How can co-design of alternative agricultural development pathways help accelerating sustainability transitions in Southern Africa?
Sabine Homann-Kee Tui, Patricia Masikati, Katrien Descheemaeker, Givious Sisito, Buhle Francis, Olivier Crespo, Elisha N. Moyo, Tariro Chipepera, Roberto O. Valdivia
4th Global Science Conference
on Climate Smart Agriculture Issues / research questions for the
agriculture and food systems of 2050
28-30 November 2017, Johannesburg, South Africa
WHY sustainability transitions?
(Changes in temperature by 2050, A. Ruane)
High urgency for new agricultural frontiers in Southern Africa
Preparing for deeper change, to an unknown future
Governments buy in –new priorities for research, investment, policy directives
Representative Agricultural Pathways (RAPS)
Adapted from Valdivia et al. 2015
National Provincial
District
GlobalSSP, Global RAPs,
Economic models and socio-economic conditions
Prices, production trends
RegionalRegional RAPS, CCAFS scenarios
Key drivers that are likely to affect future bio-physical and
socio-economic conditions
Dri
vers
Co
nsisten
cy
RCP 8.5RCP 4.5
Better understand interplay
of key drivers, how these
may influence development
outcomes
Antle et al. 2015
Regional Integrated Assessments (AgMIP RIA)
Protocol-based approach
• Integrated modeling framework (climate, crops,
livestock, whole farm economics)
• Evaluate pathway/scenario uncertainties under
future climate, bio-physical, socio-economic
conditions
• Scaling down, up scenarios, interventions through
stakeholder engagement (disaggregation,
aggregation)
ww
j
w
B. Complex farming systems under different climate change scenarios
+2to3oC
Precipitationvariable:adecreaseby25%ispossible
Illustrate possible change for
multiple farm sub-systems, in
particular farming contexts
under future bio-physical and
socio-economic conditions
Co-learning process, researchers with stakeholders
Joint acknowledgement that
incremental change is insufficient
to lift farmers out of poverty
Co-design transitions to more
transformative sustainable
farming systems
Prepare more conducive context
for farming, where options cannot
be tested in real life situations
Inform future-oriented policy
and investment processes, at
multiple scales and building on
and scaling out existing initiatives
and partnerships.
Current agricultural systems
High poverty (85% below poverty line at 1.25 US/day), with
extremely low productivity (maize yield < 500 kg/ha)
High potential for integrated interventions (technologies,
institutions, policies) to increase on-farm profitability and
improve adaptation to climate change.
• Step 1. Crop management that increases biomass
production per unit land e.g. increasing planting
densities, improved dual purpose varieties
(>100% increased cereal yields)
• Step 2. Reconfiguration of farms for activities that
dominate the net returns, e.g. expanding groundnuts;
supplementary fodder and concentrate feeding
( > 200% increased groundnut yields)
• Step 3. Market incentives that drive improved crop and
livestock management, mechanized harvesting and
processing (overall 100-330% increased farm net
returns)
Extremely poor Poor Non-poor
43%
38%
19% extremely poor
poor
non-poor
Extremelypoor
Poor Non-poor
Cultivated land (ha)
1.4 2.0 2.7
Cattle (TLU) 0 5.4 13.9
Family size 6 7 7
Farm heterogeneity in Nkayi district
-100
-50
0
50
100
150
200
250
300
Extremelypoor
Poor
Nonpoor
Extremelypoor
Poor
Nonpoor
Extremelypoor
Poor
Nonpoor
Step1 Step2 Step3
%changeinpoverty %changeinfarmnetreturns
-100
-50
0
50
100
150
200
250
300
350
Extrem
elypoor
Poor
Nonpoor
Extrem
elypoor
Poor
Nonpoor
Extrem
elypoor
Poor
Nonpoor
Step1 Step2 Step3
%changeinpoverty %changeinfarmnetreturns
-100
-50
0
50
100
150
200
250
300
350
Extrem
elypoor
Poor
Nonpoor
Extrem
elypoor
Poor
Nonpoor
Extrem
elypoor
Poor
Nonpoor
Step1 Step2 Step3
%changeinpoverty %changeinfarmnetreturns
Extremelypoor
Poor Nonpoor
-100
-50
0
50
100
150
200
250
300
350
Extrem
elypoor
Poor
Nonpoor
Extrem
elypoor
Poor
Nonpoor
Extrem
elypoor
Poor
Nonpoor
Step1 Step2 Step3
%changeinpoverty %changeinfarmnetreturns
0
500
1000
1500
2000
2500
3000
3500
Step1 Step2 Step3
Totalfarm
netretu
rns(U
SD)
Extremelypoor Poor Nonpoor
0
500
1,000
1,500
2,000
2,500
3,000
3,500
Base Step1 Step2 Step3
Totalfarm
netreturns(USD)
Extremelypoor Poor Nonpoor
Future agricultural systems
RAP 4: “Green Zimbabwe”
Combined with RCP 4.5 and SSP 1, policy
orientation towards sustainability
- Set more land in value (all)
- Expand legumes (all)
- Integrate soil fertility management (all)
- Increase herd sizes (all)
RAP 5: “Grey Zimbabwe”
Combined with RCP 8.5 and SSP3, ineffective
global institutions, barriers to trade
- Market oriented farmers
- Expand land and herd sizes
- Intensify inorganic soil fertility
- Food security oriented farmers
- Maintain maize and goats
- Work off-farm
Climate change adaptation package:
Based on transformational changes in context,
the adaptation package would consist in the
adoption of drought and heat tolerant varieties/
Agricultural Pathways and Scenarios (RAPS)
5Now 2050
BusinessasUsual
Impacts on crop grain yieldsMaize Groundnuts
Cereals
Climate change impacts
Under improved soil fertility, cereals are sensitive to
climate change, regardless of models and soil type
• -ve effects RAP 5 > RAP4, soil 3>2>1 with
inorganic soil fertility improvement
• -ve effects under HD scenarios, +ve effects
under HW scenarios
Climate change adaptation
• Regaining crop life cycle reduces –ve effect of
CC on maize
• +ve effects RAP 4> RAP 5, DSSAT> APSIM
(stronger response to interactions between T,
H2O and N)
• +ve effects better soil> poor soil
Legumes
Climate change impacts
Legumes are slightly sensitive to climate change
under APSIM, stable under DSSAT
• -ve effects RAP 5 > RAP4, across soil types
• -ve effects under HD scenarios, +ve effects
under HW scenarios
Climate change adaptation
• Drought tolerance reduces –ve impacts of CC on
groundnuts
• +ve effects RAP 4> RAP 5, DSSAT > APSIM
(stronger response to CO2 and available water)Soil type Soil type
poor average better poor average better poor average better poor average better
Impacts on
farm milk production
APSIM DSSAT
1 2 3 1 2 3
0
1000
2000
3000
4000
5000
Ave
rag
e a
nnua
l m
ilk p
rodu
ction
(kg fa
rm−
1)
labels
RAP4_Base
RAP5_Base
RAP4_HD
RAP4_HW
RAP5_HD
RAP5_HW
RAP4_HD_AP
RAP4_HW_AP
RAP5_HD_AP
RAP5_HW_AP
Extremely
poorPoor Non
poorExtremely
poorPoor Non
poor
Climate change impacts
• Similar -ve effects under both RAPS and
crop model inputs
• -ve effects under HD scenarios, +ve effects
under HW scenarios
• Non-poor hit hard and more at risk
• With supplementary feed concentrates –
cattle are less dependent on on-farm feed
production.
Climate change adaptation
• Limited effects of crop improvement
Economic impacts of climate change adaptation (HD, HP, DSSAT)
Where productivity is currently extremely low, e.g.
Nkayi district, investments in sustainability pathways
(technologies, institutions, policies) can reduce
vulnerability and half poverty by 2050
Lower poverty, and greater impact of adaptation under
RAP 4, especially for the extremely poor – gender,
food security, nutrition
0
20
40
60
80
100
2015 2025 2035 2045 2055Povetyrate(%ofpeoplelivingfrom
lessthan1.25USD
perday)
current Ifwecontinuebusinessasusual
ifweinvestinfasteconomicgrowth ifweinvestinsustainabledevelopment
Farm types Vulnerability
(%)
Poverty
without
adaptation
(%)
Poverty
with
adaptation
(%)
%
change in
poverty
rate
Extremely poor 26 53 47 -12
Poor 46 25 21 -16
Non poor 38 15 12 -17
Aggregate 37 35 31 -13
Extremely poor 49 84 82 -2
Poor 60 33 29 -13
Non poor 64 22 18 -16
Aggregate 58 53 50 -6
RAP
4
RAP
5
Climate change impacts
• Vulnerability RAP 5 > RAP 4
• Extremely poor less
vulnerable, for both RAPs
• Vulnerability of those with
cattle due to feed gaps
Climate change adaptation
• Lower poverty rate and
stronger impact of climate
change adaptation under
RAP 4, especially for the
extremely poor
Discussion: scenarios informing future oriented
technologies, institutions, policies Challenge: Prepare enabling environment for scaling climate change
adaptation, under uncertain futures
Approaches and solutions – clearly acknowledged by decision makers
• Scenarios as projections for defining desirable trajectories, research
priorities and investment options, prepare future conditions for farming
• Having improved farm management today, adaptation to climate
change becomes easier
• Sustainability pathways to reduce poverty and mitigate destitution,
strengthening the link between women, food security and nutrition
Possible development outcomes – learning on guidance and influence
• Science to fasten decision processes (technical + political) along
desired trajectories (credibility, legitimacy, confidence, ownership)
• Out of the box testing of transformative interventions, about future
worlds that matter, for diverse farming systems
• Broader look at food systems, incl. gender, climate change,
extreme events, conflict prevention
• Bridge communication science and stakeholders, not only on
passing information, but analyses and implementation
Scaleofimpact
Intensityofimpact Farmingcommunities
PrivatesectorSupportservices
Enablers