Agritrap project : Enhancing Buprestidae monitoring in Europe
Bibliographic record
Abstract
Supplements and detailed analysis of a paper submitted to Plos One : Enhancing Buprestidae monitoring in Europe: trap catches increase with a fluorescent yellow colour but not with the presence of decoys. Kuhn A*, San Martin G*, Hasbroucq S, Beliën T, Bonte J, Bouget C, Hautier L, Sweeney J, Grégoire JC More details on the data structure and experimental design are provided in the pdf report.Abstract of the paper :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).
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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 | 0.006 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.007 | 0.002 |
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".