Soil Water Retention curve and Hydraulic Conductivity of Fungi-Treated Sand
Bibliographic record
Abstract
Filamentous fungi in soil branch hyphae through pores, creating an interconnected fiber network, which is known as mycelium. Fungal mycelium can cross-link and entangle soil particles, which alters soil pore structures. Fungi can also secret hydrophobic compounds, changing the water wettability of soils. These fungal traits can affect the hydraulic properties of soils. This study investigated the effect of fungi on soil water retention and hydraulic conductivity of the Ottawa 50/70 sand treated by a saprotrophic fungus, Trichoderma virens (commonly existing in soil). The soil water retention curve (SWRC) and hydraulic conductivity tests were performed on fungi-treated and untreated Ottawa 50/70 sand. Water repellency of fungi-treated sand was also assessed by measuring contact angles (between the water droplet and fungi on sand specimen) and water drop penetration time. The results of SWRC tests showed an approximate 6-fold increase of air entry suction in the fungi-treated sand, indicating the fungal treatment improved water retention capability. The increased air entry suction was attributed to the change of pore geometry due to mycelium network. A 2-fold reduction in hydraulic conductivity was observed in the fungi-treated sand when growing fungi for 10 days. The hydraulic conductivity reduction was attributed to the enhanced discontinuity of fluid channel by cross-linking and entangling mycelium network. Also, strong hydrophobicity of mycelium layer on the specimen surface contributed to the reduction of hydraulic conductivity. Scanning electron microscopy (SEM) imaging was conducted to assess the morphologies of sand matrix treated by fungi.
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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) | 0.001 | 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 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".