IV Global Science Conference on Climate Smart Agriculture Issues/research questions for the agriculture and food systems of 2050

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


-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


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


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


Legumes are slightly sensitive to climate change

under APSIM, stable under DSSAT

• -ve effects RAP 5 > RAP4, across soil types


under HW scenarios


• 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


• Similar -ve effects under both RAPS and

crop model inputs


under HW scenarios

• Non-poor hit hard and more at risk

• With supplementary feed concentrates –

cattle are less dependent on on-farm feed

production.


• 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


• Vulnerability RAP 5 > RAP 4

• Extremely poor less

vulnerable, for both RAPs

• Vulnerability of those with

cattle due to feed gaps


• 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

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Enablers

THANK YOU!

Government & Nonprofit

IV Global Science Conference on Climate Smart Agriculture Issues/research questions for the agriculture and food systems of 2050