Quantifying importance of marine prey in the diets of two partially anadromous fishes
Bibliographic record
Abstract
The importance of marine prey sources for partially anadromous fishes has received little study and is complicated by considerable plasticity in life history. We determined proportional contributions of marine, freshwater benthic, and freshwater pelagic prey to anadromous and resident Arctic char (Salvelinus alpinus) and lake trout (Salvelinus namaycush) from several partially anadromous populations in the Canadian Arctic. Bayesian mixing models (MixSIR) applied to δ 34 S and δ 13 C ratios in lake-specific models indicated that marine prey accounted for 90%–91% of anadromous Arctic char diet and 60%–66% of anadromous lake trout diet. When these estimates were combined with proportion of anadromous individuals in partially anadromous populations, marine food sources accounted for 31%–44% of Arctic char population productivity and 16%–26% of lake trout population productivity. Although future research is needed to refine and quantify variability around these estimates, our results will allow better predictions of the effects of anthropogenic stressors on partially anadromous fishes.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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 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".