The influence of life history traits on the phenological response of British butterflies to climate variability since the late‐19th century
Bibliographic record
Abstract
Many species of plants and animals have advanced their phenology in response to climate warming in recent decades. Most of the evidence available for these shifts is based on data from the last few decades, a period coinciding with rapid climate warming. Baseline data is required to put these recent phenological changes in a long‐term context. We analysed the phenological response of 51 resident British butterfly species using data from 83 500 specimens in the collections of the Natural History Museum, London, covering the period 1880–1970. Our analysis shows that only three species significantly advanced their phenology between 1880 and 1970, probably reflecting the relatively small increase in spring temperature over this period. However, the phenology of all but one of the species we analysed showed phenological sensitivity to inter‐annual climate variability and a significant advancement in phenology in years in which spring or summer temperatures were warm and dry. The phenologies of butterfly species were more sensitive to weather if the butterfly species was early flying, southerly distributed, and a generalist in terms of larval diet. This observation is consistent with the hypothesis that species with greater niche breadth may be more phenologically sensitive than species with important niche constraints. Comparison of our results with post‐1976 data from the UK Butterfly Monitoring Scheme show that species flying early in the year had a greater rate of phenological advancement prior to the mid‐1970s. Additionally, prior to the mid‐1970s, phenology was influenced by temperatures in March or April, whereas since 1976, February temperature had a stronger influence on the phenology. These results suggest that early flying species may be approaching the limits of phenological advancement in response to recent climate warming.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".