1. LBA 17-19.11.08, Manaus Jan Börner (CIAT, Amazon Initiative) Arisbe Mendoza (ECOSUR) Secondary forest valuation on family farms in the Eastern Brazilian Amazon

2. LBA 17-19.11.08, Manaus Outline Why value secondary forests? Evidence on the fallow-yield relationship A two-step approach to value the role of capoeira in slash-and-burn farming Policy and technology scenarios Implications for designing conservation incentives

3. LBA 17-19.11.08, Manaus Why value secondary forests? > 8.7 million ha on farms in the Brazilian Amazon are covered by secondary forests About a quarter is frequently converted for agricultural purposes (crops, pastures) Depending on agricultural practices and technology, farmers may perceive secondary forest growth as cost or benefit factors i.e., conservation incentives can only be effective if these factors are taken into account

4. LBA 17-19.11.08, Manaus Secondary forests, pastures and staple crop fields Secondary forest fallows supply nutrients and other ecosystem services in crop producing S&B systems Secondary forest re-growth reduces the productivity of pastures

5. LBA 17-19.11.08, Manaus Evidence on the fallow-yield relationship Cited in Mertz (2002) Agroforestry S. Positive fallow-length/yield relation rarely empirically proven Breakdown points could not be empirically established Yield is only one of the factors influencing farming decisions Fallow/yield relationship is only half the story

6. LBA 17-19.11.08, Manaus Key questions How will policy incentives affect secondary forest cover and related ES? –What value to farmers attach to fallows (their length)? –What impact does access and use of different technologies have on this value? –How do conservation incentives (e.g. PES) affect secondary forest cover and value under different technology scenarios?

7. LBA 17-19.11.08, Manaus An example from the Eastern Brazilian Amazon ZEF Bonn NAEA/UFPA

8. LBA 17-19.11.08, Manaus Recently burned Pasture Cassava Passion fruit Fallow vegetation

9. LBA 17-19.11.08, Manaus Approach plot-level profit function estimation farm-level bio-economic land use modeling model calibration plot-level annual crop production data from 450 plots value of fallowing in the S&B system value of secondary forest fallows at farm-level farm-level data from 270 farm-households technical coefficient data from 30 representative farm-households classification (cluster analysis) Result Method Analysis Data Legend:

10. LBA 17-19.11.08, Manaus Results of econometric model II Fixed Factors (standard errors in parentheses) Factor demandLandFamily labourFallow lengthSoil pH Fertilizer0.222 (0.048)-0.032 (0.007)-0.052 (0.014)-0.041 (0.008) Hired Labour1.713 (0.162)-0.000 (0.000) 0.014 (0.001)-0.175 (0.016) Obs.: Mean and standard errors of farm elasticities are calculated using one observation for each farm evaluated at mean farm prices. The standard errors are calculated by bootstrapping on 500 data re-sampling.

11. LBA 17-19.11.08, Manaus Results of econometric model (plot-level) VariablesElasticities (standard errors in parentheses) Land 0.955 (0.122) Fallow 0.222 (0.020) Hired labour 0.140 (0.034) Fertilizer 0.099 (0.013) Elasticity Estimates of Profit with Respect to Farm Resources Obs.: Mean and standard errors of farm elasticities are calculated using one observation for each farm evaluated at mean farm prices. The standard errors are calculated by bootstrapping on 500 data re-sampling. Equivalent to R$ 385 per ha of 6 year old fallow!

12. LBA 17-19.11.08, Manaus Results of bio-economic model (farm-level) Key indicatorsUnitsResults Annual Net incomeR$4064 Area under annualsha2.79 Area under perennialsha0.97 Fallowha9.2 Fallow ageYears4 Fallow valueR$/ha128 R$1 ≈ 0.28 Euro

13. LBA 17-19.11.08, Manaus Model validation No statistically significant bias in predicted 1 st -year land use across farm types Long-term trends in average fallow age, and fallow/cropland ratio correspond to farmers’ observations of the past Model versus Reality

14. LBA 17-19.11.08, Manaus A selection of available technologies? Farm- household choices Technology / Land Use Options Slash & Burn Mechanical Plowing Chop-and- mulch Green Revolution Agroforestry & Processing

15. LBA 17-19.11.08, Manaus What would happen if farmers adopted? IncomeSecondary forest/fallows Fallow ageSequestered carbon Labor demand Adoption of continuous cropping + mechanical land preparation reduces fallow valuation by 71% to R$/ha 38

16. LBA 17-19.11.08, Manaus Payments for environmental services R$1 ≈ 0.28 Euro

17. LBA 17-19.11.08, Manaus Competitiveness Avoided emissions (t CO 2 per farm) in T=20 CER price at CCX

18. LBA 17-19.11.08, Manaus Conclusions & Implications For representative family farms in the Northeastern Amazon annual payments of > R$/ha 100 are needed to induce carbon sequestration Technology access reduces absolute carbon content on farms, but allows capturing additional carbon at 50% lower costs Hence, PES needed to be differentiated to increase scheme efficiency and reduce rent capture by capitalized and well off farmers