Dear colleagues, I am pleased to share our (~relatively~) recent paper in which we propose a new methodology for dive-data analysis and detect a diurnal pattern in narwhal diving behavior. I am posting it now because this approach has just been extended to bowhead whales (Podolskiy et al., Phys. Rev. Res., 2024, https://doi.org/10.1103/PhysRevResearch.6.033174), as mentioned in my previous announcement.
Strange attractor of a narwhal (Monodon monoceros). by Podolskiy EA & Heide-Jørgensen MP (2022) PLOS Comput. Biol. 18(9): e1010432. https://doi.org/10.1371/journal.pcbi.1010432 [Abstract] Detecting structures within the continuous diving behavior of marine animals is challenging, and no universal framework is available. We captured such diverse structures using chaos theory. By applying time-delay embedding to exceptionally long dive records (83 d) from the narwhal, we reconstructed the state-space portrait. Using measures of chaos, we detected a diurnal pattern and its seasonal modulation, classified data, and found how sea-ice appearance shifts time budgets. There is more near-surface rest but deeper dives at solar noon, and more intense diving during twilight and at night but to shallower depths (likely following squid); sea-ice appearance reduces rest. The introduced geometrical approach is simple to implement and potentially helpful for mapping and labeling long-term behavioral data, identifying differences between individual animals and species, and detecting perturbations. Best regards, Evgeny Podolskiy, Assoc. Prof. Arctic Research Center, Hokkaido University, Japan
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