WILD BEE ABUNDANCE AND SEED PRODUCTION IN CONVENTIONAL, ORGANIC, AND GENETICALLY MODIFIED CANOLA
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The ecological impacts of agriculture are of concern, especially with genetically modified and other intensive, modern cropping systems, yet little is known about effects on wild bee populations and subsequent implications for pollination. Pollination deficit (the difference between potential and actual pollination) and bee abundance were measured in organic, conventional, and herbicide‐resistant, genetically modified (GM) canola fields ( Brassica napus and B. rapa ) in northern Alberta, Canada, in the summer of 2002. Bee abundance data were collected using pan traps and standardized sweep netting, and pollination deficit was assessed by comparing the number of seeds per fruit from open‐pollinated and supplementally pollinated flowers. There was no pollination deficit in organic fields, a moderate pollination deficit in conventional fields, and the greatest pollination deficit in GM fields. Bee abundance was greatest in organic fields, followed by conventional fields, and lowest in GM fields. Overall, there was a strong, positive relationship between bee abundance at sampling locations and reduced pollination deficits. Seed set in B. napus increased with greater bee abundance. Because B. rapa is an obligate outcrossing species, the lack of pollination deficit in the organic ( B. rapa ) fields likely was due to the high bee abundance rather than a lower dependence of B. rapa on pollinators than B. napus canola. Our study illustrates the importance of wild bees to agricultural production and suggests that some agroecosystems may better sustain wild bee abundance, resulting in greater seed production. Further research on why some cropping systems, such as genetically modified, herbicide‐resistant canola, have low wild bee abundance would be useful for management of agroecosystems to promote sustainability of food production.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 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) | 0.000 | 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 it