Patterns of exotic plants in relation to anthropogenic edges within urban forest remnants
Bibliographic record
Abstract
Abstract Question How is the abundance of exotic plants within urban forest remnants influenced by distance to the edges of forest boundaries and recreational trails? Location Halifax,NovaScotia,Canada. Methods Gradients in the cover of exotic plants, as well as the richness of exotic and native vascular species, were examined as a function of distance from anthropogenic forest boundaries and recreational trails. Plants were sampled in 2 m × 10 m and 10 m × 10 m plots distributed among 11 urban forest remnants. Randomization tests were used to quantify the distance of edge influence from both forest boundaries and trails, and to determine if there was an interaction between them. Results The cover and richness of exotic plants and richness of native species decreased with increasing distance from forest boundaries and trails. Edge influences extended to distances of ca. 50 and 3 m for forest boundaries and trails, respectively, and were stronger for measures of understorey than of overstorey vegetation. Vegetation was simultaneously influenced by both edge types such that exotic cover and richness were higher when in close proximity to two edges than when subject to either edge alone (i.e. a positive interaction). Conclusions It is important to consider the influence of edges in the design and management of forest remnants to improve the ability to conserve native biodiversity within cities. Results from this study may be used to guide the design of such systems, particularly by suggesting appropriately sized patches and trail densities.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.001 |
| 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".