Willow aboveground and belowground traits can predict phytoremediation services
Bibliographic record
Abstract
We explored traits-services correlations with plantations of short-rotation coppiced willows (Salix spp.). We conducted a four-year field trial (2016-2019) on a brownfield contaminated by trace elements (As, Ba, Cd, Cu, Mn, Pb, Se, and Zn), using split-plots nested into four blocks. We sampled 16 willow plantations (4.5m X 2.5m) of one or four cultivars from which half was coppiced after three years. For each plot, we measured ten functional traits from aboveground and belowground tissues (LA, SLA, LDMC, RDMC, LNC, RNC, LCC, RCC, SSD, and leaf pH) and six phytoremediation services (Phytoextraction, phytostabilisation, translocation factors, soil decontamination, and bioconcentration factors of total and belowground tissues). To do so, we measured trace elements in plant tissues and soil. We tested the impacts of treatments (willow diversity and coppicing) on the services and traits through linear mixed models and controlled for spatial heterogeneity with soil covariates (OM, texture and initial contamination). We explored the traits-services correlations through a redundancy analysis (RDA).
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.003 |
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".