The response of carbon dioxide exchange to manipulations of <i>Sphagnum</i> water content in an ombrotrophic bog
Bibliographic record
Abstract
Abstract Sphagnum mosses contribute to the long‐term carbon sequestration of many northern peatlands. Variability in both Sphagnum and peatland CO2 exchange is strongly influenced by water availability, but there is limited work examining the links between these relationships, particularly in a field setting. In this study, the effects of varying moss water content (WC), through precipitation exclusion (PE) and water addition (WA) treatments, on net ecosystem CO2 exchange (NEE) and component fluxes were assessed during a single growing season at Mer Bleue bog, a temperate ombrotrophic peatland. CO2 exchange by Sphagnum, vascular plants, and the total ecosystem were measured in situ using chambers. On average, the hummock species of Sphagnum dominant at the site maintained WCs within the optimal range for photosynthesis in all treatments and no treatment effect on CO2 exchange was observed. However, in a few samples associated with below optimal WCs, Sphagnum photosynthesis was reduced. Water table (WT) depth and direct precipitation were both important controls on Sphagnum WC, suggesting that frequent small rain events may be important in maintaining Sphagnum WC. This study only explored one variable associated with drought conditions (i.e. water availability through intercepted precipitation). Consequently, further study is necessary to assess the relative importance of deep WT positions and high temperatures on moss WC. Nevertheless, the results of this study suggest that decreased Sphagnum photosynthesis has the potential to influence peatland CO2 uptake at Mer Bleue in drought years, but only if moss WC is reduced below the optimal range. Copyright © 2010 John Wiley & Sons, Ltd.
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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".