Effects of Warming and Permafrost Thaw on Carbon Dioxide Fluxes from Boreal Peatlands in northwestern Canada
Bibliographic record
Abstract
The Taiga Plains ecozone in northwestern Canada is warming rapidly which alters the carbon dioxide (CO2) fluxes of the boreal peat landscape in two ways: 1) directly by increasing temperatures going along with increasing fluxes and 2) indirectly via permafrost thaw and resulting wetland expansion. However, we still lack an understanding of how direct and indirect effects vary across a latitudinal climate gradient covering different extents of permafrost. In this study, we will compare two years of concurrent eddy covariance measurements made over forested permafrost peat plateaus at Smith Creek (discontinuous permafrost) and Scotty Creek (sporadic permafrost) to assess differences in net CO2 exchange and its two component fluxes, gross primary productivity (GPP) and ecosystem respiration (ER). Footprint analysis will be used to assess the net CO2 balance of peat plateaus and thermokarst wetlands at both sites. We hypothesize that GPP and ER will be higher at the warmer Scotty Creek site, due to both, more abundant thermokarst wetlands and higher GPP and ER of peat plateaus at this southern site. We also hypothesize that the effects of warming on GPP are greater than on ER and thus that the warmer Scotty Creek site is a greater net CO2 sink. Our study will conclude on the carbon feedback of warming peat landscapes near the southern limit of permafrost in northwestern Canada in response to Climate Change.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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) | 0.001 | 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".