Stocks of "Blue Carbon" in Soils of Coastal Ecosystems of High-Latitude Seas of the Northern Hemisphere
Bibliographic record
Abstract
The article presents a review of data from Russian and foreign sources, as well as our own research, concerning carbon stocks in soils of coastal zone ecosystems: marshes and seagrasses of the USA, Canada, Great Britain, continental Europe, Scandinavia and Greenland, as well as Russia. These soils are formed under conditions of amphibious water regime and are mainly classified as Tidalic Fluvisols. The mean values of carbon stock in the 0–10 cm layer of marsh soils were 34.3 ± 21.5 t/ha, and the aquatic soils of marine meadows were 7.8 ± 6.5 t/ha. As a rule, carbon reserves in soils directly depend on the productivity of phytocenosis. A positive dependence of carbon stock on seawater temperature has been established. It is shown that with increasing salinity of water, carbon reserves in the soils of marshes decrease, while in marine meadows they increase. On the shores, carbon reserves are maximal in the soils of the rarely flooded high marsh. In the mineral soils of the marshes, higher carbon reserves are observed in heavy-textured soils than in less clayey soils. High carbon reserves in sandy–sandy loam soils are commonly found in the soils of marine meadows. The results of the study can be used to assess the impact of coastal ecosystems on the content, dynamics and potential for carbon absorption, climate change, and serve as a basis for developing measures for the protection and rational use of natural resources in coastal landscapes.
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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 | 0.003 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| 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".