Ecosystem CO<sub>2</sub>and CH<sub>4</sub>exchange in a mixed tundra and a fen within a hydrologically diverse Arctic landscape: 1. Modeling versus measurements
Bibliographic record
Abstract
Abstract CO 2 and CH 4 exchange are strongly affected by hydrology in landscapes underlain by permafrost. Hypotheses for these effects in the model ecosys were tested by comparing modeled CO 2 and CH 4 exchange with CO 2 fluxes measured by eddy covariance from 2006 to 2009, and with CH 4 fluxes measured with surface chambers in 2008, along a topographic gradient at Daring Lake, NWT. In an upland tundra, rises in net CO 2 uptake in warmer years were constrained by declines in CO 2 influxes when vapor pressure deficits ( D ) exceeded 1.5 kPa and by rises in CO 2 effluxes with greater active layer depth. Consequently, net CO 2 uptake rose little with warming. In a lowland fen, CO 2 influxes declined less with D and CO 2 effluxes rose less with warming, so that rises in net CO 2 uptake were greater than those in the tundra. Greater declines in CO 2 influxes with warming in the tundra were modeled from greater soil‐plant‐atmosphere water potential gradients that developed under higher D in drained upland soil, and smaller rises in CO 2 effluxes with warming in the fen were modeled from O 2 constraints to heterotrophic and belowground autotrophic respiration from a shallow water table in poorly drained lowland soil. CH 4 exchange modeled during July and August indicated very small influxes in the tundra and larger effluxes characterized by afternoon emission events caused by degassing of warming soil in the fen. Emissions of CH 4 modeled from degassing during soil freezing in October–November contributed about one third of the annual total.
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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 | 0.005 | 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 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".