Comparing the effect of landscape context on vascular plant and bryophyte communities in a human‐dominated landscape
Bibliographic record
Abstract
Abstract Aims It is important to understand the effect of landscape context on biological communities to predict how biodiversity will be affected on human‐dominated landscapes. While many studies have tested the effects of landscape context on the species richness and composition of vascular plants, few have compared the responses of vascular plants and bryophytes on the same landscape. We sampled non‐epiphytic bryophytes and vascular plants in 184 plots to test whether three landscape context factors measured four years or four decades previously could predict bryophyte or vascular plant species richness and composition after accounting for local factors. Location Temperate forests and oak savannahs, Vancouver Island, British Columbia, Canada. Methods We used model selection and comparisons to test the effects of surrounding road density, total amount of forest, and distance to the nearest forest edge on species richness, species richness of non‐disturbance‐associated species, and community composition after controlling for important local predictors including substrate availability and topography. Results The species richness of non‐disturbance‐associated vascular plants was lower in plots with greater surrounding historical road density, and perennial stayer bryophyte richness declined with increasing historical road density and lower historical forest amount, suggesting a potential extinction debt. Landscape context significantly affected total species richness and community composition of vascular plants, but not bryophytes. Conclusion While bryophytes appear to be less sensitive overall to landscape context than vascular plants, disturbance‐intolerant perennial stayer bryophytes may decline in the future in response to the increased road density and loss of forest cover that has occurred over the past four decades.
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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 | 0.000 | 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".