Regional modelling for REDD+ project development: the case of the Suruí Forest Carbon Project
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Regional modelling for REDD+ project development: the case of the Suruí Forest Carbon Project MEASUREMENT, REPORTING AND VERIFICATION IN LATIN AMERICAN REDD+ PROJECTS – CIFOR WORKSHOP PETROPOLIS, MARCH 8 TH 2012. GABRIEL C. CARRERO
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Credible baseline setting and accurate and transparent Measurement, Reporting and Verification (MRV) of results are key conditions for successful REDD+ projects. In this presentation, Gabriel Carrero from IDESAM explains the process of regional spatial and non-spatial modeling for determining a baseline in the Surui Forest Carbon Project. Gabriel Carrero gave this presentation on 8 March 2012 at a workshop organised by CIFOR, ‘Measurement, Reporting and Verification in Latin American REDD+ Projects’, held in Petropolis, Brazil. The workshop aimed to explore important advances, challenges, pitfalls, and innovations in REDD+ methods — thereby moving towards overcoming barriers to meeting MRV requirements at REDD+ project sites in two of the Amazon’s most important REDD+ candidate countries, Peru and Brazil. For further information about the workshop, please contact Shijo Joseph via s.joseph (at) cgiar.org
Transcript of Regional modelling for REDD+ project development: the case of the Suruí Forest Carbon Project
Regional modelling for REDD+ project development: the case of theSuruí Forest Carbon Project
MEASUREMENT, REPORTING AND VERIFICATION IN LATIN AMERICAN REDD+ PROJECTS – CIFOR WORKSHOPPETROPOLIS, MARCH 8TH 2012.
GABRIEL C. CARRERO
IDESAM’s Climate Change and Environmental Services Program
PMC
• REDD+ and A/R projects• Juma REDD Project • Suruí REDD+• Greener Apui Program• Carbon Neutro Program
• UNFCCC, GCF, etc.• Latin American REDD Forum• “Articulación Regional Amazonica” (ARA)• National: OC, FBMC, Amazonas State
Government• Nesting State Level Programs into National
Programs (AM- RO)
• REDD Projects Development• Katoomba Group Courses• Amazonas State REDD+ and CC • Others
Baseline Approaches
• Projecting historical average X modeling rates
• Regional modeling– Need local understand, identifying agents, drivers
and underlying causes
Simamazonia I
Soares Filho et al. 2006
Baseline construction
Project Boundaries
208,039 ha
3,416.6 ha31,994ha
Suruí people identified as the sole agents of deforestation.
– Control over the Territory– Logging agreements– Lease pastures and
sharecropping systems
Baseline Scenario - Agents
– Cash income from external actors (logging, sharecropping and pasture leasing)
– Population growth– Increased labor available
Baseline Scenario - Drivers
Average:157.4 ha/year
SimSurui Modeling
• Non-spatial modeling– Vensim software (http://www.vensim.com/index.html)
• Spatial modeling– Dinamica Ego platform (http://www.csr.ufmg.br/dinamica/)
PhD Student Claudia S. Vitel (Agroparistech & INPA).
Non-spatial model: SimSurui
System Dynamics>Modeling method of variables of interest based on
empirical data for testing and assessing patterns and responses of the system in question.
– Conceptual model– Causal Diagram– Selected variables
• Profitability scenarios
SIMSURUI Causal diagram
Datasets
Interviews Number families Families (No.) % 2009 2038
Group 0Without Productive Activity/Subsistence
11 9.1 18 39
Group 1 Coffee Growers 53 44 85 187
Group 2Coffee Growers and
Ranchers48 40 78 170
Group 3 Ranchers 9 7.4 14 31Total 121 100 195 428
Description / Class 2009 2038Suruí Population (individuals) 1142 2504[0-15 years] 518 705[15 - 65] 597 1266[> 65] 27 532Suruí Households 195 428Employed Individuals 62 316Labor available in Surui territory 534 949
Number of
Households
Fixed Income *(R$/ yr)
Fixed expenses*
(R$/ yr)
Timber*(R$/ yr)
Handicrafts*(R$/ yr)
Net revenue
own livestock
**(R$/ ha)
Livestock net
revenue lease **(R$/ ha)
Net revenue
own coffee **(R$/ ha)
Net income ** coffee
sharecropping(R$/ ha)
Group 0 11 11,663 8,857 4,840 116 - - - -Group 1 53 6,974 7,026 7,120 148 - - 294.0 121.6Group 2 48 6,042 9,060 9,984 344 190.8 60.0 294.0 121.6Group 3 9 5,006 8,423 7,875 12 190.8 60.0 - -
Economic dynamics of the productive agent groups
Net Household’s financial flows
Net household financial
balance (R)
Percentage spent on
consumer goods
Percentage invested in real estate
Percentage invested in productive activities (livestock, coffee*)
Total
>10,000 31.2% 59.2% 9.6% (7.91%, 1.69%) = 100%
[5000-10000] 46.0% 22% 32% (21.34%, 10.56%) = 100%
[0-5000] 47.0 6.2% 46.8% (25.74%, 21.06%) = 100%
Model calibration
Data 2009 2004 Proportions 2009
Population 1,142 956 Number of individuals
Adults 597 500 Adults / total population 0.52
Dependent 518 434 Dependent / total population 0.45
Elderly 27 23 Elderly / total population 0.02
Families Group 1 86 72 Productive area
Families Group 2 77 65 Coffee G1/area cleared 0.06
Families Group 3 15 12 Coffee G2/area cleared 0.11
Families subsistence agriculture 154 129.1 G2/areas cleared pastures 0.41
Income wood Group 1* 7,120.3 10,680 G3/area cleared pastures 0.10
Income wood Group 2* 9,984.4 14,977 Subsistence agriculture/deforested area 0.04
Income wood Group 3* 7,875.0 11,813 Groups
Areas in use Coffee Group 1 * 2.3 1.26 Group total 1/população 0.44
Areas in use Pasture Group 2 * 16.8 9.40 Group 2 / total population 0.40
Areas in use Coffee Group 2* 4.4 2.46 Group 3 / total population 0.07
Areas in use Pasture Group 3* 21.6 12.11 Subsistence agriculture / total population 0.79
Subsistence farming areas * 0.7 0.41
Areas of initial Capoeiras 230 230.3
Initial areas of native forest 240,033 241,748
Deforested initial 3,187 1,498
Areas of non-forest 4,073 4,073
Total area 247,845 247,845
Period comparison 2005-2009
* Mean values per Suruí family
• Model X historical “cumulative area cleared”• Least squares method for find the best fit
minimizing the sum of squares (payoff).
Model calibration
ParametersOriginal value
Less 80% of the
parameter
More 80% of the
parameter
Payoff min
Payoff max
Value parameter
(Payoff min)
Ratio of investment in productive activities to net family income [families earning R$5,000-10,000] combined with a ratio of investment in productive activities to net family income [families earning more than R$10,000] of 0.094
0.492 0.0984 0.8856 1.02 2.16 0.301
Ratio of investment in productive activities to net family income [families earning R$5000-10,000]
0.492 0.0984 0.8856 4.36 7.86 0.102
Ratio of investment in productive activities to net family income [families earning more than R$10,000]
0.228 0.0456 0.4104 1.11 42.45 0.094
Average Surui coffee profitability (R$ / year)
294 58.8 529.2 3.16 5.3 417.76
Average return on Surui livestock (R$ / year)
190.8 38.16 343.44 3.46 5.39 39.59
Birth rate multiplier 1 0.2 1.8 4.34 4.49 1.79
Mortality rate multiplier 1 0.2 1.8 4.34 4.49 1.79
Timber income multiplier 1 0.2 1.8 0.712 20.16 0.26
After model calibrationCumulative historical deforestation, observed and modeled between 2004 and 2009
Sensitivity of the Baseline Scenario
• Average profitability of leasing pasture land (R$/year): [11,133.9-21.145,5 hectares] 10,012.4 hectares,
• Birth rate coefficient multiplier [10,256.8- 18,154] 7,897.2 hectares,
• Average profitability of Surui-managed ranching (R$/year) [10,330.9-15,896.6] hectares 5,565.7 hectares,
• Ratio of investment in productive activities to net family income [families earning R$0-5000] [12,372.4- 15,101] 2,728.6 hectares.
Monte Carlo Sensitivity Analysis of Vensim PLE Plus
Baseline Scenario – Deforestation 2038
Accumulated: 13,575 haAverage: 452.5 ha/year
Spatial allocation
Baseline Projection
50% - Estado de Rondônia 50% - Estado de Mato Grosso
Integration with the National REDD+ Strategy
PCFS (tCO2)Sistema Estadual
REDD+ RO0 29.649.843,50 0 29.649.843,50 0 29.649.843,50
176.866,61 29.649.843,50 178.855,01 29.649.843,50 246.806,97 29.649.843,50 238.932,35 29.649.843,50 228.469,98 29.649.843,50 221.420,10 29.649.843,50 212.096,97 29.649.843,50 200.232,39 29.649.843,50 182.565,87 29.649.843,50 154.574,93 29.649.843,50 161.547,84 29.649.843,50 168.805,49 29.649.843,50
2.371.174,52 444.747.652,50 0,27%
PCFS (tCO2)Sistema Estadual
REDD+ MT0 81.833.568,17 0 81.833.568,17 0 81.833.568,17
176.866,61 81.833.568,17 178.855,01 81.833.568,17 246.806,97 81.833.568,17 238.932,35 81.833.568,17 228.469,98 81.833.568,17 221.420,10 81.833.568,17 212.096,97 81.833.568,17 200.232,39 81.833.568,17 182.565,87 81.833.568,17 154.574,93 81.833.568,17 161.547,84 81.833.568,17 168.805,49 81.833.568,17
2.371.174,52 1.227.503.522,55 0,10%
