Global analysis of floral longevity reveals latitudinal gradients and biotic and abiotic correlates
Bibliographic record
Abstract
The length of time a flower remains open and functional - floral longevity - governs important reproductive processes influencing pollination and mating and varies considerably among angiosperm species. However, little is known about large-scale biogeographic patterns and the correlates of floral longevity. Using published data on floral longevity from 818 angiosperm species in 134 families and 472 locations world-wide, we present the first global quantification of the latitudinal pattern of floral longevity and the relationships between floral longevity and a range of biotic and abiotic factors. Floral longevity exhibited a significant phylogenetic signal and was longer at higher latitudes in both northern and southern hemispheres, even after accounting for elevation. This latitudinal variation was associated with several biotic and abiotic variables. The mean temperature of the flowering season had the highest predictive power for floral longevity, followed by pollen number per flower. Surprisingly, compatibility status, flower size, pollination mode, and growth form had no significant effects on flower longevity. Our results suggest that physiological processes associated with floral maintenance play a key role in explaining latitudinal variation in floral longevity across global ecosystems, with potential implications for floral longevity under global climate change and 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 | 0.000 |
| 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 | 0.000 | 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".