2. CLEANED-R tool
• Landscape scale & spatially explicit
• Integration of open geographical
data to get quick context specific
data
• Based on 5 core module (production,
ghg, water, soil, biodiversity) and
simple exogenous land use change
module
• User interface in R-shiny
– Simple user with “vignettes”
– Advanced user
• Improvement and testing of the tool
within the ReSLeSS project
4. Resless components
• Economics
– Success factors as seen by the
community (more money is
not always better)
• Equity
– Understanding who is
marginalized and making sure
that marginalized group get a
voice in the learning space
• Environment
– CLEANED tool : understanding
the environmental impact of
interventions
=> INTEGRATION into the
learning space
5. Transformation Game :
enabling the learning space
Board game to
define scenarios
Number of
animals per
category
Feed baskets per
category
CLEANED
tool
Environmental score
card (generated
through CLEANED)
Stakeholder defined
socio-economic score
card
(generated through
discussions)
Renegotiation
of the scenario
6. Preliminary results from Burkina Faso
Scenario based on the pastoral vision
Baseline Initial Negotiated Diff. with initial
Vign. Number Vign. Number Vign. Number Vignettes Number
A (tr*) ABR 100 GT
238 PT
ABR 300 ST
200 LT
ABR 300 ST
200 LT
0 0
0
L (tr) LBR 200 LBR 300 L1 300 + 0
D (an*) DBR 1’400 D1 2’400 D2 1’400 + - 1000
F (an) FBR 55’000 FBR 110’000 F1 110’000 + 0
T (an) TBR 22’500 T1 23’000 T1 17’000 0 -5000
Total 123’460 201’400 194’400
7. Preliminary results from Burkina Faso
Environmental score cards
Productivity measure Initial Negotiated Change
Meat produced (tons) + 83 + 83 0
Milk produced (tons) + 57 + 31.6 -
Cropland used (ha) + 57 + 51 -
Grazing land used (ha) + 56 + 49 -
Rice area used (ha) + 100 + 100 0
Environmental indicators Initial Negotiated Change
water
Total + 60 + 52 -
Per animal - 1.4 - 1.7 -
Greenhous
e gases
Total + 61 + 57.5 -
Per animal + 0.2 + 1.5 +
Nitrogen + 31 + 27 -
All values are in
percentage change
compared to the base
run
8. Preliminary results from Burkina Faso
Socio-economic score card
Socio- economic indicators Score initial
scenario
Score negoc.
scenario
change
Improved breeds, infrastructures and services Low High ++
To be generous and helpful Medium Medium 0
Children go to school without hunger High High 0
Land rights are well defined High Medium to
high
-
Incomes are diversified Medium to
high
High +
Pastoralist household own two herds at any
time
High Medium -
9. Burkina Faso preliminary results
Identified trade-off and synergies
• Agreement in a long lasting conflict
between agro-pastoralists and mixed
crop livestock farmer could be found
– Agro-pastoralist will not intensify their
livestock production and relay in
natural grass.
– Crop farmers will get better breeds
and will feed them with planted
fodder.
– Tractors will replace some of the draft
animals
• More production and more
environmental impacts are necessary
to reach the socio-economic
objectives.
10. Reflection from the Burkina Faso learning
space
CLEANED tool as a boundary
object :
• Enables the learning space
• Entry point to discuss
environmental impacts
• “neutral participant” that all
conflicting parties could
agree on
11. This presentation is licensed for use under the Creative Commons Attribution 4.0 International Licence.
better lives through livestock
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Data integration : the CLEANED tool make use of the richness of open GIS data, and queries them to get locally relevant data. This data is also combined with expert knowledge that has been collected from key informant interview (reconnaissance tour) and a participatory GIS workshop. This data helps to defined the number of livestock categories that CLEANED will handle, and to define the feedbaskets and to set up initial numbers. To the initial numbers of animals per category, we have developped a trianglulation methodology that makes use of all available data, including the workshop data, census, dhs.
The main idea of Resless is that tools such as the CLEANED tool are useless unless they are used in a participatory process. Why useless? Because CLEANED is a model and therefore will never present the “reality”. The cleaned tool as a base run based on the most credible possible parameters. Simulating the future value chains, can teach us about environmental dynamics but it will never give the “true” future. Therefore, tools like CLEANED are here for us to learn about non-linearities that shape the environmental impact.
So to make a meaningful use of the CLEANED R tool, the ResLess project aims at social learning by creating an environmental trade-off learning space, that integrates economic, equity and environment
So in the Resless project, there are 3 major components, economics, equity and the environment.
Economics : this component is based on participatory economics, and assumes the most often what people value and how the define success is not accurately measured by money. SEI developed a participatory approach based on future personal stories to come up with a set of socio-economic indictors that will be used to value the scenarios.
The Equity component uses an anthropological approach to understand who are the marginalized people in the area, and insure that all people have a voice. This is done by having observers during the workshop and adjusting the facilitation styles immediately when marginalization is observed. Also the dynamics and power games are documented to give advice on equity for future participatory processes.
The environment component provides the CLEANED simulation tool that has been simplified so that it can be used live during the workshop and give real-time impact computation as participants negociate interventions.
We have also an integration component, which we see it the learning space. Yet as you can imaging, this is a very difficult process, to get an economist, an anthropologist, and environmental specialist and a modeler on the same page. It has actually led to quite some tensions. But let us show you have we manage to create an integrated learning space : a the solution was THE TRANSFORMATION GAME
Stephen this might be your part : Explain the game with the vignette and the game board on the table, then show the interface of cleaned-r and then explain the result from CLEANED where put in an environmental score card that is discussed by participants and socio-economic indicators are ranked by participants. Then the group can negotiate new intervention and test them