Responses to simulated winter conditions differ between threespine stickleback ecotypes
Bibliographic record
Abstract
Abiotic factors can act as barriers to colonization and drive local adaptation. During colonization, organisms may cope with changes in abiotic factors using existing phenotypic plasticity, but the role of phenotypic plasticity in assisting or hindering the process of local adaptation remains unclear. To address these questions, we explore the role of winter conditions in driving divergence during freshwater colonization and the effects of plasticity on local adaptation in ancestral marine and derived freshwater ecotypes of threespine stickleback (Gasterosteus aculeatus). We found that freshwater-resident stickleback had greater tolerance of acute exposure to low temperatures than marine stickleback, but these differences were abolished after acclimation to simulated winter conditions (9L:15D photoperiod at 4 °C). Plasma chloride levels differed between the ecotypes, but showed a similar degree of plasticity between ecotypes. Gene expression of the epithelial calcium channel (ECaC) differed between ecotypes, with the freshwater ecotype demonstrating substantially greater expression than the marine ecotype, but there was no plasticity in this trait under these conditions in either ecotype. In contrast, growth (assessed as final mass) and the expression of an isoform of the electroneutral Na(+)/H(+) exchanger (NHE3) exhibited substantial change with temperature in the marine ecotype that was not observed in the freshwater ecotype under the conditions tested here, which is consistent with evolution of these traits by a process such as genetic assimilation. These data demonstrate substantial divergence in many of these traits between freshwater and marine stickleback, but also illustrate the complexity of possible relationships between plasticity and local adaptation.
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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 | 0.000 |
| 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".