Resource polymorphism in a Patagonian fish Percichthys trucha (Percichthyidae): phenotypic evidence for interlake pattern variation
Bibliographic record
Abstract
Within-species differentiation in phenotypic characters related to resource use (resource polymorphism) is frequently thought to result from divergent natural selection in a heterogeneous environment with 'open niches'.In this study we found consistent resource-based polymorphism within three different populations of Percichthys trucha , a lake-dwelling fish native to the southern Andes.In each of three lakes we found two morphotypes that could be clearly distinguished by differences in gill raker length.However, the magnitude of the polymorphism, and the suite of phenotypic characteristics associated with the polymorphism, differed between lakes.Patterns of divergence were more similar between the two northern lakes which ultimately drain into a common river, than between these two lakes and a more southern, unconnected lake.The southern population, which had the largest divergence in gill raker length (32% vs. 16% and 19%), also showed substantial differences in diet.Evidence from the southern population suggests that polymorphism in P. trucha is present early during ontogeny.We conclude that while there are some strong parallels among lakes in the development of a trophic polymorphism, differences in environmental conditions and/or colonization history have led to substantial differences in the evolutionary history, resulting in different ecological roles of common morphotypes within different lakes.
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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 | 0.000 |
| 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".