Floral strips adjacent to Manitoba crop fields attract beneficial insects shortly after establishment regardless of management type or landscape context
Bibliographic record
Abstract
Abstract Insects provide valuable ecosystem services to agriculture, but their populations are often lower in these areas. We established floral strips on the edges of eight organic and seven conventional crop fields in southern Manitoba. We then compared the capture rates of ground beetles, syrphid flies and bees in floral strips; control (unmodified) field edges; nearby semi‐natural sites; and within the strip and control fields at six distances away from field borders (5–150 m). The effects of farm management and landscape context on insect abundance, diversity and associated species traits were investigated. Capture rates of bees and beetles were significantly higher within the floral strips than the control treatment. However, capture rates of syrphids were significantly higher in the control. Beetles and bees responded positively to blooming forb cover and edge density (0.5 km), whereas syrphids responded positively to non‐rewarding agriculture and negatively to the semi‐natural areas (1 km). We found no significant difference in insect abundance or diversity between organic and conventional management types, and no differences in insect abundances within the fields were detected. No significant associations between insect traits and landscape variables were identified. These results show that floral strips are effective at attracting ground beetles and bees shortly after establishment, but these communities are functionally similar to those present in control fields. Longitudinal studies are needed to determine whether populations continue to increase over time and become more functionally diverse in fields with floral strips.
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How this classification was reachedexpand
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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".