Biodiversity of oribatid mites as a tool to monitor soil health in the agroecological transition: Digging deeper into French Mediterranean vineyards
Bibliographic record
Abstract
Oribatid mites play a vital ecological role in soil ecosystems by driving key processes like decomposition and nutrient cycling. Their abundance and sensitivity to environmental changes make them valuable bioindicators of soil health. This study evaluates varying agricultural management practices through shifts in oribatid mite communities, using them as a tool to monitor the progress of the agroecological transition in Mediterranean vineyards. In autumn 2023, soil samples were collected from 30 plots cosisting in conventional and organic vineyards with varying inter-row vegetation cover managment intensities, as well as natural garrigue vegetation used as a reference. A total of 7,574 oribatid mites were extracted using a modified Berlese-Tullgren funnel. We analysed the effect of vineyard management practices on oribatid mite abundance, family richness, and diversity using generalized linear models. Natural systems exhibited significantly higher abundance, richness, and diversity compared to vineyard soils. Among vineyards, those with permanent vegetation cover had mite communities more similar to natural systems, while temporarily covered and bare-soil showed reduced diversity and abundance. No strong differences in oribatid mite abundance were observed between conventional and organic vineyards, but organic plots showed higher diversity. Indicator species analysis revealed several oribatid mite families strongly associated with natural habitats and vineyards with permanent vegetation cover. These findings support that agroecological practices might create more suitable conditions for oribatid mites in vineyards, helping in maintain communities similar to those found in natural habitats.
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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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".