Modeling sperm whale seasonal dynamics using probabilistic machine learning of passive acoustic data
Year: 2026
Type: article
Abstract: Seasonal variability in sperm whale acoustic activity in the northern Gulf of Mexico remains poorly understood. Using two years of passive acoustic data, hourly click counts were analyzed to characterize seasonal patterns in whale presence and behavior. A generalized linear modeling framework was used to accommodate temporally-correlated, over-dispersed, and zero-inflated click-count data. Baseline activity differed significantly among seasons, with the highest levels occurring in winter and fall and the lowest in spring. These results establish a quantitative seasonal baseline of regional sperm whale acoustic activity important for future studies linking habitat-use behavior to environmental and anthropogenic drivers in the Gulf.
Source: JASA Express Letters
DOI: 10.1121/10.0043211
Institution: University of Louisiana at Lafayette
Language: English
Subfield: Ecology
Field: Environmental Science
Domain: Physical Sciences
SDG: Life below water
Open Access status: diamond
OpenAlex ID: W7146946670