John Garcia discussed palm oil expansion in Columbia

1. Reconciling targets for the environment,
development and oil palm expansion in Colombia
John Garcia‐Ulloa
Lian Pin Koh
Jaboury Ghazoul
Sean Sloan
Pablo Pacheco

2. Oil palm
 One of the most profitable oil crops in the world
 Wide range of uses
 Expansion driven by growing demand for food and energy
16'000
Indonesia
Malaysia
14'000
Nigeria
Americas
12'000
Rest of Africa
Area harvested (1000 ha)
10'000 Rest of South East Asia
8'000
6'000
4'000
2'000
0
1961
1963
1965
1967
1969
1971
1973
1975
1977
1979
1981
1983
1985
1987
1989
1991
1993
1995
1997
1999
2001
2003
2005
2007
FAOSTAT (2010)
Year

3. Oil Palm farming in Colombia
 5th largest producer in the
world
 2007: 316 402 ha cultivated
 75% planted area belongs
productive units > 500 ha

4. Government Policies on Oil Palm
 Key sector for making the transition to a higher
domestic use of Biofuels
 Key component in the government plans for
development of large scale agro‐industries in
Colombia.
Projections of national demand of biofuels.
Biofuel 2008 2010 2015 2020
Ethanol 61’660’680 62’346’768 81’925’066 115’711’178
Biodiesel 9’957’503 39’926’415 120’090’479 244’134’427
Colombian Ministry of Agriculture 2009

5. Expansion of oil palm cultivation in Colombia
Aim to increase crude palm oil production from 0.7 Mt/yr to
3.5 Mt/yr by 2020.
How this expansion will affect:
Food production systems?
Biodiversity and Ecosystems ?
Carbon stocks?

6. Can we reconcile the expansion of oil palm with
agricultural and environmental objectives?

7. Spatially‐explicit tradeoff analysis model
 Simulate the spatial pattern of oil palm expansion in
Colombia in different scenarios.
 Construction of scenarios
 Creation of a spatial database
 Modelling exercise

8. Scenario
Expansion rulea
Business as usual From areas with high yield potential for oil palm, close
to roads and established plantations, to areas with
lower scores for these variables
Agroindustry development Favouring conversion of areas with low yield potential
Single‐priority scenarios
for rice , maize and sugarcane
Ecosystem protection Expansion prioritized to areas with high level of human
intervention, minimizing transformation of natural
areas. Modified land uses ranked by profitability
(conversion prioritized to low profitable areas)
Carbon conservation Expansion prioritized to areas with low levels of above
and below ground carbon stocks
A combined scenario of all single priority scenarios
Hybrid approach (Multi‐priority
scenario)

9. Spatial data base
Land use cover Yield potential for oil palm Protection status
Forest Suitable (High) Protected
Pastures Not Suitable Not protected

10. Spatially‐explicit tradeoff analysis model
 Creation of a spatial database
 Land use cover (IGAC 2008)
 Vegetation carbon stocks (Above and below ground) (Ruesch &
Gibbs 2008)
 Yield potential for oil palm, rice, maize, sugarcane and soya
(based on soil and climate characteristics) (IIASA 2002)
 Location and extent of protected areas (minorities’ territories,
national parks) (IGAC 2008)
 Road network (IGAC 2008)
 Administrative divisions (IGAC 2008)
 Profitability of agricultural and ranching lands (Garcia‐Ulloa et al
2011)

11. Assigning probabilities of conversion to OP
 Land cover: Forest
 Distance to road network and
established plantation: <25 km
 Oil palm suitability: Very High
 Maize/Rice suitability: Marginal
 Sugarcane suitability: Marginal
 Carbon stored in biomass: 19300 t/ha
P(Business as usual): High P(Ecosystem conservation): Low
P(Food production): High P(Carbon): Low
P(hybrid): Medium

12. Modeling exercise
 The model then progressively converts polygons according to
the story line of each scenario
 Expansion only allowed in areas with a moderate or higher
suitability for oil palm.
 Measure 4 outcomes directly related to each of the scenarios.
 Land use change: Area converted to oil palm
 Ecosystem conversion and biodiversity losses
 Biomass carbon losses
 Food production capacity losses (Cereals and sugarcane)

13. What about impacts on livelihoods of
local communities?
 Lack of social explicit spatial data (census available but
very difficult to join to land use covers)
 Social impacts are difficult to model, we don’t know in
which ways oil palm development affects the
livelihoods of local communities:
 Business models: smallholders vs. large companies
 Absorption of local labour?
 Does it generate income to local goverments?

14. Results
The results from this research will be soon published (II
semester 2011), for further information on this project
visit www.ecology.ethz.ch or email to
john.garcia@env.ethz.ch .
The original spatially‐explicit approach model was
published in:
LP Koh & J Ghazoul. 2010. Proc Natl Acad Sci USA
107:11140‐11144