A practical comparison of manual and autonomous methods for acoustic monitoring

Digby, Andrew, Towsey, Michael W., Bell, Ben D., & Teal, Paul D. (2013) A practical comparison of manual and autonomous methods for acoustic monitoring. Methods in Ecology & Evolution, 4(7), pp. 675-683.

View at publisher

Abstract

  1. Autonomous acoustic recorders are widely available and can provide a highly efficient method of species monitoring, especially when coupled with software to automate data processing. However, the adoption of these techniques is restricted by a lack of direct comparisons with existing manual field surveys. 2. We assessed the performance of autonomous methods by comparing manual and automated examination of acoustic recordings with a field-listening survey, using commercially available autonomous recorders and custom call detection and classification software. We compared the detection capability, time requirements, areal coverage and weather condition bias of these three methods using an established call monitoring programme for a nocturnal bird, the little spotted kiwi(Apteryx owenii). 3. The autonomous recorder methods had very high precision (>98%) and required <3% of the time needed for the field survey. They were less sensitive, with visual spectrogram inspection recovering 80% of the total calls detected and automated call detection 40%, although this recall increased with signal strength. The areal coverage of the spectrogram inspection and automatic detection methods were 85% and 42% of the field survey. The methods using autonomous recorders were more adversely affected by wind and did not show a positive association between ground moisture and call rates that was apparent from the field counts. However, all methods produced the same results for the most important conservation information from the survey: the annual change in calling activity. 4. Autonomous monitoring techniques incur different biases to manual surveys and so can yield different ecological conclusions if sampling is not adjusted accordingly. Nevertheless, the sensitivity, robustness and high accuracy of automated acoustic methods demonstrate that they offer a suitable and extremely efficient alternative to field observer point counts for species monitoring.

Impact and interest:

29 citations in Scopus
Search Google Scholar™
31 citations in Web of Science®

Citation counts are sourced monthly from Scopus and Web of Science® citation databases.

These databases contain citations from different subsets of available publications and different time periods and thus the citation count from each is usually different. Some works are not in either database and no count is displayed. Scopus includes citations from articles published in 1996 onwards, and Web of Science® generally from 1980 onwards.

Citations counts from the Google Scholar™ indexing service can be viewed at the linked Google Scholar™ search.

ID Code: 60659
Item Type: Journal Article
Refereed: Yes
Keywords: acoustic monitoring, bioacoustics, automated animal call recognition, census, research techniques
DOI: 10.1111/2041-210X.12060
ISSN: 2041-210X
Subjects: Australian and New Zealand Standard Research Classification > ENVIRONMENTAL SCIENCES (050000) > ECOLOGICAL APPLICATIONS (050100) > Ecological Applications not elsewhere classified (050199)
Australian and New Zealand Standard Research Classification > BIOLOGICAL SCIENCES (060000) > ZOOLOGY (060800) > Animal Behaviour (060801)
Divisions: Past > Schools > School of Information Technology
Current > QUT Faculties and Divisions > Science & Engineering Faculty
Deposited On: 07 Jun 2013 07:29
Last Modified: 25 Oct 2016 23:41

Export: EndNote | Dublin Core | BibTeX

Repository Staff Only: item control page