The impact of reconstructed soils following oil sands exploitation on aspen and its associated belowground microbiome
Bibliographic record
Abstract
The objective of this study was to investigate the impact of different soil covers used to reclaim decommissioned oil sands mining sites on the genetic diversity of aspen and their associated belowground microbiota. Aspen genotyping showed that trees mostly originated from sexual reproduction on sites reclaimed with soil covers made of upland forest floor-mineral mix (FFMM) and lowland peat-mineral mix (PMM). In contrast, most individuals in mature and burned stands sampled as benchmarks for natural disturbances originated from vegetative reproduction. Nonetheless, aspen populations in the FFMM and PMM sites were not genetically different from those in mature and burned stands. DNA metabarcoding of bacteria and fungi in root and soil samples revealed that the diversity of the belowground microbiota associated with aspen and the relative abundance of putative symbiotic taxa in PMM were significantly lower than for FFMM and naturally disturbed sites. Despite similar aspen genetic diversity between FFMM and PMM sites, trees were not associated with the same belowground microbiota. Because the soil microbiome and more specifically the mycorrhizal communities are variable both in space and time, long-term monitoring is particularly important to better understand the ecological trajectory of these novel ecosystems.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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 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".