Pollen sources for honeybees in Israel: Source, periods of shortage, and influence on population growth
Bibliographic record
Abstract
The nutritional demands of honeybees are met by two plant-produced components: nectar and pollen, the contents of which vary among floral sources. In Israel, there is an extraordinary richness in plant species, and one of the dominant insect pollinators is the honeybee (Apis mellifera L.). July to February is characterized as a period of low flower abundance for local species in general and for bee forage plants in particular. In this study, we monitored the amount and number of pollen sources collected by honeybees, and where possible also identified the plant source of pollen, in four geographically distinct sites in Israel. We also assessed honeybee colonies (population level, sealed brood area, and pollen and honey stores) and studied the effect of pollen levels on population growth. Our results show that peak pollen-collection times differ according to site. The number of pollen sources from trapped pollen pellets varied during the year, between sites, and between colonies in the same site, and ranged between 5 and 20 plant species per sampling date per site. The most abundant pollen source in each sample comprised between 22 and 94% of the pollen pellets. There were only a few cases in which pollen was collected from fewer than five or more than nine plants in each colony's sample. Thus, colonies seem to specialize in only a small number of species of the available flora. Overall, in all sites, the daily amount of pollen collected was significantly correlated with sealed brood and pollen store areas.
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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".