Reduced water motion enhances organic carbon stocks in temperate eelgrass meadows
Bibliographic record
Abstract
Abstract Organic carbon (OC) storage in coastal vegetated ecosystems is increasingly being considered in carbon financing and climate change mitigation strategies. However, spatial heterogeneity in these “blue carbon” stocks among and within habitats has only recently been examined, despite its considerable implications. Seagrass meadows have potential to store significant amounts of carbon in their sediments, yet studies comparing sediment OC content at regional and meadow scales remain sparse. Here, we collected sediment cores from six temperate eelgrass ( Zostera marina ) meadows on the coast of British Columbia, Canada, to quantify sediment OC stocks, accumulation rates, and sources, and to examine local and regional drivers of variability. Sediment OC content was highly variable—across all sites, stocks in the top 0–5 cm ranged from 83 to 1089 g OC m −2 , while the 15–20 cm stocks exhibited a 24‐fold difference, from 59 to 1407 g OC m −2 . Carbon accumulation rates ranged from 4 to 33 g OC m −2 yr −1 . Isotopic mixing models revealed that sediment OC was primarily terrestrial carbon (41.3%) and canopy‐forming kelps (33.3%), with a smaller contribution of eelgrass (25.3%). Here, we show that regional variability in OC content exceeds meadow‐scale variability. This result is likely driven by landscape factors, most notably relative water motion, representing a more dominant control on seagrass OC accumulation than meadow‐scale factors such as canopy complexity. These findings elicit caution when scaling up seagrass meadow OC content and demonstrate that measures of the hydrodynamic environment could improve estimates of carbon storage in temperate soft sediment habitats.
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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 | 0.000 |
| 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) | 0.001 | 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 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".