Presented by James Hammond, Léo Gorman, Simon Fraval, Mark van Wijk at the 9th Multi-Stakeholder Partnership Meeting of the Global Agenda for Sustainable Livestock, Manhattan, Kansas, 9-13 September 2019

1. Livestock, human welfare, and sustainability: the
challenge of harmonizing farmer interview data
from 30+ countries and conducting coherent
analyses
James Hammond, Léo Gorman, Simon Fraval and Mark van Wijk
9th Multi-Stakeholder Partnership Meeting of the Global Agenda for Sustainable
Livestock, Manhattan, Kansas, 9-13 September 2019

2. Livestock, Human Welfare, Sustainability
Contributions
• Assets, sources of income
• Nutritious food supply
• Make use of plant matter inedible to humans
• Provide energy and land management
• Genetic Diversity
Risks
• GHGs
• Human health from over-consumption of animal
sourced foods
• Undesirable ecosystem impacts
• Diseases, anti-microbial resistance

3. Can we move beyond single-site
studies?
Can we harmonise data
between many sites and many
studies?

4. How we build “big data” on smallholder
farms – using the RHoMIS tool
The Rural Household Multi-
Indicator Survey
• A system for building farm
household surveys (<1h length), giving
a general overview of farm system
• Used in development and research
projects, for scoping and monitoring
• Produces standardised and
harmonised data
Hammond et al Ag Sys 2017
+ optional modules and
bespoke questions

5. www.rhomis.org
>28,000 interviews
in 31 countries

6. All the data are now
harmonized in terms of content
We can do some nice analyses
But how to overcome
differences in sample design?

7. Livestock descriptions by African region
Drop Southern AfricaPool data from large
number of
households, but with
no claim to spatial
representation

8. Chickens – surprisingly little egg
consumption

9. Ownership and Use of Cattle
– by wealth tercile

10. Ownership and Use of Cattle

11. Milk Productivity and Genetic Stock

12. Do the animals eat crop residues?
East West Central
Can this lead towards more nuanced GHG
calculations?

13. Role of livestock in Female Control of
Income and Foodstuffs
Tavenner et al, 2019, Frontiers in Sus Food Sys
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1
Female control over crop-related decision making
Crop Sales Crop Consumption
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1
Female control over livestock related
decision making
Sales Consumption
livesale meat eggsmilk
2,859 households analysed
in KE, TZ, ET.
Households are mixed
agriculture <2ha farmers.
Pool data from
projects with
compatible sampling
strategies for greater
spatial coverage

14. Role of Livestock in Household Nutrition
6300 households in 8 countries
Fraval et al. Frontiers in Sust. Food Syst., in press
Countries:
BF
CD
KE
UG
TZ
ML
MW
ET
Relate sampled
households to farm
typologies

15. Towards Scaling: Typologies and AEZ
method
no off-farm inc
land cultivated small land cultivated medium land cultivated large land cultivated
livestock holdings little/none medium large medium large little/none medium large
commercial focus low sales
crops -
medium
sales
crops - high
sales
mixed -
medium
sales
livestock
- high
sales
mixed
- high
sales
low
sales
low sales
crops -
medium
sales
low
sales
livestock -
high sales
mixed -
medium
sales
crops -
medium
sales
crops
- high
sales
crops -
medium
sales
crops
- high
sales
mixed -
medium
sales
letter A B C D E F G H I J K L M N O P Q
AEZ present cool
semiarid,
warm
subhumid,
warm
humid
warm
semiarid,
cool
semiarid,
warm
subhumid,
cool
subhumid,
cool humid
warm
subhumid,
warm
humid
warm
semiarid,
cool
semiarid
cool
semiarid,
warm
humid,
cool
humid
cool
humid
cool
humid
cool
semiarid
warm
subhumid
warm
humid
warm
semiarid,
warm
subhumid,
warm
humid,
cool humid
cool
subhumid
warm
subhumid,
cool
subhumid
warm
humid
cool
humid
warm
humid
cool
semiarid
• >45,000 observations,
from multiple sources
• Identify common farm
types across regions
• Need to evaluate
blindspots in AEZs
• Modelling to upscale

16. Summary
• We welcome collaboration to compile farm
system data through our RHoMIS tool or other
datasets
• Rich potential to answer basic questions about
the ways in which livestock are used in LMICs,
and the impacts on sustainable development
• Bringing together other data types may permit
scaling observations over large areas by use of
typologies

17. There are lots of Sustainability Indicators to
consider
Icon Indicator Median Unit
Staple crop yield 2.0 t ha-1
yr-1
Crop value 1720 USD ha-1
yr-1
Crop diversity 5 species grown
Milk yield 1.5 litres cow-1
day-1
Lstk value 120 USD TLU-1
yr-1
Lstk diversity 3 species kept
Total Value
Activities
1.4 USD person-1
day-1
Income Sources 5 count
Market
Orientation
70 % produce sold
Off Farm Income 0 USD household-1
yr-1
PPI (asset score) 68 % chance out of poverty
GHG emissions 3.7 tCO2eq pers-1
yr-1
Irrigation 3 months yr-1
Land
Conservation
6 count of practices
Soil Quality 2 farmer perception (0-3)
HFIAS (hunger) 4 Severe to no experience of hunger (1-4)
Months Food
Secure
12 months yr-1
Diet Diversity 5 food groups consumed weekly (0-10)
Education 3 ordinal (1-7)
Novel Practices
Trialled
3 count over last 5 years
Female Assets
Owned
3
Assets owned or co-owned by females
(0-4)
Female Income
Control
30
% of income and produce controlled by
females
Dependency
Ratio
95 ratio of non-workers:workers
Group
membership
2 group membership yr-1
Extension
received
9
extension services frequency and quality
(1-18)
Skill sharing 4 count dissemination of skills
Gifts and
exchange
2 count substantial gifts yr-1
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18. This presentation is licensed for use under the Creative Commons Attribution 4.0 International Licence.
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