You are the colour of what you eat: higher invertebrate consumption correlates with redder muscle pigmentation in anadromous Arctic char (Salvelinus alpinus) along western Hudson Bay, Nunavut, Canada
Bibliographic record
Abstract
Abstract Salmonid fishes exhibit marked intra-specific variation in muscle pigmentation, primarily due to individual differences in the accumulation and assimilation of dietary carotenoids. Carotenoids are synthesized by primary producers and microorganisms, and present in the tissues of crustaceans that can serve as important prey for salmonids. Despite anadromous Arctic char ( Salvelinus alpinus ) being a key subsistence and economic resource across Inuit Nunangat, their muscle pigmentation in relation to diet and environmental variability (e.g., sea ice dynamics) has not been investigated. Using carotenoid spectrophotometry analysis and a muscle colour scale, we examined the influence of Arctic char diet, inferred from stomach contents, stable isotopes (δ 15 N), and highly branched isoprenoids on their muscle pigmentation, as well as muscle pigmentation of their prey near the communities of Rankin Inlet and Naujaat, Nunavut in two years (2021, 2022) with contrasting sea ice cover. Among prey types, invertebrates had higher carotenoid concentrations than fishes. Arctic char in Naujaat contained higher muscle carotenoid concentrations and redder muscle than in Rankin Inlet in 2021, associated with a higher invertebrate-based diet and more prevalent sea ice cover. In 2022, muscle carotenoid concentrations of Naujaat and Rankin Inlet Arctic char were similar, associated with a largely fish-based diet and similar sea ice cover, although muscle still remained redder in Naujaat Arctic char. Inter-annual variation in carotenoid concentration and muscle pigmentation associated with diet variability observed in this species may affect local resource users over the long-term due to unpredictable climate-driven environmental changes, resulting in socioeconomic impacts across the Arctic.
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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 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".