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Climate Smart Agriculture in Zambia Programme 2016-2021
A not for profit NGO formed in 1995
โ€ข Operations currently in Zambia, Tanzania, Uganda and Kenya
and providing TA services in Mozambique, Madagascar, Ghana
and Mali
โ€ข Programmes: UNDP/GEF , RCASP, CSAZ and and 3 others
CFU- Our Current Mandate
โ€ข Accelerate and deepen the adoption of conservation and
climate smart agricultural practices; with a view to balancing
food security and livelihood needs with priorities for
adaptation and mitigation
โ€ข Identify and promote innovative technologies and practices
that can be applied to increase CA/CSA adoption; to better
manage climate risks and impacts
โ€ข Facilitate and contribute to the strengthening of agricultural
market systems; to enhance the benefits of CA and CSA
Where do we operate?
TYPE OF CA PROMOTED IN
ZAMBIA
Systems have been developed for Hoe, ADP and
Mechanised farmers cultivating from 0.5 ha to
50ha and above
There is also considerable emphasis on private
ADP and Mechanised MT service provision
We conduct Research to test technology and most importantly to provide evidence
on CA and CSA and guide our interventions
Our research may be inhouse or outsourced. It maybe scientific or
socio-economic
HOUSEHOLD ECONOMY OUTCOME ANALYSIS
FOR IMPACT ASSESSMENT OF THE
CLIMATE SMART AGRICULUTURE โ€“ ZAMBIA (CSAZ)
โ€ข The Outcome Analysis was aimed at clearly establishing existing
food deficits/surpluses,
โ€ข Seek to establish whether or not it makes any difference to be a
CA adopter or not in terms of household food security.
โ€ข Calculate values for the two Impact level Indicatorsโ€
โ€“ Impact Indicator 1: Proportion of Households above the Survival
Threshold
โ€“ Impact Indicator 2: Proportion of Households above the
Resilience/Livelihood Protection Threshold
Livelihood Zones in CFU Region District
Commercial Rail line Maize, Livestock and cotton โ€“ ZM08 Chongwe
Mazabuka
Southern Plateau Cattle, Maize and Tobacco โ€“ ZM09 Choma
Eastern Plateau Maize, Cotton, and Groundnut โ€“ ZM16 Katete
Eastern Plateau Maize, Groundnut, Tobacco and Trade โ€“ ZM17 Chipata
BASELINE + HAZARD/INTERVENTION + COPING = OUTCOME
Livelihood
Zoning
Wealth
Breakdown
Livelihood
Strategies
Problem
Specification
Analysis of
Coping
Projected
Outcome
Livelihood Baseline Data
(The context)
Monitoring Data
(The changes)
+
On-going Analysis of Current
and Projected Situation and
Intervention Needs
(The outcome)
Adop
.
Conv
.
Adop
.
Conv
.
Adop
.
Conv
.
Adop
.
Conv
.
ZM08 ZM09 ZM16 ZM17
Maize -28% -60% -22.00 -48.00 -12% -35% -15% -35%
Groundnuts -21% -44% -12.00 -39.00 -13% -37% -7% -33%
-70%
-60%
-50%
-40%
-30%
-20%
-10%
0%
Currentproductionas%ofbaseline
Both categories of
farmers were affected by
the drought
But adopters consistently
performed better than
their Conventional
farming counterparts
There were several Key
Parameters but for the
sake of the presentation
we used only 2
Margin of difference in the Fall
ZM08 ZM09 ZM16 ZM17
Maize 32% 26% 23% 20%
Groundnuts 23% 27% 24% 26%
On Average,
Conventional
Farmers fell short of
the Adopters by
25% for both
cereals and legumes
Here we calculate the
difference between
the magnitude of the
fall from baseline
values (Conventional -
Adoptersโ€™ fall)
Loosely translated,
what this means is
that โ€œIn the event of
adverse climatic
conditions,
conventional farmers
are the worst affected
while Adopters are
cushionedโ€.
Thus, in the face of the drought,
Adopters were 32% above
conventional farmers in Zone
ZM08; Adopters were
comparatively LESS affected by
adverse Climatic conditions
Conventi
onal
Adopters
Conventi
onal
Adopters
VP. Baseline VP. Current
wild foods/other 1% 1% 1% 1%
firewood/charco
al
3% 2% 2% 2%
self employment 16% 18% 15% 17%
agric. labour 82% 80% 67% 60%
livestock sales 2% 2% 2% 6%
crop sales 2% 4% 0% 0%
crops 46% 60% 29% 45%
LP/Threshold 13% 13% 13% 13%
Surv. Threshold 116% 116% 116% 116%
WG = VP
Zone= ZM08
Note that during baseline
both adopters and
conventional farmers were
well above the ST and the
LPT
But after adverse climatic
conditions, conventional farmers
barely reached the ST and fell far
below the LPT. Adopters were
indeed affected but not in the same
drastic way as to make them fall
below the LPT
WG = VP
Zone= ZM16
Convent
ional
Adopter
s
Convent
ional
Adopter
s
VP. Baseline VP. Current
agric. labour 91% 88% 91% 86%
livestock sales 2% 4% 3% 5%
crops 72% 56% 27% 44%
LP/Threshold 18% 18% 18% 18%
Surv.
Threshold
111% 111% 111% 111%
The same story is
repeated in
Livelihood Zone
ZM16.
Livelihood Zone ZM16 presents a very
interesting picture and perhaps makes the
adoption narrative even bolder!
Check the Baseline; Conventional farmers
were actually faring better than Adopters!!
But ONE season of adverse climatic
conditions quickly showed that Conservation
is indeed Climate Smart!
WG = P
Zone= ZM17
Conventi
onal
Adopters
Conventi
onal
Adopters
P. Baseline P. Current
Small business 33% 33% 33% 33%
Petty trading 44% 46% 40% 52%
local labour 62% 65% 62% 62%
agric. labour 54% 44% 35% 104%
livestock sales 13% 13% 13% 13%
crop sales 54% 78% 46% 66%
crops 54% 75% 36% 53%
LP/Threshold 73% 73% 73% 73%
Surv. Threshold 121% 121% 121% 121%
Take note of the fact that Households in this zone pursue a
variety of livelihoods due to their proximity to Malawi
This is a zone where the
contribution of Agriculture
to the HH economy is
heavily supported by
other livelihoods and
hence households here
are less ravaged by the
vagaries of nature.
2018 Impact Indicator Values
Indicator Wealth
Group
Adopting
Households
Conventional
Farmers
Impact Indicator 1:
Proportion of
Households above
the Survival
Threshold
Very Poor 100% 100%
Poor 100% 100%
Middle 100% 100%
Better-Off 100% 100%
Impact Indicator 2:
Proportion of
Households above
the Resilience/
Protection Threshold
Very Poor 16% 0%
Poor 26% 14%
Middle 33% 24%
Better-Off 35% 29%
Averages โ€“ Proportion of Population
above LPT
Ado
pt.
Con
v
Ado
pt.
Con
v
Ado
pt.
Con
v
Ado
pt.
Con
v
VP Poor Middle
Better
Off
Above Resilience 16% 0% 26% 14% 33% 24% 35% 29%
16% More 12% More 11% More 6% More
Key Recommendation
๏ƒผ Bring a human face to the impact evaluation (evidence from program participants) by
employing other more qualitative methodologies so as to clearly bring out
explanations and attributions to the programme. Such methods could be case studies
or the use of the Most Significant Change (MSC) stories be also added.
0.000
0.050
0.100
0.150
0.200
0.250
0.300
0.350
01.11.17
04.11.17
07.11.17
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Moisutrecontent(vol/vol)
Choma growing season 2017-2018
MEAN.Conventional_mยณ/mยณ VWC MEAN.CF_rip_mยณ/mยณ VWC MEAN.CF_rip_manure_mยณ/mยณ VWC MEAN.CF_rip_BC_mยณ/mยณ VWC
Moisture content (vol/vol) based on the average of 4 blocks per treatment in Choma.
TDR soil moisture data from our sites 2017-2018 season
Soil moisture data from our sites 2018-2019 season
0.000
0.050
0.100
0.150
0.200
0.250
0.300
0.350
01.11.18
04.11.18
07.11.18
10.11.18
13.11.18
17.11.18
20.11.18
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26.11.18
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10.04.19
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20.04.19
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26.04.19
29.04.19
Moisturecontent(vol/vol)
Choma growing season 2018-2019
MEAN.Conventional_mยณ/mยณ VWC MEAN.CF_rip_mยณ/mยณ VWC MEAN.CF_rip_manure_mยณ/mยณ VWC MEAN.CF_rip_BC_mยณ/mยณ VWC
Fig. 3. Moisture content (vol/vol) based on the average of 4 blocks per treatment in Choma. Growing season 2018-19.
soil moisture data from our sites to include dry season
0.000
0.050
0.100
0.150
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0.300
0.350
13.10.17
22.10.17
31.10.17
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10.05.19
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28.05.19
06.06.19
14.06.19
23.06.19
02.07.19
Moisturecontent(vol/vol)
Choma 13.10.17 to 09.07.19
MEAN.Conventional_mยณ/mยณ VWC MEAN.CF_rip_mยณ/mยณ VWC MEAN.CF_rip_manure_mยณ/mยณ VWC MEAN.CF_rip_BC_mยณ/mยณ VWC
Fig. 4. Moisture content (vol/vol) based on the average of 4 blocks per treatment in Choma. 13.10.17 to 09.07.19.
CFU CSAZ Training versus
Adoption Figures โ€“ Year 1,
Year 2 and Year 3
Number of farmers Trained
Actual Number of Farmers
Adopting
Year 2016 137336 91466
Year 2017 259251 106293
Year 2018 268692 143482
Year 2016 Year 2017 Year 2018
Actual Number of Farmers
Adopting
91466 106293 143482
% of Farmer Adopting
Minimum Tillage
66.6% 41.0% 53.4%
3. 2018 Farmer Training
โ€ข The first CSAZ Output: โ€œZambian
farming families depending on
rain fed agriculture trained in
CSA practicesโ€
โ€ข The Milestone for 2018 season
was training 216,000 (Of which
women: 45%).
โ€ข 268,692 is the total number of
farmers trained and 49.5% were
women.
โ€ข 2019 trainings are currently on-
going
Male Female Disabled
All Regions 135,764 132,928 3,880
Promotional events- these are aimed at showcasing technology
and also trying to influence policy.
Some promotional events target policy makers
Minister of Agriculture being trained โ˜›
โ† Presidential briefing on CA at his farm
Financing and markets
Lead farmers as in-community agents and commodity
aggregators (private sector involvement).
-linkages to financial markets, financial literacy and lease
schemes
-on-farm research centres
Value for Money 1:11.73

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Conservation farming unit presentation: Climate Smart Agriculture in Zambia Programme 2016-2021: regional conservation agriculture dialogue meeting

  • 1. Climate Smart Agriculture in Zambia Programme 2016-2021
  • 2. A not for profit NGO formed in 1995 โ€ข Operations currently in Zambia, Tanzania, Uganda and Kenya and providing TA services in Mozambique, Madagascar, Ghana and Mali โ€ข Programmes: UNDP/GEF , RCASP, CSAZ and and 3 others
  • 3. CFU- Our Current Mandate โ€ข Accelerate and deepen the adoption of conservation and climate smart agricultural practices; with a view to balancing food security and livelihood needs with priorities for adaptation and mitigation โ€ข Identify and promote innovative technologies and practices that can be applied to increase CA/CSA adoption; to better manage climate risks and impacts โ€ข Facilitate and contribute to the strengthening of agricultural market systems; to enhance the benefits of CA and CSA
  • 4. Where do we operate?
  • 5. TYPE OF CA PROMOTED IN ZAMBIA Systems have been developed for Hoe, ADP and Mechanised farmers cultivating from 0.5 ha to 50ha and above There is also considerable emphasis on private ADP and Mechanised MT service provision
  • 6. We conduct Research to test technology and most importantly to provide evidence on CA and CSA and guide our interventions Our research may be inhouse or outsourced. It maybe scientific or socio-economic
  • 7. HOUSEHOLD ECONOMY OUTCOME ANALYSIS FOR IMPACT ASSESSMENT OF THE CLIMATE SMART AGRICULUTURE โ€“ ZAMBIA (CSAZ)
  • 8. โ€ข The Outcome Analysis was aimed at clearly establishing existing food deficits/surpluses, โ€ข Seek to establish whether or not it makes any difference to be a CA adopter or not in terms of household food security. โ€ข Calculate values for the two Impact level Indicatorsโ€ โ€“ Impact Indicator 1: Proportion of Households above the Survival Threshold โ€“ Impact Indicator 2: Proportion of Households above the Resilience/Livelihood Protection Threshold
  • 9. Livelihood Zones in CFU Region District Commercial Rail line Maize, Livestock and cotton โ€“ ZM08 Chongwe Mazabuka Southern Plateau Cattle, Maize and Tobacco โ€“ ZM09 Choma Eastern Plateau Maize, Cotton, and Groundnut โ€“ ZM16 Katete Eastern Plateau Maize, Groundnut, Tobacco and Trade โ€“ ZM17 Chipata
  • 10. BASELINE + HAZARD/INTERVENTION + COPING = OUTCOME Livelihood Zoning Wealth Breakdown Livelihood Strategies Problem Specification Analysis of Coping Projected Outcome
  • 11. Livelihood Baseline Data (The context) Monitoring Data (The changes) + On-going Analysis of Current and Projected Situation and Intervention Needs (The outcome)
  • 12.
  • 13. Adop . Conv . Adop . Conv . Adop . Conv . Adop . Conv . ZM08 ZM09 ZM16 ZM17 Maize -28% -60% -22.00 -48.00 -12% -35% -15% -35% Groundnuts -21% -44% -12.00 -39.00 -13% -37% -7% -33% -70% -60% -50% -40% -30% -20% -10% 0% Currentproductionas%ofbaseline Both categories of farmers were affected by the drought But adopters consistently performed better than their Conventional farming counterparts There were several Key Parameters but for the sake of the presentation we used only 2
  • 14. Margin of difference in the Fall ZM08 ZM09 ZM16 ZM17 Maize 32% 26% 23% 20% Groundnuts 23% 27% 24% 26% On Average, Conventional Farmers fell short of the Adopters by 25% for both cereals and legumes Here we calculate the difference between the magnitude of the fall from baseline values (Conventional - Adoptersโ€™ fall) Loosely translated, what this means is that โ€œIn the event of adverse climatic conditions, conventional farmers are the worst affected while Adopters are cushionedโ€. Thus, in the face of the drought, Adopters were 32% above conventional farmers in Zone ZM08; Adopters were comparatively LESS affected by adverse Climatic conditions
  • 15. Conventi onal Adopters Conventi onal Adopters VP. Baseline VP. Current wild foods/other 1% 1% 1% 1% firewood/charco al 3% 2% 2% 2% self employment 16% 18% 15% 17% agric. labour 82% 80% 67% 60% livestock sales 2% 2% 2% 6% crop sales 2% 4% 0% 0% crops 46% 60% 29% 45% LP/Threshold 13% 13% 13% 13% Surv. Threshold 116% 116% 116% 116% WG = VP Zone= ZM08 Note that during baseline both adopters and conventional farmers were well above the ST and the LPT But after adverse climatic conditions, conventional farmers barely reached the ST and fell far below the LPT. Adopters were indeed affected but not in the same drastic way as to make them fall below the LPT
  • 16. WG = VP Zone= ZM16 Convent ional Adopter s Convent ional Adopter s VP. Baseline VP. Current agric. labour 91% 88% 91% 86% livestock sales 2% 4% 3% 5% crops 72% 56% 27% 44% LP/Threshold 18% 18% 18% 18% Surv. Threshold 111% 111% 111% 111% The same story is repeated in Livelihood Zone ZM16. Livelihood Zone ZM16 presents a very interesting picture and perhaps makes the adoption narrative even bolder! Check the Baseline; Conventional farmers were actually faring better than Adopters!! But ONE season of adverse climatic conditions quickly showed that Conservation is indeed Climate Smart!
  • 17. WG = P Zone= ZM17 Conventi onal Adopters Conventi onal Adopters P. Baseline P. Current Small business 33% 33% 33% 33% Petty trading 44% 46% 40% 52% local labour 62% 65% 62% 62% agric. labour 54% 44% 35% 104% livestock sales 13% 13% 13% 13% crop sales 54% 78% 46% 66% crops 54% 75% 36% 53% LP/Threshold 73% 73% 73% 73% Surv. Threshold 121% 121% 121% 121% Take note of the fact that Households in this zone pursue a variety of livelihoods due to their proximity to Malawi This is a zone where the contribution of Agriculture to the HH economy is heavily supported by other livelihoods and hence households here are less ravaged by the vagaries of nature.
  • 18. 2018 Impact Indicator Values Indicator Wealth Group Adopting Households Conventional Farmers Impact Indicator 1: Proportion of Households above the Survival Threshold Very Poor 100% 100% Poor 100% 100% Middle 100% 100% Better-Off 100% 100% Impact Indicator 2: Proportion of Households above the Resilience/ Protection Threshold Very Poor 16% 0% Poor 26% 14% Middle 33% 24% Better-Off 35% 29%
  • 19. Averages โ€“ Proportion of Population above LPT Ado pt. Con v Ado pt. Con v Ado pt. Con v Ado pt. Con v VP Poor Middle Better Off Above Resilience 16% 0% 26% 14% 33% 24% 35% 29% 16% More 12% More 11% More 6% More
  • 20. Key Recommendation ๏ƒผ Bring a human face to the impact evaluation (evidence from program participants) by employing other more qualitative methodologies so as to clearly bring out explanations and attributions to the programme. Such methods could be case studies or the use of the Most Significant Change (MSC) stories be also added.
  • 21. 0.000 0.050 0.100 0.150 0.200 0.250 0.300 0.350 01.11.17 04.11.17 07.11.17 10.11.17 13.11.17 16.11.17 19.11.17 22.11.17 25.11.17 28.11.17 01.12.17 04.12.17 07.12.17 10.12.17 13.12.17 16.12.17 19.12.17 22.12.17 25.12.17 28.12.17 31.12.17 03.01.18 06.01.18 09.01.18 13.01.18 16.01.18 19.01.18 22.01.18 25.01.18 28.01.18 31.01.18 03.02.18 06.02.18 09.02.18 12.02.18 15.02.18 18.02.18 21.02.18 24.02.18 27.02.18 02.03.18 05.03.18 08.03.18 11.03.18 14.03.18 17.03.18 20.03.18 23.03.18 27.03.18 30.03.18 02.04.18 05.04.18 08.04.18 11.04.18 14.04.18 17.04.18 20.04.18 23.04.18 26.04.18 29.04.18 Moisutrecontent(vol/vol) Choma growing season 2017-2018 MEAN.Conventional_mยณ/mยณ VWC MEAN.CF_rip_mยณ/mยณ VWC MEAN.CF_rip_manure_mยณ/mยณ VWC MEAN.CF_rip_BC_mยณ/mยณ VWC Moisture content (vol/vol) based on the average of 4 blocks per treatment in Choma. TDR soil moisture data from our sites 2017-2018 season
  • 22. Soil moisture data from our sites 2018-2019 season 0.000 0.050 0.100 0.150 0.200 0.250 0.300 0.350 01.11.18 04.11.18 07.11.18 10.11.18 13.11.18 17.11.18 20.11.18 23.11.18 26.11.18 29.11.18 03.12.18 06.12.18 09.12.18 12.12.18 15.12.18 19.12.18 22.12.18 25.12.18 28.12.18 31.12.18 04.01.19 07.01.19 10.01.19 13.01.19 17.01.19 20.01.19 23.01.19 26.01.19 29.01.19 02.02.19 05.02.19 08.02.19 11.02.19 14.02.19 18.02.19 21.02.19 24.02.19 27.02.19 02.03.19 06.03.19 09.03.19 12.03.19 15.03.19 18.03.19 22.03.19 25.03.19 28.03.19 31.03.19 04.04.19 07.04.19 10.04.19 13.04.19 16.04.19 20.04.19 23.04.19 26.04.19 29.04.19 Moisturecontent(vol/vol) Choma growing season 2018-2019 MEAN.Conventional_mยณ/mยณ VWC MEAN.CF_rip_mยณ/mยณ VWC MEAN.CF_rip_manure_mยณ/mยณ VWC MEAN.CF_rip_BC_mยณ/mยณ VWC Fig. 3. Moisture content (vol/vol) based on the average of 4 blocks per treatment in Choma. Growing season 2018-19.
  • 23. soil moisture data from our sites to include dry season 0.000 0.050 0.100 0.150 0.200 0.250 0.300 0.350 13.10.17 22.10.17 31.10.17 08.11.17 17.11.17 26.11.17 05.12.17 14.12.17 23.12.17 31.12.17 09.01.18 18.01.18 27.01.18 05.02.18 14.02.18 22.02.18 03.03.18 12.03.18 21.03.18 30.03.18 08.04.18 16.04.18 25.04.18 04.05.18 13.05.18 22.05.18 31.05.18 08.06.18 17.06.18 26.06.18 05.07.18 14.07.18 23.07.18 31.07.18 09.08.18 18.08.18 27.08.18 05.09.18 14.09.18 22.09.18 01.10.18 10.10.18 19.10.18 28.10.18 06.11.18 14.11.18 23.11.18 02.12.18 11.12.18 20.12.18 29.12.18 06.01.19 15.01.19 24.01.19 02.02.19 11.02.19 20.02.19 28.02.19 09.03.19 18.03.19 27.03.19 05.04.19 14.04.19 22.04.19 01.05.19 10.05.19 19.05.19 28.05.19 06.06.19 14.06.19 23.06.19 02.07.19 Moisturecontent(vol/vol) Choma 13.10.17 to 09.07.19 MEAN.Conventional_mยณ/mยณ VWC MEAN.CF_rip_mยณ/mยณ VWC MEAN.CF_rip_manure_mยณ/mยณ VWC MEAN.CF_rip_BC_mยณ/mยณ VWC Fig. 4. Moisture content (vol/vol) based on the average of 4 blocks per treatment in Choma. 13.10.17 to 09.07.19.
  • 24. CFU CSAZ Training versus Adoption Figures โ€“ Year 1, Year 2 and Year 3
  • 25. Number of farmers Trained Actual Number of Farmers Adopting Year 2016 137336 91466 Year 2017 259251 106293 Year 2018 268692 143482
  • 26. Year 2016 Year 2017 Year 2018 Actual Number of Farmers Adopting 91466 106293 143482 % of Farmer Adopting Minimum Tillage 66.6% 41.0% 53.4%
  • 27. 3. 2018 Farmer Training โ€ข The first CSAZ Output: โ€œZambian farming families depending on rain fed agriculture trained in CSA practicesโ€ โ€ข The Milestone for 2018 season was training 216,000 (Of which women: 45%). โ€ข 268,692 is the total number of farmers trained and 49.5% were women. โ€ข 2019 trainings are currently on- going Male Female Disabled All Regions 135,764 132,928 3,880
  • 28. Promotional events- these are aimed at showcasing technology and also trying to influence policy.
  • 29. Some promotional events target policy makers Minister of Agriculture being trained โ˜› โ† Presidential briefing on CA at his farm
  • 30. Financing and markets Lead farmers as in-community agents and commodity aggregators (private sector involvement). -linkages to financial markets, financial literacy and lease schemes -on-farm research centres Value for Money 1:11.73