Effect of Dung Quantity and Quality on Greenhouse Gas Fluxes From Tropical Pastures in Kenya
Bibliographic record
Abstract
Abstract To improve estimates of agricultural greenhouse gas emissions in sub‐Saharan Africa, we measured over six individual periods of 25–29 days fluxes of methane (CH 4 ), carbon dioxide (CO 2 ), and nitrous oxide (N 2 O) with subdaily time resolution from dung patches of different quality (C/N ratio: 23–41) and quantity (0.5 and 1.0 kg) on a Kenyan rangeland during dry and wet seasons. Methane emissions peaked following dung application, whereas N 2 O and CO 2 fluxes from dung patches were similar to fluxes from rangeland soils receiving no N additions. Greenhouse gas emissions scaled linearly with dung quantity during both seasons. Dung with a low (23) C/N ratio produced up to 10 times more CH 4 than dung with a high (41) C/N ratio. Overall, CH 4 emission factors (EFs) ranged from 0.001 to 0.042%, lower than those derived in temperate regions. Cumulative CO 2 and N 2 O emissions were similar for all treatments across the different seasons. The N 2 O EF ranged from 0 to 0.01%, less than 1% of the Intergovernmental Panel on Climate Change Tier 1 default EF (2%) for N 2 O emissions from dung and urine patches, likely because of the low dung N content (9.7–16.5 g N kg −1 dry matter). However, these results were consistent with the updated cattle dung EF (0.2%) developed for Kenya in 2016/2017 (EF database ID# 422665). In view of the wide range of climates, soils, and management practices across sub‐Saharan Africa, development of robust GHG EFs from dung patches for SSA requires additional studies.
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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".