Role of high-flow extremes in aquatic carbon export from peatlands
Bibliographic record
Abstract
Peatland streams have repeatedly been shown to be highly supersaturated in gaseous carbon and export significant loads of both dissolved (DOC) and particulate (POC) organic carbon. Previous studies have shown that aquatic carbon export is strongly bias towards high flow events, which may become more frequent under predicted climate change scenarios. However, due to technical limitations and the lack of high flow representation in many regular spot sampling regimes, our understanding of high flow concentration dynamics is limited. Here we bring together 2 separate analyses of (i) the role of high-flow ‘extremes’ on DOC export based on long term (1993-2007) weekly spot samples across 7 UK upland streams, and (ii) stormflow CO2 dynamics across 5 headwater streams (UK, Sweden, Finland and Canada) using continuous, in-situ CO2 sensors. Catchment weighted DOC exports from the 3 peatland streams included in analysis (i) ranged from 16.9 to 28.0 g C m-2. Results showed 38.4%-44.9% of this DOC was exported during ‘extreme’ highs, which represented only 5% of time and 38.4%-40.6% of runoff. Although DOC export was greater from peatland streams, the proportion exported during ‘extreme’ events was similar across all 7 catchments. A comparison between the effects of storm intensity and duration on annual DOC export, and a seasonal breakdown of storm contributions, will also be presented. As well as quantifying the downstream export of CO2 during storm events (6%-33% of total CO2 export in 5% time), analysis (ii) will also consider high-resolution concentration responses across individual storms.
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 | 0.037 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.000 | 0.004 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.008 | 0.011 |
| Research integrity | 0.001 | 0.010 |
| Insufficient payload (model declined to judge) | 0.017 | 0.005 |
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; both teacher heads agree on what is shown here.
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".