Use of Nest and Pollen Resources by Leafcutter Bees, Genus Megachile (Hymenoptera: Megachilidae) in Central Michigan
Bibliographic record
Abstract
Many landscapes throughout the Great Lakes region have experienced reductions in floral and nesting resources for bees. Identifying the resources used by bees in the family Megachilidae can be used to inform conservation programs that aim to support this group. In this study, we identified the preferred nesting substrate and size, as well as the proportion of distinct pollen types used for offspring provisioning by Megachile species. A total of 39 completed artificial nesting tubes were collected between July 25 and August 30, 2016. A majority of completed nests were in 4 mm diameter tubes. However, more 6 mm and 7 mm diameter nests were occupied later in the season. A total of 98 cells from 20 nests were analyzed for the composition of the pollen provisions. Nesting females gathered pollen primarily from Trifolium repens-type (70.2% of total pollen) and the majority of collection of this species occurred between July 25 and August 10. There was also frequent pollen collection from Centaurea stoebe (L.) (9.0%), Rudbeckia-type (8.4%), and Cirsium spp. (8.3%) with the majority of collection from these species occurring after August 10. Our results show that Megachile species at our mid-Michigan site exhibited strong preferences for specific nest hole sizes, and they primarily collected pollen from non-native plants. This information can inform efforts to build local populations of these summer-active bees using combined nesting and foraging resources.
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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 | 0.000 | 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".