Your SlideShare is downloading. ×
Mariana Rufino 2013: Identifying Pro-Poor Mitigation Options for smallholder agriculture in the developing world
Upcoming SlideShare
Loading in...5
×

Thanks for flagging this SlideShare!

Oops! An error has occurred.

×
Saving this for later? Get the SlideShare app to save on your phone or tablet. Read anywhere, anytime – even offline.
Text the download link to your phone
Standard text messaging rates apply

Mariana Rufino 2013: Identifying Pro-Poor Mitigation Options for smallholder agriculture in the developing world

3,837
views

Published on

The goal for pro-poor mitigation activity, is to develop a low-cost protocol to quantify greenhouse gas emissions and to identify mitigation options for smallholders at whole-farm and landscape …

The goal for pro-poor mitigation activity, is to develop a low-cost protocol to quantify greenhouse gas emissions and to identify mitigation options for smallholders at whole-farm and landscape levels. Learn more: www.ccafs.cgiar.org

Published in: Education

0 Comments
0 Likes
Statistics
Notes
  • Be the first to comment

  • Be the first to like this

No Downloads
Views
Total Views
3,837
On Slideshare
0
From Embeds
0
Number of Embeds
9
Actions
Shares
0
Downloads
26
Comments
0
Likes
0
Embeds 0
No embeds

Report content
Flagged as inappropriate Flag as inappropriate
Flag as inappropriate

Select your reason for flagging this presentation as inappropriate.

Cancel
No notes for slide

Transcript

  • 1. Identifying pro-poor mitigation options forsmallholder agriculture in the developing world:a multi-criteria and across-scales assessmentMariana Rufino, Todd Rosenstock, Lini Wollenberg, Klaus Butterbach-Bahl
  • 2. • Why multiple scales?• Why multi-criteria?
  • 3. The concerns• Mitigation not linked to livelihoods• Fragmented and diverse landscapes• No data on mitigation• Multi-criteria approaches missing
  • 4. The goalDevelop a low-cost protocol to quantify greenhouse gasemissions and to identify mitigation options forsmallholders at whole-farm and landscape levels
  • 5. How to identify mitigation options at farm andlandscape level?
  • 6. Phase I: Targeting, priority setting and infrastructure Landscape analysis Set-up of state-of-the-art and targeting laboratory facilities Landscape implementation Training of laboratory and field staff Capacity buildingPhase II: Data acquisition Productivity GHG Profitability Social acceptability assessment measurements evaluation assessment Joint scientific & stakeholderPhase III: Multi-dimensional evaluation of evaluationDevelopment of systems-level mitigation optionsmitigation options System-level estimation of mitigation potentialPhase IV:Implementation with Scalable and social acceptable (UPCOMING)development partners mitigation options
  • 7. GIS analysis, Complex landscape: f (m, n, o, p, q) remote sensing, landuse trends Physical environment m Landscape units Land Food Livestock security, poverty Other assets n Farm types o Common lands Sources of levels incomesProductivity, GHG Characterise emissions, fertility x p Field types q Land types crop managementpreferences
  • 8. LandscapepatternsNyando,westernKenya
  • 9. Cultivated (subsistence)Cultivated (cash crops) id 15id 11 Mixed id 2 Landscape patterns simplified
  • 10. LandscapestructureNyando,westernKenya
  • 11. 2001 2002 2003 2004 Mean NDVI2005 2006 2007 20082009 2010 2011 2012 MODIS time series – Nyando, western Kenya
  • 12. NDVI across landscape units (Timesat) Nyando, western Kenya Baldi et al. 2013
  • 13. Landscapeunits +householdsurveyNyando,westernKenya
  • 14. Landscape units andland users Sampling intensity (sites: area) In terms of a 250 m square grid class sites area (km2) sites:area cultivated (cash and subsistence) 28 2.74 10.23 cultivated (cash) 47 5.94 7.91 cultivated (grasslands and pastures) 47 12.69 3.70 cultivated (subsistence) 141 41.54 3.39 mixed 93 34.69 2.68 uncultivated vegetation 4 2.39 1.67
  • 15. Landscape units and landusersNyando, Kenya
  • 16. GIS analysis, Complex landscape: f (m, n, o, p, q) remote sensing, landuse trends Physical environment m Landscape units Land Food Livestock security, poverty Other assets n Farm types o Common lands Sources of levels incomesProductivity, GHG Characterise emissions, fertility x p Field types q Land types crop managementpreferences
  • 17. Targeting and upscaling: fromlandscape to fields and back…
  • 18. Step 1. Landscape analysis Targeting: - Landscape units, farm types, field types, soils - Site selectionStep 2. Installing measurement stations Site characterization: - Soils, crops, biomass Installation of Informing and chamber frames interviewing farmers
  • 19. Step 3. Measurements applying gas pooling Field work: - Overcoming spatial variability by gas pooling method Gas sampling(closed Storage of gasArias-Navarro et al., Soil Biol. Biochem. submitted chamber method) samples in vialsStep 4. Lab analysis and flux calculations Determination of trace Lab work: gas concentrations via - Analyzing gas samples gas chromatography - Calculating concentrations and fluxes Flux b * Mw * VCh * 60 * 106 calculation F formula ACh * Vm * 109
  • 20. Step 5. Intepretation and 500 250 Forest individual chambers gas pooling upscaling 100 75 50 N2O flux [µg N m h ] -1 25 0 -2 500 Grassland 250 100 75 Temporal variability of N2O 50 25 fluxes at three sites 0 500 differing in land use at 250 Cropland Maseno, Kenya. 100 75 50 25 0 30 Oct 4 Nov 9 Nov 14 Nov 19 Nov 24 Nov 29 Nov 2012 Arias-Navarro et al., Soil Biol. Biochem. submitted Synthesis of GHG measurements: information useful to derive emission factors, empirical models, calibrating and validating of detailed models Upscaling: using the targeting approach (assigning emissions to landscape elements) and/or of GIS coupled biogeochemical models
  • 21. GIS analysis, Complex landscape: f (m, n, o, p, q) remote sensing, landuse trends Physical environment m Landscape units Land Food Livestock security, poverty Other assets n Farm types o Common lands Sources of levels incomesProductivity, GHG Characterise emissions, fertility x p Field types q Land types crop managementpreferences
  • 22. Multi-dimensional assessment of mitigation optionsFarm Field Profit Production Emissions Emissions Social acceptabilitytype type ($/ha) (kg/ha) (t CO2eq (kg CO2 per (ranking) per ha) kg product)1 1 50 500 0.6 1.2 11 2 140 5000 3 0.6 21 3 120 2000 2 1.0 21 4 40 4500 3 0.7 12 1 30 800 0.7 0.9 32 3 180 8000 3 0.4 22 4 250 300 0.5 1.7 1n m Vn,m Wn,m Xn,m Yn,m Zn,m Trade-off analysis on multiple dimensions
  • 23. Phase I: Targeting, priority setting and infrastructure Landscape analysis Set-up of state-of-the-art and targeting laboratory facilities Landscape implementation Training of laboratory and field staff Capacity buildingPhase II: Data acquisition Productivity GHG Profitability Social acceptability assessment measurements evaluation assessment Joint scientific & stakeholderPhase III: Multi-dimensional evaluation of evaluationDevelopment of systems-level mitigation optionsmitigation options System-level estimation of mitigation potentialPhase IV:Implementation with Scalable and social acceptable (UPCOMING)development partners mitigation options
  • 24. • Why multiple scales? -> landscape redesign• Why multi-criteria? -> landusers are (often) poor
  • 25. Thanks for your attentionm.rufino@cgiar.org

×