Wetland cover in agricultural landscapes is positively associated with bumblebee abundance
Bibliographic record
Abstract
Abstract Conversion of land for agricultural use is a leading driver of global biodiversity loss. Natural and semi‐natural lands within agricultural landscapes are targeted for protection because they provide habitat for many organisms. Pothole (or kettle) wetlands occur across the Northern Hemisphere and are a focus for conservation both because of their location within agriculturally intensive landscapes and their importance to vertebrates, especially migratory birds. Recent evidence suggests that wetlands may also be an important habitat for arthropods, including insects that provide ecosystem services. To understand how insects associate with wetlands and landscape features, we examine the relationship between bumblebees ( Bombus ), and wetland area, cropland area and wetland perimeter‐area ratio. We found that wetland area is significantly positively associated with the occurrence and abundance of the species studied. We also found that the relationship between bumblebees and wetland perimeter‐area ratio varied across the growing season. This suggests that the importance of wetland edge as a foraging habitat varies across the season. These results show the utility of wetlands to bees, though their resources are likely not being used uniformly by all bumblebee species or across the entire growing season. Our results also suggest that pothole wetlands in agricultural landscapes are likely to support biodiversity, and their conservation contributes to overall ecosystem health and function.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.004 | 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".