Effect of boundary type and season on predatory arthropods associated with field margins on New Zealand farmland
Bibliographic record
Abstract
Pitfall traps were used to monitor predatory arthropod numbers along two types of field boundary, a post and wire fence line and a Cupressus macrocarpa hedge, along the same paddock margin in Canterbury, New Zealand, over 24 months. The seven most abundant predator groups recorded were: Araneae > Phalangiidae > Staphylinidae > Coccinellidae > Chilopoda > Hemerobiidae > Carabidae. Araneae, Phalangiidae, Staphylinidae, Chilopoda and Hemerobiidae were found in larger numbers at the wire fence than at the hedge site, whereas the numbers of Carabidae and Coccinellidae adults exhibited no field margin preference. However, more species of Araneae and Staphylinidae were caught at the hedge site, whereas species richness of carabid beetles was greatest at the wire fence. Principal component analysis clearly separated the samples collected from the two habitats based on the assemblages of Araneae, Staphylinidae and Carabidae, and certain species in each of these taxonomic groups appeared to be particularly associated with one boundary type or the other. All the main taxonomic groups exhibited clear seasonal patterns, with distinct peaks in abundance occurring at certain times of the year. The results of the study reinforce the idea that management of field boundaries can be used to manipulate the type and abundance of particular groups of predatory arthropods, and that seasonal patterns should be taken into account in schemes of integrated pest management so that any adverse effects of biocide application on these beneficial species may be minimised.
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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 | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".