Exploring how soil fungi can be used to restore native trees on reclaimed substrates containing petroleum hydrocarbons
Bibliographic record
Abstract
As part of reclaiming landscapes mined for bitumen, ecosystems must be revegetated to restore self-sustaining ecosystems in the boreal forest of western Canada. Current reclamation practices can involve the construction of large landforms, sometimes from overburden containing up to 8% hydrocarbons, known as lean oil sand (LOS). This overburden is capped with a layer of salvaged soils, which acts as a base for revegetation. However, residual petroleum hydrocarbons can be present in these reclaimed landforms, and it is unclear what effect they may have on establishing native vegetation. In this same region, forests occur on natural surficial bitumen deposits and some vegetation persists on abandoned ore piles. Understanding how trees are able to survive in naturally occurring shallow-bituminous soils may be key to restoring forests on reclaimed landscapes, where residual petroleum hydrocarbons remain. The majority of the boreal forest plants interact with a group of root-associated fungi, namely mycorrhizal fungi. In addition to providing nutritional benefits, these fungi also have been found to increase a plant’s tolerance to refined petroleum hydrocarbons. Exploring the interaction between trees and mycorrhizal fungi in naturally occurring bituminous soils provides a unique opportunity to investigate whether mycorrhizas promote plant tolerance to residual hydrocarbons in LOS. First, I tested whether LOS is detrimental to plants as a result of hydrocarbons and/or barriers including poor nutrient concentration, water availability, and air availability. I found even at low concentrations (0.88%); LOS reduces plant growth. I also found that none of the ‘barrier modifications’ alleviated the detrimental effects of LOS on plant biomass. Next, I surveyed soil fungi across sites varying in hydrocarbon concentrations and fractions. I then used small amounts of soil from the field sites as inoculum for two conifer species grown in pots. The effect of inoculum varied by origin and tree species suggesting that soil inoculum may be an effective method for establishing some tree species on reclaimed landscapes. This experiment was followed by further testing across several experiments on the effect of LOS on fungal growth. I found that even at low concentrations (1.5%), LOS reduces fungal growth. Overall, my research provides evidence that even at low concentrations, if LOS is present within the rooting zone, plant and fungal growth may be impeded.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.002 | 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 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".