Rapid carbon accumulation following managed realignment on the Bay of Fundy
Bibliographic record
Abstract
Salt marshes are highly effective carbon (C) sinks and have higher rates of soil C burial (per square meter) than terrestrial ecosystems. Marsh reclamation and anthropogenic impacts, however, have resulted in extensive losses of salt marshes. Restoration of marshes drained and "reclaimed" for agriculture (referred to in Canada as dykelands) and degraded marshes can generate C credits, but only if C burial is reliably quantified. To date, studies reporting on C burial rates have been limited primarily to restored marshes which are more than 10 years old. Here we report on a study which assessed C burial six years after the return of tidal flooding to a section of dykeland in Aulac, New Brunswick on Canada's Bay of Fundy. The C burial rate in the restored marsh averaged 1 329 g C m-2 yr-1, more than five times the rate reported for a nearby mature marsh. Carbon density in the recovering marsh was relatively consistent with depth and although salt marsh cordgrass (Spartina alterniflora) became established in 2012, the bulk of the C in the new marsh deposit is assumed to be allochthonous. Financial constraints are a barrier to marsh restoration projects and C markets could provide a considerable source of funding for restoration work in the future. For marsh restoration projects to be recognized in C crediting systems, however, it must also be demonstrated that the allochthonous C would not otherwise have been sequestered; the potential for this is discussed.
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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 | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".