The Attractiveness of Five Common Mediterranean Weeds to Pollinators
Bibliographic record
Abstract
Concerns about a global decline in pollinators have called for more knowledge about the factors influencing wild pollinator abundance and diversity in agroecosystems. Agricultural intensification has been identified as the main cause of this “global pollinator crisis”, particularly due to reductions in natural areas holding critical floral and nesting resources. Maintaining native wild plants in agricultural landscapes (e.g., in field margins) is often recommended as a cost-effective and efficient method for pollinator conservation. In this study, the role of common wild flowers, often considered weeds, in supporting pollinators in a Mediterranean agroecosystem was investigated. This work involved a two-year field trial to compare five native weed species common in Mediterranean cereal agroecosystems: Convolvulus arvensis L., Daucus carota L., Malva sylvestris L., Papaver rhoeas L., and Sonchus oleraceus L. The goal was to compare the attractiveness of these species, and a mixture of all five, to different flower-visiting insect groups in order to assess their value in supporting wild pollinators. Overall, D. carota had the highest number of insect visits, followed by P. rhoeas. C. arvensis, M. sylvestris, and S. oleraceus, which had lower numbers of visits. On the basis of their overall attractiveness to pollinators and low risk for invasiveness, D. carota, P. rhoeas, and M. sylvestris are the most likely to contribute positively to the conservation of pollinators in agroecosystems. Our results also suggest that it is advantageous for wild flowers sown for the purpose of pollinator conservation to be grown in clumps, rather than highly intermingled, for improved visitation rates.
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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".