Combined Presentations for climate-smart agriculture (CSA) Tools for Africa webinar
Post on 12-Feb-2017
162 Views
Preview:
Transcript
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
Not
CSA CSA
Many practices can be CSA somewhere
But none are likely CSA everywhere
Context
What is CSA and what is not CSA?
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
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 Predictable
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 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%
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, t.rosenstock@cgiar.org 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
c.corner-dolloff@cigar.org
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
Caitlin Corner-Dolloff
c.corner-dolloff@cigar.org
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
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
WWW.CARECLIMATECHANGE.ORG
• Climate informed decision
making and planning…
But:
Uncertain climate
information – planning for
inexact is challenging
Large vs local scale
Participatory Scenario Planning (PSP)
WWW.CARECLIMATECHANGE.ORG
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
WWW.CARECLIMATECHANGE.ORG
• 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
WWW.CARECLIMATECHANGE.ORG
Building adaptive capacity & resilience…
Value of PSP in Climate-Smart Agriculture
WWW.CARECLIMATECHANGE.ORG
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
WWW.CARECLIMATECHANGE.ORG
Integration of PSP in…
Thank You!
Adaptation Learning Programme (ALP) www.careclimatechange.org/adaptation-initiatives/alp
alp@careclimatechange.org
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”
WWW.CARECLIMATECHANGE.ORG
ALP is supported by
targetCSA - a decision support tool to target CSA practices -
Patric Brandt, Marko Kvakić, Klaus Butterbach-Bahl and Mariana Rufino
March, 3 2014
Key elements
• National - regional scale
• Spatially explicit
• Combining vulnerability indicators & CSA practices
• Participatory process
• Consensus oriented
?
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
top related