variety for security: a case study in western kenya

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Variety for security: A case study in Western Kenya Mary Kanui, PhD student (Geography & Environment)

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Variety for security: A case study in Western Kenya. A presentation given by Mary Kanui, PhD student (Geography & Environment) Find out more about this research: http://www.bioversityinternational.org/news/detail/improving-nutrition-through-local-agricultural-biodiversity-in-kenya/

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Page 1: Variety for security: a case study in Western Kenya

Variety for security: A case study in Western Kenya

Mary Kanui, PhD student (Geography & Environment)28th August 2014

Page 2: Variety for security: a case study in Western Kenya

Outline

1. Background & objectives

2. Methods

3. Completed research: results3.1 Farm agrobiodiversity3.2 Market agrobiodiversity

4. Upcoming research: overview4.1 Nutrient diversity4.2 Dietary diversity

5. Conclusions & recommendations

Page 3: Variety for security: a case study in Western Kenya

Background & objectives

Page 4: Variety for security: a case study in Western Kenya

1. Agrobiodiversity as a path to household food security?

• Food security: availability, accessibility, utilization of adequate food

• Agrobiodiversity: components of biodiversity of relevance to food & agriculture

• In Africa, up to 80% of agriculture practised by smallholder farmers

• To what extent does agrobiodiversity contribute to food, nutrition & health?

Page 5: Variety for security: a case study in Western Kenya

1. Agrobiodiversity- Kenyan context

• Species numbers:• ~ 35,000 animal, plant & micro-organism species• 3 sustaining species: maize, wheat, rice (Ekesa, 2009)

• High food shortfalls and malnutrition rate• Yet local agrobiodiversity under-utilized as primary food security resource (Frison et al., 2006)

• Western Kenya:• High agrobiodiversity• But 50% population below poverty line with high malnutrition and poor health (Abukutsa-Onyango, 2002)

Page 6: Variety for security: a case study in Western Kenya

1. Study objectives

Food accessibility & market integration

Food plant diversity (animals and plants) & underlying factors

Functional diversity (animals and plants)

Dietary diversity (overall household, women)

Page 7: Variety for security: a case study in Western Kenya

Methods

Page 8: Variety for security: a case study in Western Kenya

2. Study sites

Teso southLM1, LM2

1550-1800 mm

Teso southLM1, LM2

1550-1800 mm

BondoLM 3-5

1020-1100 mm

BondoLM 3-5

1020-1100 mm

MumiasLM1

1800-2000 mm

MumiasLM1

1800-2000 mm

VihigaUM1

1800->2000 mm

VihigaUM1

1800->2000 mm

© Bioversity 2012

Page 9: Variety for security: a case study in Western Kenya

2. Research instruments

Farm survey

•Goals: 1) ABD richness, abundance& usage ( 2) food sources (3) dietary diversity (T3)

•Scope: 30 farms (0.37ha) in 6 villages

•Time: Sep/Oct ‘12(T1), Nov/Dec ‘12 (T2) & July/Aug ‘14 (T3)

Market survey

•Goal: Food sources, prices & availability

•Scope: 7 markets

•Time: Sep/Oct ‘12 (T1) & July/Aug ‘14 (T2)

Focus Group Discussions

•Goal: Perceptions on ABD by farmers (gender-disaggregated)

•Scope: 12 discussions

•Time: Sep/Oct ‘12

Page 10: Variety for security: a case study in Western Kenya

Results (completed research)

Page 11: Variety for security: a case study in Western Kenya

3.1 Farm agrobiodiversity

3. Completed research

3.2 Market agrobiodiversity

Page 12: Variety for security: a case study in Western Kenya

• Species: basic taxonomic unit for distinct organisms• Varieties: different types within a species naturally occurring• Cultivars: cultivated varieties

• Species richness: number of different distinct organisms• Species abundance: number of individuals per species

Differentiation of key terms

Page 13: Variety for security: a case study in Western Kenya

3.1.1 ABD (on-farm food plant) richness

Teso71 species

Teso71 species

Bondo72 species

Bondo72 species

Mumias48 speciesMumias

48 species

Vihiga 47 species

Vihiga 47 species

© Bioversity 2012

Page 14: Variety for security: a case study in Western Kenya

Sorghum Sorghum bicolorbicolor

VegetablesVegetables

Zea maysZea mays

CerealsCereals

Starchy rootsStarchy rootsPulses Pulses

PhaseolusPhaseolusvulgarisvulgaris

Saccharum Saccharum officinarum L.officinarum L.High-sugar foodsHigh-sugar foods

FruitsFruits

3.1.1 Most common plant ABD (Mumias & Vihiga)

Brassica Brassica oleraceaoleracea

VignaVignaunguiculataunguiculata

Ipomoea Ipomoea batatasbatatas

Persea Persea americanaamericana

Musa Musa sapientumsapientum

Capsicum Capsicum annuumannuum SpicesSpices

Page 15: Variety for security: a case study in Western Kenya

Sorghum Sorghum bicolorbicolor

VegetablesVegetables

Zea maysZea mays

CerealsCereals

Starchy rootsStarchy rootsPulses Pulses PhaseolusPhaseolus

vulgarisvulgaris

Saccharum Saccharum officinarum L.officinarum L.High-sugar foodsHigh-sugar foods

FruitsFruits

Commelina Commelina Spp.Spp.

BidensBidenspilosapilosa

ManihotManihotesculentaesculenta

Lantana Lantana camaracamara

Psidium Psidium guajavaguajava

3.1.1 Most common plant ABD (Teso & Bondo)

SpicesSpicesCapsicum Capsicum annuumannuum

Page 16: Variety for security: a case study in Western Kenya

3.1.1 ABD importance in the 2 agro-ecological zones

Summed Dominance Ratio (SDR) of food plant species

Page 17: Variety for security: a case study in Western Kenya

3.2.2 Factors influencing plant ABD

Species richness

Shannon index

Shannon evenness

Adjusted R2

Predictor variables

TLU/household member (0.00-0.41; TLU=Tropical Livestock Units)

Household head age (22-57)Farming years (0.5-30)Ethnicity of household head is Luhya (0=no, 1=yes)

Shannon index Diversity

Shannon evenness

Page 18: Variety for security: a case study in Western Kenya

3.2.2 Factors influencing plant ABDSpecies richness Shannon index Shannon

evennessAdjusted R2 49.1** 22.8** 25.8*

Predictor variables

TLU/household member (0.00-0.41; TLU=Tropical Livestock Units)

0.5*** ns ns

Household head age (22-57)

0.5** ns ns

Farming years (0.5-30) ns 0.5** 0.4*

Ethnicity of household head is Luhya (0=no, 1=yes)

ns ns 0.4*

For each of the predictor variables, standardized beta (β) coefficients are indicated. *, **and *** represent significant differences at p ≤0.05, p ≤0.01, p ≤0.001, respectively according to F-Test (for the model) or T-Test (for predictor variables)

Page 19: Variety for security: a case study in Western Kenya

3.1.2 Farm types: plant ABD composition

Minimum variance- Squared Euclidean - Data log(e) transformed density matrix

M-053M-060M-059M-092M-144M-054M-098M-099M-145M-148V-012V-071V-074M-056V-018V-121V-072M-100V-079V-078V-015V-020M-095V-123V-122V-126

720 600 480 360 240 120 0

‘Long-standing cereal-sweet potato’

‘Cereal’

‘Large sugarcane’

Page 20: Variety for security: a case study in Western Kenya

3.1.3 ABD & household food security: is there a relationship?

Proportion of on-farm food consumed during the last five times of consumption

No direct relationship between food plant ABD & household hunger scores

Page 21: Variety for security: a case study in Western Kenya

3.1 Farm agrobiodiversity: Summary

Importance of some food groups varies with agro-ecological zones

Food plant species richness is mainly influenced by socio-economic factors

There is no direct relationship

Page 22: Variety for security: a case study in Western Kenya

3.1 Farm agrobiodiversity

3. Completed research

3.2 Market agrobiodiversity

Page 23: Variety for security: a case study in Western Kenya

3.2.1 What is the role of markets in household food access?

(M)=Mumias, (V)= Vihiga Proportion of food sources during the last five times of consumption

Page 24: Variety for security: a case study in Western Kenya

3.2.2 What are the uses of on-farm produce?

(M)=Mumias, (V)= Vihiga Main food uses

Page 25: Variety for security: a case study in Western Kenya

3.2.3 What is the extent of smallholder market integration?

• Out of the interviewed market traders:

• 15%: smallholder farmers/part-time traders

•10%: small scale/travelling traders

•75%: large scale traders/ wholesalers

Page 26: Variety for security: a case study in Western Kenya

3.2 Market agrobiodiversity: Summary

Smallholders access from multiple sources

Smallholders produce food for both home consumption and for sale

Smallholders are least involved as sellers in formal markets

Page 27: Variety for security: a case study in Western Kenya

Overview (upcoming research)

Page 28: Variety for security: a case study in Western Kenya

4.1 Nutrient diversity

4. Upcoming research

4.2 Dietary diversity

Page 29: Variety for security: a case study in Western Kenya

4.1 Nutrient diversity• Species richness explains taxonomic identity, not functional identity

• Nutritional functional diversity metrics:• summarize nutritional diversity of cropping systems

• Previous studies: •Presence/absence-based functional diversity metric (Remans et al., 2011, DeClerck et al., 2011)

• Gap on abundance-based functional diversity metric:• Available data: abundance of on-farm food plants and livestock• Unavailable data: abundance of foods sourced off-farm

Page 30: Variety for security: a case study in Western Kenya

4.1 Nutrient diversity: key questions

What nutrients are available and what are missing for smallholders to have a diverse diet?

Using market price as proxy for food accessibility, how does food accessibility compare to income levels?

Page 31: Variety for security: a case study in Western Kenya

4.1 Nutrient diversity

4. Upcoming research

4.2 Dietary diversity

Page 32: Variety for security: a case study in Western Kenya

4.2 Dietary diversity

• Households with higher incomes can compensate for reduced on-farm ABD…

… but depends on who controls the income

• Subsistence-oriented crops viewed as women’s ‘domestic’ domain

•On-farm cultivation of nutritious foods…

… doesn’t translate to equal food access for all household members

Page 33: Variety for security: a case study in Western Kenya

4.2 Dietary diversity: key questions

How does food diversity vary across households, using 1-day and 7-day recalls?

Is there a relationship between agricultural and dietary diversity among these households?

Page 34: Variety for security: a case study in Western Kenya

Conclusions & recommendations

Page 35: Variety for security: a case study in Western Kenya

• Smallholder farmers utilize multiple channels to attain household food security

• Households with subsistence-oriented farming systems are not necessarily more food and nutrition secure

• Smallholder farmers need support to:– diversify more into high-value nutrient-dense crops and livestock

species (mention lydia’s concl.on ASFs to create connection)– get organised to fill in local market gaps & add value to surplus

(perishable) produce– improve access to formal markets & market traders

5. Conclusions & recommendations

Page 36: Variety for security: a case study in Western Kenya

• Supervisors:– Dr. Gudrun Keding (Bioversity)– Dr. Katja Kehlenbeck (ICRAF)– Dr. Patricia Daley (Oxford)– Dr. Shonil Bhagwat (Oxford)

• Funding sources:– Tuition funding at Oxford:

Rhodes Trust– Project funding at Bioversity:

GIZ-BMZ & CRP A4NH

• Plant specialists:– Patrick Maundu

Acknowledgements

• Smallholder farmers & market traders

• Local administration & contact persons

• Research assistants & data entry clerks

• INULA colleagues & Bioversity Staff

Page 37: Variety for security: a case study in Western Kenya

www.bioversityinternational.org

Thank you