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Agricultural Carbon Sequestration and Poverty

Agricultural Carbon Sequestration and Poverty. John M. Antle Dept of Ag Econ & Econ, Montana State U. Thanks to my colleagues without whose support this research would not be possible: Charles Crissman, CIP, Nairobi Bocar Diagana, Montana State U Kara Gray, Montana State U

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Agricultural Carbon Sequestration and Poverty

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  1. Agricultural Carbon Sequestration and Poverty John M. Antle Dept of Ag Econ & Econ, Montana State U

  2. Thanks to my colleagues without whose support this research would not be possible: • Charles Crissman, CIP, Nairobi • Bocar Diagana, Montana State U • Kara Gray, Montana State U • Ibrahima Hathie, ENEA, Senegal • Andre de Jager, LEI, the Netherlands • Jetse Stoorvogel, Wageningen UR • Roberto Valdivia, Montana State U • Alejandra Vallejo, Wageningen UR • David Yanggen, CIP, Lima

  3. Basic Concepts • Linkages to Poverty • Evidence from Peru, Senegal and Kenya • Conclusions

  4. I. Basic Concepts • Land use & management practices increase or decrease ecosystem C (key indicator of soil health)

  5. I. Basic Concepts • Land use & management practices increase or decrease ecosystem C • Payments to farmers can create incentives for farmers to change LU & management to increase C until stock is max’ed • Issues in C seq literature: • Technical vs economic potential • Productivity effects & dynamics • Permanence & leakage • Adoption costs • Incentive design • Additionality • Per-hectare vs per-ton payments • Symmetric vs asymmetric incentives • Transaction costs

  6. Contract participation decision (Antle et al, JEEM, 2003): • g > NR + A + TC • For per-ton carbon payment, g = PC, thus • P > (NR + A + TC)/C

  7. II. Linkages to Poverty • Those who benefit most have low opp cost of adoption • Are the poorest farmers on the adoption margin? • Additionality targets non-adopters … • Fixed cost and trans cost create adoption threshold • These costs have greatest impact at low C prices and where carbon rates are low. • Opp cost NR may decline over time as C accumulates and system productivity increases

  8. Carbon Permanece as an Emergent Property of Production Systems: Farmers who lack knowledge of system dynamics can be provided an incentive to learn the benefits of improved soil management. This can lead to permanent adoption of improved practices without permanent external incentives. (Antle and Diagana, AJAE 2004)

  9. III. Evidence from Three Case Studies • Case studies: • Terracing and agroforestry in the Peruvian Andes • Nutrient and crop residue management in Senegal’s peanut basin • Nutrient management (mineral fertilizer, manure, crop residues) in Machakos district of Kenya • Methods: • Case studies based on statistically representative samples of spatially-referenced data • Bio-physical and econometric-process models simulate site-specific land use and management decisions under base scenario and carbon contract scenarios • Spatial distribution of contract participation decisions are used to derive carbon supply curves for the population in the region

  10. Tradeoff Analysis: Integrated Assessment of Agricultural Production Systems DSSAT/Century Econometric- Process NUTMON Spatial Aggregation

  11. The Tradeoff Analysis Software is a GIS-based system designed to integrate disciplinary data and models for integrated assessment of agricultural systems. An on-line course, the software, and applications for Ecuador, Peru, Senegal and Kenya can be downloaded at www.tradeoffs.nl.

  12. Terracing and agroforestry in the Peruvian Andes (Cajamarca) • Evidence shows terracing and agroforesty are profitable for some farmers but adoption is only about 30% • Incomplete adoption explained by spatial heterogeneity in bio-physical and economic conditions • Carbon contracts would provide payments for carbon in soil and above-ground biomass • In contrast to conservation “projects” that subsidize all farmers, only farmers at the adoption margin would have an incentive to participate

  13. The importance of heterogeneity: profitability of terracing is a function of site-specific conditions (e.g., slope). Carbon payments create incentive for additional adoption.

  14. Carbon Supply Curves for Terracing and Agroforestry for Low (LC) and High (HC) Carbon Rate Scenarios

  15. The adoption margin: What conditions favor additional adoption of carbon-sequestering practices?

  16. Nutrient and crop residue management in Senegal’s Peanut Basin • Field data show very low use of mineral fertilizer, high rates of nutrient depletion, very low SOM • Carbon contracts would pay farmers to increase mineral fertilizers and incorporate crop residues

  17. Crop residues are the key to increasing soil C in nutrient-deficient systems Note participation at zero carbon price

  18. Key constraint is opportunity cost of crop residues that are used by small, poor farmers to feed livestock

  19. Transaction costs constrain participation in C contracts at low carbon prices

  20. Nutrient management in Machakos, Kenya • Mineral fertilizer use low in this maize-based, mixed crop-livestock system • Extensive terracing has reversed catastrophic soil erosion seen in the early-mid 20th Century (Tiffen et al., More People, Less Erosion), but WUR Nutrient Monitoring data show high rates of nutrient depletion • Carbon contracts would pay farmers to increase use of mineral and organic fertilizers

  21. Technology: Zero-grazing units provide opportunity to improve nutrient management efficiency and livestock productivity.

  22. Machakos C Supply Curves • for Low, Medium and High Carbon Rates

  23. Machakos: Impact of Carbon Sequestration Payments • on Poverty (% < $1/day)

  24. Machakos: Impact of Carbon Sequestration • on Nutrient Depletion (kg/ha/season)

  25. Machakos: Impact of Carbon Sequestration • on Poverty and Nutrient Depletion

  26. Importance of Heterogeneity: Impact of C Sequestration on Poverty and Nutrient Depletion in Machakos, by Village (Medium C Rate)

  27. Conclusions • Evidence shows ag C sequestration has some potential to reduce poverty and enhance sustainability in semi-subsistence systems • However evidence also suggests that disadvantaged areas may benefit less than more productive regions. • Key issues are: • System dynamics and heterogeneity • Opportunity costs of improved practices • Transaction costs & institutional capability • Can participation in carbon markets help disadvantaged areas overcome constraints on technology adoption? • For example, could a carbon-based rural micro-credit program enhance farmers’ ability to reverse soil nutrient depletion in marginal areas?

  28. This presentation and related publications are available at: www.tradeoffs.montana.edu www.climate.montana.edu www.tradeoffs.nl

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