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14 msangi impact_livestock


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  • 1. Livestock within a multi-market modeling framework: the example of IMPACT Siwa Msangi, Dolapo Enahoro An Notenbaert, Mario Herrero, Signe Nelgen Petr Havlik Conference on Mainstreaming Livestock Value Chains, Section 4: Data and Tools Best Western Premier Airport Hotel, Accra , Ghana. 5-6 Nov, 2013
  • 2. Livestock in the context of global agriculture  The challenge of modeling global agriculture comes from: • Representing the various linkages between markets – in terms of consumer choice behavior, linkages b/w output markets & important mkt inputs (e.g. labor, fertilizer) • Accounting for the scarcity of important inputs into production (land, water, feed, etc) – in quantity terms • Adequately representing the producer decisions and objectives (profit maximize/cost minimize/stock-holding) • Representing the heterogeneity of production systems • Differentiating behaviors for annual vs perennial activities Page 2
  • 3. Improving livestock representation in IMPACT  Starting from the IFPRI IMPACT model – we have been working to improve the representation of livestock – in a way that addresses these challenges  Have undertaken this in a number of steps • Disaggregate livestock production across systems • Capture differences in feed requirements across these systems • Link the availability of these feeds to what is available on the landscape or what can be obtained through markets  Has been a step-wise process, that has required rethinking some key aspects of how livestock is modeled Page 3
  • 4. Overview of model structure
  • 5. The Global Livestock Production Systems Source: FAO, 2011
  • 6. Distributions of Livestock 60 50 Mixed Rangeland 40 Urban Other 30 20 Developed Countries Developing Countries 10 Fig 2: Distribution of Cattle in Livestock Systems in Developed Countries 0 Mixed Rangeland Urban Fig 4: (Percent) Distribution of Sheep and Goat in Livestock Systems Other Fig 3: Distribution of Cattle in Livestock Systems in Developing Countries
  • 7. Key components of livestock modeling  Demand-side factors are similar to those for other nonlivestock commodities.  Food demand is mainly driven by • Per-capita income growth • Population • Urbanization (and other preference shifters)  Feed demand occurs for marketed and non-marketed feed products – whereas we observe marketed feeds in data, we have to calculate the non-marketed feed uses  This is often where FAOSTAT data do not agree with the feed demands derived from biophysical requirements for animal growth Page 7
  • 8. Consumption of Meat As people get richer they consume more animal products
  • 9. Key components of livestock modeling  The supply-side of agricultural markets are driven by both biophysical & economic drivers of change  Biophysical components relate to • Climate (temp, water) – determine biological stress • Soil quality – matters to vegetative growth (grasslands) • Animal growth and nutrient requirements  Economic factors relate to  Technological change (productivity, efficiency)  System change (extensive -> mixed -> intensive)  Animal numbers – monogastrics are annual activities, whereas ruminants have herd dynamics that reflect producer decisions and biophysical determinants  Yield per animal – relates to feed (availability & practices) Page 9
  • 10. Key components of livestock modeling  The key decisions we should model for livestock are: • Feed mix (across marketed & non-marketed feeds) • Stocking rates (has an implicit land use dimension) • Off-take and cull  The land use dimensions of livestock are complex and differ across systems (which we don’t capture well)    Extensive systems – needs to be explicit Mixed systems – depends on prodn of crop residues & availability of other supplementary feeds Intensive systems – has no explicit LU dimension  The land use dimensions of transhumance are entirely missed in much of the macro-modeling that is done Page 10
  • 11. Breakdown of Livestock Feed Demand for pasture & grass expected to grow the fastest IMPACT model (2013) Page 11
  • 12. Aquaculture Now a Major Meat Sector  In only 20 years, aquaculture has grown to nearly match the share of beef in global meat production Page 12
  • 13. Aquaculture: Fastest Growing Food Sector  Growth of aquaculture almost 2x as fast as other food/meat sectors Page 13
  • 14. Changes in Global Use of Fishmeal for Feed  Aquaculture ‘crowding out’ livestock for fishmeal feed use  Fishmeal and protein meals are substitutable, but with limits  Livestock (esp poultry) have been able to find substitutes for fishmeal more easily compared to fish Source: Shepherd (2012)
  • 15. Global Demand for Fishmeal from Livestock and Aquaculture IMPACT model (2013) Page 15
  • 16. Feed sourcing from co-products  Important co-products from industrial processes like biofuels production will continue to be used as feed IMPACT model (2013) Page 16
  • 17. The importance of co-products  The future success of the bioeconomy depends on the added-value of co-products derived from chemical conversion processes (e.g. DDGS from biofuels) – for use in important sectors such as livestock  When ‘by-products’ become ‘co-products’ (i.e. something to be used rather than disposed of) – then the commercial potential & profitability improves  The failure of jatropha to take off is due to low yields as well as limited co-product value for uses in animal feed (compared to other oilseeds) – needs more R&D  The processing waste from fish food preparation will become increasingly valuable source of feed for fish Page 17
  • 18. Summary & Implications for Policy The future for livestock (and fish) depends heavily on the ability to manage feed & disease  Gains in technical efficiency and sourcing of additional feeds will be critical for livestock and fish (fish & poultry are the most efficient feed converters)  Monogastrics & aquaculture will still compete for feed  Sharing of best practices in management is crucial Some key weaknesses in modeling livestock are:  Modeling rangeland/grassland availability  Relatively few biophysical models (compared to crops) – still don’t capture heat/water stress directly  Capturing the land-use dimensions still a challenge
  • 19. THANK YOU! See: