Pollen chemical and mechanical defences restrict host-plant use by bees
Bibliographic record
Abstract
Plants produce an array of chemical and mechanical defences that provide protection against many herbivores and pathogens. Putatively defensive compounds and structures can even occur in floral rewards: for example, the pollen of some plant taxa contains toxic compounds or possesses conspicuous spines. Yet little is known about whether pollen defences restrict host-plant use by bees. In other words, do bees, like other insect herbivores, tolerate the defences of their specific host plants while being harmed by non-host defences? To answer this question, we compared the effects of a chemical defence from Lupinus (Fabaceae) pollen and a putative mechanical defence (pollen spines) from Asteraceae pollen on larval survival of nine bee species in the tribe Osmiini (Megachilidae) varying in their pollen-host use. We found that both types of pollen defences reduce larval survival rate in some bee species. These detrimental effects were, however, mediated by host-plant associations, with bees being more tolerant of the pollen defences of their hosts, relative to the defences of plant taxa exploited by other species. This pattern strongly suggests that bees are adapted to the pollen defences of their hosts, and that host-plant use by bees is constrained by their ability to tolerate such defences.
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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 | 0.000 | 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".