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 CO2and CH4exchange are strongly affected by hydrology in landscapes underlain by permafrost. Hypotheses for these effects in the modelecosyswere tested by comparing modeled CO2and CH4exchange with CO2fluxes measured by eddy covariance from 2006 to 2009, and with CH4fluxes measured with surface chambers in 2008, along a topographic gradient at Daring Lake, NWT. In an upland tundra, rises in net CO2uptake in warmer years were constrained by declines in CO2influxes when vapor pressure deficits (D) exceeded 1.5 kPa and by rises in CO2effluxes with greater active layer depth. Consequently, net CO2uptake rose little with warming. In a lowland fen, CO2influxes declined less withDand CO2effluxes rose less with warming, so that rises in net CO2uptake were greater than those in the tundra. Greater declines in CO2influxes with warming in the tundra were modeled from greater soil‐plant‐atmosphere water potential gradients that developed under higherDin drained upland soil, and smaller rises in CO2effluxes with warming in the fen were modeled from O2constraints to heterotrophic and belowground autotrophic respiration from a shallow water table in poorly drained lowland soil. CH4exchange 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 CH4modeled 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 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 | 0.001 | 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 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".