Aquatic metabolism after impoundment of a low productivity boreal reservoir using free water oxygen
Bibliographic record
Abstract
Inland waterbodies play a significant role in the global cycling of greenhouse gases. Impoundment of rivers changes their greenhouse gas dynamics and leads to a pulse of emissions, primarily due to the respiration of introduced organic matter. Aquatic metabolism estimates using free water oxygen curves were calculated at 5 sites on the lower Nelson River, Manitoba, Canada, in 2021 to assess immediate conditions after impounding a hydroelectric reservoir at the Keeyask Generating Station. Net ecosystem production varied significantly across the study area (P < 0.001), with the most heterotrophic sites found in the reservoir. More specifically, ecosystem respiration (R) and gross primary production rates varied significantly (P < 0.001) within the reservoir itself. The greatest R (mean [standard deviation]) was observed in a former tributary inflow (−1.94 [1.03] g C m−2 d−1) and then in the forebay (−1.06 [0.74] g C m−2 d−1), an order of magnitude greater than the upstream extent of the reservoir area (−0.13 [0.29] g C m−2 d−1). Benthic and pelagic R had greater relative importance in the former tributary inflow and the forebay, respectively. Loading of organic matter seemed to vary across the reservoir, and evidence suggests it was a key factor regulating R. Light limitation seemed prevalent throughout the study area, consistent with previous studies in the region. The results presented here update understanding of aquatic metabolism in a region characterized by hydroelectric development.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| 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 source (direct Gemma or distilled Codex), 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".