Réponses fonctionnelles des communautés de pelouses calcicoles aux facteurs agro-écologiques dans les Préalpes françaises
Bibliographic record
Abstract
The identification of functional groups in calcareous grasslands of southern Vercors (Rhône-Alpes, France) is investigated through relationships between biological traits of the species and agro-ecological factors. Community patterns are determined by (i) the level of edaphic stress (oligotrophy and xericity) and (ii) the regime and the intensity of agropastoral management (grazing and mechanical cutting). In such grasslands submitted to regular disturbance, life traits related to dispersal and regeneration processes have greater importance for the differentiation of species than morphological traits, and Grime's adaptative strategies are the best predictors of species ordination on agro-ecological gradients (e.g., stress and disturbance). A classification of species in functional groups based on the same life traits and similar responses to disturbances is proposed, and its role in defining adequate conservation management of calcareous grassland by low-intensity livestock farming is discussed. The functional role of grazing is emphasized by the relationship between species dominance or rarity and their levels of consumption and dispersion by sheeps. In calcareous grassland communities, dominant species are the most palatable and the most dispersed by sheeps, while rarer species depend on other dispersal modes, such as seed rain or mowing machinery.Key words: life traits, functional groups, agropastoral practices, conservation management, RLQ analysis.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".