Interactions Between Soybean Supply Chains, Governance, and

Report
Interactions between
Global Supply Chains, Land Use, & Governance: The
Case of Soybean Production in South America
Rachael D. Garrett
Postdoctoral Fellow in Sustainability Science  Harvard University
[email protected]
Population & income growth & urbanization are increasing
demand for livestock products
Soybeans
107
290
94
240
81
Million Tons
Million Tons
Pig Meat
190
68
140
55
90
Data: FAO STAT
Canada!
Canada!
Brazil!
Soybean area and yields by countryUruguay!
-1986 &
2010
Paraguay!
Soy Yield (MT/Ha)!
3!
• Increased demand
met both by increased
yields & increased
area, esp. in Argentina
& Brazil
2.6!
2.2!
1.8!
1986!
1.4!
2010!
1!
1986!
Total Soy Area = 37Mha !
2010!
Total Soy Area = 79 Mha !
Argentina!
Argentina!
Bolivia!
USA!
Brazil!
Bolivia!
USA!
Paraguay!
Uruguay!
Canada!
Canada!
Uruguay!
Notes: Yields are country averages.
Data: FAOSTAT
Brazil!
Paraguay!
)!
3!
Garrett, Rueda, Lambin – Environ. Research Letters, Forthcoming
Land cover change in South America
from Agricultural Expansion
Woody Vegetation Area
Agriculture & Herbaceous Area
2000-2010
(Δ KM2)
<-4000
-3999 to 500
-499 to -250
-249 to 0
1 to 250
251 to 500
>500
Clark et al. 2010
Counties w/ 50,000 ha or more of
agricultural expansion in last 10 years
Motivating question
What can be done to halt land cover change in the Amazon,
Cerrado, and Chaco for cropland expansion, while still allowing
Brazil to develop (via agricultural intensification & value added
activities)?
Knowledge gaps
• Interactions between the supply chain actors, institutions,
Discussion
land use
Governance
&
Institutions
Land Use
Supply C hain
1
• Non-linear feedbacks that can lead to rapid and unexpected
changes
Questions Addressed
• How do consumer preferences in Europe influence trade
& supply chain infrastructure in Brazil?
• How does supply chain infrastructure influence Brazilian
farmers’ ability to access premiums for environmentally
responsible soy?
• How does competition & diversity in the supply chain
influence prices, rules, & information faced by farmers,
thereby influencing incentives to expand cropland?
Questions Addressed
• How do consumer preferences in Europe influence trade
& supply chain infrastructure in Brazil?
• How does supply chain infrastructure influence Brazilian
farmers’ ability to access premiums for environmentally
responsible soy?
• How does competition & diversity in the supply chain
influence prices, rules, & information faced by farmers,
thereby influencing incentives to expand cropland?
European Soy Preferences
• > 70% of Japanese & European consumers prefer foods that do
not contain GM materials
• GM imports are not banned, but must be labeled
– Meat & dairy products are excluded
• Total demand for certified non-GM soy is about 10% of world
export market
• Now also asking for soybeans that do not result in deforestation –
“Environmentally Responsible”
Potential Effects of Preferences
• Shift trade patterns
• Incentivize land use through price premiums
– Non-GM & eco-certification programs
Production of non-GM soy
100
Total Non-GM soy area by country – 1996 & 2010
45
80
Non-GM
area
ofTotal
totalSoy
soy Area)
area
Non−GMsoy
Area
(asas%%of
35
0
20
40
%
60
Non-GM Soy Area (MHa)
40
Argentina
Bolivia
Brazil
Paraguay
Uruguay
US
Canada
1990
1995
2000
2005
2010
Year
Notes: Total includes only North and South America.
Data: Isaaa.org
80% decrease
30
USA
25
Canada
20
Paraguay
15
Brazil
Argen na
10
5
0
1996
2010
Garrett, Rueda, Lambin – Environ. Research Letters, Forthcoming
• Many EU countries with a strong non-GM preference shifted their
imports to Brazil and away from countries that decreased their nonGM soy area, despite prices favoring US & Argentina
Garrett, Rueda, Lambin – Environ. Research Letters, Forthcoming
Total eco-certified area by country - 2012
Country
ProTerra
RTRS
Argentina Bolivia
Ha
Brazil
Paraguay Uruguay Canada
China
India
USA
-
-
1,100,000
-
-
-
-
-
-
123,687
-
230,768
2,765
372
-
-
29,801
-
RTRS area by state - 2012
Area (Ha)
200,000
>160,000 hectares controlled by Maggi Group
150,000
100,000
50,000
0
Brazil
Argentina
Data sources: Responsiblesoy.org, proterrafoundation.org, & direct communication
Paraguay Uruguay
Conclusions
• Brazil’s continued production of non-GM caused EU importers to shift
trade to this country
• The development of supply chains able to segregate GM from non-GM
soybeans gave Brazil an advantage in producing eco-certified soy
• Mato Grosso has been state most able to capitalize on certifications;
especially large traders that have highly vertically integrated supply
chains
• Ironic because Mato Grosso is the state that experienced highest levels
of direct deforestation for soy in 2000-2010 period (Macedo et al 2012)
Question Addressed
• How does competition & diversity in the supply chain
influence prices, rules, & information faced by farmers,
thereby influencing incentives to expand cropland?
Ricardian & Thunian theories of rent (profit)
Biophysical
conditions
Distance
from markets
Technology
Output & Prices
Incentives to
expand
New economic geography theory - Process of agglomeration
Profit from existing
biophysical conditions &
transportation costs
Variety of technology
& services produced
in the city
Number of producers
that location in region
Number of specialized
agricultural firms that can
be supported
• Agglomeration creates positive externalities
- Better prices, info, technology
• Influences incentives to expand
Garrett, Lambin, Naylor – Land Use Policy, 2013; (based on Fujitsa & Krugman 1996)
Santarém: good biophysical condtions
low transport costs
Farmer networks & access to services
Cargill
Aves Para
Sojeiro
Case studies
Syndicate
Input reseller
Noble Cargill
Dreyfus
Maggi
Group
COOP.
Sorriso
Caramuru
Bunge
Syndicate
Sojeiro
SICRED
good biophysical conditions
high transport costs
Nideira
Input
reseller 1
APROSOJA
Sorriso:
ADM
Rabobank
HSBC
Input
reseller 2
FIAGRIL
Bank of
EMBRAPA
Brazil
Garrett, Lambin, Naylor – Land Use Policy, 2013
Crop Area in Case Studies
Santarém
Sorriso
70
50
2011
1990
Soy
Corn
40
30
20
10
0
1990
Corn
500
Rice
400
300
200
100
1995
2000
2005
<1% of area in soy
Source: IBGE
Soy
600
Area (1,000 Ha)
Area (1,000 Ha)
60
700
Rice
2010
0
1990
1995
2000
2005
2010
63% of area in soy
Garrett, Lambin, Naylor – Land Use Policy, 2013
Santarém: good biophysical condtions
low transport costs
constraining institutions
Farmer networks & access to services
Cargill
Aves Para
Sojeiro
Case studies
Syndicate
Input reseller
Noble Cargill
Dreyfus
Maggi
Group
COOP.
Sorriso
Caramuru
Bunge
Syndicate
Sojeiro
SICRED
good biophysical conditions
high transport costs
enabling institutions
Nideira
Input
reseller 1
APROSOJA
Sorriso:
ADM
Rabobank
HSBC
Input
reseller 2
FIAGRIL
Bank of
EMBRAPA
Brazil
Garrett, Lambin, Naylor – Land Use Policy, 2013
Conclusions
• Institutions influence how local supply chains develop
• Clustering of many related agribusiness firms together creates
many positive externalities that can overcome disadvantages
from high transportation costs – lead to rapid expansion
1990
Sorriso - 2010
Source: Google Earth
Garrett, Lambin, Naylor – Land Use Policy, 2013
Conclusion
• Consumer preferences influence trade flows & supply chain structures,
which influences producers ability
to adopt eco-certifications
Discussion
Governance
&
Institutions
Non-linear process that
amplify role of roads,
climate, policy
interventions, etc..
Land Use
Can lead to unexpected
development patterns
Supply C hain
1
• Institutions help determine how supply chains develop, which influences
profitability, compliance w/ rules, & incentives to expand cropland area
Questions?
Rachael D. Garrett
Postdoctoral Fellow in Sustainability Science  Harvard University
[email protected]

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