Long-term recovery of vegetation communities after harvesting in the coastal temperate rainforests of northern British Columbia
Bibliographic record
Abstract
We sampled second-growth forests ranging in age from 28 to 98 years and compared them with old-growth forests to quantify rates of terrestrial vegetation recovery following harvesting on the northcentral coast of British Columbia. Species richness approximately doubles, while Simpson’s index of diversity increases from 0.81 to 0.91 from young to old forests. Nonmetric multidimensional scaling ordinations showed differentiation, with some overlap, of old-growth and second-growth forests and a fairly strong correlation of stand age with plot scores, driven by plant species presence and cover. Vegetation succession following logging disturbance is driven primarily by predisturbance species composition; most species found in the young forests are present in old forests and the higher species richness typical of old growth is largely due to the establishment of additional cryptogam and herb species of low cover and constancy. Significantly higher cover of shrub, herb, and bryophyte species differentiates old forests from second-growth forests. Forests 41–100 years old average 63%–73% similarity (depending on site type) to old-growth forests based on species presence–absence and 53%–58% similarity based on species cover. The scarcity of western redcedar ( Thuja plicata Donn ex D. Don) in second-growth stands is of particular concern because of the high ecological, cultural, and economic importance of this tree species.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".