Restoring Piping Plover Habitat and Building Coastal Resilience with Nature-based Solutions in Atlantic Canada
Bibliographic record
Abstract
Located in north-eastern Canada near Shippagan, New Brunswick, the Shippagan Gully Conservation Offsetting Project is leveraging salt marsh creation and sand motor techniques to create Piping Plover habitat while increasing resiliency of the Chaisson Office Spit and surrounding communities to climate change. The spit has been altered by more than a century of human activity and is increasingly impacted by climate change and sea-level rise. The project, which employs a holistic approach to improve marine navigation through the Gully and install nature-based solutions for coastal protection and habitat creation, is the first sand motor in Atlantic Canada and the most northern created marsh with sill to date. Extensive modeling was undertaken by NRC prior to the commencement of baseline data collection and design in 2017. Several monitoring and research initiatives are associated with the project, including a fifteen-year monitoring program (regulatory requirement), five-year post-graduate scientific research program, and a 3-year research project which will augment and build on the NRC-led Nature-Based Infrastructure for Coastal Resilience project. Construction began on the sand motor in 2020, with the marsh and marsh sill scheduled to be built in winter 2023 from on-site materials and planted in spring 2023. The final stages of the implementation will include dune and wetland restoration following the removal of old infrastructure, returning nearly the entire spit to a more natural state and restoring natural processes. The first two years of monitoring following the sand motor implementation have shown a shift in conditions to those more closely matching a nearby control site, as well as the first successful nesting and fledging of Piping Plover (Federally Endangered Species) on the site in over 20 years. The project is the result of a collaborative effort that includes federal and provincial government departments, private industry, academia, and environmental NGOs.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 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".