Quantifying blue carbon for the largest salt marsh in southern British Columbia: implications for regional coastal management
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Understanding blue carbon storage and accumulation prior to engineering projects is essential for assessing the potential co-benefit of carbon storage for natural climate solutions. This study collected sediment cores from the western portion of Boundary Bay, Delta, British Columbia (BC), where implementation of a living dike pilot project is planned to alleviate impacts of sea level rise. Total carbon stocks were 10,034 ± 3,148 Mg C for the western 140 ha of marsh, with stocks averaging 83.3 ± 29.3 Mg C/ha (high marsh) and 39.3 ± 24.2 Mg C/ha (low marsh). Carbon accumulation rates (CARs) exhibited substantial variability, ranging from 19.5 to 454 g C/m2/yr (median 70.1 g C/m2/yr). Both stocks and accumulation rates were at least 45% lower than globally averaged estimates, likely due to the shallow depth and dominant vegetation type of the marsh. Despite historical modifications to the marsh, our study indicates that the western marsh has expanded by about 20% since 1930, which we estimate increased carbon stocks by about 1,549-1,698 Mg C. This study's quantification of carbon stocks and CARs is an important first step towards leveraging the co-benefit of salt marshes for improved management, restoration, and preservation. However, additional data are needed to document the greenhouse gas budgets for carbon accounting purposes, along with exploration of law and policy issues related to carbon stewardship in a multi-jurisdictional coastal environment. We outline subsequent research needed for salt marshes such as Boundary Bay to be included in voluntary carbon markets in British Columbia.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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) | 0.000 | 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 it