Elemental stoichiometry and insect chill tolerance: Evolved and plastic changes in organismal Na <sup>+</sup> and K <sup>+</sup> content in <i>Drosophila</i>
Bibliographic record
Abstract
Abstract Acclimation and evolutionary adaptation can produce phenotypic change that allows organisms to cope with challenges like those associated with climate change. Determining the relative contributions of acclimation and adaptation is of central importance to understanding animal responses to change. Rates of evolution have traditionally been considered slow relative to ecological processes that shape biodiversity. Many organisms nonetheless show patterns of spatial genetic variation suggestive of adaptation and some evidence is emerging that adaptation can act sufficiently fast to allow phenotypic tracking in response to environmental change (‘adaptive tracking’). In Drosophila , both plastic and evolved differences in chill tolerance are associated with ionoregulation. Here we combine acclimation, latitudinal field collections, and a replicated field experiment to assess the effects of acclimation and adaptation on chill coma recovery and elemental (Na and K) stoichiometry in both sexes of Drosophila melanogaster . Acclimation and spatial adaptation both shape chill coma recovery, with acclimation producing the greatest magnitude response. Leveraging knowledge on the physiological mechanisms that underlie variation in chill tolerance traits, we find that the relationship between K content and chill tolerance differs among flies acclimated vs. adapted to cold. Taken together, these data reinforce the importance of acclimation in responses to abiotic challenges and illustrate that the mechanisms of phenotypic change can differ between acclimation and basal tolerance 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".