A test of simultaneous resource and pollen limitation in <i>Stylidium armeria</i>
Bibliographic record
Abstract
This study tests the Haig-Westoby model, which predicts that seed output will be limited simultaneously by pollen and resources when plants optimally distribute their reproductive investment. The test was conducted over 2 yr using Stylidium armeria in a factorial design that fully crossed three pollination levels (small stigmatic loads, open pollination, and supplementation of natural loads) with three levels of resource availability (reduction through partial defoliation, unmanipulated resource conditions, and supplementation through nitrogen, phosphorus and potassium (NPK) addition). There was no evidence of pollen limitation from supplemental pollination; however, pollen reductions (to about half the normal mean stigmatic loads) sharply reduced seed output. There was no evidence of resource limitation, in that NPK addition did not, by itself, significantly elevate seed output in either year of the study, while resource reduction by defoliation lowered seed output in the second year. Simultaneous addition of both pollen and resources strongly and significantly increased seed production. These results match the direction of effects predicted by the Haig-Westoby model, and suggest that S. armeria plants at our site are at or near an equilibrium of joint limitation of seed production by pollen capture and resource availability.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".