Seed dispersal in the Iberian pear,<i>Pyrus bourgaeana</i>: A role for infrequent mutualists
Bibliographic record
Abstract
Seed dispersal by animals is a key interaction, with effects on the population ecology and evolution of many plant lineages. Despite the fact that infrequent seed dispersers can potentially provide important services to plant populations, little attention has been paid so far to scarce mutualists. We assessed different aspects of quantity and quality of seed dispersal from fruit removal to seed germination in the Iberian pear, Pyrus bourgaeana, finding that fruit consumers markedly differed in the nature of their interaction with the tree. Whereas the abundant rodents, rabbits, and deer damaged all seeds eaten, the uncommon carnivores badger and fox and the abundant boars dispersed a large fraction of ingested seeds as viable propagules, acting as legitimate seed dispersers. Despite low rates of visitation by badgers to fruiting trees, they transported more viable seeds than the abundant boars, due to better seed treatment and a higher feeding rate on pears. Seed dispersal by all 3 legitimate dispersers, especially the badger, enhanced post-dispersal P. bourgaeana seed survival, supporting the “escape” predation hypothesis. Pyrus bourgaeana showed relatively high frequencies of visits by a myriad of frugivores; however, it relied on the dispersal service provided by an infrequent carnivore, the badger, rather than on those provided by the abundant mammalian herbivores. Therefore, under some circumstances, uncommon animal counterparts play major roles in their mutualistic interactions with flowering plants.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".