The contribution of honey bees, flies and wasps to avocado (<i>Persea americana</i>) pollination in southern Mexico
Bibliographic record
Abstract
Although avocado is native to Mexico, there are no comparative measures in this country on the performance of its flower visitors as pollinators. The contribution of honey bees, flies and wasps to the pollination of avocado from tropical Mexico was assessed by comparing abundance, speed of flower visitation, quantity of pollen carried per individual and pollen deposited on virgin flowers after single visits. The values of abundance and frequency of flower visitation with pollen deposition were combined to obtain a measure of pollinator performance (PP). The most abundant insects on avocado were flies (mean ± SE: 15. 2 ± 6.2), followed by honey bees (9.4 ± 6.3) and wasps (4.2 ± 3.1) (ANOVA F = 91.71, d.f. = 2,78; P < 0.001). Honey bees and wasps visited similar number of flowers (8.2 ± 3.1 and 7.5 ± 2.6 respectively), and more than flies (4.1 ± 1.2) in the same time period (F = 17.63; d.f. = 2,33; P < 0.01). Although flies carried far more avocado pollen on their bodies (44.9 ± 16.8 grains) compared with honey bees and wasps, (21.3 ± 6.2 and 23.8 ± 8.11 grains, respectively; H = 26.522, df = 2, P = 0.001), the number of pollen grains deposited on a stigma after a single visit was similar for the three taxa (2-5). There was evidence for a significant and similarly positive PP of both honey bees and flies as avocado pollinators over wasps, given their abundance, potential for pollen transport and deposition of pollen on stigmas.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.000 | 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".