Selection effects on early life history traits and thermal resistance in brook charr <i>Salvelinus fontinalis</i>
Bibliographic record
Abstract
In the context of climate change, it is crucial to understand whether animals that have been domesticated and (or) selected maintain their abilities to adapt to changes in their thermal environment. Here, we tested how selection for absence of early sexual maturation combined with better growth performance may have impacted thermal resistance and gene expression response in the presence of thermal stress in brook charr Salvelinus fontinalis (Mitchill, 1814). We performed temperature challenge tests on brook charr 0+ juveniles and studied the expression of genes involved in the response to oxidative stress, in synthesis of heat shock proteins, or involved in regulation of apoptosis, in heart and liver tissues. Juveniles from the selected lineage had a higher thermal resistance than controls and a loss of equilibrium occurred on average 1 °C above what was observed for the controls. The relative expressions of catalase and HSP70 were significantly higher in juveniles from the selection program. Overall, thermally sensitive fish were characterized by low mass and length and lower relative expressions of genes associated with stress response. Our results indicate that selection for traits of interests may be indirectly related to the significant lineage effect on growth in early stages of development.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".