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Analyzing Whale Calling through Hawkes Process Modeling

Authors
Kang, BokgyeongSchliep, Erin M.Gelfand, Alan E.Yack, Tina M.Clark, Christopher W.Schick, Robert S.
Issue Date
Oct-2025
Publisher
Taylor & Francis
Keywords
Gaussian process; North Atlantic right whales; Random time change theorem; Spatial process; Temporal point patterns
Citation
Journal of the American Statistical Association, v.120, no.552, pp 2040 - 2052
Pages
13
Indexed
SCIE
SCOPUS
Journal Title
Journal of the American Statistical Association
Volume
120
Number
552
Start Page
2040
End Page
2052
URI
https://scholarworks.dongguk.edu/handle/sw.dongguk/58679
DOI
10.1080/01621459.2025.2501711
ISSN
0162-1459
1537-274X
Abstract
Sound is assumed to be the primary modality of communication among marine mammal species. Analyzing acoustic recordings helps to understand the function of the acoustic signals as well as the possible impact of anthropogenic noise on acoustic behavior. Motivated by a dataset from a network of hydrophones in Cape Cod Bay, Massachusetts, using automatically detected calls in recordings, we study the communication process of the endangered North Atlantic right whale. For right whales, an "upcall" is a known signal used to facilitate communication among individuals. We present novel spatiotemporal excitement modeling consisting of a background process and an excitement process. The background process incorporates the influences of diel patterns and ambient noise on contact calls-initial vocalizations aimed at initiating contact. The excitement process captures potential countercalls-responses excited by previous upcalls. Upcall incidence is found to be clustered in space and time; an upcall seems to excite more upcalls nearer to it in time and space. We find evidence that whales make more upcalls at night, respond to other whales nearby, and are likely to remain quiet in the presence of increased ambient noise. Supplementary materials for this article are available online, including a standardized description of the materials available for reproducing the work.
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College of Natural Science (Department of Statistics)
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