1) The document presents findings from a study examining the adoption of climate-smart agriculture practices through a gendered intersectionality lens in Western Kenya. 2) The study found that both female and male farmers were aware of and using climate-smart practices, and that women were just as likely or more likely to adopt practices as men. 3) However, factors like education level, ethnicity, age, marital status and asset ownership intersected with gender to influence levels of adoption of different practices.

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Adoption of Climate-Smart Agriculture through a
Gendered Intersectionality Lens: Experiences from
Western Kenya
Presentation made at the “Symposium on Climate Change Adaptation in Africa", Addis
Ababa, Ethiopia, 21-23 February 2016
Catherine Mungai – CIRCLE Post-Masters Fellow
Supervisors: Drs. Maggie Opondo and George Outa, UON
Mentors: Drs. James Kinyangi and Mary Nyasimi, CCAFS/ILRI
Advisor: Valerie Nelson, NRI

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Presentation Outline
• About CIRCLE
• Introduction
• Objectives
• Study area description
• Methodology
• Findings
• Conclusion & Recommendations
• Key references
• Acknowledgements

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What is CIRCLE
• Climate Impact Research Capacity and Leadership Enhancement in Sub-
Saharan Africa (CIRCLE) - Initiative of the Department for International
Development (DFID)
• Develop the skills and research output of early career African researchers in the
field of climate change and development.
• Implementation by the Association of Commonwealth Universities (ACU) and
the African Academy of Sciences (AAS)
• Target - Post-Masters and Post-Doctoral Fellows. More information -
https://www.acu.ac.uk/focus-areas/early-careers/circle/

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Introduction
• Emerging evidence shows that climate change and variability presents
challenges for agricultural production in Africa (IPCC, 2014;Thornton et al.,
2006).
• Kenya has in recent years had its share of climate-related impacts: prolonged
droughts; frost; hailstorms; extreme flooding; receding lake levels; drying of
rivers and other wetlands etc. leading to large economic losses and adversely
impacting food security (GoK, 2013).
• Climate-smart agriculture (CSA) offers unique opportunities to improve food
security and enhance adaptation to climate change and reduce greenhouse
gas emissions at local scales. (AGRA, 2014; FAO, 2012).

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Introduction
• Determinants of adoption of CSA technologies and
practices include socio-cultural and economic factors at
all levels (Adesina & Chianu, 2002).
• Physiological, behavioral and socio-institutional factors
also influence how communities react to climate related
stress (Gifford, 2011).
• In depth understanding of the political, economic,
environmental and socio-cultural factors that influence
the uptake of CSA technologies and practices at local
scales.

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Introduction
• Individuals and communities experience the impacts of climate change differently
depending on their position in society, as determined by gender, race, class,
ethnicity, religion, and age, among other factors (Beuchelt & Badstue, 2013; IPCC,
2014; Nelson et al., 2002; Ray‐Bennett, 2009; Skinner, 2011).
• Adoption rates and trends amongst the farmers are also influenced by life
experiences, needs, issues and priorities which vary for different groups of men
and women.

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Climate-smart agriculture
As concept aims to sustainably improve
agricultural productivity, increase
farmers’ resilience, reduce and/or
remove greenhouse gas emissions, and
support the achievement of food-security
and development goals (FAO, 2012).
Intersectionality
• ‘Inequalities are never the result of single,
distant factors. Rather, they are the
outcomes of intersections of different social
locations (i.e. race/ethnicity, gender, class,
age , socio-economic status , religion etc)
power relations and experiences’
(Hankivsky, 2014)
• Intersectionality as an analytical tool
recognizes that how individuals relate to
climate change depends on their positions
in context-specific power structures based
on social categorizations. (Kaijser &
Kronsell, 2014)
Key Concepts
Gender
The relations between men and
women, both perceptual and
material (FAO, 1997)

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Objectives
1. To identify the CSA technologies and practices different
categories of female and male farmers are adopting.
2. To examine how factors such as age, ethnicity, education,
marital status intersect with gender to influence the uptake
of CSA technologies and practices.

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A map showing Nyando CSVs (Source: https://ccafs.cgiar.org/atlas-
ccafs-sites#East Africa)
• Lower Nyando Basin in western
Kenya - Nyakach sub-County in
Kisumu County and Soin- Sigowet
sub-county in Kericho County
• Low productivity, erratic rainfall
and severe soil erosion
• CCAFS Climate-smart villages
since 2011
• Luo and Kalenjin communities
neighboring each other
Study Area

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• Mixed method design – Survey and FGDs
• Purposeful sampling to ensure the following considerations: gender, age,
ethnicity, education, marital status. Also ensure selection of CCAFS CSV
farmers
Methodology
• Data Collection Methods:
 Focus Group Discussions (different categories of men
and women farmers)
 Survey (different categories of men and women
farmers)
• Data analysis – SPSS, thematic and content analysis

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Results

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CSA technologies and practices %HH aware of and using CSA practices and technologies
Male Female Total n (51)
Improved high yielding varieties (HYVs) 53.1 46.9 96.1
Scientific weather forecasting 52.2 47.8 92
Efficient fertilizer use 52.3 47.7 86.3
Cover cropping 50 50 82.4
Improved stress tolerant varieties (STVs) 54.8 45.2 82.4
Manure management 43.9 56.1 80.4
Terraces/bunds 51.3 48.7 78
Agroforestry 56.8 43.2 72.5
Integrated pest management 45.9 54.1 72.5
Destocking 61.1 38.9 70.6
Crop residue mulching 51.5 48.5 64.7
Water harvesting 51.6 48.4 62
Composting 55.2 44.8 58
Improved feed management 61.5 38.5 51
Adoption of resilient livestock breeds 60.9 39.1 46
Traditional weather forecasts 38.1 61.9 41.2
Tree nurseries 63.2 36.8 37.3
No/minimum tillage 41.2 58.8 34
Green house production 40 60 19.6
Gender
Both female and male
are aware and using CSA
interventions
Women are just as likely,
or more likely to adopt
CSA practices as men –
when aware

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Education lens
0
10
20
30
40
50
60
70
Green houses HYVs STVs Agroforestry Tree Nurseries Terraces Feed management Destocking Resilient breeds
Crop related CSA Technologies and practices SLM related CSA Technologies and practices Livestock related CSA Technologies and practices
%Households
None Primary Secondary Post secondary

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Ethnicity Lens
0
10
20
30
40
50
60
Green houses HYVs STVs Agroforestry Tree Nurseries Terraces Feed
management
Destocking Resilient breeds
Crop related CSA Technologies and practices SLM related CSA Technologies and practices Livestock related CSA Technologies and practices
%Households
Luo Kalenjin

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Age lens
0
10
20
30
40
50
60
70
80
90
Green houses HYVs STVs Agroforestry Tree Nurseries Terraces Feed
management
Destocking Resilient
breeds
Crop related CSA Technologies and
practices
SLM related CSA Technologies and
practices
Livestock related CSA Technologies and
practices
%Households
<15 yrs 15-64 yrs >64 yrs
Dependency Ratio

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Marital Status
0
10
20
30
40
50
60
70
80
Green houses HYVs STVs Agroforestry Tree Nurseries Terraces Feed
management
Destocking Resilient breeds
Crop related CSA Technologies and practices SLM related CSA Technologies and practices Livestock related CSA Technologies and practices
%Households
Single without partner Married living together Married living apart Divorced/Separated/Widowed

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Assets use and access
• Asset ownership and access is highly correlated to economic status,
gender, educational level, sources of income and position in the household
• Unmarried women with children and unmarried youth own few assets and
have limited access to some.
• Married women unable to buy or sell even small animals without consulting
their husbands.
• Cultural norms hindering women from having large animals.
• Men both young and old, married or single able to migrate freely in and out
of the home.
• For all categories of men and women farmers membership to social groups
is determined by access to membership fees.

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Other factors influencing uptake
• Enabling frameworks – institutions and policy (credit, insurance,
safety nets etc.)
• Financing and investments for CSA.
• Availability of CSA inputs and technology.
• Psychological, behavioral and socio-institutional.
• Cultural factors that determine selection of preferred crops and
varieties.
• Increased labor requirements, an inability to use technologies and
equipment.

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Conclusion and Recommendations
• The interplay between gender dimensions and other
factors such as social norms influence how the
community deals with the changing climate.
• To make progress towards a gender equity goal,
attention must be given to the interrelated issues of
social structure, and relations that define the interactions
between men and women.
• Placing emphasis on climate-smart interventions that
are likely to be beneficial to different categories of men
and women in different households is important.

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Key References
• AGRA. (2014). Africa agriculture status report: Climate change and smallholder agriculture in sub-Saharan Africa. nairobi,
Kenya Alliance for Green Revolution in Africa.
• FAO, (2012), Gender and Climate Change Research in Agriculture and Food Security for Rural Development Training Guide,
Rome: Food and Agriculture Network.
• Förch, W., Sijmons, K., Mutie, I., Kiplimo, J., Cramer, L., Kristjanson, P., . . . Bhatta, G. (2013). Core Sites in the CCAFS
Regions: East Africa, West Africa and South Asia Version 3: Copenhagen, Denmark: CCAFS.
• Mango et al., (2011), Summary of Baseline Household Survey Results: Lower Nyando, Kenya. CGIAR Research Program on
Climate Change, Agriculture and Food Security (CCAFS).
• Hankivsky, O. (2014). Rethinking Care Ethics: On the Promise and Potential of an Intersectional Analysis. American Political
Science Review, 108(02), 252-264.
• IPCC. (2014). Climate Change 2014: Impacts, Adaptation, and Vulnerability.
• Kaijser, A., & Kronsell, A. (2014). Climate change through the lens of intersectionality. Environmental politics, 23(3), 417-433.
• Nelson, V., Meadows, K., Cannon, T., Morton, J., & Martin, A. (2002). Uncertain predictions, invisible impacts, and the need to
mainstream gender in climate change adaptations. Gender & Development, 10(2), 51-59.
• Ray‐Bennett, N. S. (2009). Multiple disasters and policy responses in pre‐and post‐independence Orissa, India. Disasters,
33(2), 274-290.
• Skinner, E. (2011). Gender and climate change: Overview report: Bridge.

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This research is supported by funding from the Department for International
Development (DfID) under the Climate Impact Research Capacity and Leadership
Enhancement (CIRCLE) programme.
Acknowledgment

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THANK YOU! ASANTE!