Contrasting CO<sub>2</sub> concentration discharge dynamics in headwater streams: A multi‐catchment comparison
Bibliographic record
Abstract
Abstract Aquatic CO 2 concentrations are highly variable and strongly linked to discharge, but until recently, measurements have been largely restricted to low‐frequency manual sampling. Using new in situ CO 2 sensors, we present concurrent, high‐frequency (<30 min resolution) CO 2 concentration and discharge data collected from five catchments across Canada, UK, and Fennoscandinavia to explore concentration‐discharge dynamics; we also consider the relative importance of high flows to lateral aquatic CO 2 export. The catchments encompassed a wide range of mean CO 2 concentrations (0.73–3.05 mg C L −1 ) and hydrological flow regimes from flashy peatland streams to muted outflows within a Finnish lake system. In three of the catchments, CO 2 concentrations displayed clear bimodal distributions indicating distinct CO 2 sources. Concentration‐discharge relationships were not consistent across sites with three of the catchments displaying a negative relationship and two catchments displaying a positive relationship. When individual high flow events were considered, we found a strong correlation between both the average magnitude of the hydrological and CO 2 response peaks, and the average response lag times. An analysis of lateral CO 2 export showed that in three of the catchments, the top 30% of flow (i.e., flow that was exceeded only 30% of the time) had the greatest influence on total annual load. This indicates that an increase in precipitation extremes (greater high‐flow contributions) may have a greater influence on the flushing of CO 2 from soils to surface waters than a long‐term increase in mean annual precipitation, assuming source limitation does not occur.
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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 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".