Consequences of Increased Variation in Peatland Hydrology for Carbon Storage: Legacy Effects of Drought and Flood in a Boreal Fen Ecosystem
Bibliographic record
Abstract
Globally important carbon (C) stores in boreal peatlands are vulnerable to altered hydrology through changes in precipitation and runoff patterns, groundwater inputs, and a changing cryosphere. These changes can affect the extent of boreal wetlands and their ability to sequester and transform C and other nutrients. Variation in precipitation patterns has also been increasing, with greater occurrences of both flooding and drought periods. Recent work has pointed to the increasing role of algal production in regulating C cycling during flooded periods in fen peatlands, but exactly how this affects the C sink-strength of these ecosystems is poorly understood. We evaluated temporal trends in algal biomass, ecosystem C uptake and respiration (using static and floating chamber techniques), and spectroscopic indicators of DOM quality (absorbance and fluorescence) in a boreal rich-fen peatland in which water table position had been experimentally manipulated for 13 years. Superimposed on the water table treatments were natural variations in hydrology, including periods of flooding, which allowed us to examine the legacy effects of flooding on C cycling dynamics. We had a particular focus on understanding the role of algae in regulating C cycling, as the relative contribution of algal production was observed to significantly increase with flooding. Ecosystem measures of gross primary production (GPP) increased with algal biomass, with higher algal biomass and GPP measured in the lowered water table treatment two years after persistent flooding. Prior to flooding the lowered treatment was the weakest C sink (as CO 2 ), but this treatment became the strongest sink after flooding. The lower degree of humification (lower humification index, HIX) and yet lower bioavailability (higher spectral slope ratio, Sr) of DOM observed in the raised treatment prior to flooding persisted after two years of flooding. An index of free or bound proteins (tyrosine index, TI) increased with algal biomass across all plots during flooding, and was lowest in the raised treatment. As such, antecedent drainage conditions determined the sink-strength of this rich fen—which was also reflected in DOM characteristics. These findings indicate that monitoring flooding history and its effects on algal production could become important to estimates of C balance in northern wetlands.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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 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".