No mean peat - the controls on peat growth and stream morphodynamics in peat-filled valleys
Bibliographic record
Abstract
Peat-filled valley systems are characterized by a lack of clastic sediment, having most of the valley filled with organic material. These systems provide a wide range of ecosystem services, such as a carbon sink, floodwater retention, drought resilience and enhance biodiversity. It is clear that chances for peat growth and preservation strongly depend on stream morphodynamics. However, there is a lack of quantitative understanding of peat stream morphodynamics, as peat streams functioning differs from that of alluvial streams. In this study we quantify peat stream morphodynamics to determine the potential for carbon storage within peat-filled valleys.Many studies have ascribed the presence of laterally continuous valley peat to the presence of dispersed wetland systems, i.e. systems without concentrated discharge in an established channel. However, our detailed investigations of the sedimentary records for peat-filled valleys show that channels were present even for systems characterized by low stream power. Here we show how these streams have formed highly sinuous planforms during the Holocene due to oblique aggradation, while stream power is too low for lateral migration (i.e. meandering). We also show that peat streams with a slightly higher degree of clastic sediment input show a different planform development than when clastic sediment input is limited, depending on the cohesivity of the sediments. We generalize our concepts for systems found around the world, such as in Canada, USA, Poland and Siberia. Finally, we will elaborate upon the upstream and downstream control of clastic sediments and hydrology on stream morphodynamics and peat growth in stream valleys.
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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 | 0.001 | 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".