Changing times, spaces, and faces: tests and implications of adaptive morphological plasticity in the fishes of northern postglacial lakes
Bibliographic record
Abstract
The phenotypic diversity exhibited within and among populations of freshwater fishes in postglacial lakes has intrigued biologists for two reasons: (i) their high phenotypic variation and (ii) the apparently recent and rapid divergence of forms. Genetic and ecological studies of these taxa are shedding new light on mechanisms of divergence and species formation. Surprisingly, the roles of phenotypic plasticity in the origins, maintenance, and generation of phenotypic diversity in this system are rarely directly addressed. We synthesize the available literature on morphological plasticity in these fishes and, using a meta-analysis, test for adaptive plasticity. We conclude that (i) morphological plasticity is common in at least six families of northern freshwater fishes, (ii) plastic responses can often be induced by conditions related to littoral and pelagic lake environments, (iii) plasticity often represents adaptive responses to conditions in these habitats, and (iv) that although rarely tested, heritable variation in morphological plasticity is present. The rich amount of phenotypic plasticity has not constrained recent adaptive divergence and species formation in postglacial fishes, and instead plasticity may play a role in the notably high rates of divergence observed in these and other fishes currently undergoing adaptive radiation.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.000 | 0.001 |
| 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".