Natural selection for body shape in resource polymorphic Icelandic Arctic charr
Bibliographic record
Abstract
Resource polymorphisms exhibit remarkable intraspecific diversity and in many cases are expected to be maintained by diversifying selection. Phenotypic trade-offs can constrain morphologically intermediate individuals from effectively exploiting both alternate resources, resulting in ecological barriers to gene flow. Determining if and how phenotypic trade-offs cause fitness variation in the wild is challenging because of phenotypic and environmental correlations associated with alternative resource strategies. We investigated multiple pathways through which morphology could affect organismal performance, as measured by growth rate, and whether these effects generate diversifying selection in polymorphic Icelandic Arctic charr (Salvelinus alpinus) populations. We considered direct effects of morphology on growth and indirect effects via trophic resource use, estimated by stable isotopic signatures, and via parasitism associated with trophic resources. We sampled over 3 years in (lakes) Thingvallavatn and Vatnshlíðarvatn using the extended selection gradient path analytical approach and estimating size-dependent mortality. We found evidence for diversifying selection only in Thingvallavatn: more streamlined and terminally mouthed planktivore charr experienced greater growth, with the opposite pattern in small benthic charr. However, this effect was mediated by parasitism and nontrophic pathways, rather than trophic performance as often expected. Detection of between-morph differences in the presence (Vatnshlíðarvatn) and direction (Thingvallavatn) of size-dependent mortality, together with nontrophic effects of shape, suggests that a morphological trophic performance explanation for polymorphism is insufficient. This rare insight into selection during early diversification suggests that a complex of interacting local factors must be considered to understand how phenotype influences fitness, despite morphological variation reflecting intuitive trade-off explanations.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.000 |
| 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 teacher head, 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".