Linking Dissolved Organic Matter to CO<sub>2</sub> and CH<sub>4</sub> Concentrations in Canadian and Chilean Peatland Pools
Bibliographic record
Abstract
Abstract Peatland open‐water pools can be net carbon (C) emitters within heterogeneous peatland ecosystems that are generally net C sinks. However, the intra‐ and inter‐regional patterns and drivers of CO2 and CH4 production, as well as their link with dissolved organic matter (DOM) quality and quantity, remain poorly understood. We analyzed a range of optical characteristics and chemical variables controlling DOM and CO2 and CH4 concentrations in peatland pools across two regions with contrasting geographical properties (i.e., climate, topography, morphometry, and vegetation cover) of eastern Canada and Chilean Patagonia. We found inter‐regional patterns in CO2, CH4 and DOM concentrations and composition that were coherent with patterns in mean annual temperature and precipitation, and vegetation cover. Cross‐regional patterns of CO2 and CH4 were driven by morphometry, vegetation cover, and protein‐like DOM composition, a proxy of high biological activity, whereas temporal variations of CO2 and CH4 concentrations were further influenced by seasonal changes in humic‐like DOM composition, dissolved organic carbon and nutrients (i.e., total phosphorus and total nitrogen) concentrations, as well as pH and oxygen levels. Our results suggest that geophysical constraints associated with local peat and pool characteristics as well as climate patterns are major drivers of DOM and greenhouse gases concentrations and the links between them in broadly distributed peatland pools.
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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 | 0.001 | 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".