Diversity and species identity effects on fine root productivity and turnover in a species-rich temperate broad-leaved forest
Why this work is in the frame
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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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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 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) | 0.000 | 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 it