Long‐Term Response of Peatland Carbon Exchange to Climatic Changes in the Hudson Bay Lowlands
Bibliographic record
Abstract
Abstract Northern peatlands have been a persistent net sink of atmospheric carbon (C) due to the greater rates of gross primary production (GPP) compared to ecosystem respiration (ER). Global warming has raised concerns about the C sink strength of northern environments. In the vast peatlands of the Hudson Bay Lowlands (HBL) region of Canada, warming‐induced changes in sea ice dynamics over the Bay have altered its advective influence on the adjacent lowlands. Despite our knowledge of the short‐term C exchange in these peatlands, there remain uncertainties in the long‐term combined response of GPP and ER to climate change. In this study, the satellite‐data‐driven Vegetation Photosynthesis and Respiration Model was employed to investigate the response of peatland GPP, ER, and net ecosystem exchange to temperature and moisture changes. The results show contrasting net CO2 exchange at the two peatland sites over the last 20 years, with the fen acting as a net C source (+24 g C m−2) to the atmosphere and the bog serving as a net C sink (−130 g C m−2). There is ample evidence that a warmer and wetter climate enhanced GPP more than ER, while cooler temperatures weakened the peatland net C sink, regardless of the moisture conditions. Additionally, the advective influence of Hudson Bay on the lowlands produced markedly different C dynamics between offshore and onshore winds, with higher respiration rates (12%–26%) during offshore winds. We discuss the implications for peatland C balance under more frequent onshore winds in the region.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 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".