Comparing the results of four widely used automated bat identification software programs to identify nine bat species in coastal Western Europe
DOI:
https://doi.org/10.26496/bjz.2018.21Keywords:
bats, Chiroptera, echolocation, automated bat identification softwareAbstract
Commercially available automated bat identification software packages are widely used in environmental studies to identify bat species from recordings of bat echolocation calls. Caution is, however, needed if the results are used without further verification, as the programs do not guarantee that the results are correct, and wrong species identifications often happen. Taking automated species identifications for granted might hence lead to erroneous conclusions in environmental studies.
The goal of our study was to objectively assess the performance of four commercially available and commonly used automated identification software programs by processing an identical reference dataset with all four programs. The reference dataset consisted of nine species selected based on their preference for open habitats in Western Europe or because they occur as vagrants at sea and therefore are vulnerable to the development of onshore and offshore wind farms. Offshore areas are being increasingly examined, as recent studies have identified possible conflicts of offshore wind farms and certain bat species.
In our test, we included two automated identification programs that have not yet been tested in other studies, and a reference dataset from a different geographical region (Western-Europe) with a different species composition compared to other studies. Our data hence add to the knowledge base needed for an appropriate assessment of the reliability of analytical software.
In general, BatIdent (77% correct species identifications) and Kaleidoscope (71%) seem to be relatively reliable while the performance of BatExplorer (31%) is relatively poor. SonoChiro correctly identified 65% of the sequences to species level. While the tested programs may be considered valuable tools to detect bat calls from the recordings, a trained bat expert needs to cross-check the automated species identifications to avoid erroneous conclusions. Our test hence affirms the conclusions of previous studies in Northern Europe and the USA.
References
Ahlén I. & Baagøe H.J. (1999). Use of ultrasound detectors for bat studies in Europe: experiences from field identification, surveys, and monitoring. Acta Chiropterologica, 1 (2): 137–150.
Barataud M. (2015). Acoustic Ecology of European Bats. Species identification, habitat studies and foraging behaviour. Biotope - National Museum of Natural History, Paris.
Barclay R.M. (1999). Bats are not birds - a cautionary note on using echolocation calls to identify bats: a comment. Journal of Mammalogy, 80: 290–296.
Biotope (2013). Notice de SonoChiro 3.0. Biotope, Recherche & Développement, 18p.
EcoObs (2013). Manual for BatIdent. Version 1.5, 12p.
EcoObs (2014). Manual bcAdmin 3.0. Version 1.05, 47p.
Fenton M.B. & Simmons N.B. (2014). Bats: a World of Science and Mystery. Chicago, University of Chicago Press.
Herr A., Klomp N.I. & Atkinson J.S. (1997). Identification of bat echolocation calls using a decision tree classification system. Complexity International, 4: 1–10.
Kalko E.K.V. (1995). Insect pursuit, prey capture and echolocation in pipestirelle bats (Microchiroptera). Animal Behaviour, 50 (4): 861–880.
Lagerveld S., Jonge Poerink B., Haselager R. & Verdaat H. (2014). Bats in Dutch offshore wind farms in autumn 2012. Lutra, 57 (2): 61–69.
Lagerveld S., Gerla D., Tjalling van der Wal J., de Vries P., Brabant R., Stienen E., Deneudt K., Manshanden J. & Scholl M. (2017). Spatial and Temporal Occurrence of Bats in the Southern North Sea Area. Wageningen Marine Research (University & Research Centre), Wageningen Marine Research report C090/17, 52 p.
Lemen C., Freeman P., White J.A., Andersen B.R. (2015). The problem of low agreement among automated identification programs for acoustical surveys of bats. Western North American Naturalist. 75(2): 218–225. https://doi.org/10.3398/064.075.0210
Neuweiler G. (1989). Foraging ecology and audition in echolocating bats. Trends in Ecology & Evolution, 4 (6): 160–166.
Obrist M. K. (1995). Flexible bat echolocation: the influence of individual, habitat, and conspecifics on sonar design. Behavorial Ecology and Sociobiology, 36: 207–219.
Parsons S. & Jones G. (2000). Acoustic identification of twelve species of echolocating bat by discriminant function analysis and artificial neural networks. Journal of Experimental Biology, 203: 2641–2656.
Parson S. & Szewczak J.M. (2009). Detecting, recording, and analyzing the vocalizations of bats. In: Kunz T.H. & Parsons S. (eds) Ecological and Behavioral Methods for the Study of Bats. 2nd edition: 91 – 111. Baltimore, Johns Hopkins University Press.
Runkel V. & Gerding G. (2016). Akustische Erfassung, Bestimmung und Bewertung von Fledermausaktivität. Germany.
Russo D. & Jones G. (2002). Identification of twenty-two bat species (Mammalia: Chiroptera) from Italy by analysis of time-expanded recordings of echolocation calls. Journal of Zoology, 258 (1): 91 – 103. https://doi.org/10.1017/S0952836902001231
Russo D. & Voigt C.C. (2016). The use of automated identification of bat echolocation calls in acoustic monitoring: A cautionary note for a sound analysis. Ecological Indicators, 66: 598 – 602. https://doi.org/10.1016/j.ecolind.2016.02.036
Russo D., Ancillotto L. & Jones G. (2018). Bats are still not birds in the digital era: echolocation call variation and why it matters for bat species identification. Canadian Journal of Zoology, 96 (2): 63 – 78. https://doi.org/10.1139/cjz-2017-0089
Rydell J., Nyman S., Eklöf J., Jones G. & Russo D. (2017). Testing the performance of automated identification of bat echolocation calls: A request for prudence. Ecological Indicators, 78: 416 – 420. https://doi.org/10.1016/j.ecolind.2017.03.023
Rydell J., Nyman S., Eklöf J., Jones G. & Russo D. (2018). Corrigendum to “Testing the performance of automated identification of bat echolocation calls: A request for prudence” [Ecol. Indic. 78 (2017): 416–422]. Ecological Indicators, 78: 273. https://doi.org/10.1016/j.ecolind.2017.08.070
Skiba R. (2009). Europäische Fledermäuse. Westarp Wissenschaften, Hohenwarsleben.
Vaughan N., Jones G. & Harris S. (1997). Identification of British bat species by multivariate analysis of echolocation call parameters. Bioacoustics, 7 (3): 189–207. https://doi.org/10.1080/09524622.1997.9753331
Downloads
Published
How to Cite
Issue
Section
License
All published papers will be put on-line as high resolution PDF’s. Copyright thus remains with the authors. All manuscripts will be licensed under a Creative Commons Attribution 3.0 License https://creativecommons.org/licenses/by/4.0/.