Response of dissolved organic carbon in a shallow groundwater ecosystem to a simulated global warming experiment
Bibliographic record
Abstract
Dissolved organic carbon (DOC) in marine and freshwater ecosystems represents an immense reservoir of organic matter with varied and significant ecological value. Global warming poses a significant threat in that it has the capacity to alter the concentration and distribution of DOC. Since groundwater constitutes approximately two-thirds of the available freshwater on earth, it is crucial to determine how global warming may affect its DOC balance. However, in higher latitudes carbon cycling is poorly understood, and ecosystem-scale studies are urgently required. We conducted an in situ temperature manipulation of a shallow groundwater system in Ontario, Canada that simulated temperature increases predicted by general circulation models for this region. Specifically, treatment block temperatures in spring, summer, and fall were elevated 3.9 0.6 SD C, whereas winter temperatures were elevated 5.0 0.6 C compared with a control block. We found no significant difference in DOC between control and treatment blocks during the pre-manipulation study period. However, there was a significant increase in DOC with groundwater depth in both blocks: 4.54 0.25 mg/l at -20 cm to 5.79 0.24 mg/l at -100 cm. During this period there was also a difference in DOC among seasons: fall and winter concentrations were lower than spring and summer. During the manipulation period there was also no difference in DOC between the control and treatment blocks, however, a positive trend in the treatment block was observed for all collections. Also, seasonal and depth differences between blocks were still apparent. Although during the manipulation period nitrate and total phosphorus showed no difference between control and treatment blocks, ammonia showed a significant decrease in the treatment block. We discuss the implications of these findings to the biogeochemistry and ecology of shallow aquifers.
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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".