Screening large audio datasets to determine the time and space distribution of Screaming Piha birds in a tropical forest

Abstract : Acoustic monitoring has proved to be an efficient approach to monitor wildlife, notably in environments with limited visibility, such as tropical rainforests. Today, recording equipment allows acoustic data to be gathered in remote areas at wide spatial and temporal scales. The resulting datasets are large and the use of automated processing systems to extract relevant information can greatly facilitate their analysis. Here, we have developed signal processing techniques to reveal the spatio-temporal dynamics of an emblematic bird voice of the neotropical forest: the song of the Screaming Piha (Lipaugus vociferans). Using recordings made in a French Guianan lowland forest, with an array of 24 microphones in a three dimensional space, we implemented a detection system based on spectrogram cross-correlation to trace the vocalisations of L. vociferans. We tuned the detection system based on the percentage area under the Receiver Operating Characteristic curve, finding a maximum of 95.88%. To strictly minimise false positives, we set the operating point to have 34.9% true positives and 0% false positives. We detected a total of 12,735 songs attributed to the study bird during 25 study days. We found that spatial patterns of lower activity corresponded to a zone having smaller trees and more tree gaps — a known liana forest patch — suggesting that Screaming Piha birds tend to avoid non-mature primary forests. The sampling sites near the creeks had more detections than the sites further away, suggesting that the lek mating arenas might be distributed strategically to be near to a source of water. We also found a marked temporal pattern. The lek was active during the whole day, from sunrise to sunset, with two peaks of activity shifted by more than 2 h from the dawn and dusk chorus. The approach described here can be tested using other conspicuous and stereotyped sounds that occur within a heterogeneous and noisy background. To decipher the complex interacting sounds of the tropical forest, these focal studies on specific acoustic elements should be complemented with community or soundscape analysis, to demonstrate the human impact on the ecosystem and to provide guidelines for natural resource management.
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Submitted on : Monday, July 18, 2016 - 10:35:04 AM
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Juan-Sebastiano Ulloa, Amandine Gasc, Phillipe Gaucher, Thierry Aubin, Maxime Réjou-Méchain, et al.. Screening large audio datasets to determine the time and space distribution of Screaming Piha birds in a tropical forest. Ecological Informatics, Elsevier, 2016, 31, pp.91-99. ⟨10.1016/j.ecoinf.2015.11.012⟩. ⟨hal-01346004⟩

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