Different semi-natural habitat types provide complementary nesting resources for wild bees
Bibliographic record
Abstract
Semi-natural habitats provide refuge for pollinating insects such as wild bees. Different types of semi-natural habitat can provide complementary floral resources throughout the year, but it is uncertain to what extent different semi-natural habitat types provide nesting habitat for wild bees. In this study, nesting resources for wild bees and nest-searching bees were surveyed visually in three different types of semi-natural habitat (i.e., hollow roads, tree rows, and forest edges). The composition of nesting resources for wild bees varied across the three types of semi-natural habitat. We also identified clear indicators of nesting resources within the different habitat types. We conclude that different types of semi-natural habitat provide varying and complementary nesting resources for wild bees. This study further highlights the importance of semi-natural habitat for pollinator conservation and emphasizes the need for further research to increase our understanding how different wild bee species use different habitat types for nesting.
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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".