Effects of temperature and salinity on the reproductive success of Arctic charr, <i>Salvelinus alpinus</i> (L.): egg composition, milt characteristics and fry survival
Bibliographic record
Abstract
The effects of temperature and salinity on the reproductive success of Arctic charr, Salvelinus alpinus (L.), were examined by holding broodstock under the following conditions from mid-May until the end of September: fresh water at ambient temperature (NFW; 8–16 °C); salt water (25–30‰) at ambient temperature (NSW; 4–10 °C); fresh water cooled to saltwater temperature (CFW; 4–10 °C); or salt water heated to freshwater temperature (HSW; 8–16 °C). The relative fecundity of females was similar among groups (P > 0.05; 2685 ± 706 eggs), but females reared in NSW produced significantly larger eggs than those raised in NFW. The highest spermatozoa concentrations were found in milt from males reared in SW and the highest milt glucose concentration was from males kept under coldwater conditions (CFW, NSW). Eggs from NSW and HSW females contained more proteins than eggs produced by NFW females. Eggs from NSW females also contained 40% more lipids than was observed in the other groups, and total energy content was 27% higher in eggs from NSW females than in eggs from NFW females. When FW was cooled (CFW), females produced eggs with protein contents similar to those in NSW, but the lipid contents remained 30% lower. Finally, the best survival at the eyed stage and at hatch was observed in families produced by NSW broodstock. Intermediate values were observed in families from NFW or CFW while the highest mortality occurred in families from the HSW group. All these results suggest that, under the experimental conditions used in the present study, coastal seawater conditions offered the most favourable summer rearing conditions with respect to the reproductive success of Arctic charr.
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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 | 0.000 | 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) | 0.001 | 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".