Evaluation of the Suitability of Engineered Growth of Fungal-Mycelial Networks for Reinforcement of Sands
Bibliographic record
Abstract
Naturally occurring sandy soils are often susceptible to erosion by water and/or wind, thus requiring stabilization. Conventional approaches used as temporary remedial measures prior to the establishment of vegetation (and where suitable vegetation cannot be established) are often associated with high potable water use, application and installation/maintenance costs, significant energy inputs, and increased carbon emissions. This study presents findings from bench-scale rainfall erosion tests conducted to evaluate the suitability of a nature-based engineered living system consisting of fungal mycelium for erosion mitigation. The vegetative component of filamentous fungal species, known as mycelium (Figure 1), grows in soils through the formation of massive 3-dimensional networks of natural fibers at micron-scale. These networks are capable of modifying the hydraulic and mechanical behavior of soils. Mycelia secrete extracellular polysaccharides that bind soil particles together thus improving the formation of water stable aggregates and beneficially altering the surface wettability of the soil grains. Previous studies have shown that mycelium could induce water repellency in sands (Salifu & El Mountassir, 2020), delay infiltration, and reduce hydraulic conductivity (Salifu et al., 2021) thereby reducing the erodibility of sand. However, the influence of engineered mycelium growth on soil erodibility under simulated rainfall conditions is largely unexplored. <fig><graphic xlink:href=23045_files/23045-01.jpg id=DF1E5645-088F-4B69-BDA9-8A83DD4025E4></graphic></fig> Ottawa 20/30 sand amended with lignocellulose fibers was treated with a fungal spores‘ suspension (FSS) of Pleurotus ostreatus fungus. The treated sand was compacted into a 30x15x5 cm test pan and incubated at 25°C for 7-, 10-, and 14-days prior to a rainfall simulation erosion test. Untreated control specimens were prepared using water instead of FSS. A rainstorm of intensity ~6.7 cm/min falling from a height 25cm was induced using a calibrated garden sprinkler (adapted from a Nasco Soil Erosion Simulator Laboratory kit). The specimens were inclined at a slope of 30°. During each rainfall simulation event, runoff and eroded soil were collected from the base of respective specimens 1-minute intervals up to 5 minutes, and then at 3 minutes intervals until sample collapsed. <fig><graphic xlink:href=23045_files/23045-00.jpg id=C2EE4790-27DE-443D-8E29-151B3CF3D707></graphic></fig> Untreated soil slopes collapsed after <2 mins of rainstorm, while all treated soil slopes remained stable for at least 8 minutes duration with significantly less soil yield. The 10-day sample withstood up to 13 mins of simulated rainstorm, as shown in Figure 2. Mycelium regrowth was observed in the treated samples 48 hrs. after the end of the erosion tests, showing the potential for long-term low-cost treatment using mycelium. Replenishing moisture loss during growth period could sustain mycelium growth and further enhance soil resistance to erosion over time. These results demonstrate that the engineered growth of mycelium in soils is promising as a nature-based environmentally friendly alternative to the current engineering practices for erosion mitigation.
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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 | 0.015 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".