Phenotypic plasticity is maintained despite geographical isolation in an African cichlid fish, <i>Pseudocrenilabrus multicolor</i>
Bibliographic record
Abstract
Gene flow among populations in different selective environments should favor the evolution of phenotypic plasticity over local adaptation. Plasticity in development is a common response to long-term hypoxia in some widespread African fishes, including Pseudocrenilabrus multicolor, a cichlid that exploits both normoxic (high oxygen) rivers/lakes and hypoxic (low oxygen) swamps. Previous studies have shown that fish from normoxic and hypoxic sites differ in many traits, including gill size, brain size and body shape, and that much of this variation reflects developmental plasticity. However, these earlier studies focused on areas in Uganda where gene flow between swamp and river or lake populations is high. In this study we tested the hypothesis that P. multicolor from a relatively isolated lake population (Lake Saka, Uganda) exhibit low levels of plasticity in traits related to oxygen uptake. Multiple broods of P. multicolor from Lake Saka were reared under low and high dissolved oxygen, and traits related to gill size, brain mass and body shape were quantified. Surprisingly, both gill size and brain mass showed high levels of developmental plasticity. We suggest that high levels of plasticity, particularly in the gill size of P. multicolor, reflects low costs of maintaining the plastic response, even in relatively isolated populations.
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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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| 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".