Dependency of Ecosystem Respiration in a Cool Temperate Bog on Peat Temperature and Water Table
Bibliographic record
Abstract
We measured ecosystem respiration (ER) from nighttime net ecosystem exchange of carbon dioxide determined from an eddy covariance tower located in a large ombrotrophic bog near Ottawa, Canada. Measurements were made from May to October over 5 years, 1998 to 2002. Ecosystem respiration ranged from $<$0.05 mg CO2/m2/s in spring (May) and late fall (late October) to 0.10-0.15 mg CO2/m2/s during the summer (July-August). As anticipated, there was a strong relationship between ER and peat temperatures, such as at a depth of 5 cm (r2 = 0.63). Q10 over 5$\deg$ to 15$\deg$C varied from 2.2 to 4.2 depending upon the choice of temperature level and location within a hummock or hollow. Unexpected for a wetland ecosystem, there was only a weak relationship between ER and water table position (r2 = 0.11). Comparison of ER in early and late summer, 2002 with similar surface temperature revealed no significant difference in ER. A laboratory incubation of peat cores at different moisture contents showed that CO2 production was reduced by drying in the surface samples, but there was little decrease in samples from below a depth of 30 cm. We believe that the lack of correlation between ER and water table position in this ecosystem results from an increase in CO2 production at depth compensating a decrease in production of CO2 by heterotrophic respiration in the near surface layers and autotrophic respiration in the moss community.
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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".