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Record W4400776355 · doi:10.1371/journal.pone.0307397

Enhancing Buprestidae monitoring in Europe: Trap catches increase with a fluorescent yellow colour but not with the presence of decoys

2024· article· en· W4400776355 on OpenAlexafffundabout
Alexandre Kuhn, Gilles San Martin, Séverine Hasbroucq, Tim Beliën, Jochem Bonte, Christophe Bouget, Louis Hautier, Jon Sweeney, Jean‐Claude Grégoire

Bibliographic record

VenuePLoS ONE · 2024
Typearticle
Languageen
FieldEnvironmental Science
TopicForest Insect Ecology and Management
Canadian institutionsNatural Resources CanadaCanadian Forest Service
FundersCanadian Forest ServiceInstituut voor Landbouw-, Visserij- en Voedingsonderzoek, Vlaamse OverheidU.S. Forest ServiceU.S. Department of AgricultureInstitut National de Recherche pour l'Agriculture, l'Alimentation et l'EnvironnementFOD Volksgezondheid, Veiligheid van de Voedselketen en Leefmilieu
KeywordsBuprestidaeAgrilusEmerald ash borerTrap (plumbing)BiologyDeciduousZoologyEcologyGeographyFraxinus

Abstract

fetched live from OpenAlex

This study investigated the efficacy of various traps differing in colour (green or yellow), presence or absence of decoys (dead Agrilus planipennis) or design (commercial MULTz or multifunnel traps, and homemade bottle- or fan-traps) for monitoring European Buprestidae in deciduous forests and pear orchards. Over two years, we collected 2220 samples on a two-week basis from 382 traps across 46 sites in Belgium and France. None of the traps proved effective for monitoring Agrilus sinuatus in infested pear orchards (17 specimens captured in 2021, 0 in 2022). The decoys did not affect the catch rates whatever the trap model, colour, buprestid species or sex. The fluorescent yellow traps (MULTz and yellow fan-traps) tended to be more attractive than the green traps (green fan-traps and, to a lower extent, multifunnel green traps). Most Agrilus species showed similar patterns in mean trap catches, with the exception of Agrilus biguttatus, which had the largest catches in the green multifunnel traps. Finally, we observed a high variation in catch rates between localities: the site explained 64% of the catches variance, while the tree within the site and the type of trap explained only 6-8.5% each. In many sites, we captured very few specimens, despite the abundance of dying mature trees favourable to the development of Buprestidae. For the early detection of non-native Buprestidae, it therefore seems essential to maximise the number of monitoring sites. Due to their cost-effectiveness, lightweight design, and modularity, fan-traps emerged as promising tools for buprestid monitoring. The study's findings extend beyond European fauna, as a preliminary trial in Canada suggested that yellow fan-traps could also improve captures of non-European buprestid species and catch species of interest such as Agrilus bilineatus (a species on the EPPO A2 list of pests/pathogens recommended for regulation in the EU).

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.003
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.016
GPT teacher head0.201
Teacher spread0.185 · 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 source (direct Gemma or distilled Codex), 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

Citations9
Published2024
Admission routes3
Has abstractyes

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