294Google Scholar

Copyright information

© Springer Science+Business Media New York 2013

Authors and Affiliations

  • Charlotte L. Walters
    • 1
  • Alanna Collen
    • 2
  • Tim Lucas
    • 2
  • Kim Mroz
    • 2
  • Catherine A. Sayer
    • 1
  • Kate E. Jones
    • 2
    Email author
  1. 1.Institute of Zoology, Zoological Society of LondonLondonUK
  2. 2.Department of Genetics, Evolution and EnvironmentUniversity College LondonLondonUK

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