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Alto Mayo Protected Forest REDD Initiative, Peru
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Alto Mayo Protected Forest REDD Initiative, Peru

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To measure the success of REDD (Reducing Emissions from Deforestation and forest Degradation), it is crucial to first set baseline emissions from which the reduction can be measured in each project or …

To measure the success of REDD (Reducing Emissions from Deforestation and forest Degradation), it is crucial to first set baseline emissions from which the reduction can be measured in each project or region. In this presentation, Fabiano Godoy from Conservation International shared experiences with applying the VCS VM0015 model in the Alto Mayo protected forest of Peru in order to set baseline emissions.

Fabiano Godoy 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. Credible baseline setting and accurate and transparent Measurement, Reporting and Verification (MRV) of results are key conditions for successful REDD+ projects. 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

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  • 1. Alto Mayo Protected Forest REDD Initiative Peru Fabiano Godoy March- 2012 Photo 1 Photo 2 4.2” x 10.31” 5.51” x 10.31” Position Positionx: 4.36”, y: .18” x: 8.53”, y: .18”
  • 2. REDD initiative profileAlto Mayo Protected Forest – Department San Martin –Peru National protected area with highest deforestation rate in Peru (0.34% yr-1) ~ 5000 families live within the AMPF AMPF size: 182,000 ha project start date: 2008 main threat: forest conversion to coffee plantation co-benefit: provision of water supply strategy: capacity building and incentives to improve coffee production through conservation agreements
  • 3. Major Steps and Inputs – VM0015 1996 Trans. Potent. 2001 2006 2020Historical Land change CO2 emissiondeforestation modeling reductions Ref area Elevation Spatial boundaries Carbon map tC ha-1 Dist to roads Drivers of deforestation Defor rate
  • 4. Historical land cover and changeIn-house processing Image acquisition - Landsat 5 & 7 1996-2001-2006 (path-row 8-64 and 9-64) Interpretation and classification Ortho, cloud removal Decision tree algorithm (See5-ERDAS) Forest, non-forest, cloud and water Post-processing and map accuracy MMU 2ha Field visit – high resolution satellite images – aerial photos accuracy 92% forest-non forest
  • 5. Spatial BoundariesSpatial BoundariesProject Area forested area inside AMPF 153, 929 haReference Region similarity with project area same drivers & agents of deforestationLeakage Belt mobility analysis MCE Fuzzy based on hist deforestation
  • 6. Carbon Pools Included / TBD / Carbon pools Justification / Explanation of choice Excluded Represents the pool where the greatest carbon stock change will Above-ground tree included occur. The baseline land use in the project area is conversion of forest Above-ground non-tree included to perennial crops (coffee), therefore the carbon stock in this pool is likely to be relatively large compared to the project scenario. Recommended by the methodology as it usually represents Below-ground included between 15% and 30% of the above-ground biomass. Conservatively excluded (the carbon stock in this pool is not Dead wood excluded expected to be higher in the baseline compared to the project scenario). Under the baseline scenario, illegal selective logging occurs in Harvested wood products excluded very small scale and, therefore, harvested wood products have been considered insignificant. Not to be measured according to the latest VCS AFOLU Litter excluded Requirements (version 3.0). The baseline land-use of the project area is conversion of forest to perennial crop (coffee) followed by conversion to pasture. The Soil organic carbon excluded soil organic carbon is not to be measured in such cases according to the latest VCS AFOLU Requirements (version 3.0).
  • 7. Sources of GHG emissions Sources Gas Included/ excluded Justification / Explanation of choice CO2 Excluded counted as carbon stock change The major baseline activity is conversion of forest to conventional coffee plantation using slash and burn techniques. The project aims to reduce this Biomass activity by providing technical assistance to CH4 Excluded burning establish sustainable, shade-grown organic coffee plantations and therefore, the non-CO2 emissions related to biomass burning are conservatively excluded. N2 O Excluded See above explanation. Raising livestock is not a widespread baseline activity and the AMCI project will not promote the CO2 Excluded raising of livestock or result in an increase of this Livestock activity compared to the baseline. Therefore, emissions livestock emissions are conservatively excluded. CH4 Excluded See above explanation. N2 O Excluded See above explanation.
  • 8. Drivers and Agents of Deforestation Identify the main drivers of deforestation, the agents and the underlying causes compilation of relevant scientific publications + public consultation Drivers of deforestation conversion to coffeeplantation conversion to pastureland conversion to agriculture ofsubsistence conversion to infrastructure clearance to illegal land trade illegal logging
  • 9. Drivers and Agents of Deforestation
  • 10. Drivers and Agents of Deforestation Identify the main drivers of deforestation, the agents and the underlying causes Map the threat distribution Understand the deforestation dynamic and provide a comprehensive list of variables tobe used in the modeling of future deforestation Past Future
  • 11. Deforestation Rate The major drive of deforestation in the project area is conversion to coffee plantation deforestation rate was model as function of coffee production over time. direct correlation between deforestation and coffee production in the past constant (increasing) coffee production (1996-2007) coffee production do not follow the price trends Deforestation as function of Coffee Production (in Rioja, Moyobamba and Huallaga proportional to reference area) 5.000 deforestation as y = 0,1188x - 36,338 4.000 function of coffee R² = 0,9417 production 3.000 Linear 2.000 (deforestation as function of coffee 1.000 production) - Annual Coffee Production in Rioja + Moyobamba + 0 10.000 20.000 30.000 40.000 Huallaga Coffee Price in Peru (proportional to reference area)16.000 1996-2001 & 2001-2006 300014.000 y = 604,47x - 1.200.357,57 R² = 0,86 250012.000 Annual Coffee10.000 Production 2000 8.000 Linear 1500 (Annual 6.000 Coffee 1000 4.000 Production) 2.000 500 0 0 1995 2000 2005 2010 1996 1998 2000 2002 2004 2006 2008
  • 12. LCM Tool Concept – IDRISI Taiga 2006 actual 1996 2001 Land Cover 1996 Land Cover 2001 Land Cover 2006 NO Drivers Change 96-01 2006 proj Validation Change 96-01 Land Proj. 2006 YES Suit. Map Trans. Potential Modeling Suitab. Map 2020 2025 2030 Elevation Land Proj 2012 Elevation 2020 2040 Dist to villages Dist. Villages Dist to roads Dist. Roads Input Output Process
  • 13. Projected DeforestationTransition Potential Map(Neural network) Model future land use changeP-FOM = 60% cloud forest= 8% pre montane
  • 14. Carbon Mapbased on forest classification 89% cloud forest (1000-2500masl) 7% pre montane forest (below 1000masl) 4% dwarf forest (above 2500masl) biomass measurement 107 plots above ground biomass root to shoot ratio weighted-area average non-forest Next Steps - REDD project is under VCS validation currently addressing the findings (NIR, CAR) verification (monitoring report 2008-2011) by Sept CCBS validation and verification by December
  • 15. Photo 1 Photo 2 4.2” x 10.31” 5.51” x 10.31” Position Positionx: 4.36”, y: .18” x: 8.53”, y: .18”

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