Spatiotemporal variation in anadromous Arctic char (Salvelinus alpinus) foraging ecology and its influence on muscle pigmentation along western Hudson Bay, Nunavut, Canada
Bibliographic record
Abstract
Climate-induced alterations to Arctic sea ice dynamics are influencing the availability and distribution of resources, and in turn, the nutrient and energy intake of opportunistic predators across the food web. These temporal changes in local prey communities likely influence the availability of carotenoid-rich prey types, as well as the foraging ecology of opportunistic predators that forage in the marine environment, such as anadromous Arctic char (Salvelinus alpinus). Despite its socioeconomic importance across its range, anadromous Arctic char foraging ecology and its influence on muscle pigmentation, particularly in relation to sea ice dynamics, remains understudied. Here, over two years (2021, 2022) with contrasting sea ice dynamics, I investigated the foraging ecology of anadromous Arctic char and its influence on their muscle pigmentation at a southern (Rankin Inlet) and northern (Naujaat) location along western Hudson Bay using a combination of stomach contents, stable isotopes (δ¹³C and δ¹⁵N), highly branched isoprenoids, carotenoid spectrophotometry, and a standard muscle colour scale (DSM SalmoFan). Spatiotemporal variation in Arctic char diet occurred, where Rankin Inlet Arctic char generally consumed more fish and phytoplankton-based carbon sources, occupied a higher trophic position, and displayed a similar isotopic niche breadth compared to Arctic char in Naujaat. Invertebrates were higher in carotenoid concentration than fishes, and in association with a more invertebrate-based diet, Arctic char in Naujaat contained higher muscle carotenoid concentrations (e.g., astaxanthin) compared to Rankin Inlet Arctic char in 2021. In 2022, however, muscle carotenoid concentrations in Naujaat and Rankin Inlet Arctic char were more similar, as the diet of Arctic char in both locations was largely fish-based despite muscle colour remaining redder in Naujaat Arctic char. Overall, the observed plastic foraging ecology of Arctic char highlights this species' ability to adjust to inter-annual variability in environmental changes, which then impacts their muscle carotenoid concentration. Such inter-annual variation in Arctic char foraging ecology is anticipated to increase with unpredictable climate-driven environmental changes in the region, which could therefore negatively affect local resource users over the long term, resulting in socioeconomic impacts across the Arctic.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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".