Monitoring considerations for a dynamic dune restoration project: Pacific Rim National Park Reserve, British Columbia, Canada.
Bibliographic record
Abstract
ABSTRACT Historically, management of coastal dune systems has often involved artificial stabilization of active sand surfaces in order for coastal areas to be more easily controlled and modified for human benefit. In North America, the introduction of invasive grasses, namely European and American beach (marram) grasses ( Ammophila spp.) has been one of the most successful strategies used for stabilizing active coastal dune sands. Recent research has demonstrated, however, that stabilization of coastal dunes often leads to reduced landform complexity and resilience, as well as declines in species diversity. More ‘dynamic’ restoration efforts have emerged over the past 20 years that encourage dune mobility and aeolian activity in order to provide a more resilient biogeomorphic system. In North America, there is generally little research relating restoration methods and outcomes to geomorphic responses despite the fundamental importance of sedimentary processes and dune morphodynamics in broader ecosystem function. This paper aims to better situate dynamic dune restoration within current geomorphic understanding. A brief review of key terms and concepts used in the emerging field of dynamic dune restoration is provided and expanded upon with respect to geomorphologic considerations. A case study of a recent dynamic restoration effort in Pacific Rim National Park Reserve, British Columbia, Canada is provide to demonstrate how these concepts are applied. Introduction of European marram at this site, coupled with a warming climate and increased precipitation in recent decades at this site, is thought to be associated with a rapid decline in aeolian activity, system stabilization and accelerated ecological succession. Preliminary results on the response of the dune system to mechanical removal of Ammophila are presented to provide the foundation for a research framework to guide the broader restoration project. Recommendations for improving treatment methodologies and monitoring protocols are provided to aid future restoration projects of this nature. Copyright © 2013 John Wiley & Sons, Ltd.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.005 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.010 | 0.001 |
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".