Limits to the accurate and generalizable use of soundscapes to monitor biodiversity.
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Peer-reviewed
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Abstract
Although eco-acoustic monitoring has the potential to deliver biodiversity insight on vast scales, existing analytical approaches behave unpredictably across studies. We collated 8,023 audio recordings with paired manual avifaunal point counts to investigate whether soundscapes could be used to monitor biodiversity across diverse ecosystems. We found that neither univariate indices nor machine learning models were predictive of species richness across datasets but soundscape change was consistently indicative of community change. Our findings indicate that there are no common features of biodiverse soundscapes and that soundscape monitoring should be used cautiously and in conjunction with more reliable in-person ecological surveys.
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Acknowledgements: We would like to thank staff at the SAFE project, the Cornell Lab of Ornithology and Ecoacoustics and Spatial Ecology Lab at Academia Sinica for their support in data collection and preprocessing. Specific thanks go to J. Sleutel, A. Shabrani, N. Zulkifli, R. Mack, B. Thomas, A. Anand, C. Das, A. Rajan, C.-Y. Lee and S.-H. Liu. This project was supported by funding from the Herchel Smith Fund (S.S.S.), World Wildlife Fund (Malaysia data), Sime Darby Foundation (Malaysia data), National Science and Technology Council (NSTC 111-2321-B-002-019 and 111-2927-I-001-513; Taiwan data) and Biodiversity Research Center at Academia Sinica (Taiwan data). Feature computations for the US dataset were performed on resources provided by Sigma2—the National Infrastructure for High Performance Computing and Data Storage in Norway. Data were collected from Malaysia under an SaBC permit granted to S.S.S. (JKM/MBS.1000-2/2 JLD.8 (63)).
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2397-334X

