Exclusion Fencing Affects Beetle (Coleoptera) Abundance in Broccoli.
Bibliographic record
Abstract
Exclusion fencing represents a potentially useful management tool for key insect pests in broccoli but may also affect other invertebrates that have important roles in agroecosystems. Because beetles (Coleoptera) are generally abundant and diverse in agriculture and some species (i.e., members of the Carabidae and Staphylinidae) are important for biological control, pitfall traps were used in this study to compare beetle communities during late spring and early summer 2013 in fenced, unfenced and control plots of broccoli. Control plots were separated from fenced and unfenced plots to determine whether fencing increased captures in adjacent unfenced plots. Early on, fewer beetles (total and for most functional trait categories) were captured in fenced plots, but as the season progressed captures were similar among plot types. There was little evidence that fencing increased beetle diversity or activity density in adjacent unfenced plots, and later in the season some ground beetle species were instead strongly associated with control plots. Pitfall traps captured relatively high numbers of crucifer flea beetle, Phyllotreta cruciferae Goeze. Most captures were in unfenced and control plots early in the season, suggesting that fencing was effective in keeping this pest away from broccoli. Overall, fencing could limit or delay surface-active predatory beetles from accessing broccoli fields, having a negative effect on biological control services. However, since many beetles eventually permeated fencing, modifications to the fencing design may allow beetles entry, restrict exit, and allow increase of beetle communities to improve biological control services in fenced areas.
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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 | 0.000 | 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) | 0.001 | 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".