Adaptive and non-adaptive plasticity and fine-scale genetic variation in life-history reaction norms in Atlantic cod (Gadus morhua)
Bibliographic record
Abstract
The persistence of a species in the face of environmental change is a function of the extent to which populations respond differently to changes in their environment and the spatial correspondence between the scale of disturbance and the scale of adaptation. The pattern by which a population, or genotype, expresses a range of phenotypes across an environmental gradient is called a norm of reaction. The level of phenotypic plasticity displayed within a population (i.e. the slope of the reaction norm) reflects the short-term response of a population to environmental change while variation in reaction norm slopes among populations reflects the spatial scale of variation in these responses. Using a reaction norm framework, I examined the spatial scale of genetic variation in plasticity for life-history traits in Atlantic cod (Gadus morhua), a marine fish of global biological and socioeconomic importance. Through common-garden experiments, I found evidence of both adaptive and non-adaptive plasticity for larval growth rate and survival in two cod populations that experience contrasting thermal environments in nature. A comparison of these reaction norms with those of four cod populations studied previously revealed significant genetic divergence in adaptive traits at a smaller spatial scale than has previously been shown for a marine fish with no apparent physical barriers to gene flow (<250 km). This fine-scale genetic structure is likely the result of populations being locally adapted to seasonal changes in temperature during the larval stage caused by differences in spawning times and may be maintained by behavioural barriers to gene flow. Implications of variation in life-history trait plasticity to fisheries management in the face of predicted changes in climate are discussed.
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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 | 0.002 |
| 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 | 0.001 |
| 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".