Carbon accumulation in bay of fundy salt marshes: Implications for restoration of reclaimed marshes
Bibliographic record
Abstract
Transformation of agricultural land to natural terrestrial vegetation has been suggested as a means to increase soil carbon storage. However, the capacity for carbon storage in terrestrial soils is limited as compared to soils of tidal salt marshes, the original vegetation of many coastal agricultural lands. In a number of countries, tidal salt marshes have been “reclaimed,” that is drained and diked to prevent tidal flooding and create suitable conditions for dry land agriculture. In this study we examine spatial and temporal patterns of carbon accumulation in tidal salt marshes of the Bay of Fundy and estimate the carbon storage potential of the bay's extensive area of reclaimed marsh. Rates of carbon accumulation vary from the upper to the outer Bay, over which there is a gradient of decreasing tidal range and suspended sediment supply. In the outer bay, high‐marsh densities are highest (0.042 ± 0.009 g C cm −3 ), but carbon accumulation rates over the past 30 years are lowest (76 g C m −2 yr −1 ). The reverse pattern occurs in the upper bay where carbon densities in the high‐marsh environment are lowest (0.036 ± 0.002 g C cm −3 ), but carbon accumulation rates over the past 30 years may be as high (184 g C m −2 yr −1 ). Compared to other ecosystems, the rates of carbon accumulation presented in this study were similar over timescales of years to centuries. Increases in relative sea level (over time) and suspended sediment supply (across the bay) positively affect the marsh soil accumulation rate and the rate of carbon sequestration. Parameters such as %C are not useful predictors of a marsh's potential for carbon sequestration. Soil carbon densities of functioning marshes and reclaimed marsh soils are similar, but marsh soils have a storage capacity that increases with rising sea level, while agricultural soils, such as those in reclaimed marshes, have a fixed (or possibly decreasing in reclaimed marshes) volume over time.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 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".