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David Landholm
Prajal Pradhan
Desiree Door
Wei Weng
Jurgen Kropp
(PIK)
01-03 March
Cali, Colombia
GHG mitigation potential
through sustainable
land use change
Colombia and Peru contribute 0,46 and 0,3% to global GHG emissions
GHG Reduction commitment: 20% of BAU by 2030 (30%?)
> 50% Colombia and Peru GHG emissions are from AFOLU sectors
Introduction: context
Source: iNDCs (2015)
Objectives
1. Characterize carbon emissions performance of identified systems (extensive,
silvopastoral, agroforestry)
2. Quantify emissions reduction of proposed sustainable changes within these
systems
3. Up-scale mitigation potential of sustainable LU changes
• SAL project (1)
• Secondary data (2)
CO2 sinks and sources
Systems characterization
Carbon pools
Land use change
Farming practices
Firewood extraction, tree extraction for timber, use of fire, fertilizers (production,
soils), livestock (enteric fermentation, feed, manure), transport
Crops
Pasture
Livestock
Fertilization, productivity, use of manure, etc.
Population numbers; feed supplementation; manure
management
Secondary
data, Emission
factors
Survey data Farming practicesFarming practices
Productivity, seeds, use of fire, cover crops, fertilizer,
pesticides, herbicides, harvest, transportation, etc.
Results expression: functional unit (FU)
• Pros: useful for comparison across different
farming systems (that produce the same output)
• Cons: referring GHG emissions to certain products
must account for multi-functionality of livestock
• Pros: easier for comparison of systems that produce
different outputs
• Cons: doesn’t account for efficiency of production
(i.e. how it affects land use change elsewhere)
Products Farm (ha)
 Land use change: survey
 Agriculture practices: crops
 Inputs: fertilizers, herbicides, etc
 Soil management (e.g. till/no till)
 Transport
 Other: e.g. use of fire
 Agriculture practices: livestock
 Population charact.
 Feed charact.
 Pasture
? Carbon pools
 Soil; woody biomass
? Integrate forest land use
? Up-scaling
landholm@pik-potsdam.de
 GHG accounting of local farming systems
 What bigger picture can we learn from this project? How can we link it to
Colombia’s national goals -INDCs/NDCs? (Other mechanisms, e.g. REDD+)
 Interested in integrating other land uses in GHG assessment, e.g. forest
 Role of Silvopastoral and Agroforestry Systems in forest/landscape
connectivity
Summary of research interests within SAL
Collaborations with project members
• Soil and woody biomass carbon stocks -> Paul Peters (CIAT), Jaime Barrera
(SINCHI), others?
• Secondary data and possibilities for upscaling: Ricardo González, Jacobo
Arango (CIAT), Miguel Romero (CIAT), others projects? (e.g. LIVESTOCK+?)
• Terra-i team? (e.g. GHG of deforestation, forest fragmentation)
• Others?
landholm@pik-potsdam.de

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5. Presentación corta: GHG mitigation potential through sustainable land use change

  • 1. David Landholm Prajal Pradhan Desiree Door Wei Weng Jurgen Kropp (PIK) 01-03 March Cali, Colombia GHG mitigation potential through sustainable land use change
  • 2. Colombia and Peru contribute 0,46 and 0,3% to global GHG emissions GHG Reduction commitment: 20% of BAU by 2030 (30%?) > 50% Colombia and Peru GHG emissions are from AFOLU sectors Introduction: context Source: iNDCs (2015)
  • 3. Objectives 1. Characterize carbon emissions performance of identified systems (extensive, silvopastoral, agroforestry) 2. Quantify emissions reduction of proposed sustainable changes within these systems 3. Up-scale mitigation potential of sustainable LU changes • SAL project (1) • Secondary data (2)
  • 4. CO2 sinks and sources
  • 5. Systems characterization Carbon pools Land use change Farming practices Firewood extraction, tree extraction for timber, use of fire, fertilizers (production, soils), livestock (enteric fermentation, feed, manure), transport
  • 6. Crops Pasture Livestock Fertilization, productivity, use of manure, etc. Population numbers; feed supplementation; manure management Secondary data, Emission factors Survey data Farming practicesFarming practices Productivity, seeds, use of fire, cover crops, fertilizer, pesticides, herbicides, harvest, transportation, etc.
  • 7. Results expression: functional unit (FU) • Pros: useful for comparison across different farming systems (that produce the same output) • Cons: referring GHG emissions to certain products must account for multi-functionality of livestock • Pros: easier for comparison of systems that produce different outputs • Cons: doesn’t account for efficiency of production (i.e. how it affects land use change elsewhere) Products Farm (ha)
  • 8.  Land use change: survey  Agriculture practices: crops  Inputs: fertilizers, herbicides, etc  Soil management (e.g. till/no till)  Transport  Other: e.g. use of fire  Agriculture practices: livestock  Population charact.  Feed charact.  Pasture ? Carbon pools  Soil; woody biomass ? Integrate forest land use ? Up-scaling landholm@pik-potsdam.de
  • 9.  GHG accounting of local farming systems  What bigger picture can we learn from this project? How can we link it to Colombia’s national goals -INDCs/NDCs? (Other mechanisms, e.g. REDD+)  Interested in integrating other land uses in GHG assessment, e.g. forest  Role of Silvopastoral and Agroforestry Systems in forest/landscape connectivity Summary of research interests within SAL
  • 10. Collaborations with project members • Soil and woody biomass carbon stocks -> Paul Peters (CIAT), Jaime Barrera (SINCHI), others? • Secondary data and possibilities for upscaling: Ricardo González, Jacobo Arango (CIAT), Miguel Romero (CIAT), others projects? (e.g. LIVESTOCK+?) • Terra-i team? (e.g. GHG of deforestation, forest fragmentation) • Others? landholm@pik-potsdam.de