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Effects of climate change on feed
availability and the implications
for the livestock sector

P. Havlík, D. Leclere, H. Valin, M. Herrero, E. Schmid, M. Obersteiner
International Institute for Applied Systems Analysis (IIASA), Austria
Commonwealth Scientific and Industrial Research Organisation (CSIRO), Australia
University of Natural Resources and Life Sciences in Vienna (BOKU), Austria

Mainstreaming Livestock Value Chains: Conference
Accra, Ghana, November 5-6, 2013
Introduction


Climate change impacts on livestock







Quality and quantity of feed
Heat stress
Diseases and disease vectors
Water

Adaptation response is complex



Crop management
(sowing dates, fertilizers, irrigation rates,…)
Switch to a different production system







irrigated  rainfed
grass based  mixed crop livestock)

Switch to a different production activity
(new crop, livestock species,…)
Change in the volume of production
Source: Arblaster et al. 2013 (IPCC AR5)



Modeling tools need to be adapted




2



Climate change is a global phenomenon
CC impacts vary across space
CC impacts natural environment
Adaptation in production

 global context
 high spatial resolution
 link to biophysical models
 explicit technology
Methodological approach


Modelling chain integration

Climate

Biophysical

Economic

General
circulation
models:
5 GCMs

Global
gridded
crop models:
EPIC
LPJmL

Partial
equilibrium
model:
GLOBIOM



HadGEM2-ES, IPSL-CM5A-LR, GFDL-ESM2M, MIROC-ESM-CHEM, NorESM1-M

x 2 Crop models


EPIC, LPJmL

 uncertainty across 10 different inputs
3

ΔYield

Yield, Area,
Consumption,
Trade change

5 GCMs




ΔT°C
ΔPrec.
ΔCO2
Gridded structure for crop and grass
HRU = Altitude & Slope & Soil

Altitude class, Slope class,
Soil Class
PX5
PX5
Altitude class (m): 0 – 300, 300 – 600, 600 – 1200, 1200 – 2500 and > 2500;
Slope class (deg): 0 – 3, 3 – 6, 6 – 10, 10 – 15, 15 – 30, 30 – 50 and > 50;

LC&LUstat

Soil texture class: coarse, medium, fine, stony and peat;

Simulation Units (SimU)
 HRU
 50x50km grid
 Country boundaries
> 200.000 SimUs

Country

HRU*PX30

SimU delineation related
statistics on LC classes and
Cropland management systems
PX5

reference for geo-coded data on crop management;
input statistical data for LC/LU economic optimization;

4

Source: Skalský et al. (2008)
Cropland productivity from EPIC

EPIC
Evaporation
and
Transpiration

Rain, Snow,
Chemicals

Surface
Flow

Below Root
Zone

Subsurface
Flow
Grasslands productivity

(t/ha DM)

6

Source: EPIC model
GLOBIOM: model general structure








7

Partial equilibrium model on land use at global scale
(endogenous prices balance supply and demand)
 Agriculture, forestry and bioenergy
 30 economic regions
 Bilateral trade flows
Supply defined at the grid cell resolution
 Bottom-up sectoral models for biophysical consistency
 Explicit technology by production system
All market balanced consistent with FAOSTAT
Optimization of the social welfare
 Maximizing producer + consumer surplus
 Non-linear expansion costs
 Resource and technology constraints
Long term: base year 2000, recursively dynamic (10 year periods)
8
Livestock sector coverage



Livestock categories:
Gridded Livestock of World
(Wint and Robinson 2007)








Bovines: Dairy & Other
Sheep & Goats: Dairy & Other
Poultry: Laying hens, Broilers,
Mixed
Pigs

Production systems:
Seré and Steinfeld (1996) classification


Ruminants





Monogastrics



9

Grass based: Arid, Humid,
Temperate/Highlands
Mixed crop-livestock: Arid, Humid,
Temperate/Highlands
Smallholders
Industrial
Production systems parameterization


Reconciliation with FAOSTAT data

Herrero, Havlík et al., forthcoming

10
Results: biophysical impact on feed
Change in yield compared to NoCC [%]

11
Impact on production
Change compared to 2000 [%]

12
Impact on prices
Change compared
to 2000 [%]

13

Change compared to NoCC [%]
Composition of ruminant diets by production system
World average [%]

14
Adaptation through livestock systems switches
Absolute change in percentage shares of ruminants by system

15
Land use requirements
Land cover change between 2000 and 2050 [Mha]

16
Food availability
Change to 2000 [%]

17

Change to NoCC [kcal/cap/day]
Trade
Absolute change in share: net trade / (supply+demand)

18
Conclusions


When looking at feed availability
 Impact of climate change on livestock is expected to be positive
 Ruminant production benefits more than monogastric systems
 Increase pressure from grassland expansion



But still uncertain
 Depends on crop model and response to CO2 fertilization
 Adaptation responses matter






Production systems switches
Possibilities of reallocation to least affected regions
Trade

Further research on this field should benefit from integrated
modelling approaches to capture links between
grassland, cropland and the livestock production and markets
Thank you for your attention
Questions…



20

www.globiom.org

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Effects of climate change on livestock feed availability and adaptation

  • 1. Effects of climate change on feed availability and the implications for the livestock sector P. Havlík, D. Leclere, H. Valin, M. Herrero, E. Schmid, M. Obersteiner International Institute for Applied Systems Analysis (IIASA), Austria Commonwealth Scientific and Industrial Research Organisation (CSIRO), Australia University of Natural Resources and Life Sciences in Vienna (BOKU), Austria Mainstreaming Livestock Value Chains: Conference Accra, Ghana, November 5-6, 2013
  • 2. Introduction  Climate change impacts on livestock      Quality and quantity of feed Heat stress Diseases and disease vectors Water Adaptation response is complex   Crop management (sowing dates, fertilizers, irrigation rates,…) Switch to a different production system     irrigated  rainfed grass based  mixed crop livestock) Switch to a different production activity (new crop, livestock species,…) Change in the volume of production Source: Arblaster et al. 2013 (IPCC AR5)  Modeling tools need to be adapted    2  Climate change is a global phenomenon CC impacts vary across space CC impacts natural environment Adaptation in production  global context  high spatial resolution  link to biophysical models  explicit technology
  • 3. Methodological approach  Modelling chain integration Climate Biophysical Economic General circulation models: 5 GCMs Global gridded crop models: EPIC LPJmL Partial equilibrium model: GLOBIOM  HadGEM2-ES, IPSL-CM5A-LR, GFDL-ESM2M, MIROC-ESM-CHEM, NorESM1-M x 2 Crop models  EPIC, LPJmL  uncertainty across 10 different inputs 3 ΔYield Yield, Area, Consumption, Trade change 5 GCMs   ΔT°C ΔPrec. ΔCO2
  • 4. Gridded structure for crop and grass HRU = Altitude & Slope & Soil Altitude class, Slope class, Soil Class PX5 PX5 Altitude class (m): 0 – 300, 300 – 600, 600 – 1200, 1200 – 2500 and > 2500; Slope class (deg): 0 – 3, 3 – 6, 6 – 10, 10 – 15, 15 – 30, 30 – 50 and > 50; LC&LUstat Soil texture class: coarse, medium, fine, stony and peat; Simulation Units (SimU)  HRU  50x50km grid  Country boundaries > 200.000 SimUs Country HRU*PX30 SimU delineation related statistics on LC classes and Cropland management systems PX5 reference for geo-coded data on crop management; input statistical data for LC/LU economic optimization; 4 Source: Skalský et al. (2008)
  • 5. Cropland productivity from EPIC EPIC Evaporation and Transpiration Rain, Snow, Chemicals Surface Flow Below Root Zone Subsurface Flow
  • 7. GLOBIOM: model general structure      7 Partial equilibrium model on land use at global scale (endogenous prices balance supply and demand)  Agriculture, forestry and bioenergy  30 economic regions  Bilateral trade flows Supply defined at the grid cell resolution  Bottom-up sectoral models for biophysical consistency  Explicit technology by production system All market balanced consistent with FAOSTAT Optimization of the social welfare  Maximizing producer + consumer surplus  Non-linear expansion costs  Resource and technology constraints Long term: base year 2000, recursively dynamic (10 year periods)
  • 8. 8
  • 9. Livestock sector coverage   Livestock categories: Gridded Livestock of World (Wint and Robinson 2007)      Bovines: Dairy & Other Sheep & Goats: Dairy & Other Poultry: Laying hens, Broilers, Mixed Pigs Production systems: Seré and Steinfeld (1996) classification  Ruminants    Monogastrics   9 Grass based: Arid, Humid, Temperate/Highlands Mixed crop-livestock: Arid, Humid, Temperate/Highlands Smallholders Industrial
  • 10. Production systems parameterization  Reconciliation with FAOSTAT data Herrero, Havlík et al., forthcoming 10
  • 11. Results: biophysical impact on feed Change in yield compared to NoCC [%] 11
  • 12. Impact on production Change compared to 2000 [%] 12
  • 13. Impact on prices Change compared to 2000 [%] 13 Change compared to NoCC [%]
  • 14. Composition of ruminant diets by production system World average [%] 14
  • 15. Adaptation through livestock systems switches Absolute change in percentage shares of ruminants by system 15
  • 16. Land use requirements Land cover change between 2000 and 2050 [Mha] 16
  • 17. Food availability Change to 2000 [%] 17 Change to NoCC [kcal/cap/day]
  • 18. Trade Absolute change in share: net trade / (supply+demand) 18
  • 19. Conclusions  When looking at feed availability  Impact of climate change on livestock is expected to be positive  Ruminant production benefits more than monogastric systems  Increase pressure from grassland expansion  But still uncertain  Depends on crop model and response to CO2 fertilization  Adaptation responses matter     Production systems switches Possibilities of reallocation to least affected regions Trade Further research on this field should benefit from integrated modelling approaches to capture links between grassland, cropland and the livestock production and markets
  • 20. Thank you for your attention Questions…  20 www.globiom.org