Climate Change Impact on
I d
Indonesian
i Cocoa
C
Production
P d ti
and Strategies for Adaptation
Presented at 21st Partnership Meeting & Roundtable Sessions of
World Cocoa Foundation, Washington, 1313-14 June 2012
1)
DIDIEK H. GOENADI , TEGUH WAHYUDI
1)
2)
2)
2)
& JOHN BAKO BAON
PT Riset Perkebunan Nusantara, Jl. Salak 1A, Bogor, Indonesia
Indonesian
Indonesia
n Coffee and Cocoa Research Institute
Institute,, Jl. P.B. Sudirman 90, Jember,
Jember, Indonesia
CLIMATE FAC
FACTOR
TORS
S
Light Intensity
Air Humidity
Air Temperature
R i f ll
Rainfall
COCOA FARMS
Wi d
Wind
CLIMATE
Sunlight  Wind Rainfall
ORGANISMS
Shade Weed
Animal Microbe
LAND
LAND
Soil Water
 Slope
Cocoa Crop
< Climate play important role
* Climate & weather faktor: main risk
< Susceptible to long dry season and heavy rainfall
< Distribution:
Di t ib ti
determined
d t
i d by
b climate
li t factors
f t
< Productivity: effects of ecoclimate factors
Climate change
< Very important issue
* impacts on lives
Main cause of climate change:
g
< Glasshouse gas increase in atmosphere
Climate change phenomena
< Excessive long dry season or rainfall
* will be more frequent in Indonesia.
< Climate change happen?
* drought, flood, landslide & pests
Aims
< Cocoa production development in last years
< Show indication of climate change
< Strategy of adaptation and to climate change
Data collected from plantations of
PTP Nusantara XII based on
variation of climate and rainfall:
1. Bulk cocoa farm, Kalisepanjang (Banyuwangi)
2 Fine flavor cocoa farm
2.
farm, Kalirejo (Banyuwangi).
(Banyuwangi)
When long dry season
1 EFFECTS ON NURSERY:
1.
 No/less effect
 Locations closed to water sources
2. EFFECTS ON YOUNG TREES
< Generally susceptible to drought
< Many dead trees, especially on less-prepared farms.
 Fund and time loss in replanting
3. EFFECTS ON PRODUCTIVE TREES
< Cocoa production decrease at the year of long dry season
< Damage level: lower in wet climate (rainfall type A or B:
Schmidt-Ferguson classification) than in dry climate (rainfall
type C or D)
When excessive rainfall and its period
1. Effects on soil:
* Erosion
* Landslide
* Top soil depth decrease
2 Effect on flowering
2.
- No effect on cocoa flowering and fruiting
3. Effect on p
pest and disease development
p
- Cocoa pod rot
- Stem canker
- VSD
4 Effect
4.
Eff t on b
bean d
drying
i
-
High seed water content
Longer time for drying
Mo ld beans
Mouldy
Extra energy needed
MAIN PRINCIPLES
Soil water management
SHORT TERM
Environment preparation
Plant strengthening
When long dry season
Cocoa seedlings in nursery
• Location close to
water sources
• Living shade: close, dense
• Enough NPK fertilized
• Mulch
l h in polybag.
l b
• Cancel if less preparation
For crop in fields
Short term:
 Shade management
 Soil tillage
g
 Fertilizing
 Crop protection
g
g
 Watering/irrigation
Sca 12
Long term
•
Superior clones
tolerant to drought
•
Rain water harvest
•
Establish cool farm
environment
•
Climate monitoring
and
d response to
t
climate change
When excessive rainfall
- Protect soil resource
- Shade management
- Pest-disease control
- Simple
Si l solar
l drying
d i
(use plastic sheets)
When normal condition
Use leguminous shade trees
Apply enough organic matter
When normal condition
Apply soil conservation
Fertilizing
Carbon emission reduction
2012 > 2011 > 2010
2010: too much rain
2011: first year harvest was still affected by 2010 condition
2012: strong wind affect certain central cocoa production areas
COCOA BREEDING:
- Screening of cocoa genotypes tolerant to drought stress
- Promising clones tolerant pod rot (Phytophthora palmivora)
CROP PROTECTION:
1. Biodegradable Coating to control:
- Pod rot
- Cocoa pod borer
- Helopeltis
2 Epiphytic weeds (Drimoglosum phylloseloides)
2.
SOIL AND AGROCLIMATE:
y and monitor
1. Climate analysis
2. Water harvest
3. Mycorrhizal fungi
AGRONOMY:
- Cocoa diversification with rubber and cover crops
p
POST HARVEST TECHNOLOGY:
1. Mechanical drying unit
2. Solar drying
y g unit (with
(
solar unit collector))
3. Drying unit with biogas
1. Climate change was noted in Indonesian cocoa farmers after 2006, excessive
rainfall and its period happened in 2010.
2. Cocoa production in 2010 was less than 2009 as affected by wet climate
change Cocoa production
change.
p od ction in 2011 and 2012 will
ill be less than 2010 due
d e to
very humid condition of cocoa farms which support pest and disease
infestation.
3. Strategies for adaptation and anticipation to climate change in 2012 should
be taken to reduce potential yield loss as results of excessive rainfall or
drought.
4. Some specific initiatives, projects, researches related with adaptation and
anticipation to climate change have been set up by ICCRI.
Good
governance
Economic
freedom
f d
Investments
in
i people
l
Why Green Prosperity?
• 17% of the world’s fauna species across only 1.3% of the world'ss landmass
the world
landmass
• 50% of all the world's fish species live in Indonesia’s marine and freshwater systems
But environmental degradation But environmental degradation
costs the Indonesian economy over
5 percent of GDP per year
The Green Prosperity Project
Aims to increase economic productivity by expanding renewable energy use and improving management of natural resources
1) Participatory Land Use Planning ($25M)
2) Project Identification and Development ($50M)
‐ Project Preparation Facility l
3) Project Funding and Implementation ($242.5M)
‐ Investment Facilityy
4) Green Knowledge ($15M)
‐ Science and technology centers of excellence
‐ Educating
communities for sustainable investments
Educating communities for sustainable investments
Map of Indonesia showing GP Provinces
p
g
GP Initial Phase
Candidate Provinces
GP Facility Potential Investments
• Hydropower (<10 MW),
on- and off-grid
• Other Renewable Energy
• Solar; HH biogas
p
production
• Biowaste-to-energy (e.g.
palm oil mill methane
capture)
• Smallholder agriculture intensification
programs; related certification programs
• Watershed management ; community
forestry programs
Investment Criteria Mi i
Minimum criteria includes
it i i l d
S t i bl L d U P j t h ld
Sustainable Land Use Projects should
•
10% economic rate of return
•
•
Improved environmental stewardship and contribute, directly or indirectly, d
t ib t di tl
i di tl
to the reduction of greenhouse gas emissions
Support GOI’s low carbon development goals
•
Incorporate smallholder focus as a priority
pp p
g
Appropriate safeguard measures to prevent or minimize adverse or unintended environmental and social impacts
Equal access to project benefits for women and other marginalized d h
i li d
groups. •
Include private sector with match/leverage of private sector match/leverage
of private sector
funds and clear market link;
•
Utilize local partners in design and implementation (with specific partners identified);
partners identified);
•
Include demonstrated experience of project implementers, capacity to sub‐contract and procure key i
inputs
t
•
•
Next Steps
p
Key Milestones
Stakeholder Forum in Jakarta
MCA
Indonesia CEO and GP Project Director and other key MCA‐Indonesia
CEO and GP Project Director and other key
team members in place
Targets
July 2012
July, Sept 2012
July, Sept 2012
Sector
Sector specific selection criteria and economic specific selection criteria and economic
modeling/guidance finalized
Nov
Nov 2012
2012
Long list of potential (specific) projects developed Long list of potential (specific) projects developed
Dec 2012
Dec 2012
Pre‐feasability studies and other project development and preparatory work for “short
preparatory work for short list
list” of starter (initial)projects of starter (initial)projects
Jan – April 2013
Launch of GP Finance Facility and release of operations manual May 2013
and other process requirements
and other process requirements 5‐year project implementation
2013 ‐ 2017
Resilient Farming
g
Systems for
Sustainable Cocoa
Production:
Lessons from the
Coffee Sector
Bambi Semroc
Senior Director, Food,
Agriculture & Freshwater
Photo 1
4.2” x 10.31”
Position
x: 4.36”, y: .18”
Photo 2
5.51” x 10.31”
Position
x: 8.53”, y: .18”
Agriculture Trends
Population Growth
To feed a world population expected to
surpass 9 billion in 2050, it is estimated that
agricultural output will have to increase by
70% (World Food Summit 2009).
The combined effects of climate change
change, land
degradation, cropland losses, water scarcity
and pest infestations may cause projected
yields to be 5
5–25%
25% short of demand by
2050 (UNEP 2009).
Photo 1
4.2” x 10.31”
Position
x: 8.74”, y: .18”
Climate Change
g and Agriculture
g
Climate-resilient
Cli
t
ili t
g
Agriculture
Photo 1
4.2” x 10.31”
Position
x: 8.74”, y: .18”
•
Builds resilience to climate change
impacts
p
•
Mitigates greenhouse gas emissions
•
Improves livelihoods of rural
communities and drives economic
development
Climate
Cli
t Ch
Change
Vulnerabilityy & Agriculture
g
Exposure: changes in temperature and precipitation
in key
y sourcing
g areas
Sensitivity: vulnerability of crops and livestock to
drought, pests and diseases; and impacts of
extreme weather events on supply chain
infrastructure, transport and storage systems
Adaptive Capacity: ability of farmers, processors,
traders manufacturers and retailers to shift to
traders,
alternative sources of products and livelihoods
Photo 1
4.2” x 10.31”
Position
x: 8.74”, y: .18”
Climate Change
g Impacts
p
on Coffee
Gradual Changes
- Temperature
- Precipitation
Heat/Wind/Water Stress
Pests in New Areas
Changes due to Extreme Events
- Droughts
- Floods
Water Stress
Loss of coffee trees & soil
Changes to Wet/Dry Seasons
Problems with fruiting,
o e g, d
drying
y g
flowering,
Coffee and Climate Change
Si
Sierra
Madre
M d de
d Chiapas,
Chi
Mexico
M i
Models predict that by 2030 we will see a:
 2.1-2.2°increase in average temperatures.
 80-85mm reduction in rainfall.
 Reduction in suitable land for Arabica coffee production from current
level of 265,400 ha to 60,500 ha by 2030.
 Areas
eas at 600m
600 in altitude
a t tude will no
o longer
o ge be suitable
su tab e for
o co
coffee
ee
(equivalent area will be 850-900m).
Current Coffee Suitability
Projected Coffee Suitability
Climate Change Strategy
Sierra Madre de Chiapas
• St
Strengthen
th the
th adaptive
d ti capacity
it off
coffee farmers and other stakeholders
to manage risks and reduce
vulnerabilities to climate change.
change
• Reduce greenhouse gas emissions.
• Identify alternative financial
mechanisms.
• Enact public policies and legislation at
all levels to support resilient farming
systems and supply chains.
• Implement the strategy and measure
results.
Coffee and Climate Change
Northern Sumatra
C
ff S
it bilit
Coffee
Suitability
high
low
Coffee and Climate Change
Northern Sumatra
Change in range for key pests and diseases
Vulnerability Overview for Northern Sumatra
Climate-Related
Exposure
Farmer
Feedback
Historical Climate
Data
Projections
Cyclones/Storms
-
-
-
Frost
-
-
-
Seasonality Changes
√
√
√
Higher Temperatures
√
-
√
Higher Rainfall
√
√
√
Drought/Fire Risk
-
-
-
Pest/Disease
√
√
?
Lessons Learned
• Smallholders are the most vulnerable.
• Combination of adaptation
p
approaches
pp
may be necessary in the most vulnerable
regions.
• Shade can buffer some impacts, but
some producers already have dense
shade.
shade
• Vulnerability assessments should be by
producers
producers.
Photo 1
4.2” x 10.31”
Position
x: 8.74”, y: .18”
• Effective adaptation strategies require a
participatory approach
approach.
Thank You!
Acknowledgments
Goetz Schroth
Monica Morales
Terry Hills
Fazrin Rahmadani
Saodah Lubis
University of North Sumatra
CIAT
Ecosur
Starbucks Coffee Company
Cacao +20:
Thoughts on climate change
Howard-Yana Shapiro, PhD
Global Staff Officer Plant Science and External Research
Mars, Incorporated
Adjunct Professor of Plant Sciences, UC Davis
56
13 June 2012
World Cocoa Foundation, Washington, DC
UN Framework Convention
on Climate Change
Promote and Disperse Climate
Friendly Tech
Grade
D
Promote Sustainable Land
M
Management
t
C
Prepare for the Impacts of
Cli t Ch
Climate
Change
C
Advance Climate Research
and Policy Analysis
A
Establish a Diplomatic Process
A
57
A=accomplished F=failure to act appropriately
Convention on Biological
Diversity
Reduce the Rate of
Biodiversity Loss
Grade
F
Develop Biodiversity Targets
D
Protect Ecosystems
C
Share Gene Windfall
E
Provide Funding
F
R
Regulate
l t Genetically
G
ti ll Modified
M difi d
A
Organisms
58
Report cards adapted from Nature, 7 June 2012
Cacao 1992 - 2012
Develop and Disperse High Yielding
Planting Material
Develop Water Use Efficiency Cultivars
Develop Nutrient Use Efficiency Cultivars
Develop Climatic Adaptation in New
Cultivars
Develop Pest and Disease Resistant
C lti
Cultivars
Develop Cacao Specific Fertilizers and
Distribution Systems
Collaborate Internationally on Needed
Scientific Advances
Utilize the Cacao Genome
59
Grade
E
F
F
F
D
D
E
C
What is climate change
and how does it really
affect us?
In a time of complex
climate change
g globally,
g
y
does cacao as a
internationally produced
and traded commodity
have a strong future?
60
Outline
Part 1: Earth’s energy balance and the greenhouse
effect
Part 2: Human (anthropogenic) changes to our
atmosphere and the greenhouse effect
Part 3: Temperature changes since 1750 and their
causes
Part 4: What do we expect for the future of cacao?
61
Two temperature notes
1 °C = 1.8 °F
Temp (°F) = 1.8
1 8 × Temp (°C) + 32
°F
Earth’s Energy
gy Balance
Climate = The average behavior of the atmosphere
• Includes temperatures, rainfall frequency and
amounts, flooding,
g etc.
Weather = The current behavior of the atmosphere
“Climate is what y
you expect
p
and weather is what y
you
get”
• The Earth’s climate
– Depends on the energy balance (energy in and out)
– There are many components that affect climate
• Sun,, atmosphere,
p
, oceans,, land,, plants,
p
, ice and snow…
62
Earth’s Energy Balance:
A Simple
p View
The input (solar radiation)
• Some of incoming sunlight is reflected by the atmosphere and Earth’s
surface
• Much of incoming sunlight is absorbed by the Earth and warms it
The output (Earth
(Earth’s
s radiation)
• The sunlight-warmed Earth emits longwave, terrestrial radiation
The result
• Earth’s global, annual average temperature is ~ 59 ˚F
Earth s temperature & climate
• Perturbing any part of this system alters Earth’s
• These perturbations are referred to as “radiative forcings”
63
Energy Balance:
The Greenhouse Effect
• The Greenhouse Effect is an important part of the Earth’s
Earth s energy
balance
The sun emits
shortwavelength
radiation
The Earth emits
long-wavelength
radiation
Earth’s atmosphere is mostly
transparent to short (solar)
radiation, but traps long
(terrestrial) radiation
•
•
•
•
Greenhouse gases (GHGs) in our atmosphere absorb terrestrial radiation
The GHGs then re-emit the energy in all directions, including back to Earth
Absorption off this energy by Earth makes temperature warmer (59
( ˚F
˚ vs. 0 ˚F)
˚ )
This64is the Greenhouse Effect. We all prefer 59 ˚F. So what’s the problem?
Humans are Increasing
g
Greenhouse Warming
• A natural greenhouse effect has existed for billions of
years.
• However, anthropogenic emissions of greenhouse gases
(GHGs) are causing more absorption in the atmosphere.
– We are “closing”
closing the atmospheric window that allows longwave
radiation to escape to space
– This is causing additional greenhouse warming above the
“natural”
natural amount
•
Major Greenhouse Gases
– Water vapor, H2O
– Carbon
C b di
dioxide,
id CO2
– Methane, CH4
– Ozone, O3
– Halocarbons
– Nitrous oxide, N2O
65
Relative Importance of GHGs and Other
Forcings
RF = Radiative Forcing (perturbation to Earth’s energy
b
l
+ RF = warming)
i )
balance:
Figure shows how radiative forcings have changed
from 1750 to the present
LOSU = Level of Scientific Understanding CO causes
2
most of
warming
Human
emissions of
particles cool
climate overall
Overall
anthropogenic
effect is
warming
Changes in
p
sun’s output
have been
small
66
← Cooling | Warming →
Associated Changes in Climate
• Temperature
– Increase of ~ 0.8 °C (1.4 °F) over past
150 years
– Warmer now than in last 1000 yrs
– Rate of warming since ~ 1900 is fastest in
last 10,000 years
• Other changes include
– Warming oceans & rising sea levels
– Decreased snow and ice amounts
– More extreme weather (heat, rain,
drought, hurricanes)
– Warming & thawing of permafrost
• Current IPCC assessment
– Warming of the climate system is
unequivocal
67
Annual Temperature 196419642002
Annual Temperatures for Southern Ivory Coast
Cacao Production Systems
82.0
81.5
81 0
81.0
80.0
y = 0.0491x + 78.907
79.5
CDI_Anu
Linear (CDI_Anu)
79.0
78.5
20
00
19
98
19
96
19
94
19
92
19
90
19
88
19
86
19
84
19
82
19
80
19
78
19
76
19
74
19
72
19
70
19
68
68
19
66
78.0
19
64
Degrees
s, F
80.5
Ivory Coast Rainfall
1964 – 2002
Annual Rainfall for Southern Ivory Coast
Cacao Production Systems
80.0
y = -0.4339x + 62.484
75.0
Annual
Linear (Annual)
70.0
60.0
55.0
50.0
45.0
20
00
19
98
19
96
19
94
19
92
19
90
19
88
19
86
19
84
19
82
19
80
19
78
19
76
19
74
19
72
19
70
19
68
69
19
66
40.0
19
64
Rainfall, Inches
65.0
Predictions of Global
Mean Temperature
• Greater GHG emissions  greater GHG concentrations  more
warming
• In all emissions
scenarios there is
more warming in
next 100 years
compared to last
100 years
• L
Low scenario
i
(B1): Expect
warming of ~
1 8°C
1.8
C (3.2
(3 2 °F)
F)
• High scenario
(A2): Expect
warming of ~ 3.6
70 °F)
°C (6.5
Models of Climate Change
g
To predict the response of a crop to climate change, we
need
d a model
d l off some sort.
t I am nott a proponentt off any
modeling approach in particular; they all have strengths
and weaknesses. Rather I would take a practical
p
approach and start with what’s readily available; look at
initial results, determine the weak points in the analysis,
and then,
then if necessary
necessary, refine the model (or data used)
and improve.
I find
fi d it useful
f l to
t distinguish
di ti
i h ttwo main
i classes
l
off models
d l
in this field: correlative (statistical) models and
mechanistic models
models.
71
Statistical
Statistical models combine observations of the current distribution of a
crop, and sometimes yield (the response variables), with other
geographical (environmental) data (the predictor variables)
variables). Many
different algorithms are used, but machine learning tools (such as
“maximum entropy”, “boosted regression trees”, and “random forest”
methods) are considered the most powerful for this type of application
application.
The fitted statistical model can be used to predict a crop’s maximal
geographical distribution (and yield) under current and future climates.
The extremes of a crop’s
crop s distribution are often well defined by
temperature and/or precipitation limits, and can thus be modeled
relatively easy. The distribution within the suitable “climate envelope”
is more challenging, as this will depend on other environmental factors
(e.g., soils, irrigation, ...) as well as on economical, political, and
historical factors.
72
Mechanistic Models
Mechanistic crop simulation models mimic crop growth based on
detailed system analysis of the processes involved. The processes
(photosynthesis partitioning of assimilates,
(photosynthesis,
assimilates etc) are studied
independently and then combined into a single model. This has
proven to be useful in research settings, e.g. to look at new
management practices
practices, the benefit of a new variety in different
places, and also for climate change effects. A disadvantage of a
mechanistic model is that, because of its generality, it cannot predict
important differences in crop distribution that are caused by non
nonenvironmental factors, whereas a statistical model can do this more
easily.
Developing such a model is a complicated and long term endeavor
endeavor,
particularly for a tree crop. However, simple “reduced form”
mechanistic models can also be developed.
73
Predicted Warming is
Spatially Heterogeneous
• In all scenarios,
land warms
more than
oceans
74
Predicted Increase in Temperature (°C)
• Warming over
the next ~ 20
years is
relatively
insensitive to
emissions b
emissions,
butt
warming by
2100 is
sensitive to
emissions.
37
%
Approximately
a third comes
from ‘local’
sources
% of rainfall derived from ‘short cycle’
terrestrial
origins(recalculated from Basilovich et al.)
58
%
30
%
68
%
Ellison D, Futter MN,
Bishop K, 2011.On the
forest cover–water yield
debate: from demandto supply-side thinking.
Global Change Biology,
doi: 10.1111/j.13652486.2011.02589.x
42
%
40
%
22
46
41
%
%
%
1) Mackenzie river basin, 2) Mississippi river basin, 3) Amazon river basin, 4) West Afri75
ca, 5) Baltics,
6) Tibet, 7) Siberia, 8) GAME (GEWEX Asian Monsoon Experiment) and
9) Huaihe river basin.
What Must/Should/Can
Be
Done?
Reduce greenhouse gas levels
–
–
–
–
Includes reductions in emissions as well as sequestration/geo-engineering
Climate will not stabilize unless emissions are reduced below current levels
The lower emissions can be reduced, the less climate will be altered
However, even if we could stop all emissions now, we are committed to a
relatively small amount additional warming because of our past emissions
– IPCC: “Unmitigated climate change would, in the long term, be likely to exceed
the capacity of natural, managed and human systems to adapt.”
Adapt to changes in climate
– Adaptations can be technological), behavioral (e.g., food choices), managerial
(e.g., altered farming practices),
– Rich societies will be better able to adapt than poor societies or natural
ecosystems
t
– Societies will not be able to adapt to all climate changes, especially in the
longer term where changes will be larger
– Vulnerability is exacerbated by other stressors (e
(e.g.,
g poverty
poverty, pollution
pollution, disease
disease,
conflict)
76
We Know How to Increase Yields 3x
Potential Impact Cocoa Farm Productivity
Increases (Gains in Kg/Ha)
South Asia: Increasing Cereal Yields, Decreasing Poverty
1600
New Productivity – 1521 Kg/Ha
1400
351
1200
>3X
Sub-Saharan Africa: Flat Cereal Yields, Persistent Poverty
Cocoa Yie
eld (Kg / Ha)
1000
585
800
600
135
400
200
450
0
Current
Knowledge
/ Pest
Control
Plant
Material
Fertilizer
Note: Poverty level defined as income of $1/day/person
S
Source:
World
W ld D
Development
l
tR
Reportt 2008
2008; C.
C P
Peter
t Timmer,
Ti
“A i lt
“Agriculture
and
dP
Pro-Poor
P
Growth“,
G
th“
Syngenta Foundation
77
Do We Use the Best
Science Available to
Determine Where to
Grow Cacao
U de sta d g
Understanding
Climate Change?
Here’s a Data Set.
78
Processing the data
79
Parameter
Specification
Precipitation
Annual mean
Driest month
Driest quarter
Seasonality
Annual
Coldest quarter
Temperature
Radiation
Soil
Annual
Driest quarter
Type
Ph.
Ph
Base Saturation
Organic carbon
80
Minimum
Maximum
1403
18
168
45
24
22
1800630
386376
Acrisol (Major)
Ferrasol/Cambisol
(minor)
Units
1789 Millimeters
37
102
81
26 Degree Celsius
24
Watts per
1881450 meter square
410422
81
Resolution 30m x 30m
Based on 280 (56 x 5) ground truthed cocoa locations
Maximum likelihood classifier spectral landcover reflectance probability
A Few ConfusingTerms
Science (noun) – to know,
know knowledge
Scaling up – to bring more benefits, to
more people, more quickly and more
lastingly
82
Call To Action
Scaling of the productivity
model for all cocoa producers
Access to improved germplasm,
micro-credit cocoa
micro-credit,
appropriate fertilizers
Understand weather volatility
National institutional capacity
building
83
To Build a Sustainable Cacao
Sector that Adapts
p to Climate
Change Which is Real and
Happening Before Our Eyes, We
Must Share Our Experiences,
Collaborate to Solve Collectively
th Pressing
the
P
i Issues
I
Internationally,
I t
ti
ll
Move Quickly Towards Consensus
and
d Protect
P t t the
th Lives
Li
off Millions
Milli
off
Cacao Farmers.
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