Prey assemblage isotopic variability as a tool for assessing diet and the spatial distribution of bowhead whale Balaena mysticetus foraging in the Canadian eastern Arctic
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 469:161-174 (2012) - DOI: https://doi.org/10.3354/meps10004 Prey assemblage isotopic variability as a tool for assessing diet and the spatial distribution of bowhead whale Balaena mysticetus foraging in the Canadian eastern Arctic C. Pomerleau1,6,*, V. Lesage2, S. H. Ferguson3, G. Winkler1, S. D. Petersen4, J. W. Higdon5 1Institut des Sciences de la Mer, Université du Québec à Rimouski, Rimouski, Quebec G5L 3A1, Canada 2Fisheries and Oceans Canada, Maurice Lamontagne Institute, Mont-Joli, Quebec G5H 3Z4, Canada 3Fisheries and Oceans Canada, Freshwater Institute, Winnipeg, Manitoba R3T 2N6, Canada 4Assiniboine Park Zoo, Winnipeg, Manitoba R3P 2N7, Canada 5Higdon Wildlife Consulting, Winnipeg, Manitoba R3G 3C9, Canada 6Present address: Fisheries and Oceans Canada, Institute of Ocean Sciences, Sidney, British Columbia V8L 4B2, Canada *Email: corinne.pomerleau@dfo-mpo.gc.ca ABSTRACT: The eastern Canada-West Greenland (EC-WG) bowhead whale Balaena mysticetus population is slowly recovering from the intensive commercial whaling of the 18th and 20th centuries. However, climate change, through effects on ice conditions and prey availability, is one of several threats that might affect bowhead whale recovery. In this study, we exploited the variability observed in isotopic signatures of prey assemblages across the eastern Arctic to examine variability in diet among bowhead whales (n = 202) and identify their potential foraging areas. We compared δ13C and δ15N isotope ratios of biopsied skin samples with those of potential zooplankton prey species collected across the Canadian eastern Arctic, and calculated the proportional contributions of various sources (zooplankton) to the diet of bowhead whales using a Bayesian stable isotope mixing model. A cluster analysis indicated some variability in isotopic composition among groups of individuals, but not between males and females or age classes. The isotopic model discounted Davis Strait and Disko Bay as potential foraging areas for bowhead whales, at least in spring and summer. Lancaster Sound, Baffin Bay and the Gulf of Boothia were the 3 main areas likely used for summer feeding, where bowhead whales fed primarily on large Arctic calanoid copepods (Calanus hyperboreus, C. glacialis, Metridia longa, and Paraeuchaeta spp.), mysids and euphausiids. While some inter-individual variability in diet was observed, the strong dependence of this endemic Arctic species on Arctic zooplankton may make them vulnerable to the predicted latitudinal shift in prey species composition caused by ongoing warming. KEY WORDS: Canadian Arctic · Bowhead whale · Diet · Foraging behaviour · Marine mammal · Zooplankton · Stable isotopes · Bayesian mixing model · SIAR · Trophic ecology Full text in pdf format PreviousNextCite this article as: Pomerleau C, Lesage V, Ferguson SH, Winkler G, Petersen SD, Higdon JW (2012) Prey assemblage isotopic variability as a tool for assessing diet and the spatial distribution of bowhead whale Balaena mysticetus foraging in the Canadian eastern Arctic. Mar Ecol Prog Ser 469:161-174. https://doi.org/10.3354/meps10004 Export citation RSS - Facebook - Tweet - linkedIn Cited by Published in MEPS Vol. 469. Online publication date: November 26, 2012 Print ISSN: 0171-8630; Online ISSN: 1616-1599 Copyright © 2012 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 | 0.002 | 0.001 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".