combined presentations for climate-smart agriculture (csa) tools for africa webinar

Agroforestry

What Works, Where:

The CSA Compendium and X-Ray

Nutrition security

Poverty alleviation

Natural resource

management

Improved

cook-stove

Conservation

agriculture

Increased yields

Soil quality & carbon

Erosion

Dietary

diversity

Intercropping Participatory

approach

Todd Rosenstock & Christine Lamanna World Agroforesty Centre (ICRAF) | Nairobi

Large Scale Initiatives and Investments

Launched Sept 2014

80+ members

Some CSA initiatives

Not

CSA CSA

What is CSA and what is not CSA?

Not

CSA CSA

Many practices can be CSA somewhere

But none are likely CSA everywhere

Context

What is CSA and what is not CSA?

Photo: K. Tully

What works where?

Key word search

Abstract/title review

Full text review

Data extraction

144,567

papers

16,254

papers

6,100

papers

~175,000 data points

Systematic review and meta-analysis 68 practices/28 indicators of CSA outcomes

Response ratio =

ln(mean(treatment)

/mean(control))

Effect size =

weighted mean of

response ratios

●●

● ●● ● ●●● ●●● ●● ●●

●

● ●● ●●

Diet management

Crop rotation

Fertilizer

Agroforestry

−1.0 −0.5 0.0 0.5Effect size

Agroforestry

Inorganic

fertilizer

Crop rotation

Imp. diets

Impact of select practices on productivity

(N = 9,940)

●●

● ●● ● ●●● ●●● ●● ●●

●

● ●● ●●

Diet management

Crop rotation

Fertilizer

Agroforestry

−1.0 −0.5 0.0 0.5Effect size

Agroforestry

Inorganic

fertilizer

Crop rotation

Imp. diets

● ●●

●●● ●● ●● ●●●

non−Legumionous

Leguminous

−1.0 −0.5 0.0 0.5Effect size

● ●●

●●● ●● ●● ●●●

non−Legumionous

Leguminous

−1.0 −0.5 0.0 0.5Effect size

- N fixing trees

+ N fixing trees

● ●

●

Alt. feeds

Inc. protein

−0.2 0.0 0.2 0.4Effect size

Selecting ‘best bets’ for CSA by practice at

global level

Alt. feeds

Inc. protein

Selecting ‘best bets’ for CSA for a place

Mitigation

Productivity

Resilience

−1

0

1

2

−1

0

1

2

−1

0

1

2

Crop ManagementDiet ManagementIntercropping AgroforestryNutrient ManagementPostharvest StorageSoil ManagementTree ManagementWater Management

Practice

Effe

ct S

ize

Country

Tanzania

Uganda

P1 P2 P3 P4 P5 P6 P7 P8

Productivity

Resilience


Mitigation

Productivity

Resilience

−1

0

1

2

−1

0

1

2

−1

0

1

2


Practice

Effe

ct S

ize

Country

Tanzania

Uganda

P1 P2 P3 P4 P5 P6 P7 P8

Productivity

Resilience Predictable


Mitigation

Productivity

Resilience

−1

0

1

2

−1

0

1

2

−1

0

1

2


Practice

Effe

ct S

ize

Country

Tanzania

Uganda

P1 P2 P3 P4 P5 P6 P7 P8

Productivity

Resilience Predictable

Less so

−1.0

−0.5

0.0

0.5

1.0

−1.0 −0.5 0.0 0.5 1.0Productivity

SO

C

Productivity (Effect size)

Resi

lience

(Eff

ect

siz

e)

11%

15% 56% Synergies Tradeoffs

Tradeoffs

Synergies and tradeoffs with CSA

19%

Practices differ in magnitude of co-benefits

Studies with indicators for at least 1

component of CSA

Studies with indicators on 2 or more CSA

objectives

~40% of the available research

Studies with indicators for all 3 components

1.5% of the available research

Turning data in decision-support

‘CSA X-ray’

Evidence-based

and digestible

assessments of

CSA practices and

places

Figures and icons: Morningstar

Financial support: CCAFS, UN FAO, IFAD, CIFOR-EBF

Contributors:

K Tully, C. Corner-Dolloff, E Girvetz, D-G Kim, M Lazaro, A Jarvis,

P Bell, S Chesterman, S MacFatrige, H Strom, A Madalinska, A-S

Eyrich, C Champalle, W English, A Akinleye, A Poultouchidou, A

Kerr, H Neufeldt, A Arshan, J Rioux, F. Atieno, M Ravina, C Zhuo,

S Abwanda, W Zhuo, C Ardilla, P Laderach, D Grunzel, S

Vermuellen, O Bonilla-Findji, K Morris, J Dohn, M Richards, B

Campbell, A Arslan, J Rioux

Thank you, [email protected] Data will be publically available in 2016

Directing Investment in Climate-Smart Agriculture (CSA)

CSA Prioritization Framework

Climate-Smart Agriculture Tools for Africa Webinar

13 October 2015

Caitlin Corner-Dolloff

CIAT, Decision and Policy analysis

[email protected]

Miguel Lizarazo (CCAFS-LAM), Andreea Nowak (CIAT), Fanny Howland (CIAT), Nadine

Andrieu (CIAT/CIRAD), Osana Bonilla (CCAFS), Ana Maria Loboguerrero (CCAFS-LAM),

Andy Jarvis (CIAT-CCAFS)

© CIAT/Neil Palmer

Alliance for CSA in Africa

Vision

25 x 25 West Africa CSA

Alliance (WACSAA)

Global momentum building for CSA

Map of a selection of CIAT-ICRAF CSA initiatives with CCAFS, WB, USAID from 2014-2105

6 million farmers by 2021

Linking 19 countries

500 million farmers globally

CSA one of 5 priority

investment areas

Niger, Kenya 200 million in CSA

A set of filters for

evaluating CSA options

& establishing

CSA investment portfolios

CSA Prioritization Framework

Multi-

level

Linkable

Stakeholder

Driven

Flexible

Simple

Intended users 1° National and sub-national

decision makers

2° Donors, NGOs, implementers

CSA Prioritization Framework Filters for selecting CSA investment portfolios

*Identify scope

*Match practices with context

*Participatory metrics selection

Long list of CSA practices

*Ex-ante assessment based on CSA indicators

*Stakeholder workshop

Ranked short list of priorities

*Economic analysis – assess costs and benefits, including externalities

Ranked short list based on CBA

*Integrated analysis of opportunities & constraints

* Stakeholder workshop

CSA investment portfolios

Pilots

underway

Ethiopia

Ghana

Uganda

Workshop 1

Guatemala

Filtering: Indicators of CSA Pillars

Workshop

Literature

review

Expert

interview

+

+

Lessons:

• Participatory indicator selection -

link science with desired change

• Improved communications and

visualization of data key for CSA

decision-making

Dry corridor

Region

Set scope: geographic,

production systems

© CIAT

Ranked long list of possible

CSA Practices

Score CSA Practices

Guatemala

Filtering: Economic Evaluation

Lesson: Econ analysis in high demand

- data and tools needed to better assess and easily visualize options

Prioritized Practices

Portfolios Designers

Producers Research MoAgr

Agroforestry systems: live fence Varieties tolerant to pests & diseases

1: low resource farmers

Varieties tolerant to drought and water stress

1: low resource farmers

Conservation agriculture

2: FS, drought

Crop rotation (maize-beans) Reservoirs + Drip irrigation

X: FS, drought

Guatemala

Filtering: Integrated Analysis CSA indicators, CBA, externalities, barriers and opportunities

Lesson:

Prioritization does not

imply one output

• Multi-variate analyses

allow users to create

differentiated

portfolios based on

intended

application and

beneficiaries

Lesson:

Process is as important as

the content

• Discussions of data create

space for collaborative

integrated planning

between users

• EU modifying calls based on

results – other potential

applicants linked from

beginning

Mali

CSA at the Regional Level

Policy/Research forums (AEDD)

Regional governments

NGOs (C-GOZA, Sahel Eco)

Donors (EU, Swedish

Embassy)

CO

NT

EX

T

PO

TE

NT

IAL

US

ER

S

- Lead Team: NGO

Foundation Río las

Piedras, Cauca.

and CCAFS-CIAT.

- Farmers organizations:

Asocampo and

Asoproquintana

- Indigenous councils:

Puracé, Quinata and

Poblazón

- Civil society councils:

Pisojé alto and El Hogar

LOCAL PARTNERS

- Municipal

governments:

Mayor’s office of

Popayán

Mayor’s office of

Puracé

- Environmental

Regional Authorities:

Coporación Autónoma

Regional del Cauca

POTENTIAL

Las piedras river

basin 6626 ha

Lesson: Local ownership is critical to prioritization

• Local communities act as researchers

• Minimize extractive data collection

• Adapt metrics to local context and socialize prior to users.

Training on Survey

Discussion

on indicators

Colombia

CSA at the Local Level

© CIAT/Andreea Nowak

CSA-Plan

Uptake of CSA Plan components, including CSA PF,

in 15+ countries in Asia and Africa 2015-2018

ICRAF - T. Rosenstock, C. Lamanna CIAT - E. Girvetz, C. Corner-Dolloff

Ongoing CSA initiatives

Caitlin Corner-Dolloff

[email protected]

additional information at:

ccafs.cgiar.org/climate-smart-agriculture-prioritization-framework

Thank you!

Climate Smart Agriculture Rapid Appraisal (CSA-RA)

Caroline Mwongera, Leigh

Winowiecki, Kelvin

Mashisia, Jennifer Twyman,

Peter Laderach, Edidah

Ampaire,

Steve Twomlow 13 October 2015

Climate Smart Agriculture Rapid Appraisal (CSA-RA)

• Combine socio-economic and biophysical

realities across scales in order to prioritize,

implement and out-scale CSA

A tool for Prioritization of Climate Smart Agriculture

across Landscapes

PRA Tools Scale

1. Village

resource

maps

2. Climate

calendars

3. Historical

calendars

4. Cropping

calendars

5. Organizatio

n mapping

using Venn

diagrams

Household-

farm

Community-landscape Sub-regional scales

Gendered

lens

climate

focus

CSA-RA Methodology

Participatory Approach 1. Farmers’

Workshops

2. Expert Interviews

3. Farm visits

(interviews

/

transect walk)

Gender disaggregated

Site-specific targeting of CSA

interventions

Expert opinion Socio-economic data

1. Crop & Livestock listing/uses/gender association

2. Community/ village resource maps

3. Cropping calendar

4. Historical calendar

5. Climate calendar

6. Institutional mapping /Venn diagrams

Challenges Current

practices Community

resources Climate impacts Local

organizations for:

Women Men Youth (< 30

yrs.)

Farming systems

Current practices

Recommendations on site-specific CSA interventions

Barriers and constraints to adoption

HH size, farm size HH food sufficiency Labor (HH & hired) Production

(crop/livestock) Yield HH

consumption Sales

Off farm income Remittances,

donations, savings

HH expenses Use of agricultural

inputs Current practices CSA needs

CSA Prioritization

o Awareness and use of agricultural

o Prioritization of practices by gender & AEZ

o Ranking indicators considered in adopting a practice

o Demonstration plots

o Practices

o Sites

3. Prioritization Workshops

Cropping calendar

Identifies most

important crops by

gender, division of

responsibilities and

different crop

management

activities

Crop management activities by month for groundnut, cassava and sesame as

detailed by the male participants in the farmer workshop in March 2014 in Gulu

district of Uganda. Logograms indicate whether men or woman undertake the

activity

Crop management activities by month for beans, cassava and sesame as

detailed by the female participants in the farmers workshop in March 2014

in Gulu district of Uganda. Logograms indicate whether men or woman

undertake the activity.

Organization mapping

Organization mapping and linkages as detailed by the female participants (left panel) and male participants

(right panel) in the farmers workshop in September 2014 in Mbarali district of Tanzania. Blue circles denote

those ranked as of high importance, yellow circles of medium importance, and pink circles of low

importance. Acronyms represent the organizations.

Indicate

organization

linkages, as well

as gendered

differences in

their ranking

Climate calendars

Reveal climate

variability

perceptions over

time, gendered

impacts and

vulnerability

Organization mapping and linkages as detailed by the female and male participants in the

farmers workshop in September 2014 in Mbarali district of Tanzania. Blue circles denote

those ranked as of high importance, yellow circles of medium importance, and pink circles of

low importance. Acronyms represent the organizations.

CSA Prioritization

Prioritization of agricultural practices in Anaka, Northern

Uganda by gender and by agro-ecological zone

Targeting & Out-scaling site-specific CSA practices

• Guide agricultural investments

• PRELNOR Project (IFAD)

• Select project sites

• Socio-economic surveys

• Land Health Surveys

• Select location of CSA demonstration sites

• Institutional support

• Local stakeholders/organizations

Manual and Reports

Available at CCAFS Harvard

Dataverse:

https://dataverse.harvard.edu/datas

et.xhtml?persistentId=doi:10.7910/

DVN/28703

Output for the CIAT-led, project “Increasing Food

Security and Farming System Resilience in East Africa

through Wide-Scale Adoption of Climate-Smart

Agricultural Practices” funded by IFAD

https://dataverse.harvard.edu/dataset.xhtml?persistentId=doi:10.7910/DVN/28703



Participatory Scenario Planning: A decision support approach for

Climate-Smart Agriculture

Adaptation Learning Programme – CARE International CSA Tools in Africa

CCAFS, CARE Webinar 13th October 2015

Known and unknown?

Changing climate and weather patterns.

Growing challenge for smallholder farmers, pastoralists, VCA.

Future climate risks, opportunities?

Future climate impacts - agricultural productivity, incomes, vulnerable communities, women, men?

WWW.CARECLIMATECHANGE.ORG

What needs to be done?

• Adaption in agriculture & building resilience to climate

(CSA)…How?

• Community-based adaptation: social decision-making

processes + support to technical adaptation strategies


• Climate informed decision

making and planning…

But:

Uncertain climate

information – planning for

inexact is challenging

Large vs local scale

Participatory Scenario Planning (PSP)


Multi-stakeholder forum for: • Accessing, understanding seasonal climate forecasts and

• Collectively interpreting them – locally relevant, actionable

information for decision making and planning.

Why PSP?

• Scenarios: planning for likely & less certain outcomes

• Earlier, better informed: advisories to take advantage of

opportunities, reduce risks


• Learning now to continually

manage seasonal climate

variability, risks and

uncertainties […] provide

potential pathways for

strengthening stakeholders’

adaptive capacities to

manage climate change in the

long term (Niang, et al., 2014)

Step 1. Designing the PSP process

Developing a well thought out, locally

relevant and appropriate PSP

process, including deciding the level

(national, county/province,

district etc.) at which to conduct PSP and forming partnerships for sustainability of

the process

Step 2. Preparing for a PSP workshop

Engaging stakeholders,

bringing out their information needs for the coming season

and using this to plan for targeted

workshop outcomes.

Step 3. Facilitating a PSP workshop

Multi-stakeholder forum – access, understanding &

combining meteorological & local seasonal

forecasts; interpretation into

locally relevant and actionable

information for seasonal decision making & planning.

Step 4. Communicating

advisories from a PSP workshop

Reaching all actors who need to use the information, in good

time to inform decisions and plans.

Step 5. Feedback, monitoring and

evaluation

Two-way communication and feedback between

producers, intermediaries and

users of climate information enabling continuous, iterative and shared learning and improving the PSP process and

outcomes.

PSP is an iterative learning process

The PSP process

Value of PSP in climate-smart agriculture


Building adaptive capacity & resilience…

Value of PSP in Climate-Smart Agriculture


Building adaptive capacity…

• Institutions, entitlements and governance – multi-stakeholder

dialogue, responsiveness & accountability

• Regular planning – informed by changing risks, vulnerability,

capacity, resources, knowledge and information

Way forward?

• Projects, programmes: e.g.

Kenya Agriculture Sector

Development Support

Programme – link with VCA

platforms

• Development plans, budgets:

e.g. N. Ghana DMTDP; Kenya

Garissa County CIDP,

Agriculture work plan

• Policy: e.g. Malawi

Meteorology Policy


Integration of PSP in…

Thank You!

Adaptation Learning Programme (ALP) www.careclimatechange.org/adaptation-initiatives/alp

[email protected]

Joto Afrika Special Issue 12 on Climate communication for adaptation:

http://www.alin.net/Joto%20Afrika

Building resilience to climate change and enhancing food security in north eastern Kenya:

http://www.careclimatechange.org/files/stories/ALP_Kenya_Noor_Aug2012_final.pdf

Facing Uncertainty: the value of climate information for adaptation, risk reduction and resilience in

Africa: www.careclimatechange.org/files/Facing_Uncertainty_ALP_Climate_Communications_Brief.pdf

Coming soon “Climate information for resilient agricultural decision-making and planning in rural

communities: A Guide to Participatory Scenario Planning”


ALP is supported by

http://www.careclimatechange.org/adaptation-initiatives/alp



mailto:[email protected]

http://www.alin.net/Joto Afrika

http://www.careclimatechange.org/files/stories/ALP_Kenya_Noor_Aug2012_final.pdf

http://www.careclimatechange.org/files/Facing_Uncertainty_ALP_Climate_Communications_Brief.pdf

targetCSA - a decision support tool to target CSA practices -

Patric Brandt, Marko Kvakić, Klaus Butterbach-Bahl and Mariana Rufino

March, 3 2014

http://www.ccafs.cgiar.org

Key elements

• National - regional scale

• Spatially explicit

• Combining vulnerability indicators & CSA practices

• Participatory process

• Consensus oriented

?


targetCSA – the framework

Vulnerability indicators CSA practices Ex

amp

le

Expert opinions

• Stakeholder preferences on prioritizing:

• Vulnerability indicators

• CSA practices

• Consensus = minimized dissent

NGO GO

Sci. Priv.

Optimization model


Spatial indices

Aggregated & consensually weighed by stakeholder opinions

+

Maps are based on example data.

majority vs. minority

Identifying regions of high vulnerability & CSA suitability


targetCSA: Take home

• Problem structuring & complexity reduction

• Spatial indices built on consensus & evidence

• Exploring consensus scenarios may lead to higher acceptance

• Demand-based assessment of CSA potential

• Transferability & flexibility


Asanteni sana!
