CCAFS Seminar on Science to Deliver Adaptation and Mitigation in East African Agriculture

Science to Deliver Adaptation and Mitigation
in East African Agriculture
CCAFS Science Seminar
JVC Auditorium, ILRI Nairobi – Kenya
2:00 -5:30 p.m.

Laura Cramer and Philip Thornton
Vision for CCAFS Phase II

Overview
• Highlights of CCAFS Phase I
• CCAFS Phase II
 Outcomes and targets
 Impact pathway and theory of change
 Flagships and Gender and Social Inclusion
 Regions and Regional Program Leaders
 Cross-scale activities
• East Africa portfolio

Highlights of CCAFS Phase I
(2011 – 2016)
• Scaling up tailored seasonal advisories (Senegal, Colombia,
Honduras)
• Development of the Climate Smart Village concept
• Scenario building and use in policy processes (outcomes in 9
countries)
• Index insurance for crops, livestock and floods trialed in 6 countries
• Use of science to inform climate investments worth > $350 million
• Engagement in UNFCCC processes and partnership with the
World Business Council for Sustainable Development
• Gender and social inclusion toolbox adopted by partners
• Inclusion of CGIAR research in IPCC 2014 report
• Open access climate data and methods for estimating smallholder
emissions used by thousands of researchers

CCAFS Phase II overview
• CGIAR System Level Outcomes:
 Reducing poverty: target is to have 11 million farm households adopt
CSA by 2022; assist 9 million people (50% of whom are women) to exit
poverty
 Improving food and nutrition security for health: remove nutritional
deficiencies of one or more essential micronutrients in 6 million people
(50% of whom are women) by 2022
 Improving natural resource systems and ecosystem services:
contribute to reduce ag-related GHG emissions by 160 Mt CO2e per
year by 2022 comparted to business-as-usual scenario

CCAFS Phase II Impact Pathway and
Theory of Change
• To be achieved through strong partnerships:
 Regional bodies (AU, NEPAD, ECOWAS, COMESA, APAN, CAC,
ECLAC, IICA)
 National agricultural research services and meteorological services
 International and local NGOs
 Other CRPs (PIM, A4NH, FTA, etc.)
 Universities (Wageningen University and Research Centre, Lancaster
University, etc.)
 Global bodies (UNFCCC, FAO, WFP, etc.)
• Capacity building
• Gender and social inclusion
• Monitoring, evaluating, and learning

CCAFS Flagships
• FP1: Priorities and Policies for CSA, Philip Thornton
• FP2: Climate Smart Technologies and Practices, Andy Jarvis
• FP3: Low Emissions Development, Lini Wollenberg
• FP4: Climate Services and Safety Nets, Jim Hansen
• Cross-cutting: Gender and Social Inclusion, Sophia Huyer

CCAFS Regions and RPLs
Latin America
Ana Maria
Loboguerrero
West Africa
Robert
Zougmore
South Asia
Pramod
Aggarwal
East Africa
Dawit
Solomon
Southeast Asia
Leocadio
Sebastian

Communication, Gender and Social Inclusion, Capacity Strengthening
Center led RPL led Bilateral
Develop Index insurance for
drought-prone maize and
bean-based farming systems
in East & West Africa
(CIMMYT - 2018)
Mitigation in livestock and
LED pathways + SAMPLES
coordination
(ILRI/CIFOR – 2018)
Influencing and linking policies
and institutions from national to
local level for the development
and adoption of climate-resilient
food systems (IITA/CIAT – 2017)
Partnerships for scaling climate-
smart agriculture (P4S-CSA)
(CIAT/ICRAF – 2018)
East Africa NAMA for Dairy
Development with UNIQUE
(ICRAF - 2018)
Design of Kenya County Climate Risk
Profiles (MoA) - CIAT
Climate Smart Agriculture Country Profiles
Africa – CIAT (WB – US)
Surveillance of Climate-smart Agriculture for
Nutrition – ICRAF
Tanzania Climate Smart Agriculture
Reference/Learning Sites (ICRAF-USDA)
Strengthening Capacity in Tanzania to
Implement Agriculture Climate Resilience
Actions (USDA) - ICRAF
Feasibility of using mobile phones to
monitor nutrition outcomes (WFP – Italy) –
ICRAF
Enhancing climate-resilience of Agricultural
Livelihoods (USAID)
Policy Action for Sustainable Intensification
of Ugandan Cropping Systems (Netherlands
Embassy - Uganda)
Climate smart coffee and cocoa: from theory
to practice (BMZ – Germany)
Greening Livestock: Incentive-based
interventions for reducing the climate
impact of livestock in East Africa -
ILRI (IFAD)
In situ assessment of GHG emissions
from two livestock systems in East
Africa (BMZ)
Climate Services for Agriculture:
Empowering Farmers to Manage Risk
and Adapt to a Changing Climate in
Rwanda – CIAT (USAID)
Local Governance and Adapting to Climate
Change in Sub-Saharan Africa (LGACC) -
ILRI
Climate Services for Africa – ILRI
(USAID)
Analyzing the science-policy-
practice interface in climate change
adaptation in EA & WA
(ILRI – 2017)
Bringing CSA practices to
scale: assessing their
contributions to narrow
nutrient and yield gaps -
(WUR - 2019)
Production and use of biochar, compost and lime as component of ISFM and
sustainable land use (Austria) – IITA
N2Africa - Putting nitrogen fixation to work
for smallholder farmers in Africa
(BMGF – US) – IITA
Mitigating Drought Impacts in Southern
Mozambique through Resilient, Nutritious
Sweet potato (USAID) – CIP
Regional and national engagement, synthesis and strategic research
CCAFS East Africa Portfolio, 2017-2018

• Scenario-based policy reviews
• Tanzania National Environment Policy
• Ugandan Agriculture Sector Strategic Plan
• Climate change mainstreaming guidelines
for the agricultural sector, Uganda
• Generating more evidence to feed policy
decision making
• Multi-stakeholder platforms
• Joint learning
• Adaptation planning
• Engaging policy decision makers
• Engagement with policy decision-makers
Ampaire et al. (2017)
From Scenarios to Policy Planning in East
Africa

Incubating a Promising
Financial Solution for the Drylands:
Toward Sustainable Index-Based Livestock Insurance (IBLI) for
Pastoralists
CCAFS Science Seminar, May 30th ILRI Nairobi
Science to Deliver Adaptation and Mitigation in East African
Agriculture

Insurance as a Development Tool
• Decades of evidence exist that risk
• Makes people poor by reducing incomes & destroying
assets: and,
• Keeps people poor , by discouraging investment &
distorting patterns of asset accumulation
• The arid pastoral regions of Northern Kenya, and
Southern Ethiopia are an archetype of risk & coping
• Development impacts of risk reduction technologies
(insurance) should therefore be significant.
• Index-based livestock insurance (IBLI) – an innovative
insurance product leveraging satellite data to estimate
livestock losses – first deployed as a pilot in 2010.

Insurance as a Development Tool
THE IBLI R&D CHALLENGE
Can index-based insurance make a significant and sustainable
contribution to the challenge of helping pastoralists manage the
considerable risk of drought-related livestock losses they face?

IBLI Program Summary
• IBLI R&D agenda, supported by a range of donors, has been comprehensive and
contributed to catalyzing a nascent but growing industry.
• Program launched in 2008 to offer a timely, sustainable, safety net against
catastrophic drought shocks on pastoralists.
• 2011 drought triggered contracts in all covered areas serving as an important proof-
of-concept indicator.
• 2012 initial pilot launch in Southern Ethiopia. 2013 IBLI began to scale in Kenya
beyond pilot site in Marsabit
• Rigorous IBLI impact assessments have revealed considerable socioeconomic and
behavioral benefits drawing policy and development partner support.
• Government of Kenya has committed to scaling up IBLI under the Kenya Livestock
Insurance Program (KLIP).
• March 2017, KLIP/IBLI paid out over Ksh225 million to 12,500 households
representing close to 90% of insured households. 25% of these received the
maximum payment possible for short rains failure.
• Work remains to ensure efficient and sustainable large scale coverage

1. Precise contract design:
2. Evidence of value and Impact:
3. Establish informed effective demand,
4. Low cost, efficient, delivery mechanisms
5. Policy and institutional infrastructure.
Components of a Sustainable Index-Insurance
Program

Precise Contract Design
• Objective (Initially): To insure
against drought- related livestock
mortality. Asset Replacement.
• Index: Predicted average livestock
mortality.
• Contract Evolution: From Asset
Replacement to Asset Protection
• Index: Seasonal Forage Availability
For references refer to https://ibli.ilri.org/publications/
DATA
- Livestock
mortality
- Remotely
sensed
NDVI
Respon
se
Functio
n
Predicte
d
Livesto
ck
Mortalit
y

Evidence of Impact and Value
Methods:
• Panel survey for impact assessment
• Monitoring Evaluation and Learning
surveys and interactions
Evidence:
• Wide range of positive household
impacts
• Quantification of risk-coverage precision
of contracts
• Indication of value-for-money for public
expenditure
For references refer to https://ibli.ilri.org/publications/

Establish Informed Effective Demand
• Capacity Development, Training,
Extension and Marketing
 Critical for ensuring impact and scaling
efficiently
 Unlocks a rich and important new research
agenda
Level 1: Knowledge and
tools for government and
insurance industry policy
makersLevel 2: Knowledge, skills
and job aids for IBLI/KLIP
sales agents and
promoters
Level 3: Awareness raising
for potential clients

Low-cost, Efficient Delivery
• Need to solve for the cost of service provision in the drylands
• Application of digital technological solutions
 will be critical to reducing costs and going to scale

Policy and Institutional Structure
• Sustainable, large-scale index insurance
program requires a clear and well articulated
policy structure
• No example of unsubsidized private market for
index insurance in developing countries.
Globally only 7% of transaction volume is purely
private.
• Experience and evidence suggests that for
programs to go to scale they need to build on
strong, well-coordinated public and private
sectors
• In Kenya we serve together with the World Bank
as invited technical and policy advisors for KLIP
• What are the key roles for each sector?

Moving Toward Sustainable Scale
Africa Classification for IBLI
“Relevance Zones”
(Mills et al., 2017 ILRI Brief)
• Growing body of evidence continues to highlight the socioeconomic
and risk-management value of index insurance programs, and the
logic of public support.
• IBLI experience has made a contribution to this evidence, and to
identifying some of the barriers to scale and trying to solve for them
• Going to scale will require careful research and development efforts
to further unlock the barriers, and an alignment of policy and
technological forces.
• INVESTMENTS NEEDED IN:
• Additional evidence on household and poverty impacts of IBLI, integration with
other complementary interventions targeting poverty alleviation, risk-
management and graduation to prosperity (cash transfers, graduation etc)
• Improvements in contract design and validation and alignment with other
related index-based products/programs (ARC, scalable HSNP etc)
• Development of internationally recognized product quality metrics
• Development of digital platforms and data infrastructure for cost-efficient
product and information delivery, capacity development, impact assessment
and product design

IBLI Policy and Academic Workshop – July 2015
It Takes a Village

This presentation is licensed for use under the Creative Commons Attribution 4.0 International Licence.
better lives through livestock
ilri.org
ILRI thanks all donors and organizations who globally supported its work through their contributions to the CGIAR system
Thank you!
For more information on IBLI, visit https://ibli.ilri.org/

Gender Power in the Kenyan Dairy
Sector
Katie Tavenner, PhD
Post-Doctoral Fellow – Gender Research
CCAFS Science Seminar
JVC Auditorium, ILRI Nairobi campus
May 30, 2017

Why focus on gender power?
 Dairy is a male dominated sector
 Increased commercialization (re: adoption of
intensification practices) tends to reinforce men’s
dominance in value chains
 Gender dynamics mediate farmers’ ability to effectively
participate in and benefit from low emissions dairy
development
 Gender analysis reveals how intrahousehold dynamics,
social institutions, and value chains work together to
influence on-farm practices and market engagement

Gender Power Issue I: Milk Marketing
 Intensification of dairy production in Kenya is being
achieved through formal milk market participation
 Market participation is embedded in local gender norms,
that affect how men and women engage in milk
marketing
 Localized notions of masculine household headship
influence farmer decisions over whether/where to sell
morning and evening milk
 Example: Direct payments to women for formal evening milk
marketing may not actually address whether women can control that
income!

Gender Power Issue II: Labor
Dynamics
 Daily dairy labor is predominantly carried out by women
– Need for trainings to be targeted towards
women….but also to go beyond quotas to understand
intrahousehold labor and decision making dynamics
 Additional labor from intensification of production likely
to be borne by women – Need for labor alleviating
technologies
OnAfricanDairyPortal

Gender Power Issue III:
Intersectionality
 Intersectional axes create different gendered capabilities
for farmers to engage in and benefit from dairy
intensification
 Farmer’s engagement in dairying is patterned not only
by whether they identify as male or female, but by how
their gender ‘intersects’ with their ethnicity, culture,
marital status, age, race, wealth status, and religious
affiliation
 Example: Single women may not need to deal with ‘contested
headship’ issues (they can own cattle, make decisions about
resources), but they may lack the financial support or time to
intensify dairy production

Gender Power Issue IV: Gender Equity
 Gender equity defined as, “fairness in participation and
benefit from development” - is a cultural construct
 While development practitioners often have specific
notions of what constitutes equity, men and women
smallholders do too
 A sole focus on “getting the indicators right” obscures the
complexity of how gender power operates dynamically
and relationally within and across households,
institutions, and value chains

Questions/Comments?
Contact Details
Katie Tavenner | Postdoctoral Fellow -
Gender
International Livestock Research
Institute |ilri.org
Box 30709 -00100, Nairobi, Kenya
E-mail: K.Tavenner@cgiar.org

Mazingira Centre:
Improving Estimates of Greenhouse Gas
Fluxes from Livestock in Sub-Saharan Africa
David E. Pelster, John Goopy, Lutz Merbold, Klaus Butterbach-Bahl and the
Mazingira Team
International Livestock Research Center (ILRI), Nairobi, Kenya
CCAFS Science Seminar, 30 May, 2017

Mazingira?
Swahili for “environment”
Multi-disciplinary approach:
 Soils, air, water
 Natural and crop/livestock systems
 Point of entry – improving productivity of land -
sustainably

AFOLU and GHG emissions
Approx. 70% of
emissions related
to livestock
production
Contribution of AFOLU
GHG emissions by country
category
Manure applied to soils
Enteric fermentation
Manure left on pasture
Manure management
Burning - savanna
Synthetic fertilizer
Rice cultivation
Crop residues
Cultivation org. soil
Burning – crop res.
GHG-emissions by sector
FAO, Tubiello et al. 2014 2

Richards et al. 2016 Scientific Reports
Why we need empirical studies
Prediction error for smallholder cropping
systems
Models likely using incorrect emission factors
Hickman et al.
2014
Why are the emission factors
incorrect?
• Limited dataset
•Models use emission factors from other
regions
•These other regions have different climate /
soils / management / animal breeds, etc

Why is this important?
• National inventories for IPCC calculated using (most likely)
incorrect data (TIER 1 approach),
• Nationally Appropriate Mitigation Actions (NAMA) depend on
correct understanding of current emissions and projected
effects of the mitigation actions,
• (Intended) Nationally Determined Contribution ((I)NDCs) can
only be tackled with profound understanding of the systems ,
• Currently we have no accurate estimates of either of these, nor
do we know the direction of change with changes to land
management
• Environmental in-situ data for African continent remains scarce
-> bias not-only in earth system models
14

What have we found so far:
GHG emissions from smallholder farms in east Africa
•Baseline N2O emissions from agricultural soils
were also low when compared to other regions
• Soils are often depleted of both C and N and likely require
inputs of both to improve fertility
• (Pelster et al. 2017, BG)
Background N2O Emissions (Kg N2O-N ha-1)
Median Mean
Study 1* 0.18 0.28
Global average (Kim et al.
2012)
0.70 1.52

However…
• Moving from Tier 1 to Tier 2, without changing the methane
conversion factors increases emission estimates
• Likely the same for N2O (Owino et al. in prep)
Herd
component
Tier 1 EF
(kg CH4
head-1 yr-
1)
Total Nandi manure
management Tier 1
emissions (Gg CH4
yr-1)
Tier 2 EF
(kg CH4
head-1 yr-1)
Total Nandi manure
management Tier 2
emissions (Gg CH4
yr-1)
Adult female
(pregnant)
1 0.024 9.54 0.233
Adult female
(not)
1 0.057 6.00 0.342
Adult male 1 0.023 7.86 0.178
Young dairy
female
1 0.103 5.90 0.610
Young dairy
male
1 0.013 4.47 0.058
Total 0.220 1.422

Results: Study 2
GHG emissions from east African cattle excreta
CH4emissionfactors(gCH4-Cyr-1
250kganimal-1)
IPCC
Tier 1
valueD1 = Basal diet
D2 = Daily
supplementation
(1X)D3 = Bi-daily
supplementation
(2X)
• Emission factors for manure were much lower than in many
other regions
• Likely related to the poor quality of the livestock feed
• (Pelster et al. 2016, JEQ)
IPCC
Tier 1
value
N2Oemissionfactors(%appliedN
lostasN2O-N)

Why is this important?
Livestock and enteric fermentation
• African farmers are amongst the least efficient livestock
producers in terms of GHG emissions intensities
• Rising populations and affluence lead to greater demand
for animal-sourced protein.
• Baseline and mitigation calculations to date have been
done exclusively through the use of models
• Cheaper and faster than measurements, but has (a lot) of limitations
• It is a capital mistake to theorize before one has data. -
Sherlock Holmes
• We need to model emissions, but we need DATA to
parameterize the models
14

Enteric CH4:
What should we measure? (I)
It’s all mostly about the food:
 Intake and digestibility
70-80% of variability in enteric GHGEs
Very difficult to measure intake in smallholder situations
Key assumptions about estimating intake violated (esp.
ad lib intake)
 The “next best” is to estimate intake from energy
expenditure
 Thus, we measure LW, ∆LW, milk production and
locomotion in ruminants on smallholder farms, then apply
appropriate algorithms to estimate intake. Then we can
estimate enteric CH4 emissions.

Enteric CH4:
What have we done?
• Identified (60-120) representative farms in 3 localities (Nyando,
Nandi, Bomet) and in the process of adding 2 more (Tanzania)
• Track (measure) all ruminant livestock on those farms for 1 yr
• Estimate yields from pasture and crops
• We use this data to estimate Methane Production Rate, Emission
Factors

Enteric CH4:
What we’ve found so far:
• Emissions factors (up to) 40% less than Tier1 (default)
estimates
Females Males Calves
Live weight
(kg)
Annual
Emissions (CH4
kg/yr)
Live weight (kg) Annual
Emissions (CH4
kg/yr)
Live weight
(kg)
Annual Emissions
(CH4 kg/yr)
Highlands 262.6 28.0 231.5 36.8 87.5 20.4
Lowlands 175.9 23.4 169.5 31.6 62.7 15.9
Slopes 209.7 24.1 205.8 35.5 74.6 17.2
Mean 208.7 24.6 198.0 34.4 73.4 17.3
Mean live weight (kg) and Emission Factors (CH4 kg/animal/annum)
for three classes of cattle in the three topographic regions of the
Nyando basin, Kenya

What does this mean?
• More work is required to
validate (other areas), BUT
• Current estimates may
greatly overestimate EFs in
local cattle
• Potentially invalidate
mitigation practices because
baselines are too high

Some recent publications
Manure management to improve soil structure and food security and mitigate greenhouse
gas emission Ndambi, A., Pelster, D.E., Butterbach-Bahl, K.
Greenhouse gas fluxes in agricultural soils of Kenya and Tanzania Rosenstock, T.S.,
Mpanda, M., Pelster, D.E., Butterbach-Bahl, K., Rufino, M.C., Thiong’o, M., Mutuo, P.,
Abwanda, S., Rioux, J., Kimaro, A., Neufeldt, H.
Methane and nitrous oxide emissions from cattle excreta on an East African grassland
Pelster, D.E., Gisore, B., Goopy, J.P., Korir, D., Koske, J.K., Rufino, Mariana C., Butterbach-
Bahl, K.
Supplementation with Calliandra calothyrsus improves nitrogen retention in cattle fed low-
protein diets Korir, D., Goopy, J.P., Gachuiri, C., Butterbach-Bahl, K.
Long-term assessment of soil and water conservation measures (Fanya-juu terraces) on
soil organic matter in South Eastern Kenya Saiz, G., Wandera, F.M., Pelster, D.E., Ngetich,
W., Okalebo, J.R., Rufino, M.C., Butterbach-Bahl, K.
Simple and robust algorithms to estimate live weight in African smallholder cattle. Goopy.
JP, Pelster, D.E., Lukuyu, M., Marshall,K., Onyango,
A Smallholder Dairy Farmer Training Manual JP Goopy, J. Kagai (eds).
Groundwater recharge rates and surface runoff response to land use and land cover
changes Owuor, S.O., Butterbach-Bahl, K., Guzha, A.C., Rufino, M.C., Pelster, D.E., Diaz-
Pinés, E., Breuer, L.

This presentation is licensed for use under the Creative Commons Attribution 4.0 International Licence.
better lives through livestock
ilri.org
ILRI thanks all donors and organizations who globally supported its work through their contributions to the CGIAR system
For more information contact:
dpelster@cgiar.org
Thank You

analytical capacity
• C/N analyzer, sampling gear,
nutrition analysis
• Livestock respiration chambers
3 x small, 3 x large, 1 x mobile +
Picarro
• Eddy covariance system
(NH3, N2O, CO2, CH4), Aerodyne
QCLAS
• Automatic chambers
18 x chambers + Picarro
• Manual chambers and GC lab
6 x GC (N2O, CH4, CO2, (SF6))
• Manure/soil/plant analysis
• Nutritional lab (crude protein, fiber)
• Water analysis
NH4
+, NO3
-, DOC/DON, water
Mazingira Centre: Our Kit
11

Questions?
Mazingira team in December 2016: f.l.t.r. Jesse Owino , Hillary Rotich, George Wanyama Ibrahim Wanyam
Butterbach-Bahl, Stanley Mwangi, John Goopy, Alice Onyango, David Pelster, Yuhao Zhu, Andrew Mbithi, Victoria C
Asep Ali, Stephen Okoth, Daniel Korir, Lutz Merbold, Phyllis Ndungu Jesse Kagai, Showman Gwatibaya, Shade Aki
Kapiti cattle in the back
mazingira.ilri.org 15

DEVELOPING THE KENYA DAIRY
NAMA CCAFS Science Seminar
Charles Odhong' 30/05/2017

OVERVIEW
1. Kenya Dairy NAMA Development Process
2. Dairy NAMA Concept
3. Theory of Change
4. Lessons learnt
5. Missing links

56
• Establishment of NAMA development partnerships (SDL, KDB), including
roles and responsibilities and the set-up of a Multi-Stakeholder Platform
• First Multi-Stakeholder Platform meeting and regional consultations in
Central and Eastern regions took place in September and November
2015
• NAMA training organized for the State Department of Livestock and
Agriculture and Fisheries, and Kenya Dairy Board
• Intensive consultation with dairy processors, fodder producers & biogas
companies
• Action research with dairy and biogas companies to identify the business
case for gender inclusive business practices
•

57
(Cont...)
• In-depth studies:
 Review on financing mechanisms within the dairy sector
 Systematic review on management practices and their impact on milk yields
among smallholder farmers
 Cost-benefits analysis of commercial fodder production models
 Assessment of energy efficiency abatement potential
 Dairy productivity mitigation potential assessment (with CCAC project)
 Assessment of existing dairy M&E systems as basis for MRV in the NAMA
• Feasibility study on four mitigation opportunities within the dairy value
chain and development of initial NAMA concept
• Second Multi-Stakeholder Platform meeting, June 2016

58
3. Fodder supply4. Waste
2b. On-farm productivity
2a. On-farm productivity
1. Energy efficiency
Processors
, coops
TA
credit
Banks
Coop
s
farmers
Fodder
suppliersBiogas
TA
credit Banks
credit Banks
TA
Credit
TA
Biogas companies, banks
Processors
TA
Dairy service
providers
2. Dairy NAMA Concept

59
Impact
Outcom
es
Outputs
1.1 Increased adoption by
men and women dairy
farmers of improved on-farm
practices
1.2 Increased commercial
production and marketing of
fodder
Kenya’s dairy sector is transformed to a low-emission development
pathway, while improving the livelihoods of male and female dairy
producers
1. Increased dairy
productivity through private
sector investment in gender-
inclusive advisory services
and fodder input supply
2. 1 Dairy cooperatives
and processors increase
energy efficiency
2.2 Men and women adopt
biogas technologies on
dairy farms
3.1 Project monitoring and
national MRV systems
linked
3.2 Best practices are
captured and shared
among dairy sector
stakeholders
3.3 Dairy sector
stakeholders coordinate
their support
2. Reduced energy
consumption from non-
renewable sources
throughout the dairy value
chain
3. Strengthened institutional
and stakeholders’
capacities for scaling-up
low-emission dairy
development
Activities
1.1.1 Processor-led provision of
gender-inclusive advisory
services to their suppliers
1.1.2 Financial assistance for
on-farm investments by farmers
and cooperatives
1.2.1 Technical assistance to
commercial fodder producers
and fodder producer
associations
investments in commercial
fodder production and marketing
2.1.1 TA to support
cooperatives and processors
for energy audits and
investment proposal
preparation
investments in energy
efficiency and renewable
energy
2.2.1 TA to biogas companies
for development of business
operations
adoption of biogas by farmers
3.1.1 Capacity building for
project participants and
national organizations in
MRV
3.2.1 Monitoring and
evaluation of project
outputs, outcomes &
impacts
3.2.2 Share good practices
and lessons for adoption
and replication
3.3.1 Convene stakeholder
coordination meetings
3. Theory of Change

60
4. Lessons Learnt
• Strong country ownership is critical from the start, then
stakeholder engagement is important to ensure broad-based buy-
in
• Building on past and ongoing interventions provides a strong guide
to feasibility and financial viability
• To attract climate finance, there must be a clear commercial driver
of long-term sustainability; close engagement with the private
sector grounds planned interventions in industry trends
• Financing mechanisms must be tailored to different actors’ needs

61
5. Missing links
• There is much more research on effectiveness of mitigation options
than there is on equity dimensions
• Research on adaptation implications of mitigation strategies is
limited
• Research on effectiveness of delivery mechanisms (e.g. dairy
extension methods, gender-inclusive approaches) is limited
• Further work is needed to linking the NAMA MRV system to
national MRV systems (e.g. GHG inventory, ‘MRV+’)

Schnewlinstr. 10
79098 Freiburg, Germany
Tel: +49 761 208534 – 0
unique@unique-landuse.de
www.unique-landuse.de
© UNIQUE forestry and land use GmbH
Current
Status
The concept note has been submitted to the GCF. IFAD is keen to take
the concept note to the proposal development phase
Partners;

Science and Partnership for
Impact
Bruce Campbell, Program Director

Where we are
Where we must be
• Development $$$
 not National Science
Foundation $$$
• Not in the real world….
• Private sector key
• Funder’s national interests
• Outcome reporting
More:
• Effective
• Outcome-orientated
• Focused
• Different

Engagement
Evidence
Outreach
• Join in, listen &
navigate
• Demand driven,
targeted & tailored
• Credibility
• Opportunism &
flexibility
• Communication
• Capacity building
Three-
thirds
approach
An outcome-orientated approach

• Improved index insurance products for > 1 million farmers in India

www.ccafs.cgiar.org
@bcampbell_CGIAR

Partnerships for
Scaling Climate-Smart
Agriculture
Evan Girvetz
Todd Rosenstock
And team
e.girvetz@cgiar.org
30 May 2017
Nairobi, Kenya

Engagement
CapacityStrengthening
CSA
Investment
Portfolios
Prioritizing Interventions
Practices, Programs and Policies
Value for Money & Trade-offs
Targets, Vulnerability & Impacts, Readiness
Stocktaking for
CSA Action
Situation Analysis
Target Setting, Climate Risks & Enabling Conditions
Program Implementation
Design, Development & Deployment
Taking CSA to
Scale
Knowledge into Action
Evidence Based Results Framework
Learning from
Experience
Monitoring and Evaluation
Across Scales and Systems
CSA-Plan

CSA-Plan
Vulnerability & Impacts + Readiness
Stocktaking for CSA
Action
Situation Analysis
Target Setting, Climate Risks & Enabling Conditions
CSA Country
Profiles
https://ccafs.cgiar.org/publications/csa-country-profiles
15 Profiles Developed
Across Africa, Asia and
Latin America
15+ additional currently
being developed globally

Kenya County Climate Risk Profiles:
Key Risks and Adaptation Options
Identified Across Value Chains
Developed to support the
World Bank Kenya
Climate Smart Agriculture
Project ($250 million)
Climate Risk Profiles
being developed for 31
Kenyan counties through
strong engagement
Provides a platform for
CSA dialogue,
engagement and capacity
building at the county level

CSA Investment
Portfolios
Trade-offs & Value for Money
Stocktaking for
CSA Action
Situation Analysis
Risks and Enabling Conditions
CSA-Plan
FA
O
Trade-
offs among
aspects of
CSA
Synergie
s between
aspects of
CSA

• Scope –
region,
commodity
• CSA indicator
selection
• long list of
CSA practices
Results
•Short list of
priority
practices and
programs
•Stakeholder
selection via
workshops
Results
Ranked short
list based on
economic
analysis
Results
•CSA
investment
portfolios
•Identified
opportunities
and
constraints
Results
Community
organizations
Governmental decision-
makers (national, local)
NGOs
Research
Developmen
t partners

CSA Compendium:
Synergies and trade-offs with CSA
ed
nd
? Rel-
gro-
st
n
on
oil
hysical
le-
e
on of
eb of
ndica-
pri-
, to
oduc-
in a
stud-
t me-
umber
ude.
comes (see Rosenstock et al. 2015 for description of sta-
tistical approach). We intentionally only select studies that
measured both outcomes, because the impact of man-
agement practices depends on location and thus it is spu-
rious to compare results of studies between locations in
different biophysical or social contexts.
−1.0
−0.5
0.0
0.5
1.0
−1.0 −0.5 0.0 0.5 1.0
Productivity
SOC
Productivity (Effect size)
Resilience(Effectsize)
11%
15% 56%
SynergiesTradeoffs
Tradeoffs
19%
+Yield
-women’s
labor
+Yield
+soil C-Net returns
+soil C
Rosenstocketal.

CSA Investment
Portfolios
Targeting & Prioritizing
Stocktaking for
CSA Action
Situation Analysis
Design & Implementation Guidelines
Taking CSA to
Scale
• CSA Program Development
• Implementation Guides
• Business models
• Incentive schemes
CSA-Plan

Program Design & Implementation:
Innovative Finance and Business Models for
Scaling CSA
Climate-
Smart
Agriculture
Intervention
s
Farmer
Field
Business
Schools
Village
Saving and
Loan
Association
s Climate
Resilience
Gender Equity
Social Capital
Farmers
Organizatio
ns &
Groups
Input
Supplie
rs
Resilience, Nutrition, Poverty and Equity
Outcomes
Markets &
Household
Consumpti
on

CSA Investment
Portfolios
Targeting & Prioritizing
Stocktaking for
CSA Action
Situation Analysis
Design & Implementation Guidelines
Taking CSA to
Scale
Evidence Based Results Framework
Learning from
Experience
Monitoring and Evaluation
Across Scales and Systems
CSA-Plan

Big Data Opportunities in Agriculture
http://bigdata.cgiar.org

82
• High-level engagement in 12
Countries across east, west and
southern Africa
• Deeper sub-national engagement
in Kenya, Tanzania, Uganda,
Zambia
• In discussions with World Bank in
Cameroon and Government of
Nigeria to conduct climate profiling
work
Partnerships for Scaling
CSA: Reach in Africa

Lessons Learned
• Engagement: Just show up! Partnerships and early engagement
with key stakeholders are critical: the process is as important as the
final product
• Evidence: Decision-makers want evidence, and they see the
CGIAR and CCAFS as key technical and knowledge partners
• Outreach: Communications and capacity building are critical to
translating high-level frameworks and guidelines into on-the-ground
impact
Engagement + Evidence + Outreach =
Impact

e.girvetz@cgiar.org
Evan Girvetz
Todd Rosenstock
24 April 2017
Galway, Ireland

Policy engagement: the role of
multistakeholder platforms

The policy challenge
Limited
capacity &
capacity
building
Insufficient
attention to
gender
Lack evidence
that informs
policy
Limited
stakeholder
inclusion
Harmonization
& coordination
challenges
At formulation
Policies focus
on short term
climate impacts
Non-functional
structures
Limited
awareness of
policies
Political
interference
Limited
enforcement
Cross-cutting
issues not
priority
Limited
capacity to
interpret
At implementation

Gaps spread across scales
Formulation
National District Community
 Lack of synergy between the
diverse sectors
• Lack of gender & social
differentiation & practical
strategies to address gender
 District inadequately
included in formulation
• Engagement with
gender restricted to
quota system
 Locals excluded in policy
formulation
• Female participation further
reduced by limited
information & technical skills
Implementation
 Lack of implementation
structures across levels
 Weak enforcement of laws and
regulations
 Climate change and gender
issues treated as cross-
cutting issues
 NRM/Climate change
issues not part of
performance evaluation
 Limited capacity to
interpret and implement
policies
 Limited access to policy
documents
 Locals not aware of
policies
 Lack of ownership, limited
compliance
 Political interference

• Policy-
gender
analysis
• Policy actor
networks
• CSA trade-
offs
• Scenario
guided policy
development
Knowledge
creation
• Co-learning
• Information
exchange
• Development
of tools +
strategies
• Engagement
actions
Collective learning
+ engagement • Enhanced
human capacity
for CCA
• Better-informed
investment
decisions for
CCA
• Inclusive policy
development
and
implementation
• Collective CCA
effort
Outcomes
Influence and link policies and institutions from national to local level for the
development and adoption of climate-resilient and gender-responsive food
systems in Uganda and Tanzania

Influencing
change in
policies
Tanzanian
NEP
ASSP
Uganda
Climate
change
mainstreaming
guidelines,
MAAIF
2 District local
governments
Tanzania
4 District Local
governments
Uganda
• Partnership with MAAIF?
• Non-state actors in LA
demanded own review;
• Capacity building for non-
state actors
• Partnership with VPO, MALF
• Govt technical planning committees mandated
• Non-state actors/LA members participated
• Local adaptation planning
at district level
• Integrated climate change
in five year district
development plans
• Influencing investment
priorities
• Partnership with MAAIF
• National & district LAs
participated in consultations
& validation
Scaling
• Kilolo scaled alliance to
lower levels
• LA scaled out to Kilosa
by NGO on LA
Achievements related to learning alliances
• Validation of research
findings
• Districts and communities converge
to learn, prioritize and plan climate
action
• Build linkages between national and international
partners who meet at or work through learning alliances
• Targeted engagement e.g. Uganda
Parliament; Tanzania water Commission

Lessons being learnt
• Motivation for sustainability?
• The need for an interested champion to keep
momentum
• Link to stakeholder needs
• Value chain showing positive signs
• Tangible benefits: policy initiatives must link
with initiatives that deliver e.g. technologies

• Documents emerging stories of
success of CSA technologies and
practices in East Africa
• Selected from a portfolio of CSA
interventions that are positively
changing lives of smallholder
farmers, with potential for scaling up
The booklet

CSVs in East Africa
• Six sites in four countries: Ethiopia,
Kenya, Uganda and Tanzania
-Borana (ET)
-Wote and Nyando (KE)
-Hoima and Rakai (UG)
-Lushoto (TZ)
• Climate-Smart Villages are clusters of
villages or landscapes that focus on
climate change hotspots around the
world
• Piloting of the interventions began in
2012.

Climate–Smart Villages components

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