Distribution of vegetation along environmental gradients on Sable Island, Nova Scotia
Bibliographic record
Abstract
Coastal sand dune ecosystems are known to be structured by disturbance along coast-to-inland gradients, but little is known about how such patterns might change on exposed islands where environmental gradients vector in multiple directions. We investigated responses in plant assemblages on Sable Island, a long (49 km) and narrow (1.25 km at the centre) mostly vegetated sand bar located 160 km off the east coast of Nova Scotia, Canada. We sampled vegetation composition across the island using a stratified random design to capture a range of environmental predictors potentially associated with substrate conditions and disturbance from coastal processes, as well as grazing by the island's feral horses. We identified 3 different vegetation assemblages using hierarchical cluster analysis and non-metric multidimensional scaling that were associated with predictor variables. Distance from shore (both north and south shore) and slope angle were strongly related to both vegetation distribution and community composition. Areas farther from shore (subject to less wind and wave disturbance) contained greater amounts of shrub and heath vegetation. However, all parts of the island contained non-vegetated areas or stress-tolerant plant communities. Patterns of vegetation succession inferred for Sable Island were not linear and are better described as responses to repeated environmental disturbance rather than to a gradual process of soil development and competitive displacement. In addition to highlighting the multi-directional environmental influences on community composition of island systems, our results establish baseline spatial information on vegetation communities necessary for the ecological monitoring of Sable Island as a new National Park Reserve.
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 | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 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".