Data from: Conflict between biotic and climatic selective pressures acting on an extended phenotype in a subarctic, but not temperate, environment
Bibliographic record
Abstract
Climatic selective pressures are thought to dominate biotic selective pressures at higher latitudes. However, few studies have experimentally tested how these selective pressures differentially act on traits across latitudes because traits can rarely be manipulated independently of the organism in nature. We overcame this challenge by using an extended phenotype—active bird nests—and conducted reciprocal transplant experiments between a subarctic and temperate site, separated by 14° of latitude. At the subarctic site, biotic selective pressures (nest predation) favoured smaller, non-local temperate nests, whereas climatic selective pressures (temperature) favoured larger local nests, particularly at colder temperatures. By contrast, at the temperate site, climatic and biotic selective pressures acted similarly on temperate and subarctic nests. Our results illustrate a functional trade-off in the subarctic between nest morphologies favoured by biotic versus climatic selective pressures, with climate favouring local nest morphologies. At our temperate site, however, allocative trade-offs in the time and effort devoted to nest construction favour smaller, local nests. Our findings illustrate a conflict between biotic and climatic selective pressures at the northern extremes of a species geographical range, and suggest that trade-offs between trait function and trait elaboration act differentially across latitude to create broad geographic variation in traits.
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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 | 0.002 | 0.009 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.075 | 0.054 |
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".