Limited transgenerational effects of environmental temperatures on thermal performance of a cold-adapted salmonid
Bibliographic record
Abstract
The capacity of ectotherms to cope with rising temperatures associated with climate change is a significant conservation concern as the rate of warming is likely too rapid to allow for adaptative responses in many populations. Transgenerational plasticity (TGP), if present, could potentially buffer some of the negative impacts of warming on future generations. We examined TGP in lake trout to assess their inter-generational potential to cope with anticipated warming. We acclimated adult lake trout to cold (10°C) or warm (17°C) temperatures for several months, then bred them to produce offspring from parents within a temperature treatment (cold-acclimated and warm-acclimated parents) and between temperature treatments (i.e. reciprocal crosses). At the fry stage, offspring were also acclimated to cold (11°C) or warm (15°C) temperatures. Thermal performance was assessed by measuring their critical thermal maximum (CTM) and the change in metabolic rate during an acute temperature challenge. From this dataset, we also determined their resting and peak (highest achieved, thermally induced) metabolic rates. There was little variation in offspring CTM or peak metabolic rate, although cold-acclimated offspring from warm-acclimated parents exhibited elevated resting metabolic rates without a corresponding increase in mass or condition factor, suggesting that transgenerational effects can be detrimental when parent and offspring environments mismatch. These results suggest that the limited TGP in thermal performance of lake trout is unlikely to significantly influence population responses to projected increases in environmental temperatures.
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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 | 0.001 |
| 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".