Efficiency in pollen foraging by honey bees: Time, motion and pollen depletion on flowers of <i>Sisyrinchium palmifolium</i> Linnaeus (Asparagales: Iridaceae)
Bibliographic record
Abstract
Honey bees depend on flower resources (nectar and pollen) to supply individual and colony needs. Although behavioural studies already assessed optimum foraging patterns of bumblebees, honey bees foraging behavioural patterns have been poorly assessed. We used Sysirinchium palmifolium L. (Iridaceae), a low-growing, abundant and anthophilous grassland flower to test the hypotheses that Apis mellifera workers would i) spend more time, ii) visit a greater number of flowers, and iii) travel greater distances within patches of S. palmifolium which were newly opened or not been visited by other pollinators when compared to foraging on patches that were available to pollinators during its whole blooming period (only one day). In two different sunny days, we measured bee activities in an area opened for visitation during the whole anthesis (OP plot treatment) and another opened for visitation only half of anthesis (CL plot treatment). We observed bees spending more time, visiting more flowers and travelling more in S. palmifolium CL treatment than the OP plot treatment. Previous studies already showed bees alter their foraging behaviour in the lack of resources. Honey bees are able to remember the period of the day when resources are usually the higher, they probably detect the most promising period to gather resources on S. palmifolium flowers. Since A. mellifera is a pollinator with a wide-distribution and is considered an important cause of changes on native pollinator communities, we support additional studies evaluating its foraging behaviours to better understand how it explores flower resources.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 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) | 0.000 | 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 teacher head, 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".