GSFS_XTM_May2015

1. An Update on the IMPACT-Livestock Module
D. Enahoro, S. Nelgen, S. Robinson, D. Mason-D’Croz,
Global Futures and Strategic Foresight Extended Team Meeting
Arbitart Hotel, Rome
25 – 28 May, 2015

2. Outline
•The IMPACT model &
Livestock
•Baseline and suggested
changes
•Livestock systems
characterization
•Yield response
•Feed supplies
•Herd growth
representation
•Feed demand allocation
•Next steps

3. Re: The IMPACT Model System
Climate models
Macro-
economic
trends
Crop models
Water
demand
trends
Hydrology, water
basin management
and stress models
IMPACT multi-
country, multi-
market
Outputs
Source: Rosegrant et al., 2014
trade
prices
production yields
harvested area
Figure 1: IMPACT System

4. Livestock in IMPACT v 2.0
Sector Representation:
• 6 commodities – beef, milk,
chicken meat, lamb, pork, eggs
• Supply modelled at level of food
production units (FPUs)
• Country-level demand responsive
to income, population trends,
commodity prices
• Internationally-traded feed grains
and concentrates
IMPACT projections to 2050
(Rosegrant et al., 2012 ):
• Expansion in demand for meat,
dairy, cereals, livestock feeds
• Higher prices of major
agricultural commodities

5. Important Gaps Identified
• Heterogeneity in production
systems not recognized
• Important livestock feed
dimensions ignored
• Non-accounting for feed
constraints on sector
expansion
• Herd dynamics largely missing
• Addressed in Msangi et. al.,
2014 (using IMPACT v2.0)
• v3.0 compatibility needed

6. Revisions to Livestock representation in IMPACT
Original Specification Suggested Updates
Supply response is relatively
homogenous within countries
Livestock supply disaggregated by system
types (intensive/extensive)
Livestock feed basket composed only
of internationally-traded feeds (mostly
coarse grains and meals)
Pasture grasses, crop residues and
occasional feeds added to livestock
feeding possibilities
Yield is exogenously determined, and
does not respond to quantity or quality
of fed rations
Meat and milk response functions are
endogenous, responding to changes in
feed quantities and nutritive values
Total herd size includes milk-producing
and slaughtered meat animals only
Total herd count includes replacement
and/or follower herds in dairy and meat
production
Animal productivity only indirectly
affected but not affected by feed
availability through price effects
Explicit feed-availability constraints
imposed on animal productivity
Source: Msangi et al., 2014
Table 1: Original specification of livestock in IMPACT and
key changes to model

7. Global Livestock Production
Source: FAO, 2011Figure 2: Global Livestock Production Systems

8. Production Systems Disaggregation in IMPACT
Following Kruska et al., 2002; FAO, 2011
1. Rangeland-Based:
•Hyper-Arid/Arid/Semi-Arid
•Humid/Sub-Humid
•Temperate/Tropical Highlands
2. Mixed (Irrigated and Rainfed):
•Hyper-Arid/Arid/Semi-Arid
•Humid/Sub-Humid
•Temperate/Tropical Highlands
3. Urban
4. Other

9. Production Systems Disaggregation in IMPACT
System-specific data for IMPACT 3.3:
1. Livestock populations – producer herds and stocks
2. Meat, milk, egg production per unit livestock
3. Per unit feed intake
4. Biomass availability in FPU-system

10. Distributions of Livestock Globally
Fig 2: Distribution of Cattle in Livestock
Systems in Developed Countries
Fig 3: Distribution of Cattle in Livestock Systems in Developing Countries
Fig 4: (Percent) Distribution of
Sheep and Goat in Global Livestock
Systems
Mixed
Rangeland
Urban
Other
Mixed
Rangeland
Urban
Other
0
10
20
30
40
50
60
Developed
Countries
Developing
Countries
Source:
Havlik et al.,
2011

11. System-Specific Yields
Region Mixed Extensive Urban Other
Beef Developed
countries
239 82 126 105
Developing
countries
66
(28)
52
(63)
78
(62)
56
(53)
Bovine
Milk
Developed
countries
8,323 6,273 5,515 5,826
Developing
countries
2,794
(34)
1,388
(22)
2,165
(39)
2,067
(35)
Shoat
Milk
Developed
countries
1,619 632 1,989 2,284
Developing
countries
729
(45)
433
(69)
616
(31)
733
(32)
Table 2: Mean Yields of Meat (Kilograms / tlu / year) and Milk
(Litres / tlu / year) by Global Livestock Production Systems
Source: Authors’ own calculations from Havlik et. al., 2011

12. The Yield Response Equations
))(11(  
d
fljdfljdfljflj XLogExpYH 
• Feed-responsive yields: Log-Linear and Quadratic functional forms
)1(2  
d
fljdfljdfljflj XYH 
)2( 
d e
fljefljdfljde XX
For YH - meat/milk yields; α – yield intercept; β - coefficient on feed variable; X -
feed intake in Mt/tlu/year; f – food production unit; l – livestock production system;
j – disaggregated livestock commodity and d, e - feed variable for grains,
pastures, residues and occasional feeds. Equation 1 is the default. Equation 2 is
applied to the fpu-system-commodity subset for which it is empirically relevant.
Eqn. 2. Revised Yield I
Eqn. 3. Revised Yield II
nittnitni YLgLYYL ,1)1( 
• The baseline yield equation with exogenous trajectory
Eqn. 1. Exogenous Yield

13. Feed Response of Livestock Yields
•Livestock production (in MTs per TLU per year)
generated from work at ILRI and IIASA
• Feed sources from four major categories:
o Grains and residues (FAO feed
commodities)
o Residues
o Grasses (grazing, cut-and-carry)
o Occasional feeds (kitchen wastes, non-
FAO)
•Simulation data generated from RUMINANT
livestock nutrition model
•FPU-systems would not switch feeding regime
in the projection years
•“Sites” of production could shift with feed
availability

14. Alternative Livestock Feed Supplies
•Crop grain-residue conversion factors from
ILRI/ICRISAT work (Blummel; Herrero et al.,)
(QN is stover dry matter from crop type b, in FPU f and livestock
system l ; QS is crop grain b production; c-, util-, and DM- fact
are grain conversion, feed utilization, and dry matter factors,
respectively)
•Occasional feeds modeled in base year to
bridge gap between feeds locally available, and
animal nutrition dietary requirements
•Pasture availability estimated from grassland
area and productivity layers (Havlik et al., 2011)
 flbflbflbflb utilfactcfactQSQN
flbDMfact Eqn. 5. Stover Production

15. Pasture Productivity
Figure 2: Global grassland productivity

16. Ruminant Numbers Accounting
Suggested:
•Distinguish meat and
milk herds/producers
•Further disaggregate
follower animals
•Account for feed
demand of entire herd
•Impose feed
availability limitations
on herd expansion, esp.
in mixed and extensive
systems
•Include in accounting
of CC effects on
livestock

17. Livestock Numbers Response
• Follower numbers incorporating region-specific
natural birth/herd growth rates
• Price- responsiveness of cull/off-take for meat
meat milk fllw
t t t tN N N N  
where N is animal numbers; C is the animals culled for meat, g are
herd-specific growth rates, ϴ is the share of animals in the meat herd
that are culled in period t;
Total Numbers growth 1 (1 )nmbr
t t t tN N C g    
, ( ) 1meat
t cull t cull meatC N f P    
Total Numbers at time t
Cull/slaughter
• From FAO data we observe milk animals (𝑁𝑡
𝑚𝑖𝑙𝑘
),
the animals culled (𝐶𝑡) and the total herd (𝑁𝑡)
• Back-out follower numbers (𝑁𝑡
𝑓𝑙𝑙𝑤
) and 𝑁𝑡
𝑚𝑒𝑎𝑡
that
are consistent with the data

18. Revised Feed Demand (for marketed feeds)
 , , ,r b r b r bPI

  
π = Share allocated to each marketed feed
QL = Demand for marketed feed
PI = The effective intermediate (feed) price
diet = Dietary requirement per animal
N = Total number of animals (including followers)
MktFeed = Feed ratio
β = Feed demand intercepts
PI = The effective intermediate (feed) price
b = Commodity indices specific to feed crops
where:
l = Commodity indices specific to livestock
γ = Price elasticity of feed demand
, ,
total
r b r b rQL MktFeed 
, , , ,
,
total
r l sys FPU l sys FPU
b mktFeeds l sys FPU
MktFeed N diet

   
Share to each marketed feed good
Allocation across sum of marketed feeds
The total demand for marketed feeds as a function of diets and numbers

19. Projections of other feed demand
Simpler treatment of non-marketed feeds:
• Crop grain-residue: availability increases with
crop production
• Pastures: fixed by given grassland area and
productivity (don’t have means of modeling
changes to this presently, inclu. CC-related)
• Occasional feeds: held constant at base year
values (change according to scenarios?)
, ,
avail
r nmf r nmfQL nonMktFeed
Essentially, a strict constraint on availability

20. IMPACT v 3 - Specific Features
Introducing simple value chain specifications
Ranch Meat
Processing
Country
Market
Cows
Meat products

21. IMPACT v 3 - Specific Features
Introducing simple value chain specifications
Ranch Meat
Processing
Country
Market
Cows
Meat products
Feed
Supplies I

22. IMPACT v 3 - Specific Features
Introducing simple value chain specifications
Ranch Meat
Processing
Country
Market
Cows
Meat products
Feed
Supplies I
Global
Market
Feed
Supplies II

23. Status of Migration to IMPACT v 3
• ‘Stand-alone’ module in livestock
• FPU disaggregated by livestock production
system – parameterized using data from
GLOBIOM model
• Livestock numbers and feed demand re-
balanced to match FAO values
• Unit/scaling issues addressed
• Module tested for one country (US) and two
years
• Well behaved so far!
• Test to extend to multiple country and years

24. Next Steps and Timelines
• Revised completion date end of June 2015
• Case study validation in months following
• Baseline and alternative scenario
development in consultation with livestock
biosciences, environment and policy experts
• Paper on ex-ante analysis of livestock
technologies by December 2015
• Climate change, policy, related modeling in
2016
• Explore feed optimization and other features
…

25. Thank You!
Questions and Discussion

26. Acknowledgements
This work has received support from:
The Bill and Melinda Gates Foundation
The CGIAR Research Program on Climate Change,
Agriculture and Food Security (CCAFS)
The CGIAR Research Program on Policies,
Institutions, and Markets (PIM)

27. The presentation has a Creative Commons licence. You are free to re-use or distribute this work, provided credit is
given to ILRI.
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