Colour lightness of butterfly assemblages across North America and Europe
Bibliographic record
Abstract
Melanin-based dark colouration is beneficial for insects as it increases the absorption of solar energy and protects against pathogens. Thus, it is expected that insect colouration is darker in colder regions and in regions with high humidity, where it is assumed that pathogen pressure is highest. These relationships between colour lightness, insect distribution, and climate between taxa and subtaxa across continents have never been tested and compared. Here we analysed the colour lightness of nearly all butterfly species of North America and Europe using the average colour lightness of species occurring within 50 km × 50 km grid cells across both continents as the dependent variable and average insolation, temperature and humidity within grid cells as explanatory variables. We compared the direction, strength and shape of these relationships between butterfly families and continents. On both continents, butterfly assemblages in colder and more humid regions were generally darker coloured than assemblages in warmer and less humid regions. Although these relationships differed in detail between families, overall trends within families on both continents were similar. Our results add further support for the importance of insect colour lightness as a mechanistic adaptation to climate that influences biogeographical patterns of species distributions.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| 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".