Blue Carbon Storage Capacity of Temperate Eelgrass (<scp><i>Zostera marina</i></scp>) Meadows
Bibliographic record
Abstract
Abstract Despite the importance of coastal ecosystems for the global carbon budgets, knowledge of their carbon storage capacity and the factors driving variability in storage capacity is still limited. Here we provide an estimate on the magnitude and variability of carbon stocks within a widely distributed marine foundation species throughout its distribution area in temperate Northern Hemisphere. We sampled 54 eelgrass ( Zostera marina ) meadows, spread across eight ocean margins and 36° of latitude, to determine abiotic and biotic factors influencing organic carbon (C org ) stocks in Zostera marina sediments. The C org stocks (integrated over 25‐cm depth) showed a large variability and ranged from 318 to 26,523 g C/m 2 with an average of 2,721 g C/m 2 . The projected C org stocks obtained by extrapolating over the top 1 m of sediment ranged between 23.1 and 351.7 Mg C/ha, which is in line with estimates for other seagrasses and other blue carbon ecosystems. Most of the variation in C org stocks was explained by five environmental variables (sediment mud content, dry density and degree of sorting, and salinity and water depth), while plant attributes such as biomass and shoot density were less important to C org stocks. Carbon isotopic signatures indicated that at most sites <50% of the sediment carbon is derived from seagrass, which is lower than reported previously for seagrass meadows. The high spatial carbon storage variability urges caution in extrapolating carbon storage capacity between geographical areas as well as within and between seagrass species.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.001 | 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".