Please do not walk on the dunes: assessing cumulative impacts on coastal vegetated \nsand dune systems in Newfoundland, Canada
Bibliographic record
Abstract
Vegetated sand dune systems are a relatively rare form of coastline on the Island of \nNewfoundland (NL), but they provide diverse benefits to regional ecology and human \nlandscape use. Despite their importance to coastal biodiversity and inland protection, few \nvegetated sand dune systems are located within protected areas in NL. Under little to no \nprotection, many of NL’s dune systems are vulnerable to anthropogenic disturbances (e.g., \ndune trampling, all-terrain vehicle use). Boreal vegetated dunes, such as those in Atlantic \nCanada, are also subject to extensive natural disturbances that result from storm and \nprecipitation events. Current climate change projections point to an increase in these types of \nevents in NL, which, combined with the ongoing anthropogenic disturbance regime, may \noverwhelm the natural rejuvenation process of dune coastlines. Using a protected areas \napproach, we characterize the vegetation cover, plant community, and disturbance features on \nNL’s dune systems. Vegetation cover was sparser in unprotected areas, which were also \nassociated with a greater cover of non-endemic plant species. Regardless of protection status, \nsubstrate disturbance was also linked with a loss of total vegetation cover across the system. \nThis research provides important empirical findings on the relationship between protected \nareas status, vegetation cover, plant community, and substrate disturbance on NL’s coastal \nvegetated dunes, highlighting the need for additional land management initiatives to protect \nthese vulnerable landscapes under the effects of human visitation and climate change.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".