Indigenous Charcoal and Biochar Production: Potential for Soil Improvement under Shifting Cultivation Systems
Why this work is in the frame
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Bibliographic record
Abstract
Abstract Biochar offers potential for enhancing the agricultural productivity of degraded lands in the humid tropics. This paper reports on charcoal and biochar production among peasant farmers who practise shifting cultivation in the Peruvian Amazon. Using wood from secondary forest fallows, farmers produce charcoal for market in earthen mound kilns, also yielding biochar, as charcoal fines, which becomes incorporated into kiln site soils. Data were collected in a riverside community near Iquitos through interviews with farmers/charcoal producers, an inventory of kiln sites, a kiln audit of the charcoal production process, and soil sampling of kiln sites and adjacent paired control sites (depth: 15 cm). Our results indicate that kilns incorporate substantial quantities of biochar into local soils (Ultisols), as much as 30 tonnes each year on 0·4–0·8 ha of kiln sites. Additions of biochar and ash significantly enhance soil fertility by increasing organic C content, raising P and other nutrient concentrations, reducing acidity and exchangeable Al, and increasing soil porosity and friability. Organic C, N, Mg, Ca, and effective cation exchange capacity did not decrease significantly with increasing kiln site age, suggesting that heightened levels may persist for more than a decade after kilns are used. Farmers recognize the elevated fertility of kiln sites and cultivate in them annual and perennial crops, as well as use kiln soil and biochar off‐site, in home gardens, nursery beds, and planting holes. Our findings point to the potential of biochar to ameliorate soils and enhance forest recovery under shifting cultivation systems that integrate charcoal production into forest fallow‐based rotations. Copyright © 2016 John Wiley & Sons, Ltd.
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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