Diversity of cavity-nesting bees (Hymenoptera: Apoidea) within apple orchards and wild habitats in the Annapolis Valley, Nova Scotia, Canada
Bibliographic record
Abstract
Abstract Solitary cavity-nesting bees, especially trap-nesting Megachilidae, have great potential as commercial pollinators. A few species have been developed for crop pollination, but the diversity, abundance, and potential pollination contributions of native cavity-nesting bees within agricultural systems have seldom been assessed. Our objectives were to compare the diversity and fecundity of cavity-nesting bees in Nova Scotia in natural ecosystems with those in apple orchards under three levels of management, using trap nests, and to determine whether any native bees show promise for development as pollinators. Our results show that species richness and numbers of bees reared from trap nests in commercially managed orchards, abandoned orchards, and natural habitats were similar, and species’ compositional patterns were not unique to specific habitats. Trap nests can be used to increase and maintain cavity-nesting bee populations within Nova Scotia apple orchards.Osmia tersulaCockerell (Megachilidae), which accounted for almost 45% of all bees captured and was the most abundant species nesting in all habitats evaluated, should be assessed for potential as a commercial pollinator of spring-flowering crops. The influence of natural cavities on bee species richness in trap-nesting surveys is also discussed.
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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 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".