A comparative analysis of pollen limitation in flowering plants
Bibliographic record
Abstract
We conducted a comparative analysis to determine life history and ecological correlates of pollen limitation among 224 species of animal-pollinated flowering plants. To test predictions concerning the occurrence of pollen limitation, species were classified categorically for six life-history traits (self-compatible vs. self-incompatible, autogamous vs. non-autogamous, specialized vs. unspecialized floral morphology, nectariferous vs. nectarless, monocarpic vs. polycarpic, herbaceous vs. woody) and two ecological conditions (presence in open vs. forested habitats and temperate vs. tropical biomes). Pollen limitation of species in contrasting categories was compared using non-parametric tests (TIPs analysis) and phylogenetically-independent contrasts (PICs). The results of TIPs and PICs analyses were generally congruent, although fewer significant contrasts were evident with PICs, probably because of low statistical power. Overall the results suggest that the influence of phylogenetic history on the intensity of pollen limitation was not particularly strong. Nonetheless, significant variation in the degree of pollen limitation was demonstrated among seven angiosperm families suggesting some phylogenetic component to the phenomenon. With both TIPs and PICs, pollen limitation was less intense in self-compatible and autogamous species. TIPs analysis demonstrated that herbaceous, nectariferous, and temperate species were less likely to be pollen-limited, but using PICs this could only be corroborated for those that were self-incompatible. None of the traits were singularly unambiguous predictors of pollen limitation, possibly reflecting the stochastic nature of pollinator service.
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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 | 0.000 |
| 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) | 0.001 | 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".