Carbon accumulation in freshwater marsh soils: A synthesis for temperate North America
Bibliographic record
Abstract
Peatland soils are of great interest for study and management because of their high carbon contents and known role in the global carbon cycle. However, carbon stocks have yet to be constrained in many wetland ecosystems. Relative to bogs, fens and saline coastal ecosystems, less is known about carbon stocks in freshwater marsh soils despite their global prevalence, and it is not well understood how disturbance of freshwater marshes may affect carbon-climate dynamics. To better understand the potential for freshwater marshes to be net carbon sinks, we review how freshwater marshes and associated soils are classified, and synthesize available data on short- and long-term rates of carbon accumulation in freshwater marsh soils in temperate North America. Although often described as mineral-based, our findings suggest that freshwater marshes are not restricted to mineral substrates, and that inconsistencies in classification may underestimate presumed carbon stocks. Organic carbon contents and bulk density measurements are highly variable, and can range between 1-45% and 0.04-1.5 g cm-3, respectively. Moreover, rates of carbon accumulation in freshwater marshes are often measured over recent time scales (50-100 years; on average 155 +/- 74 g C m-2 yr-1), while long-term rates (measured over centuries and millennia; on average 51 +/- 38 g C m-2 yr-1) are much more scarce. We suspect that short-term rates are markedly greater than long-term rates of carbon accumulation because they do not account for long-term carbon loss and may reflect large increases in sedimentation since European settlement in North America. However, we also suspect that long-term carbon storage in freshwater marsh soils is underestimated, and that freshwater marshes can have long-term rates of carbon accumulation similar to those reported for temperate peatlands. In this presentation, we will show that variability of rates of carbon accumulation, rates of sediment accretion, bulk density and organic carbon content in freshwater marshes needs to be better constrained in order to accurately quantify their regional and global carbon pools. We will discuss the importance for scientists to specify timeframes over which they are measuring rates of carbon accumulation so that the capacity for wetlands to be net carbon sinks can be correctly understood.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.009 | 0.010 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".