PARALLEL EVOLUTION BY CORRELATED RESPONSE: LATERAL PLATE REDUCTION IN THREESPINE STICKLEBACK
Bibliographic record
Abstract
Recent work has revealed the molecular mechanisms governing one of the most dramatic examples of parallel evolution in nature: the repeated loss of lateral plate armor in freshwater populations of threespine stickleback. Yet, the ecological mechanisms responsible for armor loss remain unclear. Using a balanced experimental design, we examined Heuts' (1947) hypothesis that selection due to differences in salinity indirectly drive the reduction of lateral plate armor in fresh water while maintaining armor in the sea. We measured two fitness-related traits, hatching success and juvenile growth rate, in offspring of reduced (low and partial) and complete lateral plate morphs from two polymorphic populations when raised in either fresh water or salt water. In contrast to Heuts' results, there was little difference among morphs in hatching success. However, salinity strongly influenced juvenile growth: offspring of reduced lateral plate morphs grew substantially faster (up to 65%) than offspring of completely plated morphs in fresh water, but there was little difference in salt water. We suggest that the parallel loss of lateral plates in fresh water has arisen through a correlated response to selection for faster growth during lateral plate development, but the effect of salinity on hatching success and juvenile growth rate cannot explain the predominance of completely plated morphs in marine 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 | 0.001 | 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".