Tropical artificial rural and urban ponds are net sources of carbon dioxide and methane in Rwanda, East Africa
Why this work is in the frame
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Bibliographic record
Abstract
Artificial ponds have been overlooked as sources of greenhouse gases (GHGs) despite their potential to be significant emission sources. We studied the concentration of dissolved organic carbon, [DOC], and the concentration and fluxes of CO 2 and CH 4 in five rural fishponds and five ornamental urban ponds with areas of 981 to 3,676 m 2 in the capital of Rwanda, Kigali. The mean concentration of DOC in rural ponds (60.12 ± 4.70 mg L –1 ) was lower than that in urban ponds (69.61 ± 5.97 mg L –1 ). The dissolved CO 2 concentration in rural ponds (24.20 ± 2.40 μmol L –1 ) was also lower than that in urban ponds (30.40 ± 8.61 μmol L –1 ). However, the concentration of CH 4 in rural ponds (3.31 ± 1.16 μmol L –1 ) was ∼6 times higher than that in urban ponds (0.59 ± 0.11 μmol L –1 ). Areal CO 2 fluxes in rural ponds (8.07 ± 1.57 mmol m –2 d –1 ) were slightly higher than those in urban ponds (7.86 ± 3.33 mmol m –2 d –1 ). Areal CH 4 fluxes in rural ponds (1.77 ± 0.62 mmol m –2 d –1 ), were 7 times higher than in urban ponds (0.25 ± 0.05 mmol m –2 d –1 ). The mean C flux in CO 2 equivalents (CO 2 -eq) from all ponds was 275.53 g CO 2 -eq m –2 yr –1 , of which 53% was attributed to CH 4 . These findings highlight the need to include artificial ponds in national and global greenhouse gas inventories to their overall carbon footprint.
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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 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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 it