Fungal-Mycelium Biocover: A Novel Biogeotechnology for Improving Soil Resistance to Water and Wind Erosion
Bibliographic record
Abstract
Soil erosion by water and wind poses serious threats to land resources, infrastructure, and human health. This study investigates the potential of fungal mycelium as a biocover to protect soil from erosion. Due to global warming, climate change, and human activities, land-related hazards, such as soil erosion, dust storms, and desertification, have increased in frequency and intensity. These hazards affect agricultural lands, coastal zones, fire-affected areas, and geotechnical structures, such as slopes and embankments. Planting trees and vegetation is a natural way to prevent desertification, reduce soil erosion, and sequester carbon, but it takes a long time (1–3 years) to establish. Considering the rapid rate of soil loss due to climate change, there is a need to develop alternative soil stabilization techniques that are eco-friendly, cost-effective, and supportive of vegetation growth and establishment. This study presents a novel biogeotechnology that uses living microfibers (fungal mycelia) as a soft engineering method to stabilize soil surface and minimize soil loss. Experiments were conducted on fungal-treated Ottawa 20/30 and F60 silica sands to evaluate their resistance to water and wind erosion, respectively. Sand slopes were inoculated with spore suspension of Pleurotus ostreatus fungus and grown for 7-, 10-, and 14-day periods. The slopes were exposed to simulated rainfall events, and the soil loss and runoff were measured. The Portable In Situ Wind Erosion Laboratory (PI-SWERL) was used to test the wind erosion resistance of another set of fungal-treated and untreated F60 silica sand. Results show that the fungal-mycelium treatment of loose cohesionless sand reduced soil loss (to less than 5%) compared to untreated samples. The threshold friction velocity (indicating resistance to dust entrainment) of treated sands was significantly higher than that of untreated sand due to the mycelia biocover formed after a growth period of 7 days. The results demonstrate the feasibility of engineered living systems such as fungal-mycelium growth to serve as a fast, cost-effective, eco-friendly, and soft-engineering alternative for mitigating unsustainable soil loss.
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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".