A decade of boreal rich fen greenhouse gas fluxes in response to natural and experimental water table variability
Bibliographic record
Abstract
Abstract Rich fens are common boreal ecosystems with distinct hydrology, biogeochemistry and ecology that influence their carbon (C) balance. We present growing season soil chamber methane emission ( F CH 4 ), ecosystem respiration ( ER ), net ecosystem exchange ( NEE ) and gross primary production ( GPP ) fluxes from a 9‐years water table manipulation experiment in an Alaskan rich fen. The study included major flood and drought years, where wetting and drying treatments further modified the severity of droughts. Results support previous findings from peatlands that drought causes reduced magnitude of growing season F CH 4 , GPP and NEE , thus reducing or reversing their C sink function. Experimentally exacerbated droughts further reduced the capacity for the fen to act as a C sink by causing shifts in vegetation and thus reducing magnitude of maximum growing season GPP in subsequent flood years by ~15% compared to control plots. Conversely, water table position had only a weak influence on ER , but dominant contribution to ER switched from autotrophic respiration in wet years to heterotrophic in dry years. Droughts did not cause inter‐annual lag effects on ER in this rich fen, as has been observed in several nutrient‐poor peatlands. While ER was dependent on soil temperatures at 2 cm depth, F CH 4 was linked to soil temperatures at 25 cm. Inter‐annual variability of deep soil temperatures was in turn dependent on wetness rather than air temperature, and higher F CH 4 in flooded years was thus equally due to increased methane production at depth and decreased methane oxidation near the surface. Short‐term fluctuations in wetness caused significant lag effects on F CH 4 , but droughts caused no inter‐annual lag effects on F CH 4 . Our results show that frequency and severity of droughts and floods can have characteristic effects on the exchange of greenhouse gases, and emphasize the need to project future hydrological regimes in rich fens.
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.
How this classification was reachedexpand
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 | 0.001 |
| 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 teacher head, 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".