Systemic range shift lags among a pollinator species assemblage following rapid climate change<sup>1</sup>This article is part of a Special Issue entitled “Pollination biology research in Canada: Perspectives on a mutualism at different scales”.
Bibliographic record
Abstract
Contemporary climate change is driving widespread geographical range shifts among many species. If species are tracking changing climate successfully, then leading populations should experience similar climatic conditions through time as new populations establish beyond historical range margins. Here, we investigate geographical range shifts relative to changing climatic conditions among a particularly well-sampled assemblage of butterflies in Canada. We assembled observations of 81 species and measured their latitudinal displacement between two periods: 1960–1975 (a period of little climate change) and 1990–2005 (a period with large climate change). We find an unexpected trend for species’ northern borders to shift progressively less relative to increasing minimum winter temperatures in northern Canada. This study demonstrates a novel, systemic latitudinal gradient in lags among a large species assemblage in responses to recent climate change. Even among the most mobile species and without anthropogenic barriers to dispersal, these pollinators have been unable to extend their ranges as fast as required to keep pace with climate change.
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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 | 0.001 | 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) | 0.001 | 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".