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Livestock, human welfare, and sustainability: The challenge of harmonizing farmer interview data from 30+ countries and conducting coherent analyses

  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 ZXYFm100rVM
  18. This presentation is licensed for use under the Creative Commons Attribution 4.0 International Licence. better lives through livestock ilri.org ILRI thanks all donors and organizations which globally support its work through their contributions to the CGIAR Trust Fund

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