The evolution of redd site selection in brook charr in different environments: same cue, same benefit for fitness*
Bibliographic record
Abstract
1. Despite the great interest in characterising fish reproductive habitat, the relationship between the selection of a given spawning site and individual fitness has not been experimentally tested. 2. In this study, we used an in situ experimental approach to determine (i) the relative contribution of substrate characteristics as well as hydrological and physicochemical variables to small-scale redd site selection by brook charr, Salvelinus fontinalis (Mitchill) and (ii) if hatching and emergence success, used as a surrogate of fitness, are improved in selected compared to non-selected sites in both lake and stream habitats. 3. Our results show that upwelling groundwater flow was always significantly higher in selected than in non-selected sites in both lake and stream habitats. We found no significant difference in the mean geometric substrate diameter and no consistent differences in substrate composition between selected and non-selected sites. Oxygen concentration was higher (significantly so in three of four comparisons) and conductivity tended to be lower in selected than in non-selected sites, while temperature showed no significant or consistent variations. We found a significant positive relationship between the selection of a given spawning habitat and hatching and emergence success in these systems. 4. These results show that the main cue that brook charr use to select their spawning sites is upwelling groundwater in lake and stream habitats, and that active selection of these sites increases individual fitness. This suggests that natural selection acted on the same cues in lentic and lotic environments; this could have been highly adaptive in a species that used both habitats as colonisation routes after the last glaciation.
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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 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".