Relationships between soil chemistry, microbial biomass and the collembolan fauna of southern Québec sugar maple stands
Bibliographic record
Abstract
The relationships between the presence of endogeic and epigeic collembolan species and chemical and microbiological top soil parameters were examined for eight sugar maple forests. While the composition of the tree strata was similar among sites, the soil conditions varied widely and encompassed three regions of different geological origins as well as contrasting humus types. Endogeic species were extracted using Berlese-Tullgren equipment, whereas epigeic species were collected with pit-light traps (Luminoc®). In all, 92 species from 14 families and 36 genera were identified. The association between sampling locations and soil parameters was determined by principal component analysis (PCA), and the relationships between epigeic and endogeic collembolan communities and soil parameters were determined by canonical correspondence analysis (CCA and DCCA). The DCCA revealed that the distribution of endogeic species of the collembolan fauna was related to organic matter content, including pH, C, N, and C/N ratio. Sites were clustered according to humus types. Epigeic species were influenced by available P and exchangeable K and Mg. Sites were clustered according to geographical distribution, suggesting that for epigeic species, regional occurrence could be a stronger determinant of community composition than soil parameters.
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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 | 0.001 |
| Science and technology studies | 0.001 | 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) | 0.002 | 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".