Effects of Feral Horses on Vegetation of Sable Island, Nova Scotia
Bibliographic record
Abstract
To provide necessary information for the management of biodiversity on Sable Island, Nova Scotia, we studied the effects of feral horses on vegetation using exclosures and ancillary observations. Nine plant communities inside and outside of six exclosures were compared using various vegetation parameters and Mann-Whitney tests to evaluate the significance of differences. The most important findings were as follows: (1) effects of horses were greatest in the Marram (Ammophila breviligulata) grassland and much less in the communities that were not dominated by Marram Grass; (2) effects on Marram grassland varied substantially among sites; (3) the cover of standing litter of herbaceous plants was on average of 9.3 times greater inside exclosures in grassland habitats; (4) the cover of living foliage was usually higher inside exclosures, but not all differences were significant; (5) species richness and species diversity were not substantially affected; (6) the average cover of Marram Grass, the most abundant plant and a key sand binder on the island, was greater inside exclosures in six of seven study sites, significantly so in three of them; and (7) there were inconsistent differences in cover of other species at different sites. Wetland habitats cover a relatively small portion of Sable Island, but they support much of the plant biodiversity. There is evidence of strong but variable effects of horses on wetland vegetation. “Horse lawns” are littoral habitats dominated by Agrostis stolonifera (Carpet Bentgrass) and other low-growing plants. The lawn habitats represent less than 1% of the island’s vegetation, and their presence is believed to be due to grazing and trampling by horses.
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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 | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 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".