Functional and compositional responses of microorganisms to reclamation of surface-mined boreal forest soils
Bibliographic record
Abstract
Over the last four decades, surface mining of oil sands in the boreal forest of western Canada has created large areas of disturbed land. The current regulatory framework requires that derelict land be reclaimed to pre-disturbance conditions. This has prompted the need to assess the effectiveness of reclamation, which relies on the use of salvaged materials (e.g., tailings sand and overburden), on key ecosystem components such as soil microorganisms. In this thesis, I examined landscape-scale changes in soil microbial community composition and function in response to different reclamation amendments and in natural sites comprising a regional environmental gradient. Using molecular fingerprinting (phospholipid fatty acids and denaturing gradient gel electrophoresis) and phylogenetic analyses of 16S rRNA genes, I found that microbial communities in natural soils differed from those of reclaimed soils. This dissimilarity was driven by increasing abundances of fungal and actinomycetal biomarkers in natural soils. After 30 years, however, reclamation did not place soil microbial communities on a predictable recovery path. The composition of microorganisms was particularly affected by tailings sand-based amendments. Functional potential, determined with assays targeting the activities of enzymes responsible for macromolecule degradation, was mainly impacted by prescriptions containing overburden. Variance partitioning analyses indicated that microbial responses to reclamation were partially determined by vegetation cover development, soil pH, and the fungal-to-bacterial biomass ratio. pH effects on bacterial composition were partly driven by the abundance of Acidobacteria. The relative abundances of several bacterial biomarkers covaried with individual enzyme activities, suggesting certain sub-sets of the microbial communities were functionally relevant. I tested this idea experimentally by assembling a laboratory-scale reciprocal transplant of microorganisms sourced from two distinct peat types. My main finding was that differences in initial microbial community composition were functionally significant for lignin depolymerization, while the activities of nutrient-acquiring enzymes (a more ubiquitous function) were mostly influenced by peat type. Overall, my results indicate that the responses of abundant microbial populations to reclamation were largely accounted for by abiotic properties of reclamation materials and, indirectly, by the effects of reclamation on plant growth.
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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 | 0.000 | 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 | 0.001 | 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 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".