TEMPERATURE-DEPENDENT FECUNDITY ASSOCIATES WITH LATITUDE IN CAENORHABDITIS BRIGGSAE
Bibliographic record
Abstract
Populations of organisms separated by latitude provide striking examples of local adaptation, by virtue of ecological gradients that correlate with latitudinal position on the globe. Ambient temperature forms one key ecological variable that varies with latitude, and here we investigate its effects on the fecundity of self-fertilizing nematodes of the species Caenorhabditis briggsae that exhibits strong genetically based differentiation in association with latitude. We find that isogenic strains from a Tropical phylogeographic clade have greater lifetime fecundity when reared at extreme high temperatures and lower lifetime fecundity at extreme low temperatures than do strains from a Temperate phylogeographic clade, consistent with adaptation to local temperature regimes. Further, we determine experimentally that the mechanism underlying reduced fecundity at extreme temperatures differs for low versus high temperature extremes, but that the total number of sperm produced by the gonad is unaffected by rearing temperature. Low rearing temperatures result in facultatively reduced oocyte production by hermaphrodites, whereas extreme high temperatures experienced during development induce permanent defects in sperm fertility. Available and emerging genetic tools for this organism will permit the characterization of the evolutionary genetic basis to this putative example of adaptation in latitudinally separated populations.
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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) | 0.000 | 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".