Moisture controls on CO<sub>2</sub> exchange in a <i>Sphagnum</i>‐dominated peatland: results from an extreme drought field experiment
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract Peatlands store globally significant quantities of soil carbon, and Sphagnum moss is the main peat forming vegetation type in bogs. Sphagnum moss productivity is driven by the moisture content of its apical cluster of branches, the capitulum. Capitulum moisture content is dependent on the arrangement of leaves, branches and stems for a given species and also on hydrological conditions of the underlying peat. Despite this link, the response of CO 2 exchange in Sphagnum ‐dominated peatlands to extreme drought is still unclear, particularly under field conditions. We used drainage to expose Sphagnum rubellum to extreme drought and monitored water table, volumetric water content (VWC), gross ecosystem photosynthesis (GEP), ecosystem respiration (ER) and net ecosystem exchange of CO 2 (NEE) at plots in a 25 m transect perpendicular to a deep drainage ditch and compared results to an undrained site. VWC in the upper 10 cm of peat was strongly related to water table at depths shallower than 55 cm. Below this depth, near surface VWC remained relatively constant between 25 and 28% and Sphagnum GEP was effectively shut down. This also resulted in decreased ER at these locations. The combined effect was a linear relationship between VWC and NEE with moist sites acting as net CO 2 sinks (up to −5 g CO 2 m −2 day −1 ) whereas sites closest to the ditch were consistently small carbon sources. We suggest that understanding how climate change will alter peatland hydrology relative to the moisture thresholds of Sphagnum mosses is critical to determining the fate of their carbon sink function. Copyright © 2009 John Wiley & Sons, Ltd.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.001 | 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 it