Carbon accumulation in West Siberian Mires, Russia <i>Sphagnum</i> peatland distribution in North America and Eurasia during the past 21,000 years
Bibliographic record
Abstract
The rates of carbon (C) accumulation and the role of fires in the C dynamics of the major types of boreal West Siberian mires were investigated. Detailed analysis of dry bulk density, C, and N concentration and age of the peat layers were used to determine C accumulation rates throughout the Holocene. The average long‐term apparent rate of carbon accumulation (LORCA) at 11 studied sites was 17.2±1.0 (SE) g m−2 yr−1, ranging from 12.1 to 23.7 g m−2 yr−1, and the total apparent carbon sink 11.8 Tg yr−1 (1 Tg = 1012 g) for Russian raised string bogs (68.5 million hectares). These estimates of C accumulation in West Siberian mires are roughly a half of the earlier estimates for these boreal mires. Differences in LORCA for three major mire types in the study area, the ridge‐hollow pine bogs, Sphagnum fuscum pine bogs, and dwarf‐shrub pine bogs, were not significant. The age versus depth (measured as cumulative carbon from the surface downward) curve was slightly convex, indicating a general declining trend in LORCA with decreasing age. About 55% of the present carbon store was already accumulated about 6000 cal. BP. The most intensive expansion phase of the study area occurred between 7000 and 8000 cal. BP. The subsequent lateral expansion has been very slow in the later Holocene. The charcoal data indicated that these mires have burned only 2–3 times during the past 7000–8000 cal. BP, and only a strip of a few meters along the mire margins has burned relatively frequently. No evidence of significant carbon losses due to fires could be found. The charcoal layers at the mire margins suggest a declining trend in burning rates during the later Holocene.
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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 | 0.001 |
| 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) | 0.000 | 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".