Long-term response of understory plant species to thinning and fertilization in a Douglas-fir plantation on southern Vancouver Island, British Columbia
Bibliographic record
Abstract
The 27-year response of understory vegetation in a 51-year-old Douglas-fir (Pseudotsuga menziesii (Mirb.) Franco) forest to thinning and N fertilization treatments was examined in a silviculture experiment at Shawnigan Lake on southern Vancouver Island of British Columbia. The experiment was a two-way factorial design with three levels for each of thinning and N fertilization. No significant treatment effects on the number of either vascular or nonvascular species were detected. This was also true for the covers of the majority of understory species except salal (Gaultheria shallon Pursh) and Oregon beaked moss (Kindbergia oregana (Sull.) Ochyra). Heavy thinning led to high salal and Oregon beaked moss cover, whereas heavy fertilization resulted in lower cover of salal but had no effect on the cover of Oregon beaked moss. Although thinning had a marginal effect on the cover of canopy trees 27 years after treatment, the cover of the canopy trees had only minimal effects on understory vegetation. Conversely, no adverse effect of understory vegetation on canopy trees was found. This study suggested that after 27 years thinning and fertilization had little effect on understory vegetation whether in terms of species richness or vegetation cover. An effective way to conserve species diversity is to protect specific substrate types, e.g., tree trunks, stumps, and coarse woody debris. A commercial thinning was recommended to reduce the time of stem exclusion in similar type of forests.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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".