Importance of the Water Table in Controlling Dissolved Carbon along a Fen Nutrient Gradient
Bibliographic record
Abstract
Boreal fens are minerotrophic peatlands that act as important control points for dissolved C between upland and aquatic ecosystems. Fens occupy a minerotrophic continuum from “rich,” having high water tables and large nutrient contributions from upland sources, to “poor,” having low water tables and small nutrient contributions. Dissolved C within these fens will be influenced by the degree of minerotrophy, which in turn impacts peat pore water acidity and alkalinity and downstream productivity. To examine how dissolved C concentrations change along the minerotrophic gradient and to explore possible mechanisms controlling their concentration, pore water chemistry was analyzed from piezometers at 25‐, 50‐, and 100‐cm depths in rich, intermediate, and poor fens during the snow‐free periods of 2005, 2006 (dissolved organic C [DOC] only), 2007, and 2008. We found that dissolved inorganic C (DIC) concentrations increased with higher water tables (poor < intermediate < rich) and wetter years (2005 < 2007 ∼ 2008). In contrast, DOC concentrations decreased with higher water tables (rich < intermediate < poor), but the effect differed among years. Wetter conditions resulted in high DOC concentrations in the intermediate fen, low concentration in the poor fen, and no change in the rich fen. Correlation analyses suggest that DIC concentrations may be linked to groundwater contribution of carbonate materials and DOC to ionic strength and mechanisms of productivity and decomposition. Although further experimentation is required to verify these mechanisms, the evidence points to the importance of minerotrophic status when considering the role of peatlands in watershed C balances and their response to changing climate.
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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) | 0.000 | 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".