Adaptation and acclimation of traits associated with swimming capacity in Lake Whitefish (coregonus clupeaformis) ecotypes
Bibliographic record
Abstract
BACKGROUND: Improved performance in a given ecological niche can occur through local adaptation, phenotypic plasticity, or a combination of these mechanisms. Evaluating the relative importance of these two mechanisms is needed to better understand the cause of intra specific polymorphism. In this study, we reared populations of Lake Whitefish (Coregonus clupeaformis) representing the'normal' (benthic form) and the 'dwarf' (derived limnetic form) ecotypes in two different conditions (control and swim-training) to test the relative importance of adaptation and acclimation in the differentiation of traits related to swimming capacity. The dwarf whitefish is a more active swimmer than the normal ecotype, and also has a higher capacity for aerobic energy production in the swimming musculature. We hypothesized that dwarf fish would show changes in morphological and physiological traits consistent with reductions in the energetic costs of swimming and maintenance metabolism. RESULTS: We found differences in traits predicted to decrease the costs of prolonged swimming and standard metabolic rate and allow for a more active lifestyle in dwarf whitefish. Dwarf whitefish evolved a more streamlined body shape, predicted to lead to a decreased drag, and a smaller brain, which may decrease their standard metabolic rate. Contrary to predictions, we also found evidence of acclimation in liver size and metabolic enzyme activities. CONCLUSION: Results support the view that local adaptation has contributed to the genetically-based divergence of traits associated with swimming activity. Presence of post-zygotic barriers limiting gene flow between these ecotype pairs may have favoured repeated local adaptation to the limnetic niches.
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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 | 0.001 |
| 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".