Spatial extent and severity of all‐terrain vehicles use on coastal sand dune vegetation
Why this work is in the frame
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Bibliographic record
Abstract
Abstract Questions Increases in all‐terrain vehicle (ATV) use on dunes raises concerns about an ecosystem vital for coastal protection. We asked: with distance from trails, what are the effects of ATV use on (a) total, native, and non‐native plant species richness and (b) presence and cover of the dune‐stabilising plant Ammophila breviligulata ? Specifically, how do (a) and (b) differ (1) between regions with and without ATV use; (2) with deeper ruts and increased distance from the ATV trail; and (3) between pioneer and shrub zones of dunes in each region? Location Miscou Island and Kouchibouguac National Park, New Brunswick, Canada. Methods We assessed ATV effects by conducting field vegetation surveys in a region with (Miscou Island) and without (Kouchibouguac National Park) ATV use. Line transects were used to capture gradients of effects across the dune community via plots evenly placed to measure trail effects (on the trail), close‐edge effects (edge of the trail), and distant‐edge effects (every 5 m up to 25 m away from trail), in pioneer and shrub zones of dunes. Results All‐terrain vehicle rut depth was associated with a decrease in total and native species on the trails and on the edge of trails, and with a slight increase in non‐native species beyond the trail edge. We also found a rut depth threshold of approximately 50 cm, beyond which was an abrupt decline across all species. Where ATV activity occurred, there was also a decrease of A. breviligulata in presence and cover, non‐native species increased in the pioneer zone, and the shrub zone had fewer native species. Conclusions All‐terrain vehicle use plays a major role in the vegetation changes observed on coastal dunes. A management plan that recognises the specific effects caused by ATV use on dune vegetation will help preserve dunes, enabling more cost‐effective coastal protection than engineered interventions.
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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 | 0.001 |
| 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