Sustainable Intensification of Cereal-based Farming Systems in the Sudano-Sahelian Zone of West...

Sustainable Intensification of Cereal-based Farming Systems in the Sudano-Sahelian Zone of West Africa: Project Design Workshop, Tamale, Ghana, 9-12 January 2012

Overview• Broad M&E Guiding Principles• Recap on SI Program Targeting• Monitoring and Reporting Scales • Evaluation Approaches• Site Selection• M&E Data and Analysis Platform• Issues/Questions

M&E Guiding Principles• FtF Compliance: Conform to the overall FtF core indicator guidelines• Open-access platform: Maintain a transparent, open-access M&E

data management and analysis platform to serve the needs of SI stakeholders

• Multi-scale, Multi-site reporting: Meet broad stakeholder needs and support multi-scale/multi-site M&E through;– System and sub-system reports: e.g. rice, maize, sorghum-based for WA– Site-reports: for each of the three SI system sites– Country reports: Breakout of site reports to serve national stakeholder needs– SSA-reports: cross-system reporting and SI-wide “roll-up” of indicators across

the 3 “sites” (Sudano-Sahelian zone, Ethiopian Highlands, Eastern and Southern Africa)

• Backward & forward assessment: Provide monitoring reports and ex ante evaluations (projections) of key M&E indicators, updated annually

• Scaling-up and out assessments (evaluate spillover potential/ options): Examine the potential productivity and sustainability consequences of a range of adoption and geographic/system spillover pathways beyond actual implementation sites.

HH Attributes

Urban/Rural

Income/Exp

ConsumptionPatterns

Production SystemsInputs, Tech Adoption

MarketParticipation

Policy/Market Context & ImpactUsually geo-political/admin units (policies, institutions) as the unifying concept and object of analysis.Commodity focus

Fixed Geographies of Analysis

e.g., IMPACT/WATER,GTAP & derivatives

Flexible Geographies of Analysis

e.g., DREAM,MM models

MACRO

Household/Community CharacterizationCross-country data harmonization challenges. Livelihoods, Assets, Gender & Access Foci

MICRO

Production/Market Context & ImpactGridcells/pixels as units of analysis.Natural/Human landscape patterns as well as resource and product flows are unifying concepts and objects of analysis.Systems focus.

MESO

Production Systems

Ecosystems & ES Services

Infrastructure/Market Access

Demographics/Human Welfare

Linking Data & Analysis Across Scales

SSA Farming Systems

Source: Dixon el al. 2001

Selecting SIFocus Areas

PopulationDensity

GRUMP 2005


Poverty

Wood et al 2009(now replaced)


Cropland

Ramankutty et al(2008)


Time to >50K town

HarvestChoiceGuo 2010

CAADP:National

InvestmentPlans (NIPs)

CAADP:National


CAADP:National


CAADP:National


CAADP:National


SSA Research Programs

(CGIAR CRPs,SROs, NARS)

Identify and inventorize target;(1) geographies/agroecologies(2) farming systems(3) value chains

Using standardized descriptors

DEMANDCountries

(NIP needs described in terms of standard AES/Value chain components)

SUPPLYAgroecosystems/

Value chains(entry points for existing

technologies & knowledge & pipeline R&D)

Articulate, Review,and Finalize

Coherent RegionalAgroecosystem/

Value ChainSpatial Framework

SupplyGaps?

IntegratedM&E

IndicatorDatabase

Coordination/Institutional/Investment Needs and Options

Diagnosis: Intensification ChallengesIdentify challenges and potential intensification opportunities by system

Role of Farming Systems in Bridging CAADP-CGIAR Agendas(Dublin Process Activity)

Draft Conceptual Framework, November 2011

Eastern & Southern Africa Maize-based Systems

Ethiopian HighlandsSudano-Sahelian Zone

Systems

Sub-Systems

Country A

Country B

+

+ +++

+

ActionSites

6. Country to country barriers to spillover

SI Monitoring and Reporting Scales

Fostering Spillover by Design

1. Implementation sites to local sub-systems

2. Implementation to non-implementation sub-systems

3. Sub-systems to (sub-) systems

4. Systems to systems5. Sites to sites

& Spillover Needs& Spillover Needs

Evaluation Approaches•Delineation and characterization (typologies?) of target farming systems: Relies on the fusion of spatially-explicit agricultural production, environmental, and farm/household data, and a conceptual model of impact pathways/goals.•Maintain Technology/Intervention Inventory: A characterized inventory of the nature of the individual and integrated farming system components whose adoption and impacts is being evaluated. Includes characterization of spillover potential•Recursive Modeling of Projected Change (with and w/o interventions): e.g., productivity and income change, land, labour (sex differentiated) and water use•Attribution assessment: Additional to the ability to measure and model change in indicators is the need (with additional information/assumptions) to assess attribution of changes to an agreed level of specificity.

2015 20302011

2011 2013 2030

20142011 2030

Annual Evaluation of Past and Projected Impacts

Increase in productivity or revenue

Av. Daily Temperature(mean 1960-2000)

Northern GhanaSouthern Mali

WorldClim 2005

Rainfall(mean 1960-2000)


WorldClim 2005

NDVI(mean 2001-2010)


NDVI Variability


Population Density (2005)


AfriPop 2010

Travel Time to Towns >50K Population


HarvestChoice 2010

Cropland Intensity (2005)


Ramankutty et al 2008

Household Enterprise Choices

Proportion of Household (2005-2006)

<0.100

0.101 - 0.200

0.201 - 0.300

0.301 - 0.400

0.401 - 0.500

0.501 - 0.600

0.601 - 0.700

0.701 - 0.800

0.801 - 0.900

>0.900

Maize Producing Households

Rice Producing Households

Sorghum Producing Households

Proportion ofHouseholds

Source: HarvestChoice 2011 based on Ghana Living Standards Survey 2005

Proportion of Household (2005-2006)

< 0.050

0.051 - 0.100

0.101 - 0.200

0.201 - 0.300

> 0.030

Households Owning Cattle

Household Enterprise Choices (cont.)

Proportion ofHouseholds

Source: HarvestChoice 2011 based on Ghana Living Standards Survey 2005

National Northern Regions SI Focus Districts

Rank HH Crop EnterprisesHH

Share HH Crop Enterprises

HH Share

HH Crop EnterprisesHH

Share

1 maize 0.55maize,rice,millet,sorghum,beans

0.16 maize,rice,millet 0.15

2 maize,cocoa 0.15 maize 0.12maize,rice,millet,sorghum,beans

0.14

3 cocoa 0.11maize, millet,sorghum,beans

0.12 maize 0.13

4 maize,beans 0.06 maize,sorghum 0.08 maize, sorghum, beans 0.11

5maize,rice,millet,sorghum,beans

0.04 maize, millet, sorghum 0.07 maize, millet, sorghum 0.09

Ranking of HH Crop Enterprises: Ghana

Source: Derived from GLSS 2005

Note: Crops considered are maize, rice, millet, cassava, cocoa, cocoyam, beans, eggplant, sorghum, yam,

oilpalm, okra, oranges, pawpaw, pepper, pineapples, plantain, tomatoes, vegetables

01

0,00

02

0,00

0#

of h

ous

eho

lds

maiz

e,m

illet

maiz

e,so

rghu

m

maiz

e,ric

e,m

illet,b

eans

maiz

e, m

illet,s

orgh

um,b

eans

maiz

e,ric

e,m

illet,s

orgh

um

maiz

e, m

illet,

sorg

hum

maiz

e, so

rghu

m, b

eans

maiz

e

maiz

e,ric

e,m

illet,s

orgh

um,b

eans

maiz

e,ric

e,m

illet

focus districts# of households growing

*DSSAT Cropping System Model Ver. 4.0.2.000 May 21, 2009; 16:32:33

*RUN 1 : RAINFED LOW NITROGEN

MODEL : MZCER040 - MAIZE

EXPERIMENT : UFGA8201 MZ NIT X IRR, GAINESVILLE 2N*3I

TREATMENT 1 : RAINFED LOW NITROGEN

CROP : MAIZE CULTIVAR : McCurdy 84aa ECOTYPE :IB0002

STARTING DATE : FEB 25 1982

PLANTING DATE : FEB 26 1982 PLANTS/m2 : 7.2 ROW SPACING : 61.cm

WEATHER : UFGA 1982

SOIL : IBMZ910014 TEXTURE : - Millhopper Fine Sand

SOIL INITIAL C : DEPTH:180cm EXTR. H2O:160.9mm NO3: 2.5kg/ha NH4: 12.9kg/ha

WATER BALANCE : IRRIGATE ON REPORTED DATE(S)

IRRIGATION : 13 mm IN 1 APPLICATIONS

NITROGEN BAL. : SOIL-N & N-UPTAKE SIMULATION; NO N-FIXATION

N-FERTILIZER : 116 kg/ha IN 3 APPLICATIONS

RESIDUE/MANURE : INITIAL : 1000 kg/ha ; 0 kg/ha IN 0 APPLICATIONS

ENVIRONM. OPT. : DAYL= 0.00 SRAD= 0.00 TMAX= 0.00 TMIN= 0.00

RAIN= 0.00 CO2 = R330.00 DEW = 0.00 WIND= 0.00

SIMULATION OPT : WATER :Y NITROGEN:Y N-FIX:N PHOSPH :N PESTS :N

PHOTO :C ET :R INFIL:S HYDROL :R SOM :G

MANAGEMENT OPT : PLANTING:R IRRIG :R FERT :R RESIDUE:N HARVEST:M WTH:M

*SUMMARY OF SOIL AND GENETIC INPUT PARAMETERS

SOIL LOWER UPPER SAT EXTR INIT ROOT BULK pH NO3 NH4 ORG

DEPTH LIMIT LIMIT SW SW SW DIST DENS C

cm cm3/cm3 cm3/cm3 cm3/cm3 g/cm3 ugN/g ugN/g %

-------------------------------------------------------------------------------

0- 5 0.026 0.096 0.230 0.070 0.086 1.00 1.30 7.00 0.10 0.50 2.00

5- 15 0.025 0.086 0.230 0.061 0.086 1.00 1.30 7.00 0.10 0.50 1.00

15- 30 0.025 0.086 0.230 0.061 0.086 0.70 1.40 7.00 0.10 0.50 1.00

30- 45 0.025 0.086 0.230 0.061 0.086 0.30 1.40 7.00 0.10 0.50 0.50

45- 60 0.025 0.086 0.230 0.061 0.086 0.30 1.40 7.00 0.10 0.50 0.50

60- 90 0.028 0.090 0.230 0.062 0.076 0.05 1.45 7.00 0.10 0.60 0.10

90-120 0.028 0.090 0.230 0.062 0.076 0.03 1.45 7.00 0.10 0.50 0.10

120-150 0.029 0.130 0.230 0.101 0.130 0.00 1.45 7.00 0.10 0.50 0.04

150-180 0.070 0.258 0.360 0.188 0.258 0.00 1.20 7.00 0.10 0.50 0.24

TOT-180 6.2 22.2 45.3 16.1 21.4 <--cm - kg/ha--> 2.5 12.9 87080

SOIL ALBEDO : 0.18 EVAPORATION LIMIT : 2.00 MIN. FACTOR : 1.00

RUNOFF CURVE # :60.00 DRAINAGE RATE : 0.65 FERT. FACTOR : 0.80

MAIZE CULTIVAR :IB0035-McCurdy 84aa ECOTYPE :IB0002

P1 : 265.00 P2 : 0.3000 P5 : 920.00

G2 : 990.00 G3 : 8.500 PHINT : 39.000

*SIMULATED CROP AND SOIL STATUS AT MAIN DEVELOPMENT STAGES

RUN NO. 1 RAINFED LOW NITROGEN

CROP GROWTH BIOMASS CROP N STRESS DATE AGE STAGE kg/ha LAI kg/ha % H2O N ------ --- ---------- ----- ----- --- --- ---- ---- 25 FEB 0 Start Sim 0 0.00 0 0.0 0.00 0.00 26 FEB 0 Sowing 0 0.00 0 0.0 0.00 0.00 27 FEB 1 Germinate 0 0.00 0 0.0 0.00 0.00 9 MAR 11 Emergence 29 0.00 1 4.4 0.00 0.00 27 MAR 29 End Juveni 251 0.43 4 1.6 0.00 0.09 1 APR 34 Floral Ini 304 0.44 4 1.5 0.00 0.50









WEATHER : UFGA 1982









RAIN= 0.00 CO2 = R330.00 DEW = 0.00 WIND= 0.00








-------------------------------------------------------------------------------

0- 5 0.026 0.096 0.230 0.070 0.086 1.00 1.30 7.00 0.10 0.50 2.00

5- 15 0.025 0.086 0.230 0.061 0.086 1.00 1.30 7.00 0.10 0.50 1.00

15- 30 0.025 0.086 0.230 0.061 0.086 0.70 1.40 7.00 0.10 0.50 1.00

30- 45 0.025 0.086 0.230 0.061 0.086 0.30 1.40 7.00 0.10 0.50 0.50

45- 60 0.025 0.086 0.230 0.061 0.086 0.30 1.40 7.00 0.10 0.50 0.50

60- 90 0.028 0.090 0.230 0.062 0.076 0.05 1.45 7.00 0.10 0.60 0.10

90-120 0.028 0.090 0.230 0.062 0.076 0.03 1.45 7.00 0.10 0.50 0.10

120-150 0.029 0.130 0.230 0.101 0.130 0.00 1.45 7.00 0.10 0.50 0.04

150-180 0.070 0.258 0.360 0.188 0.258 0.00 1.20 7.00 0.10 0.50 0.24

TOT-180 6.2 22.2 45.3 16.1 21.4 <--cm - kg/ha--> 2.5 12.9 87080




P1 : 265.00 P2 : 0.3000 P5 : 920.00

G2 : 990.00 G3 : 8.500 PHINT : 39.000












WEATHER : UFGA 1982









RAIN= 0.00 CO2 = R330.00 DEW = 0.00 WIND= 0.00








-------------------------------------------------------------------------------

0- 5 0.026 0.096 0.230 0.070 0.086 1.00 1.30 7.00 0.10 0.50 2.00

5- 15 0.025 0.086 0.230 0.061 0.086 1.00 1.30 7.00 0.10 0.50 1.00

15- 30 0.025 0.086 0.230 0.061 0.086 0.70 1.40 7.00 0.10 0.50 1.00

30- 45 0.025 0.086 0.230 0.061 0.086 0.30 1.40 7.00 0.10 0.50 0.50

45- 60 0.025 0.086 0.230 0.061 0.086 0.30 1.40 7.00 0.10 0.50 0.50

60- 90 0.028 0.090 0.230 0.062 0.076 0.05 1.45 7.00 0.10 0.60 0.10

90-120 0.028 0.090 0.230 0.062 0.076 0.03 1.45 7.00 0.10 0.50 0.10

120-150 0.029 0.130 0.230 0.101 0.130 0.00 1.45 7.00 0.10 0.50 0.04

150-180 0.070 0.258 0.360 0.188 0.258 0.00 1.20 7.00 0.10 0.50 0.24

TOT-180 6.2 22.2 45.3 16.1 21.4 <--cm - kg/ha--> 2.5 12.9 87080




P1 : 265.00 P2 : 0.3000 P5 : 920.00

G2 : 990.00 G3 : 8.500 PHINT : 39.000




OUTPUTS/INDICATORS

Phenologyflowering dates

grain/seed/tuber maturity dates

Yieldsgrain/seed/tuber yieldsresidues/stover yields

total biomass yield

Growthgrain/seed/tuber, biomass, LAI

SoilN, C and H2O balances

0

1

2

3

4

5

6

7

8

9

10

0 50 100 150 200

Yield(t/ha)

Fertilizer (kg[N]/ha)

Cropping System Models as Means of Tracking & Forecasting Key Indicators

Source: Jawoo Koo (HarvestChoice 2010)

Potential Productivity Gains in Maize in Northern Ghana:Yield Responses by Region, Soil Response Class & Management

Intervention for Representative OPV and Hybrid Varieties

Potential Productivity Gains in Maize in Northern Ghana

M&E Implementation Strategy (to date)

• Establish Core FtF Monitoring Obligations: Primarily with USAID Washington (e.g., agree required core indicators and reporting timelines)

• Senior M&E Coordinator: IFPRI to recruit SI M&E Coordinator (Senior International Research position, likely based in Addis) with junior staff support in addition to DC-based team.

• M&E Implementation Alliance: Establish M&E community (esp. evaluation methods and tools) to finalize project M&E design, as well as guide, participate in and review M&E work plans and deliverables (composition, e.g., M&E specialist/liaison from involved CG centers, donor and national and regional partners).

• M&E Open-Access, Web-Based Platform: To host and make accessible SI M&E plans, documents, and annual reports, as well as background publications, underlying datasets and, wherever possible, analytical tools. Promote and apply standards for farming system, technology and impact characterization.

• Annual M&E Technical Meeting: Likely aligned with proposed Project-wide Annual meeting (Need for cross-site planning and review meetings?)

Issues/Questions• What is appropriate split of M&E resources

between M & E?• Scope of donor’s minimum indicator needs?• Project management versus strategic M&E

needs?• Roles of implementation partners versus M&E

team in collecting/analysing indicator data?• Do we need to re-examine the rationale for

specific focus sites and sub-systems?• Who will join the M&E Alliance/community?• Any likely candidates for M&E Coordinator?

Sustainable Intensification of Cereal-based Farming Systems in the Sudano-Sahelian Zone of West...

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