Shifting thresholds: rapid evolution of migratory life histories in steelhead/rainbow trout, <i>Oncorhynchus mykiss</i>
Bibliographic record
Abstract
Expression of phenotypic plasticity depends on reaction norms adapted to historic selective regimes; anthropogenic changes in these selection regimes necessitate contemporary evolution or extirpation. Adaptation of conditional strategies following a change in the selection regime requires evolution of either the environmentally influenced cue (e.g. growth rate) or the state (e.g. size threshold) at which an individual switches between conditional strategies. Using a population of steelhead (Oncorhynchus mykiss) introduced above a barrier waterfall in 1910, we evaluate how the conditional strategy to migrate evolves in response to selection against migration. Common garden-raised offspring of parents from the above-barrier population were 11% smaller and 31% lighter than offspring of parents from the below-barrier source population. Using a novel analytical approach we estimate that the mean size at which above-barrier fish switch between the resident and migrant strategy is 43% larger than below-barrier fish. As a result, above-barrier fish were 30% less likely to express the migratory strategy. Our results demonstrate how rapid and opposing changes in growth rate and threshold size contribute to the contemporary evolution of a conditional strategy and indicate that migratory barriers may elicit rapid evolution towards the resident life-history on timescales relevant for conservation and management of conditionally migratory species.
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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 | 0.001 |
| 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".