Interannual variability in the peatland‐atmosphere carbon dioxide exchange at an ombrotrophic bog
Bibliographic record
Abstract
Eddy covariance measurements of net ecosystem carbon dioxide (CO 2 ) exchange (NEE) were taken at an ombrotrophic bog near Ottawa, Canada from 1 June 1998 to 31 May 2002. Temperatures during this period were above normal except for 2000 and precipitation was near normal in 1998 and 1999, above normal in 2000, and well below normal in 2001. Growing period maximum daytime uptake (−0.45 mg CO 2 m −2 s −1 ) was similar in all years and nighttime maximum respiration was typically near 0.20 mg CO 2 m −2 s −1 , however, larger values were recorded during very dry conditions in the fourth year of study. Winter CO 2 flux was considerably smaller than in summer, but persistent, resulting in significant accumulated losses (119–132 g CO 2 m −2 period −1 ). This loss was equivalent to between 30 and 70% of the net CO 2 uptake during the growing season. During the first 3 years of study, the bog was an annual sink for CO 2 (∼−260 g CO 2 m −2 yr −1 ). In the fourth year, with the dry summer, however, annual NEE was only −34 g CO 2 m −2 yr −1 , which is not significantly different from zero. We examined the performance of a peatland carbon simulator (PCARS) model against the tower measurements of NEE and derived ecosystem respiration (ER) and photosynthesis (PSN). PCARS ER and PSN were highly correlated with tower‐derived fluxes, but the model consistently overestimated both ER and PSN, with slightly poorer comparisons in the dry year. As a result of both component fluxes being overestimated, PCARS simulated the tower NEE reasonably well. Simulated decomposition and autotrophic respiration contributed about equal proportions to ER. Shrubs accounted for the greatest proportion of PSN (85%); moss PSN declined to near zero during the summer period due to surface drying.
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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 | 0.000 | 0.000 |
| Open science | 0.000 | 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".