Vegetation recovery on abandoned road segments of Highway 16 in northwestern British Columbia
Bibliographic record
Abstract
Vegetation recovery on abandoned road segments of Highway 16 in northwestern British Columbia were examined across a climate gradient. The time since road abandonment ranged from 16 to 57 years on sites sampled. Plant cover on asphalt roads was compared with that found on gravel road shoulders using paired t-tests. Plant cover by growth form was further evaluated in response to climate and other environmental predictor variables using multiple regression ‘best fit’ models. Plant community ordination analysis using nonmetric multidimensional scaling was conducted to describe patterns across study sites in species space along environmental gradients. Key drivers of current plant community composition include time since road abandonment, road substrate type, and several different annual climate variables. The best predictor of vascular plant cover and total plant cover was time since road abandonment, but plant community composition was strongly driven by the coastto-interior climate gradient. Non-vascular cover was more abundant on asphalt roads compared to gravel substrates. Woody plant cover was greatest on gravel shoulders compared to gravel or asphalt road centers. Exotic plant cover was negatively correlated with mean annual relative humidity. Plant diversity and species richness were not driven by the climate gradient but instead reflected more site-specific environmental variables. Primary succession on abandoned roads in this study area may be constrained by continued anthropogenic disturbance post-abandonment.
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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 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".