Distance to suburban/wildland border interacts with habitat type for structuring exotic plant communities in a natural area surrounding a metropolitan area in central Chile
Bibliographic record
Abstract
Background: The explosive growth of urbanisation in Mediterranean ecosystems in Chile has favoured the rapid expansion of exotic plant species, yet factors driving these invasion patterns in adjacent natural areas remain poorly assessed.Aims: To assess how distance to a suburban/wildland border, habitat type, site-scale disturbance and woody plant cover of native species influences the diversity of exotic species in a natural area surrounding the city of Santiago, Chile.Methods: Three watersheds were chosen, and the diversity of exotic species was assessed in 36 100-m-long transects, equally distributed over two distance categories and three habitats. For each transect, we measured woody plant cover of native species and frequency of rabbit faeces as a measure of competitive exclusion and site-scale disturbance, respectively.Results: Species diversity decreased as the distance from the suburban/wildland border increased, and it was found to be higher in north-facing habitats compared to south-facing and alluvial habitats. Neither native woody plant cover nor frequency of rabbit faeces had an effect on species diversity.Conclusions: The current pattern of exotic plant species in this natural area is mainly influenced by the distance to suburban border and habitat type. An adequate management of conditions favouring exotic species in suburban/wildland border may prevent the spread of these into natural areas next to urban settings.
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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) | 0.003 | 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".