Predicting the sensitivity of butterfly phenology to temperature over the past century
Bibliographic record
Abstract
Studies to date have documented substantial variation among species in the degree to which phenology responds to temperature and shifts over time, but we have a limited understanding of the causes of such variation. Here, we use a spatially and temporally extensive data set (ca. 48 000 observations from across Canada) to evaluate the utility of museum collection records in detecting broad-scale phenology-temperature relationships and to test for systematic differences in the sensitivity of phenology to temperature (days °C(-1) ) of Canadian butterfly species according to relevant ecological traits. We showed that the timing of flight season predictably responded to temperature both across space (variation in average temperature from site to site in Canada) and across time (variation from year to year within each individual site). This reveals that collection records, a vastly underexploited resource, can be applied to the quantification of broad-scale relationships between species' phenology and temperature. The timing of the flight season of earlier fliers and less mobile species was more sensitive to temperature than later fliers and more mobile species, demonstrating that ecological traits can account for some of the interspecific variation in species' phenological sensitivity to temperature. Finally, we found that phenological sensitivity to temperature differed across time and space implying that both dimensions of temperature will be needed to translate species' phenological sensitivity to temperature into accurate predictions of species' future phenological shifts. Given the widespread temperature sensitivity of flight season timing, we can expect long-term temporal shifts with increased warming [ca. 2.4 days °C(-1) (0.18 SE)] for many if not most butterfly species.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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 teacher head, 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".