Pollinator foraging tactics have divergent consequences for the mating system of a tropical plant
Bibliographic record
Abstract
Resolving the consequences of pollinator foraging behaviour for plant mating systems is a fundamental challenge in evolutionary ecology. Pollinators may adopt particular foraging tactics: complete trapline foraging (repeated movements along a fixed route), sample-and-shift trapline foraging (a variable route that incorporates information from previous experiences) and territorial foraging (stochastic movements within a restricted area). Studies that integrate these pollinator foraging tactics with plant mating systems are generally lacking. We investigate the consequences of particular pollinator foraging tactics for Heliconia tortuosa. We combine parentage and sibship inference analysis with simulation modelling to: estimate mating system parameters; infer the foraging tactic adopted by the pollinators; and quantify the impact of pollinator foraging tactics on mating system parameters. We found high outcrossing rates, ubiquitous multiple paternity and a pronounced departure from near-neighbour mating. We also found that plants repeatedly receive pollen from a series of particular donors. We infer that the pollinators primarily adopt complete trapline foraging and occasionally engage in sample-and-shift trapline foraging. This enhances multiple paternity without a substantial increase in near-neighbour mating. The particular pollinator foraging tactics have divergent consequences for multiple paternity and near-neighbour mating. Thus, pollinator foraging behaviour is an important driver of the ecology and evolution of plant mating systems.
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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 | 0.000 | 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".