| Summary: | Author Posting. © Acoustical Society of America, 2019. This article is posted here by permission of Acoustical Society of America for personal use, not for redistribution. The definitive version was published in Journal of the Acoustical Society of America 146(6), (2019): 4699, doi:10.1121/1.5139406. The sound energy from marine mammal populations vocalizing over extended periods of time adds up to quasi-continuous “choruses,” which create characteristic peaks in marine sound spectra. An approach to estimate animal distribution is presented, which uses chorus recordings from very sparse unsynchronized arrays in ocean areas that are too large or remote to survey with traditional methods. To solve this under-determined inverse problem, simulated annealing is used to estimate the distribution of vocalizing animals on a geodesic grid. This includes calculating a transmission loss (TL) matrix, which connects all grid nodes and recorders. Geometrical spreading and the ray trace model BELLHOP [Porter (1987). J. Acoust. Soc. Am. 82(4), 1349–1359] were implemented. The robustness of the proposed method was tested with simulated marine mammal distributions in the Atlantic sector of the Southern Ocean using both drifting acoustic recorders [Argo (2018). SEANOE] and a moored array as acoustic receivers. The results show that inversion accuracy mainly depends on the number and location of the recorders, and can be predicted using the entropy and range of the estimated source distributions. Tests with different TL models indicated that inversion accuracy is affected only slightly by inevitable inaccuracies in TL models. The presented method could also be applied to bird, crustacean, and insect choruses. We would like to thank Randi Ingvaldsen and the Institute of Marine Research for providing supervision, funding (Research council of Norway Grant No. 228896), and scientific freedom to S.M., and the Office of Naval Research for funding D.Z. with Grant No. N00014-18-1-2811. We also thank the reviewers and Len Thomas for ...
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