Isotopic composition of the eastern gray whale epidermis indicates contribution of prey outside Arctic feeding grounds
Bibliographic record
Abstract
Eastern gray whales' distribution range and plasticity in feeding behavior complicates the understanding of critical life-history such as pregnancy and lactation. Our goal was to determine if females who experienced gestation, gave birth, and lactated their calves, assimilated a high proportion of benthic amphipods from the Bering Sea, which are considered the species' main prey. We used Bayesian stable isotope mixing models to estimate the probability of contribution of food items sampled along the species' distributional range, using isotopic data on amphipods from the Bering Sea, mysids from Vancouver Island, and amphipods and polychaetes from Ojo de Liebre Lagoon. We sampled epidermal tissue from lactating females (n = 25) and calves (n = 34) and analyzed their carbon and nitrogen isotopic composition. Model outcome indicated that benthic amphipods from the Bering Sea were not the primary food for the eastern gray whale. Each mother performed a different feeding strategy, and prey from Vancouver Island were generally as important as that from the Bering Sea. Moreover, model results indicate a constant use of Ojo de Liebre Lagoon as a feeding ground. Our results appear to agree with previous studies that report continuous feeding by females to satisfy certain physiological requirements (e.g., fatty acids omega-6) during migration and breeding time. Future investigations of the isotopic composition of all those prey items that could be assimilated by the eastern gray whale emerge as critical. Both historical and recent information, that would provide insights in the species feeding ecology under past and present environmental conditions, should be considered as equally important to establish conservation and management plans.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| 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 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".