Effects of size, shape, and edge on vegetation in remnants of the upland boreal mixed-wood forest in agro-environments of Alberta, Canada
Bibliographic record
Abstract
Forty-one remnants of the aspen-dominated upland forest in three subregions of the dry boreal mixed-wood in Alberta were studied to determine effects of fragment size and shape on native and alien plant species richness and abundance in agro-environments. The percent cover of all vascular plant species was visually estimated in 5 m diameter circular plots along transects that covered the length and the width of each fragment. A subset of 12 of the largest fragments (>900 m2) that had distinct interiors (portions of the fragment >15 m from any edge) was used to measure edge effects on the vegetation. Regression analyses revealed significant positive relationships between species richness and area regardless of the subregion. Species richness stabilized in fragments that were larger than 11 ha. Edges did not affect shrub species richness and only affected herbaceous species richness on west- and south-facing aspects. Shrub abundance decreased and herb abundance increased up to 20 m from the edges regardless of orientation. Edges did not support a different suite of species than interiors, although several species occurred more frequently in the interior than along the edges. Alien species richness and abundance reached their highest values between 5 and 15 m from the edge, and some of those species could be found up to 40 m from the edge. Although larger fragments generally supported more alien species than smaller fragments, the smallest fragments had the greatest number of species per metre squared. Results from this study indicated that it would be preferable to conserve larger woodlots rather then several smaller woodlots on the landscape.
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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".