Geomorphic and sediment volume responses of a coastal dune complex following invasive vegetation removal
Bibliographic record
Abstract
ABSTRACT This paper documents application of an established geostatistical methodology to detect significant changes in a foredune–transgressive dune complex where Parks Canada Agency (PCA) implemented a dynamic restoration program to remove invasive marram grasses (Ammophila spp.) and enhance dynamic dune habitat for an endangered species. Detailed topographic surveys of a 10 320 m2 site in the Wickaninnish Dunes in Pacific Rim National Park, British Columbia, Canada for the first year post‐treatment are compared to a pre‐restoration LiDAR baseline survey. The method incorporates inherent spatial structure in measured elevation datasets at the sub‐landscape scale and models statistically significant change surfaces within distinct, linked geomorphic units (beach, foredune, transgressive dune complex). Seasonal and annual responses within the complex are discussed and interpreted. All geomorphic units experienced positive sediment budgets following restoration treatment. The beach experienced the highest differential volumetric change (+1656 m3) and net sediment influx (+834 m3, 0 · 19 m3 m–2) mostly from supply to the supratidal beach and incipient dune. This sediment influx occurred independent of the restoration effort and was available as a buffer against wave erosion and as supply to the landward dunes. The foredune received +200 m3 (0 · 13 m3 m‐2) and its seaward profile returned to a similar pre‐restoration form following erosion at the crest from vegetation removal and scarping by high water events. Sediment bypassing and minimal change was evident at the mid‐stoss slope with appreciable extension of depositional lobes in the lee. The transgressive dune complex experienced high accretion following restoration activity (+201 m3) and over the year (+284 m3, 0 · 07 m3 m–2) mostly from depositional lobes from the foredune, precipitation ridge growth along the downwind boundary, and growth of existing lobes within the complex. Further integration of this methodology to detect significant geomorphic changes is recommended, particularly for applications where sampling densities are limited or logistically defined. Copyright © 2013 John Wiley & Sons, Ltd.
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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 | 0.000 | 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) | 0.001 | 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".