Mangroves as a major source of soil carbon storage in adjacent seagrass meadows
Bibliographic record
Abstract
Abstract Mangrove forests have the potential to export carbon to adjacent ecosystems but whether mangrove-derived organic carbon (OC) would enhance the soil OC storage in seagrass meadows adjacent to mangroves is unclear. In this study we examine the potential for the contribution of mangrove OC to seagrass soils on the coast of North Sulawesi, Indonesia. We found that seagrass meadows adjacent to mangroves had significantly higher soil OC concentrations, soil OC with lower δ 13C, and lower bulk density than those at the non-mangrove adjacent meadows. Soil OC storage to 30 cm depth ranged from 3.21 to 6.82 kg C m−2, and was also significantly higher at the mangrove adjacent meadows than those non-adjacent meadows. δ13C analyses revealed that mangrove OC contributed 34 to 83% to soil OC at the mangrove adjacent meadows. The δ13C value of seagrass plants was also different between the seagrasses adjacent to mangroves and those which were not, with lower values measured at the seagrasses adjacent to mangroves. Moreover, we found significant spatial variation in both soil OC concentration and storage, with values decreasing toward sea, and the contribution of mangrove-derived carbon also reduced with distance from the forest.
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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 | 0.000 | 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 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".