Diversity and species identity effects on fine root productivity and turnover in a species-rich temperate broad-leaved forest
Bibliographic record
Abstract
We investigated the evidence of belowground overyielding in a species-rich temperate broad-leaved forest with an ingrowth core study in 100 plots containing five common tree species (beech, lime, maple, hornbeam, ash) in mono-specific and 2-species or 3-species combinations. This design allowed separating diversity and species identity effects on root dynamics in a mature forest with long continuity. Fine root productivity was not significantly different between mono-specific and 2- or 3-species plots, whereas fine root turnover was significantly higher in the mixed than the mono-specific plots. Species identity effects on root turnover and root productivity were important. Ash achieved in the mixtures the highest fine root productivity and root turnover of all species; it is an apparent key species in this forest. Evidence in support of a diversity effect on fine root productivity and turnover was weak, however.
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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 | 0.001 | 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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".