Soil microbial community responses to green-tree retention harvesting in coastal British Columbia
Bibliographic record
Abstract
Green-tree or variable retention harvesting is being increasingly adopted as an alternative to clearcutting in the Pacific Northwest, including British Columbia (BC), to maintain forest biodiversity and function and enhance aesthetic quality. Green-tree retention may also benefit the soil resource, and research is needed to understand how these silvicultural treatments affect soil nutrient availability and microbial community structure and function. The objectives of this study were to determine: (i) whether green-tree retention harvesting is better than clearcutting to retain nutrient availability and the structural and functional characteristics of the soil microbial community, and (ii) which spatial pattern of green-tree retention is superior for this purpose. Using an adjacent uncut forest to provide a baseline comparison, nutrient availability, substrate-induced respiration (SIR), enzyme activities, and phospholipid fatty acids (PLFA) were analysed in the forest floor and mineral soil of a second-growth Douglas-fir and western hemlock forest at the Silviculture Treatments for Ecosystem Management in the Sayward (STEMS) trial near Campbell River on Vancouver Island, BC, five years after aggregated retention harvesting, dispersed retention harvesting, and clearcutting. In general, there was no indication that nutrient availability and the structure and function of the soil microbial community in either green-tree retention treatment was intermediate between the clearcut and the uncut forest. Harvesting had no significant effect on nitrate and phosphate availabilities and SIR rates, but it generally reduced ammonium availability and enzyme activities in the forest floor. Green-tree retention harvesting caused a shift in the structure of soil microbial community, whereas clearcutting did not. Green-tree retention harvesting appeared better than clearcutting in maintaining the activities of forest floor β-glucosidase, N-acetyl-glucosaminidase, and peroxidase enzymes closer to the level found in the uncut forest, but did not offer advantages over clearcutting in maintaining soil microbial community structure. Comparing the two spatial patterns of green-tree retention, the dispersed retention treatment was superior to the aggregated retention treatment because of its ability to retain soil microbial community structure and function more evenly across the harvested site.
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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 | 0.001 |
| Science and technology studies | 0.001 | 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) | 0.001 | 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".