Bibliographic record
Abstract
Even though there is no reason to believe in a unique mechanism that would explain rarity, recognizing common patterns might aid in identifying effective conservation strategies. This study therefore approached the problem of rarity in spring habitats both at the level of multiple taxonomic groups (molluscs, oligochaeta, water mites, copepods, ostracods, chironomids, stoneflies, caddisflies, diatoms, and vascular plants) and, in more detail, at the level of a single group (bryophytes). The aim was to evaluate whether the proportion of rare species was associated with uncommon environmental conditions, while for the bryophytes an additional aim was to test whether common and rare species differed concerning their niche parameters (niche breadth and niche position), their biological traits (involved in dispersal processes), and their habitat preferences. Overall, 4 major results may be highlighted. 1) The significant concordance between the rarity of virtually all the taxonomic groups inhabiting spring habitats and their environmental conditions suggested that most of the rare species at community level might be explained by their uncommon resource requirements. 2) Rare bryophyte species not only had high niche positions, as did all the taxonomic groups, but also had narrow niche breadths. This result suggests an interesting distinction between resource use and resource availability. 3) Because the species traits linked to dispersal ability did not differ between common and rare species, the hypothesis of an important role being played by these traits in determining species distribution was not supported. 4) Among the rare bryophyte species, an undefined number were casual. Because they were less hygrophilous and less influenced by the environment, this result suggests that they might recruit essentially by chance from the surrounding 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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".