Rufino Informed sampling for targeting mitigation Nov 10 2014

Informed sampling for testing

mitigation options

Mariana C. Rufino

SAMPLES

Standard Assessment of Mi3ga3on Poten3al for

Smallholder systems

h8p://www.samples.ccafs.cgiar.org/

Three messages

•  Decide on what ma8ers, scale, boundaries

•  Address heterogeneity, don’t ignore it •  Aim at low cost, but collect meaningful data

How to iden3fy mi#ga#on op#ons at farm and landscape level?

Complex landscape: f (i, j, k, l, m)

i Landscape units

j Farm types Social and economic

environment

l Field types Local management

Physical environment

Define project

interven3on (LUC,

hotspots)

Income, tenure, food security

GHG emissions, produc3vity, economics

k Common lands

m Land types


i Landscape units


environment



k Common lands

m Land types

Top-‐down


i Landscape units


environment



k Common lands

m Land types Bo8on-‐up

Which prac3ces and what benefits?

What ma8ers at landscape level?

•  Soils •  Eleva3on gradients •  Vegeta3on pa8erns

Top-‐down: first step

Quickbird image, Lower Nyando, western Kenya

Top-‐down: zooming in

Top-‐down: eleva3on gradient?

Top-‐down: eleva3on gradient


•  Soils •  Eleva3on gradients •  Vegeta3on pa8erns

Top-‐down: soil types

Mean NDVI 2001 2002 2003 2004

2005 2006 2007 2008

2009 2010 2011 2012

MODIS 3me series – Nyando, western Kenya

Top-‐down: vegeta3on pa8ers

Slope (%)

Top-‐down: slope


•  Soils (too coarse, excluded) •  Eleva3on gradients (DEM and slope)

•  Vegeta3on pa8erns (NDVI analysis)

Top-‐down: landscape units

Landscape units: Vegeta3on pa8erns + eleva3on + slope

Which prac3ces and what benefits?

What ma8ers at farm and field level?

•  Crops, trees, livestock •  Input use (fer3lisers, crop residues, water) •  Produc3vity •  Economics

•  Tenure


i Landscape units


environment



k Common lands

m Land types Bo8on-‐up

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


Landscape units and land users -‐> basis for sampling

Field typology survey Date:Surveyor:

HH ID: ______________________ Name of respondent:___________________PLOT LOCATION AND SIZESouth_______________ East________________ Error________

Plot Subplot Subplot SubplotID

Area (m2)

Land cover

Photo ID

Land tenure: Communal Rented Owned

Does the farmer burn the plot? regularly sometimes never

Agricultural practicesCrops commonly planted in fieldCrop (e.g. Maize) Highest yields (local units)_________________ ____________________________________ ____________________________________ ___________________

Land cover prior toagriculture: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 APPLIEDType 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)UREACANMANUREAMOUNT = PER PLOTID WHICH CROP

Do animals graze the plot? regularly sometimes never

Bo8on-‐ up: field characteris3cs

Farmtype

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

Bo8on-‐ up: field and farm, several indicators

1 2 3 4 5

48

12

land class

CO2

emiss

ions

1 2 3 4 5

−10

−40

Emissions data

land class

CH4

emiss

ions

1 2 3 4 5

0.0

1.0

land class

N2O

em

issio

ns

1 2 3

48

12

land class

CO2

emiss

ions

1 2 3−1

0−4

0land class

CH4

emiss

ions

1 2 3

0.0

1.0

land class

N2O

em

issio

ns

annuals grass trees/shrubs

48

12

land class

CO2

emiss

ions


−10

−40

land class

CH4

emiss

ions


0.0

1.0

land class

N2O

em

issio

nsHighland Lowland Mid−slope

48

12CO

2 em

issio

ns

Highland Lowland Mid−slope

−10

−40

CH4

emiss

ions

Highland Lowland Mid−slope0.

01.

0N2

O e

miss

ions

Land%Class%

Field%Type%

Crop%Type%

Landscape%Posi3on%

CO2%E

missions%(T

%ha:

1 )%

CH4%Em

issions%(kg%ha

:1)%

N2O

%Emissions%(kg%ha

:1)%

Pelster et al. 2014


How to iden3fy mi#ga#on op#ons at farm and landscape level?


i Landscape units


environment



Define project

interven3on (LUC,

hotspots)

Income, tenure, food security

GHG emissions, produc3vity, economics

k Common lands

m Land types


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

Mariana C. Rufino, [email protected]

SAMPLES Standard Assessment of Mi3ga3on Poten3al for Smallholder systems h8p://www.samples.ccafs.cgiar.org/

Rufino Informed sampling for targeting mitigation Nov 10 2014

Science

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