Engagement to help adapt Makueni County farming

systems to climate change and variability

AgMIP – 3rd February 2016

Guided by Makueni County Integrated Development Plan:

2013-2017 & Kenya vision 2030 County stakeholders include Research

institutions whose role is:

(i) Research on appropriate farming technologies

(ii) Research on viable crop and livestock

Ongoing CCAFS engagement

• Works with KALRO, ICRISAT, Makueni County Dept of Agric, Livestock & Fisheries, and farmers

• Pilot research involving participatory evaluation and promotion of integrated sorghum - legume technologies

• Led to the formation of two umbrella community based organisations

Research engagement informed by climate information

Research engagement informed by climate information

Previous and ongoing research engagement in Makueni

Look at the poster on “Making the best of our climate: Understanding your climate –Kampi ya Mawe”

Agricultural Model Intercomparison and Improvement Project (AgMIP) Adapting smallholder systems to climate change and variability through a stakeholder driven, multi-modeling integrated assessment approach

Climate in Wote is highly variable

How can farmers deal with the current climate variability?

TECHNO

LOGY

Below Normal

seasons

Normal seasons Above Normal

seasons

Sorghum

varieties

KARI MTAMA 1 Serena, seredo,

Gadam, KARI

Mtama 1

Serena, Seredo,

KARI Mtama 1,

Gadama

Climate information services: SR 2011 - 2013

CCAFS IMPACT Lite Datasets used. Pilot Site: Wote, Eastern

Kenya

Farm population from 2012 survey

Sample of 200 households from 10X10 km area

Presented with a choices, would farmers take them up?

Farm population w/base tech & base indicators

(poverty, sustainability)

Sub-populations: non-adopters (base tech & indicators) adopters (improved tech, indicators)

Adoption

Base system:

Improved system:

What is the adoption rate of the technology?

Impact on Returns to farm

Mean Net farm income increases by 25%

What is the impact on poverty?

OPP COST

Poverty Rate

for Entire

Population (%)

Poverty Rate

for Farmers in

System 1 (Non-

adopters)

Poverty Rate

for Farmers in

System 2

(Adopters)

-532.9163598 27.26289003 27.68907274 5.977902971

-399.6872699 26.16489055 27.69974175 7.747326501

-266.4581799 23.92081335 27.70372998 10.12546346

-133.22909 21.2686647 27.70418861 13.11977145

0 19.93299478 27.72135482 16.44532703

133.22909 20.49491456 27.77817315 19.45574063

266.4581799 21.71983028 27.88967714 21.49560583

399.6872699 22.49526587 28.06229064 22.45714271

532.9163598 22.76270381 28.29672655 22.7575542

Population poverty rate decreases by 7%

Is this enough incentive for farmers?

System approach including other elements??

What is feasible in Wote??

ICRISAT is a member of the CGIAR Consortium