Potential of bigleaf lupine for building and sustaining<i>Osmia lignaria</i>populations for pollination of apple
Bibliographic record
Abstract
Abstract Bees of the genusOsmiaPanzer (Hymenoptera: Megachilidae) are among the contenders to replace honey bees,Apis melliferaL. (Apidae), for pollinating tree-fruit crops. One species,Osmia lignariaSay, has shown great potential in western North America and was recently introduced into Nova Scotia for evaluation as a pollinator of apple,MalusMill. (Rosaceae). A major component of that study was to develop management options forO. lignaria, including methods of sustaining nesting females following crop flowering to maximize population recovery for pollination in subsequent seasons. The objective of this study was to evaluate bigleaf lupine,Lupinus polyphyllusLindl. (Fabaceae), as a secondary food plant for nesting femaleO. lignariaby investigating nesting activity, pollen-use patterns, and fecundity. During 2002–2003, femaleO. lignariacollected high proportions of apple pollen (>70%) during mid and late flowering; after then, most pollen (>90%) was collected from bigleaf lupine. The flowering period of lupine in Nova Scotia (late May to early July) slightly overlapped that of apple, so there was no scarcity of pollen resources during the life-span ofO. lignaria. Most nests typically showed high levels (≤200%) of population growth, but recorded levels varied among nest types and locations. In 2004, nests closer to lupine plots exhibited significantly greater population recovery than nests located farther away (i.e., approximately 600 m). Bigleaf lupine is a suitable plant species for meeting the pollen requirements of nesting populations ofO. lignariafollowing apple flowering, thus promoting the recovery of populations to meet apple pollination requirements in subsequent seasons.
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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 | 0.000 | 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".