Inferring foraging locations and water masses preferred by spotted seals Phoca largha and bearded seals Erignathus barbatus
Bibliographic record
Abstract
MEPS Marine Ecology Progress Series Contact the journal Facebook Twitter RSS Mailing List Subscribe to our mailing list via Mailchimp HomeLatest VolumeAbout the JournalEditorsTheme Sections MEPS 631:209-224 (2019) - DOI: https://doi.org/10.3354/meps13145 Inferring foraging locations and water masses preferred by spotted seals Phoca largha and bearded seals Erignathus barbatus R. D. Gryba1,7,*, F. K. Wiese2, B. P. Kelly3, A. L. Von Duyke4, R. S. Pickart5, D. A. Stockwell6 1Stantec, Burnaby, BC V5H 0C6, Canada 2Stantec, Anchorage, AK 99503, USA 3Study of Environmental Arctic Change, International Arctic Research Center, University of Alaska Fairbanks, Fairbanks, AK 99709-3710, USA 4Department of Wildlife Management, North Slope Borough, Utqiaġvik, AK 99723, USA 5Department of Physical Oceanography, Woods Hole Oceanographic Institution, Woods Hole, MA 02543, USA 6College of Fisheries and Ocean Sciences, Institute of Marine Science, University of Alaska Fairbanks, Fairbanks, AK 99775, USA 7Present address: Statistical Ecology Research Group, University of British Columbia, Vancouver, BC V6T 1Z4, Canada *Corresponding author: r.gryba@gmail.com ABSTRACT: Spotted seals Phoca largha and bearded seals Erignathus barbatus are ice-associated seals that have overlapping range in the Beaufort, Chukchi, and Bering Seas, but have different foraging ecologies. The link between foraging behaviour and specific oceanographic variables is not well understood for these species, nor is the influence of different dive metrics when modelling their foraging behaviour. To explore the value of different dive metrics to estimate foraging behaviour, and the relationships between foraging and water bodies/oceanographic variables, we tagged 3 spotted seals and 2 bearded seals with satellite telemetry tags that recorded movement and oceanographic data. To infer foraging behaviour, we included dive metrics in Bayesian state-space switching models, and found that models that included depth-corrected dive duration were more parsimonious than models that included dive shape. The addition of vertical movements to the model enabled better determination of foraging areas (inferred from area-restricted searches) and provided insights into the probabilities of switching between foraging and transiting behaviours. The collection of oceanographic data in situ at a scale relevant to seals helped identify water masses, and how they were used, and potential oceanographic cues used by seals to identify foraging locations. Fine-scale spatiotemporal clustering analysis revealed spotted and bearded seal foraging 'hotspots' in the Chukchi and Bering Seas that overlap with hotspots identified for other marine mammals and marine birds. KEY WORDS: Ice-associated seals · Foraging · Bayesian state-space models · Satellite telemetry · Oceanographic variables · Spotted seals · Bearded seals · MARES Full text in pdf format PreviousCite this article as: Gryba RD, Wiese FK, Kelly BP, Von Duyke AL, Pickart RS, Stockwell DA (2019) Inferring foraging locations and water masses preferred by spotted seals Phoca largha and bearded seals Erignathus barbatus. Mar Ecol Prog Ser 631:209-224. https://doi.org/10.3354/meps13145 Export citation RSS - Facebook - Tweet - linkedIn Cited by Published in MEPS Vol. 631. Online publication date: November 21, 2019 Print ISSN: 0171-8630; Online ISSN: 1616-1599 Copyright © 2019 Inter-Research.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".