Lifelong divergence of growth patterns in Arctic charr life history strategies: implications for sustainable fisheries in a changing climate
Bibliographic record
Abstract
Arctic charr (Salvelinus alpinus Linnaeus, 1758) are phenotypically variable with multiple life history strategies including anadromous and freshwater resident individuals. The mechanism determining life history is believed to be set early in life. Anadromous individuals show greater seasonality in growth and feeding after the first seaward migration relative to resident conspecifics. We used otolith growth increment measurements to estimate lifelong growth patterns for 355 individuals with anadromous or resident life history from four populations within Cumberland Sound, Nunavut. Using a general and a generalized linear model, we discovered a linear increase (estimate = 0.006) in growth for both Arctic charr life histories between 1990 and 2016. Resident Arctic charr have lower annual growth (estimate = −0.176) and show a decrease in the annual proportion of summer growth as they age (estimate = −0.042), whereas their anadromous counterparts maintain a higher seasonality in their growth patterns with age. This suggests that growth is indeed important in life history trajectory for Arctic charr and that seasonal growth patterns differ among life histories. The results highlight the importance of improving our understanding of mechanisms influencing life history trajectory in Arctic charr to ensure sustainability of harvested Arctic charr populations in a changing climate.
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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 | 0.001 | 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 | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".