Reconstructing the seasonal dynamics and relative contribution of the major processes sustaining CO<sub>2</sub> emissions in northern lakes
Bibliographic record
Abstract
Abstract Lake CO 2 emissions are an important component of the carbon balance of northern landscapes, yet the temporal dynamics of the underlying mechanisms sustaining CO 2 emissions are less understood. Here, we reconstruct the major biotic and abiotic processes influencing CO 2 dynamics over an annual cycle in three limnologically different lakes, using a combination of empirical measurements and process‐based modeling. Our results suggest that the relative importance of each process sustaining CO 2 emissions is not only variable among lakes, but also highly variable among seasons within one lake. Spring CO 2 emissions were largely sustained by the release of under ice accumulation (between about 50–100%), although photo‐chemical DOC mineralization and hydrologic CO 2 loading were also relatively important. In summer, due to warmer temperature, pelagic and benthic metabolism were the main sources of CO 2 emissions. In the fall, lake CO 2 emissions were generally sustained by hydrologic CO 2 inputs, while hypolimnetic CO 2 accumulation and release also contributed to fall CO 2 emission in the deepest lake. On an annual basis, lake CO 2 emissions ranged between 21.4 g C m −2 yr −1 and 55.5 g C m −2 yr −1 . Our results confirm that the major processes all contributed significantly to CO 2 emissions, but their relative contributions were modulated by the seasonal patterns in climate and hydrology, and by differences in morphology and organic carbon inputs among lakes. These lake‐ and season‐specific features need to be considered both in the upscaling of lake processes at regional scales, and in predicting lake CO 2 emissions under scenarios of climate and environmental change.
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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".