No long‐term trends in <i>p</i>CO<sub>2</sub> despite increasing organic carbon concentrations in boreal lakes, streams, and rivers
Bibliographic record
Abstract
Abstract Concentrations of dissolved organic carbon (DOC) from terrestrial sources have been increasing in freshwaters across large parts of the boreal region. According to results from large‐scale field and detailed laboratory studies, such a DOC increase could potentially stimulate carbon dioxide (CO 2 ) production, subsequently increasing the partial pressure of CO 2 ( p CO 2 ) in freshwaters. However, the response of p CO 2 to the presently observed long‐term increase in DOC in freshwaters is still unknown. Here we tested whether the commonly found spatial DOC‐ p CO 2 relationship is also valid on a temporal scale. Analyzing time series of water chemical data from 71 lakes, 30 streams, and 4 river mouths distributed across all of Sweden over a 17 year period, we observed significant DOC concentration increases in 39 lakes, 15 streams, and 4 river mouths. Significant p CO 2 increases were, however, only observed in six of these 58 waters, indicating that long‐term DOC increases in Swedish waters are disconnected from temporal p CO 2 trends. We suggest that the uncoupling of trends in DOC concentration and p CO 2 are a result of increased surface water runoff. When surface water runoff increases, there is likely less CO 2 relative to DOC imported from soils into waters due to a changed balance between surface and groundwater flow. Additionally, increased surface water runoff causes faster water flushing through the landscape giving less time for in situ CO 2 production in freshwaters. We conclude that p CO 2 is presently not following DOC concentration trends, which has important implications for modeling future CO 2 emissions from boreal waters.
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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 | 0.000 | 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) | 0.000 | 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".