Simulation of six years of carbon fluxes for a sedge‐dominated oligotrophic minerogenic peatland in Northern Sweden using the McGill Wetland Model (MWM)
Bibliographic record
Abstract
Abstract Northern peatlands store ~30% of the global soil carbon, despite covering only 3% of the land. To understand the carbon balance of these systems and predict their response to changes in climate, robust and reliable models are needed. The McGill Wetland Model (MWM), originally developed to simulate the carbon dynamics of ombrotrophic bogs, was modified to simulate the CO 2 biogeochemistry of sedge‐dominated oligotrophic minerogenic peatlands, a prominent peatland type in boreal and subarctic landscapes. Three modifications were implemented: (1) a function to describe the impact of soil moisture on the optimal gross primary production, (2) a scheme to partition the peat profile into oxic and anoxic compartments based on the “effective root depth” as a function of daily sedge net primary production, and (3) a function to describe the “fen” moss water dynamics. The modified MWM was evaluated using eddy‐covariance net ecosystem production (NEP) from Degero Stormyr in northern Sweden. The root mean square error for daily NEP was ~0.46 g C m −2 d −1 , and the index of agreement was 84%. This model adequately captures the magnitude and direction of the CO 2 fluxes and simulates the seasonal and inter‐annual variability reasonably well ( r 2 > 0.8). Sensitivity analysis confirms that specifically water table depth (WTD) and moss water content are key biogeochemical hydrology processes for the carbon biogeochemistry of a sedge‐dominated oligotrophic minerogenic peatland. An increase of WTD by 15 cm or air temperature by 3°C could decrease NEP by up to 200% and make the peatland become a source of CO 2 .
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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 teacher head, 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".