A chronsequential approach to investigating microbial community shifts following clearcutting in Boreal Plain forest soils
Bibliographic record
Abstract
Impacts of forest harvesting are often assessed in short-term studies that ignore the longer term changes associated with the disturbance. A chronosequence approach was taken to investigate changes in microbial community size and composition over ∼20 years post-harvest in lodgepole pine ( Pinus contorta Douglas ex Loudon) stands of the Boreal Plain. The LFH and mineral Ae horizons of Orthic Gray Luvisolic soils were sampled in six cutblocks, aged 1–19 years since harvest, in 2009 and 2010. Changes in microbial communities were assessed using phospholipid fatty acid analysis (PLFA) and 16S rDNA analysis. Physical and chemical soil parameters were measured to delineate microsite changes impacting microbial community shifts. Total microbial biomass (PLFA) was unaffected by harvesting disturbance, although fungal biomass was significantly larger in the oldest cutblock of the chronosequence. Microbial community composition did, however, differ between younger and older cutblocks as indicated by both lipid PLFA and 16S rDNA fingerprinting techniques. Forest soil microbial communities subject to clearcutting were observed to shift in overall community composition while remaining consistent in overall community size. The shift in community composition, which occurred in concert with the maintenance of biomass, indicated that the microbial community adapted sufficiently to the new post-harvest microsite conditions.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| 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".