DataSheet_1_Blue Carbon Storage in a Northern Temperate Estuary Subject to Habitat Loss and Chronic Habitat Disturbance: Cowichan Estuary, British Columbia, Canada.docx
Bibliographic record
Abstract
<p>Vegetated coastal ecosystems can contribute greatly to long-term carbon sequestration and greenhouse gas emission mitigation, providing a strong argument for their protection and restoration. We investigated carbon sequestration in the Cowichan Estuary, a temperate estuary on Vancouver Island, Canada, in relation to habitat type (salt marsh, eelgrass, mudflats, and oyster shell beds) and habitat degradation. Stored organic carbon and inorganic carbon were quantified in the top 20 cm of sediment as well as in eelgrass and salt marsh vegetation. Sedimentation and carbon sequestration rates were quantified by <sup>210</sup>Pb radiometric dating, and organic matter sources and quality were assessed by δ<sup>13</sup>C, C:N ratios and photopigment content. We also examined the potential impact of habitat disturbance by industrial activity (log booms) on the estuary’s carbon storage capacity. The salt marsh was the most important carbon reservoir, with a mean sediment organic carbon stock of 58.78 ± 19.30 Mg C ha<sup>-1</sup>. Sediment organic carbon stocks in the upper mudflats, lower mudflats, eelgrass meadow, and oyster shell beds were 19.30 ± 3.58, 17.33 ± 3.17, 18.26 ± 0.86 and 9.43 ± 1.50 Mg C ha<sup>-1</sup>, respectively. Carbon accumulation rates in the salt marsh and eelgrass meadows were 68.21 ± 21 and 38 ± 26 g C m<sup>-2</sup> yr<sup>-1</sup>, whereas <sup>210</sup>Pb profiles indicated that mudflat sediments were subject to erosion and/or mixing. While eelgrass was absent from the log boom area, likely due to disturbance, sediments there had similar carbon sequestration and bulk properties to adjacent mudflats. Carbon stocks in the eelgrass meadow were similar to those of the mudflats and consistent with the relatively low values reported for other temperate Zostera marina meadows, compared with tropical eelgrass meadows. Stable isotope evidence was suggestive of substantial outwelling and/or decomposition of eelgrass vegetation. Finally, we compared the carbon sequestration potential of the estuary to selected sources and sinks of CO<sub>2</sub> in the surrounding region. We estimated that annual carbon sequestration in the estuary offsets approximately twice the greenhouse gas emission increases attributable to local population growth, and is equivalent to approximately twice that of a 20-year-old stand forest.</p>
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How this classification was reachedexpand
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 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.230 | 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 teacher head, 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".