Ecosystem CO<sub>2</sub> and CH<sub>4</sub> exchange in a mixed tundra and a fen within a hydrologically diverse Arctic landscape: 2. Modeled impacts of climate change
Bibliographic record
Abstract
Abstract Climate change will have important effects on arctic productivity and greenhouse gas exchange. These changes were projected by the model ecosys under an Special Report on Emissions Scenarios (SRES) A2 scenario over the 21st century for a landscape including an upland tundra and a lowland fen at Daring Lake, NWT. Rising temperatures and precipitation caused increases in active layer depths (ALD) and eventual formation of taliks, particularly in the fen, which were attributed to heat advection from warmer and more intense precipitation and downslope flow. These changes raised net primary productivity from more rapid N mineralization and uptake, driven by more rapid heterotrophic respiration and increasing deciduous versus evergreen plant functional types. Consequently, gains in net ecosystem productivity (NEP) of 29 and 10 g C m −2 yr −1 were modeled in the tundra and fen after 90 years. However, CH 4 emissions modeled from the fen rose sharply from direct effects of increasing soil temperatures and greater ALD on fermenter and methanogenic populations and from indirect effects of increasing sedge growth, which hastened transfer of CH 4 through porous roots to the atmosphere. After 90 years, landscape CH 4 emissions increased from 1.1 to 5.2 g C m −2 yr −1 while landscape NEP increased from 34 to 46 g C m −2 yr −1 . Positive feedback to radiative forcing from increases in CH 4 emissions more than offset negative feedback from increases in NEP. This feedback was largely attributed to rises in CH 4 emission caused by heat advection from increasing precipitation, the impacts of which require greater attention in arctic climate change studies.
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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 | 0.004 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| 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".