A century of human‐driven changes in the carbon dioxide concentration of lakes
Bibliographic record
Abstract
Abstract Now that evasion of carbon dioxide (CO 2 ) from inland waters is accounted for in global carbon models, it is crucial to quantify how these fluxes have changed in the past and forecast how they may alter in the future in response to local and global change. Here we developed a sediment proxy for the concentration of summer surface dissolved CO 2 concentration and used it to reconstruct changes over the past 150 years for three large lakes that have been affected by climate warming, changes in nutrient load, and detrital terrigenous supplies. Initially CO 2 neutral to the atmosphere, all three lakes subsequently fluctuated between near equilibrium and supersaturation. Although catchment inputs have supplied CO 2 to the lakes, internal processes and reallocation have ultimately regulated decadal changes in lake surface CO 2 concentration. Nutrient concentration has been the dominant driver of CO 2 variability for a century although the reproducible, nonmonotonic relationship of CO 2 to nutrient concentration suggests an interplay between metabolic and chemical processes. Yet for two of these lakes, climatic control of CO 2 concentrations has been important over the last 30 years, promoting higher surface CO 2 concentrations, likely by decreasing hypolimnetic carbon storage. This new approach offers the unique opportunity to scale, a posteriori, the long‐term impact of human activities on lake CO 2 .
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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".