Transcript CIWARA – Climate change Impacts on West African agriculture – a Regional Assessment An AgMIP research venture for the West Africa region CIWARA = ? •

CIWARA – Climate change Impacts
on West African agriculture – a
Regional Assessment
An AgMIP research venture for the
West Africa region
CIWARA = ?
• In the Bambara mythology, the ciwara is a laboring wild
animal representing the creation of farming. Throughout the
Manding area of West Africa, it symbolizes courage,
selflessness and wisdom, and is awarded to meritorious
workers
CIWARA: Goals
• G1. Substantially improve the characterization
of food security risks due to climate variability
and change in semi-arid and sub-humid West
Africa.
• G2. Enhance the adaptive capacity of West
African populations for changing
environmental (biophysical, socio-economic)
and technological conditions.
CIWARA: Sites
Country
Burkina
Faso
Ghana
Mali
Niger
Senegal
Population density
Rainfall (proxy for agro(proxy for intensification)
ecological potential)
Lower
Higher
Lower
Higher
Yatenga
x
x
Kenedougou
x
x
Lawra/Jirapa
x
x
Tolon K.
x
x
Koutiala
x
x
Bougouni
x
x
Kollo
x
x
Aguie
x
x
Kaffrine
x
x
Nioro
x
x
Site
(district)
CIWARA: Sites, aridity index
CIWARA: Sites, LGP
CIWARA: Sites, Rainfall
CIWARA: Sites, Population Density
CIWARA: Sites, Dominant Language
CIWARA: facts & numbers
8 outputs:
• Climates
• Crops
• Yields
• Scales
• Trade-offs
• Farmers
• Policy
• Capacity
5 countries:
• B. Faso
• Ghana
• Mali
• Niger
• Senegal
3 capacity
builing
levels:
• 15 scientists
4 crops:
• Maize
• Millet
• Sorghum
• Peanut
3 crop models:
• APSIM
• DSSAT
• SarraH
3 CC themes:
• RAPs
• aggregation
• uncertainty
4 themes:
• climate
• crop
• Economics
• IT
(senior + junior, male + female), 10 institutions (NARS, NHMS, NGO,
ARO, academia, CGIAR, ARI), 10 students (2 /country)
CIWARA: Approach=f(theme, scale)
CIWARA: Objective 1, “climates”
• Objective: Assemble, curate and migrate local
to regional climate, crop, economic data in a
standard, open-access database
• Outcome: Adequate granularity is secured to
ensure representativeness and relevance of
the current and future assessments for West
African conditions
• Lead: S.B. Traoré / Agrhymet
• Timeline: Now-Mar 2013 (7 months)
CIWARA: Objective 2, “crops”
• Objective: Improve and compare crop models
performances for West African millets, sorghums,
and their supporting soils
• Outcome: Relevance of existing models to West
African conditions is strengthened with key
regional traits & responses incorporated,
including enrichment of intra-specific agrobiodiversity in models
• Lead: J.B. Naab / SARI, P.S. Traoré / ICRISAT
• Timeline: Now-Mar 2013 (7 months)
CIWARA: Objective 3, “yields”
• Objective: Generate contrasted yield baselines
(2) and scenarios (4) for West African maize,
millets, peanuts, and sorghums
• Outcome: Regional climate variability and change
patterns (historical, projected) are translated into
yield probabilities for representative germplasm,
management practices, and locations
• Lead: J.B. Naab / SARI
• Timeline: Jan-Jun 2013 (6 months)
CIWARA: Objective 4, “scales”
• Objective: Aggregate point-level yield
probabilities to sub-national scale and assess
uncertainty thereof against independent datasets
• Outcome: Sources of bias and uncertainty in
aggregate production statistics (conversely:
downscaled farm information services) are better
understood for heterogeneous smallholder
agricultural landscapes
• Lead: P.S. Traoré / ICRISAT, M. Adam / CIRAD
• Timeline: Apr-Sep 2013 (6 months)
CIWARA: Objective 5, “trade-offs”
• Objective: Elicit representative agricultural
pathways and quantify climate impacts using the
Trade-Off Analysis (TOA)-MD tools
• Outcome: Sub-national socio-economic,
technological trajectories subject to future
climate forcing are simulated and used as
reference in future regional assessments of
climate change impacts
• Lead: I. Hathié / IPAR
• Timeline: Apr-Sep 2013 (6 months)
CIWARA: Objective 6, “farmers”
• Objective: Improve the granularity, relevance,
and spatial coverage of agro-meteorological
advisories for smallholder farmers
• Outcome: Generic crop calendars and agrometeorological advisories are refined into
location-specific, ecotype-specific decision
support tools, and scaled out from Mali to
Senegal
• Lead: D.Z. Diarra / Meteo-Mali, O. Ndiaye /
ANACIM
• Timeline: Apr-Dec 2013 (9 months)
CIWARA: Objective 7, “policy”
• Objective: Update selected policy instruments
(e.g. NAPAs) with project results at national (5
countries), regional (ECOWAS) levels
• Outcome: West African policy makers are better
informed about local impacts of climate
variability, change, and can deploy adaptation
and mitigation strategies that are more relevant
and effective
• Lead: I. Hathié / IPAR
• Timeline: Sep 2013 - Feb 2014 (5 months)
CIWARA: Objective 8, “capacity”
• Objective: Build regional research capacity for
integrated climate change impacts assessments
at scientist, graduate student levels
• Outcome: An “AgMIP alumni” core group is
created with increased trans-disciplinary
expertise and a new generation of future PhD
graduates is in training within AgMIP and/or
affiliated networks
• Lead: S.G.K. Adiku / UG
• Timeline: now-Feb 2014 (18 months)
CIWARA: capacity gaps
BF
GH
ML
NE
SN
OI: Climate
?
n
?
y
y
O II: Crops
y
y
y
y
n
O III: Yields
y
y
?
y
n
n
n
y
?
n
n
y
n
n
y
n
n
y
n
y
n
y
n
?
Y
O IV:
Scales
O V: Tradeoff
O VI:
Farmers
OV II:
Policy
Identified student topics
Topic
Host
University
Local
Supervisor
External
Supervisor
Student name
Variability of weather X’tics
relevant to Agric win the 20th
Century and CC
UGB, Saint
Louis
Pr. Aliou Diop
+ Ousmane
Ndiaye
B. Sarr, Agrhymet,
Niamey
Bilal Sow
Defining production systems
Pr. Ali Mbaye + M. Adam + P.C.S.
diversity to run crop models
to be
UCAD, Dakar
Ibrahima
Traore, ICRISAT,
using expert knowledge, GIS
identified
Hathie
Bamako
and household statistics
Integration of indigenous
Pr. Bayoko +
S.B. Traore,
to be
knowledge in meteorological U. Bamako
D.Z. Diarra
Agrhymet, Niamey
identified
advisories to farmers
Comparative effects of tillering
Dr. M.
D.S.K. Maccarthy +
and planning density on
F. Akinseye? U. Bamako
Kouressy + M. Diancoumba, UG,
predicted millet yield in APSIM
tbi
P.C.S. Traore
Kpong
+ DSSAT
Simulation of crop growth
Pr. S.G.K. Adiku
risks and adaptation under
Ousmane Ndiaye,
UG, Legon
+ D.S.K.
tbi
variable C using modeling
ANACIM, Dakar
Maccarthy
approaches
Identified student topics (contd)
Topic
Host
University
Local
Supervisor
External
Supervisor
Implications of CC on small
holder farmers in the Guinea+
M.Sanon + T. Lodoun
Sudan Savannah zones of
UDS, Tamale J. Amikuzuno
+ Pr. Tbi, Univ. Ouaga
West Africa (NR, Ghana & S.B.
Faso)
Pr. tbi + M.
Same as previous
J. Amikuzuno, UDS,
Uni. Ouaga
Sanon + T.
(UW, Ghana & W.B.Faso)
Tamale
Lodoun
Simulating soil water
conservation methods on
P.I. Akponikpe, Uni.
Uni. Ouaga
Pr. tbi
millet yields with
Parakou
APSIM/DSSAT
CC and adaptation strategies
Pr. tbi + B.
D.Z. Diarra, Meteofor agro-meteorological
Uni. Niamey
Sarr
Mali, Bamako
services
Pr. tbi + F.
tbd
Uni. Niamey
I. Hathie, IPAR, Dakar
Dougbedji
Simulating micro dosing
Prof. Xxx
Adiku/ Dilys (UG,
effects on soil nutrients using Uni. Niamey
/Benoit
Ghana)
Student name
tbi
tbi
tbi
tbi
tbi
tbi
CIWARA: $ resources
Univ. Ghana: USD 165,741
Agrhymet: USD 174,010
ICRISAT: USD 175,954
NARES (x4): USD 186,167
NHMS (x2): USD 98,113
_____________________
Total: USD 799,986