Hymenoptera Parasitoid, a Suitable Biodiversity Resource for Vineyard Environmental Discrimination
Bibliographic record
Abstract
Vineyards host a high number of insect species and represent suitable environments to investigate the relationships among arthropod community and environmental biodiversity. Hymenoptera Braconidae summarize many of the attributes required to a reliable group of bioindicators. Indeed, they represent a complete assemblage of a family taxon and are quite well known from a taxonomical and faunistic point of view, occupying the top of the ecological (trophic) pyramid and occurring in very diverse habitats. Braconidae subfamilies are often linked to a single host order, so directly expressing in some way, a functional role in the environment. Here we compared the abundance and the community composition of braconid subfamilies in three differently managed vineyards for two years (2012 and 2013). In each vineyard, the community structure resulted quite similar (abundance and composition) during the first part, but significantly diverged in the second part of the research period. Non Metric Dimensional Scale and Permanova Analysis well described the population distribution. The abundance of some subfamilies, consistently with their ecology, resulted significantly related to the habitat variables considered, as showed by the Multiple Regression analysis. The adoption of insecticides seems to not influence negatively braconid populations, probably because the surrounding areas are provided with a rich local vegetation of bushes and trees, where natural enemies can find refuge. The abundance of some subfamilies that adopt an endophagous koinobiont strategy against lepidopteran larvae showed differences statistically significant in the vineyard where the mating disruption technique was adopted, in comparison with their abundance in the other two vineyards.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".