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Record W2051365648 · doi:10.1080/03014223.2014.953552

Effect of boundary type and season on predatory arthropods associated with field margins on New Zealand farmland

2014· article· en· W2051365648 on OpenAlexaff
Michael H. Bowie, Jan Klimaszewski, C. J. Vink, Simon Hodge, S. D. Wratten

Bibliographic record

VenueNew Zealand Journal of Zoology · 2014
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicInsect-Plant Interactions and Control
Canadian institutionsNatural Resources CanadaCanadian Forest Service
Fundersnot available
KeywordsBiologyCoccinellidaeEcologyAbundance (ecology)PredatorSpecies richnessPredation

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.361
Threshold uncertainty score0.270

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.006
GPT teacher head0.220
Teacher spread0.214 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations23
Published2014
Admission routes1
Has abstractyes

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