Contrasting Life History Characteristics Between Riverine and Lacustrine Anadromous Arctic Char ( <scp> <i>Salvelinus alpinus</i> </scp> ) in the Western Canadian Arctic
Bibliographic record
Abstract
) is typically associated with lakes, there is a small number of anadromous populations in North America that spawn, rear, and overwinter exclusively in rivers. The life history traits of these relatively understudied populations and how they differ from lacustrine Arctic char are poorly documented. We characterized life history tradeoffs expressed by anadromous Arctic char originating from a riverine (Hornaday River) and a relatively nearby lacustrine system (Tatik Lake of the Kuujjua River) in the western Canadian Arctic using a 10-year dataset. The riverine population attained smaller average size (600 mm vs. 628 mm, fork length) and mean age (7.7 vs. 10.6 years), had a lower longevity (14 vs. 26 years), and expressed a 44% higher growth rate resulting in larger size-at-age prior to reaching modeled length asymptote (700 vs. 754 mm). Furthermore, the riverine population had a younger modal age-at-maturity (approximately 6-7 vs. 11-13 years) and mean age-at-first migration (4.1 vs. 6.4 years), and a higher natural mortality rate (0.31 vs. 0.21 per year). Our results broaden knowledge on the spectrum of life history strategies exhibited by anadromous Arctic char and underscore how freshwater habitat influences vital rates and life history tradeoffs, which have implications for conservation and sustainable harvest (e.g., maximum sustainable yield) of salmonids.
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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 | 0.002 |
| Science and technology studies | 0.001 | 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".