Interactive effects of biochar and an organic dust suppressant for revegetation and erosion control with herbaceous seed mixtures and willow cuttings
Bibliographic record
Abstract
Abstract Land reclamation efforts on “non‐soil” substrates frequently involve additions of organic material coupled with soil‐stabilizing dust suppressants to control erosion, but formal experiments, particularly of interactive effects, are lacking. We examined the effects of Entac™ , a tall oil pitch emulsion, and pyrolyzed wood waste‐derived biochar on early plant establishment, growth, and survivorship, in 2 factorial greenhouse experiments: 1 using a seed mix widely used for roadside erosion control (the grasses Festuca rubra , Poa pratensis , Lolium perenne , and white clover [ Trifolium repens ]) and 1 using rooted cuttings of sand bar willow ( Salix exigua ). Biochar additions of 5, 10, and 20 t/ha enhanced biomass of clover by 14–250%, but had no significant effects on grasses. Entac additions inhibited early establishment and growth of both clover and grasses at all biochar treatment levels. Entac plus biochar treatments significantly enhanced survivorship of willows following a drought treatment in a greenhouse trial. In a field trial, Entac treatments had positive effects on willow diameter growth. Collectively, these results suggest that better soil moisture retention is the principal mechanism responsible for enhanced survivorship and growth of planted willows treated with Entac and biochar on sand substrates. Given Entac's inhibitive effects on early establishment of herbaceous species, and the abilities of Entac and biochar in combination to mitigate drought stress, these treatments may be particularly well suited for ecological restoration efforts using planted tree stock on coarse‐textured substrates and where exposure and ingress of non‐native herbaceous species are of concern.
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How this classification was reachedexpand
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 | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".