Distribution of vegetation along environmental gradients on Sable Island, Nova Scotia
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
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.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it