Assessing Wild Bee Biodiversity in Cranberry Agroenvironments: Influence of Natural Habitats
Bibliographic record
Abstract
The conservation of bee populations for pollination in agricultural landscapes has attracted a lot of recent research interest, especially for crop industries undergoing expansion to meet increased production demands. In Canada, much growth has been occurring with commercial cranberry production, a field crop which is largely dependent on bee pollination. Wild bee pollinators could be negatively impacted by losses of natural habitat surrounding cranberry fields to accommodate increased production, but growers have little insight on how to manage their lands to maximize the presence of wild bees. Here, we described a 2-yr study where bee diversity and species composition were investigated to better understand the dynamic between natural habitat and cranberry fields. Bees were sampled using pan-traps and hand netting both within cranberry fields and in one of the three adjacent natural habitat types once a week during the crop flowering period. We found that bee community composition among cranberry fields did not differ based on the respective adjacent habitat type, but fields bordered by meadows were marginally less diverse than fields bordered by forest. As one would expect, field and natural habitat communities differed in terms of species composition and species richness. There was no evidence that one type of natural habitat was more favorable for the bees than another. Future agrobiodiversity studies should simultaneously examine bee diversity comprised in both crop fields and adjacent natural environments to better understand the species dynamics essential to the preservation of pollination services.
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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".