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Rufino Informed sampling for targeting mitigation Nov 10 2014
The document discusses the informed sampling methods for assessing mitigation options in smallholder systems, emphasizing the importance of defining scale, boundaries, and addressing heterogeneity in landscapes. It outlines a structured approach to identify mitigation options at both farm and landscape levels, considering various environmental and social factors. Additionally, it highlights the necessity of collecting meaningful and cost-effective data to support these assessments.
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Rufino Informed sampling for targeting mitigation Nov 10 2014
- 1. Informed sampling fortesting mitigation options Mariana C. Rufino
- 2. SAMPLES Standard Assessment of Mi3ga3on Poten3al for Smallholder systems h8p://www.samples.ccafs.cgiar.org/
- 3. Three messages •Decide on what ma8ers, scale, boundaries • Address heterogeneity, don’t ignore it • Aim at low cost, but collect meaningful data
- 4. How to iden3fy mi#ga#on op#ons at farm and landscape level?
- 5. Complex landscape: f (i, j, k, l, m) i Landscape units j Farm types Physical environment Social and economic environment l Field types Local management Define project interven3on (LUC, hotspots) Income, tenure, food security GHG emissions, produc3vity, economics k Common lands m Land types
- 6. Complex landscape: f (i, j, k, l, m) i Landscape units j Farm types Physical environment Social and economic environment l Field types Local management k Common lands m Land types Top-‐ down
- 7. Complex landscape: f (i, j, k, l, m) i Landscape units j Farm types Physical environment Social and economic environment l Field types Local management k Common lands m Land types Bo8on -‐up
- 8. Which prac3ces and what benefits?
- 9. What ma8ers at landscape level? • Soils • Eleva3on gradients • Vegeta3on pa8erns
- 10. Top-‐down: first step Quickbird image, Lower Nyando, western Kenya
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- 14. What ma8ers at landscape level? • Soils • Eleva3on gradients • Vegeta3on pa8erns
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- 16. Mean NDVI Top-‐down: vegeta3on pa8ers 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 MODIS 3me series – Nyando, western Kenya
- 17. Slope (%) Top-‐down: slope
- 18. What ma8ers at landscape level? • Soils (too coarse, excluded) • Eleva3on gradients (DEM and slope) • Vegeta3on pa8erns (NDVI analysis)
- 19. Top-‐down: landscape units Landscape units: Vegeta3on pa8erns + eleva3on + slope
- 20. Which prac3ces and what benefits?
- 21. What ma8ers at farm and field level? • Crops, trees, livestock • Input use (fer3lisers, crop residues, water) • Produc3vity • Economics • Tenure
- 22. Complex landscape: f (i, j, k, l, m) i Landscape units j Farm types Physical environment Social and economic environment l Field types Local management k Common lands m Land types Bo8on -‐up
- 23. Top-‐down + bo8on up 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
- 24. Top-‐down + bo8on up Landscape units and land users -‐> basis for sampling
- 25. Field typology surveyDate: Surveyor: HH ID: ______________________ Name of respondent:___________________ PLOT LOCATION AND SIZE South_______________ East________________ Error________ Plot Subplot Subplot Subplot ID Area (m2) Land cover Photo ID Land tenure: Communal Rented Owned Does the farmer burn the plot? regularly sometimes never Agricultural practices Crops commonly planted in field Crop (e.g. Maize) Highest yields (local units) _________________ ___________________ _________________ ___________________ _________________ ___________________ Land cover prior to agriculture: Forest Grass or shrubland unknown How many years ago was it covered to agriculture (circle one): 0-‐2 2-‐5 5-‐10 >10 unknown Are fertilizers applied? Yes or No If yes, which sub-‐plot? __________________ YES, FERTILIZERS ARE APPLIED Type Amount Crop _______ ________ _________ _______ ________ _________ _______ ________ _________ _______ ________ _________ Woody cover (%) <4 4 -‐ 15 15 -‐ 40 40 -‐ 65 >65 Herbaceous cover (%): <4 4 -‐ 15 15 -‐ 40 40 -‐ 65 >65 Visible evidence of erosion Rill Sheet Gully none What is your best plot (or subplot) and why? Type (eg) UREA CAN MANURE AMOUNT = PER PLOT ID WHICH CROP Do animals graze the plot? regularly sometimes never Bo8on-‐ up: field characteris3cs
- 26. Bo8on-‐ up: field and farm, several indicators Farm type Field type Profit ($/ ha) Produc3on (kg/ha) Emissions (t CO2eq per ha) Emissions (kg CO2 per kg product) Social acceptability (ranking) 1 1 50 500 0.6 1.2 1 1 2 140 5000 3 0.6 2 1 3 120 2000 2 1.0 2 1 4 40 4500 3 0.7 1 2 1 30 800 0.7 0.9 3 2 3 180 8000 3 0.4 2 2 4 250 300 0.5 1.7 1 n m Vn,m Wn,m Xn,m Yn,m Zn,m
- 27. 1 2 34 5 4 8 12 land class CO2 emissions 1 2 3 4 5 −10 −4 0 Emissions data land class CH4 emissions 1 2 3 4 5 0.0 1.0 land class N2O emissions 1 2 3 4 8 12 land class CO2 emissions land class CH4 emissions 1 2 3 −10 −4 0 1 2 3 0.0 1.0 land class N2O emissions annuals grass trees/shrubs 4 8 12 land class CO2 emissions annuals grass trees/shrubs −10 −4 0 land class CH4 emissions annuals grass trees/shrubs 0.0 1.0 land class N2O emissions Highland Lowland Mid−slope 4 8 12 CO2 emissions Highland Lowland Mid−slope −10 −4 0 CH4 emissions Highland Lowland Mid−slope 0.0 1.0 N2O emissions Land%Class% Field%Type% Crop%Type% Landscape%Posi3on% CO2%Emissions%(T%ha:1)% CH4%Emissions%(kg%ha:1)% N2O%Emissions%(kg%ha:1)% Pelster et al. 2014 Top-‐down + bo8on up
- 28. How to iden3fy mi#ga#on op#ons at farm and landscape level?
- 29. Complex landscape: f (i, j, k, l, m) i Landscape units j Farm types Physical environment Social and economic environment l Field types Local management Define project interven3on (LUC, hotspots) Income, tenure, food security GHG emissions, produc3vity, economics k Common lands m Land types Top-‐down + bo8on up
- 30. Discussion • Decide on what ma8ers, scale, boundaries • Address heterogeneity: landscape units, farm types, field types, farming prac3ces • Aim at low cost, but collect meaningful data
- 31. Mariana C. Rufino,m.rufino@cgiar.org SAMPLES Standard Assessment of Mi3ga3on Poten3al for Smallholder systems h8p://www.samples.ccafs.cgiar.org/