Stream Discharge in Tropical Headwater Catchments as a Result of Forest Clearing and Soil Degradation
Why this work is in the frame
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Bibliographic record
Abstract
Abstract Tropical Africa is affected by intense land-use change, particularly forest conversion to agricultural land. In this study, the stream discharge of four small headwater catchments located within an area of 6 km2 in western Kenya was examined for 2 years (2007 and 2008). The four catchments cover a degradation gradient ranging from intact forest to agricultural land under maize cultivation for 5, 10, and 50 years. The runoff ratio (e.g., annual catchment discharge expressed as a percentage of rainfall) increased with increasing duration of cultivation from an average of 16.0% in the forest to 32.4% in the 50-yr-old agricultural catchment. Similarly, the average runoff ratio due to the stormflow component was 0.033 in the forest and increased gradually to 0.095 with increasing duration of cultivation. The conversion from forest to agricultural land in the first 5 years caused about half of the total observed increases in runoff ratio (46.3%) and discharge in relation to rainfall (50.6%). The other half of the changes in discharge occurred later during soil degradation after forest clearing. With increasing duration of cultivation, soil bulk density ρb at a depth of 0–0.1 m increased by 46%, while soil organic carbon (SOC) concentrations and total porosity decreased by 75% and 20%, respectively. The changes in hydrological responses that occurred in the initial years after forest clearing may suggest a significant potential for improved land management in alleviating runoff and enhanced storm flow and moisture retention in agricultural watersheds.
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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 | 0.000 |
| 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 it