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Automated Acoustic Detection of Bird Behavior

AutorInnen: 
Jahn, O., Ganchev, T., Marques, M.I., Schuchmann, K.-L.
Erscheinungsjahr: 
2017
Vollständiger Titel: 
Automated sound recognition provides insights into the behavioral ecology of a tropical bird
Org. Einordnung: 
Publiziert in: 
PLoS ONE
Publikationstyp: 
Zeitschriftenaufsatz
DOI Name: 
doi:10.1371/journal.pone.0169041
Bibliographische Angaben: 
Jahn, O., Ganchev, T., Marques, M.I., Schuchmann, K.-L. (2017): Automated sound recognition provides insights into the behavioral ecology of a tropical bird. PLoS ONE 12(1): e0169041. doi:10.1371/journal.pone.0169041
Abstract: 

Computer-assisted species recognition facilitates the analysis of relevant biological information
in continuous audio recordings. In the present study, we assess the suitability of this
approach for determining distinct life-cycle phases of the Southern Lapwing Vanellus chilensis
lampronotus based on adult vocal activity. For this purpose we use passive 14-min and
30-min soundscape recordings (n = 33 201) collected in 24/7 mode between November
2012 and October 2013 in Brazil's Pantanal wetlands. Time-stamped detections of V. chilensis
call events (n = 62 292) were obtained with a species-specific sound recognizer. We
demonstrate that the breeding season fell in a three-month period from mid-May to early
August 2013, between the end of the flood cycle and the height of the dry season. Several
phases of the lapwing's life history were identified with presumed error margins of a few
days: pre-breeding, territory establishment and egg-laying, incubation, hatching, parental
defense of chicks, and post-breeding. Diurnal time budgets confirm high acoustic activity
levels during midday hours in June and July, indicative of adults defending young. By
August, activity patterns had reverted to nonbreeding mode, with peaks around dawn and
dusk and low call frequency during midday heat. We assess the current technological limitations
of the V. chilensis recognizer through a comprehensive performance assessment and
scrutinize the usefulness of automated acoustic recognizers in studies on the distribution
pattern, ecology, life history, and conservation status of sound-producing animal species.