Digitised herbarium specimen data reveal a climate change‐related trend to an earlier, shorter Canadian Arctic flowering season, and phylogenetic signal in Arctic flowering times
Bibliographic record
Abstract
The Arctic is experiencing some of the world's most rapid changes in climate. Arctic plant flowering time responses to climate change are understudied. Globally, conflicting evidence exists on whether flowering time responses to temperature are evolutionarily conserved. We scored the reproductive phenology of 17 000 digitised herbarium specimens of 97 plant species collected across the Canadian Arctic since the 1900s to determine whether and how flowering times in the Canadian Arctic have shifted over the past century; how responsive flowering times are to temperature; and whether flowering times and flowering time responses to temperature are evolutionarily conserved. We found that flowering times in the Canadian Arctic are converging, with later-flowering species shifting their flowering times to a greater degree than earlier-flowering species, resulting in a shorter flowering season. We detected a significant phylogenetic signal associated with Arctic flowering times but no phylogenetic signal in flowering time responses to temperature. A shorter flowering season in the Arctic has implications for tundra food webs and species interactions, with fitness consequences across tundra trophic levels. Digitised records allowed citizen scientists to become virtual collaborators in this project, and the research provided opportunities to improve digitised record quality for future research.
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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 | 0.003 | 0.005 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".