regional modelling for redd+ project development: the case of the suruí forest carbon project
DESCRIPTION
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.orgTRANSCRIPT
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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
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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
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Baseline Approaches
• Projecting historical average X modeling rates
• Regional modeling– Need local understand, identifying agents, drivers
and underlying causes
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Simamazonia I
Soares Filho et al. 2006
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Baseline construction
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Project Boundaries
208,039 ha
3,416.6 ha31,994ha
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Suruí people identified as the sole agents of deforestation.
– Control over the Territory– Logging agreements– Lease pastures and
sharecropping systems
Baseline Scenario - Agents
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– Cash income from external actors (logging, sharecropping and pasture leasing)
– Population growth– Increased labor available
Baseline Scenario - Drivers
Average:157.4 ha/year
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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).
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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
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SIMSURUI Causal diagram
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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 - -
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Economic dynamics of the productive agent groups
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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%
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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
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• 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
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After model calibrationCumulative historical deforestation, observed and modeled between 2004 and 2009
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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
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Baseline Scenario – Deforestation 2038
Accumulated: 13,575 haAverage: 452.5 ha/year
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Spatial allocation
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Baseline Projection
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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%