Integrating Biodiversity and Ecosystem Services into Foresight Models BIOVERSITY Rome May 78 2015 What We Do Research program coled by the International Food Policy Research Institute IFPRI CGIAR and University of Minnesota ID: 687840
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Data and Tools
A Framework for Integrating multi-scale Biophysical and Socio-economic Datasets into Foresight Models
Integrating Biodiversity and Ecosystem Services into Foresight
Models
BIOVERSITY, Rome,
May
7-8, 2015Slide2
What We Do…
Research program co-led by the International Food Policy Research Institute (IFPRI, CGIAR) and University of Minnesota.
We generate data products to help guide strategic investments for more
productive and profitable farming in sub-Saharan Africa
We do this through:Harmonizing and geo-referencing datasets at administrative units down to 10-km grid across agricultural domainsAnalytics, modeling and data visualization toolsFlagship studies, interactive atlases
2Slide3
Questions
we are passionate about…
Where are the poor and what is their welfare status?
Which
farming systems do the poor most depend?How best to tune productivity targets to different sub-national conditions?What are the constraints affecting on-farm productivity, technology adoption, and market
integration?What investments in technologies and practices might best address those constraints?What is the aggregate landscape of investments across the region?
What are the benefits of investments on productivity, food security and farm income and ultimately, the reduction of poverty and hunger?3Slide4
4
Production system, market
a
ccess
a
nalysis
MESO SCALEPixels as units of
analysis
Production System
Ecosystem Services
Infrastructure/Market Access
Investment/policy
a
nalysis
MACRO SCALE
Aggregate, market-scale (geo-political)
units
Fixed
g
eographies
of
analysis
e.g
.
IMPACT/WATER,
GTAP derivatives
Flexible
units
of Analysis
e.g
.
DREAM,
MM models
Change
e.g. policy, investments
Change
e.g. climate, pests, technologies
Household
Characterization
MICRO SCALE
Farms and plots as
units
of
analysis
Urban/Rural
Consumption
Inputs
Production
Income
RegionSlide5
Meso
Scale…
Crop Modeling
at global and regional-scale on
grids
Seasonality
Soil Fertility
Harvested Area
Average Rainfall
Yield Potential
5Slide6
Meso
Scale… Market Access Modeling
6
Accessibility is determined using a cost-distance function
measuring
hours to nearest market center for each location. Estimated based on combination of global spatial
layers, incl. road and river networks, assessed in terms of their “friction” or km per hour travel time. The latter is adjusted based on a number of input variables, incl. road location and type, elevation, slope, country boundaries, bodies of water, coastline, and land cover.
Key input layers:Road network’s improvement and characterization (low/high speed)Off-road travel characteristics: terrain (elevation, slope), land cover
Markets and human
settlementsSlide7
Meso
Scale… Market Access Modeling
2010 updates
7Improving the road network affects market accessibility.
Countries for which we are able to update the road network:Country
Data Source(s)
MaliIITA
Kenya
MSU,
Google
Earth
Malawi
African Development Bank
Senegal
IITA
Uganda
World Bank
Nigeria
IITA
Tanzania
World Bank
Burundi
African Development Bank
Ethiopia
Michigan State University/IFPRI
Ghana
African Development Bank
Road network after HC
update (2010)
Original road network from Joint Research Center (2000)Slide8
Augmenting -and validating- HarvestChoice data layers with sub-national farm household characteristics, farm management practices, production, consumption and nutrition estimates. 5 harmonized
Country Snapshots released (Malawi, Uganda, Tanzania, Ghana, and Ethiopia),
2 more in pipeline.
Micro Scale
Mapping Agricultural Census, Demographic and Health Surveys, LSMS-ISA Surveys
DHS Child Stunting Prevalence
TZA AC 2007 – Tomato Yield
8Slide9
Production, Consumption, Nutrition
Production indicators (SPAM, Crop Models)
yield (kg/ha)
quantity (and value) of production
area harvestedyield variabilityNutrition indicators (DHS)child anthropometric indicators (stunting, wasting, underweight) (also LSMS)BMI for womenpercentage of women with anemia
hemoglobin of womeninfant/young child breastfeeding practicesiron and vitamin supplementation of women and <5 y.o.infant and child under 5 mortality ratepercentage of children with diarrheawealth index (also LSMS)
Consumption indicatorsper-capita total consumption expenditureGini indexper-capita food consumption expenditure (in progress)Poverty indicatorspoverty headcount ratio (std. dev.), density, gap, and severity at $1.25 and $2 PPP/day
number of poor at $1.25 and $2 PPP/day9Slide10
Open-Data Architecture
Bio-physical
land use, soils, climate, pests (IIASA, CRU, USGS, UMN,
AgMIP
)
Production
SPAM(land cover, admin records, IIASA GAEZ suitability)
Socio-Economic
pop. poverty, factor productivity
(LSMS,
ag
. census, DHS, FAO)
Markets
,
Infrastructure
road networks, transportation
Data h
armonization
Up/down scaling
C
alibration
HarvestChoice
CELL5M
catalog of 750+ 10 km resolution spatial
indicators
MAPPR
TABLR
LSMS-ISA
Map/Tile Service
(WMS)
CGIAR and BMGF Project Mapping Tools
Africa RISING
FAOSTAT
HarvestChoice
Website
Other Models, Calculators
Time-series
spatial indicators
Data API
10Slide11
Applications
…
Country, farmers, and value-chain targeting (e.g. BMGF strategy refresh)
G-8 New Alliance priority-setting tools
Fertilizer use profitability calculatorsAfrica RISING site selection and SI technology evaluation (Malawi - nitrogen fixation, legumes, nutrition; Ghana - GS3SLS approach looking at land-use changes over time and income effects)
Spatial analysis of investment effectiveness11Slide12
G8 New Alliance
Value-chain priority-setting calculator tool
Ghana
:
value-chain prioritization.Which CAADP value chains to focus on? Help identify country-specific priority commodities in terms of their economic impact, importance to the poor, nutritional values, impacts on natural resources, and attractiveness to private sector.
Prototype for each country populated by IFPRI/
HarvestChoice using available secondary data sources
National teams adapt as needed and validate or replace data sources
Prioritization criteria
and weighting
Baseline
p
roduction/adoption
Yield targets
Outcome
indicators
12Slide13
Where to Target?
Geospatial targeting t
ools
By overlaying grid-based geospatial
layers, this tool helps users select target areas in country/region matching user-defined criteria and thus have more potential for scalable impact – e.g., climate, elevation, market accessibility, and linkage to other
socio-economic factors.13
http://harvestchoice.org/products/tool?product_keyword=geospatial+targeting
. Example for irrigated rice expansion in SAGCOT http://goo.gl/fIvtXqSlide14
Africa RISING
Malawi
14
Currently in
Dedza
and
Ntcheu
districts. Employs “mother
and baby
trials” approach
(
Snapp
etal
., 2012, Kerr et al., 2007
). Innovations
being promoted
include e.g.:
Maize/pigeon pea intercrop with FULL NPK at planting
and top
dressing with FULL
urea
Maize/bean intercrop fertilized with FULL NPK at planting and top dressing with FULL urea
Pigeon pea/groundnut intercrop fertilized with HALF NPKPigeon pea/soybean intercrop fertilized with HALF NPK3 / 18
http://dev.harvestchoice.org/africarising/ Slide15
Use MAPPR to browse and download indicator maps
http://harvestchoice.org/mappr/
HarvestChoice
MAPPR
Map, summarize, tabulate, download…
#1 Select indicators
#2 Toggle and re-arrange layers
#3 Generate zonal statistics
#4 Save reports
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HarvestChoice
data API documented at http://harvestchoice.org/tools/harvestchoice-data-services
HarvestChoice Data API
16
Call data API methods and return tables and maps in
GAMS
,
STATA
,
R
, JavaScript, etc..Slide17
COMING NEXT…
Harmonized layers on
farm management practices
and
input uses (LSMS-ISA, micro scale)Sub-national poverty updated to circa 2008 and 2010Additional
nutritional indicators (200 DHS surveys for 69 countries beyond SSA)Derived climate and soil quality indicators relating changes over time (CRU, AfSIS)Footprint of agricultural technologies in sub-Saharan Africa
Current and future landscape of public and private agricultural investments in the region17Slide18
About
IFPRI
ifpri.org
The International Food Policy Research Institute (IFPRI) seeks sustainable solutions for ending hunger and poverty. IFPRI is one of 15 centers supported by the Consultative Group on International Agricultural Research (CGIAR), an alliance of 64 governments, private foundations, and international and regional organizations. HarvestChoice
harvestchoice.orgHarvestChoice generates knowledge products to help guide strategic investments to improve the well-being of poor people in sub-Saharan Africa through more productive and profitable farming. To do this, a novel and spatially explicit evaluation framework is being developed and deployed. By design, primary knowledge products are currently targeted to the needs of investors, policymakers and program managers, as well as the analysts and technical specialists who support them.HarvestChoice Team at IFPRIJAWOO KOO
crop/technology modeling, biophysical constraintsCARLO AZZARRI micro-economics, sub-national poverty, nutritionBELIYOU HAILE M&E, micro-economics
APURBA SHEE
M&E
, data modeling
ELODIE VALETTE
diffusion
of innovation,
peri
-urban agriculture
CINDY COX
technical
writer, technology evaluationCLEO ROBERTS farming systems characterization
MARIA COMANESCU web development, programmingMELANIE BACOU
microeconomics, CRP mappingQUEENIE GONG crop
production statistics data managementHO-YOUNG KWON crop and soil process modeling
ULRIKE WOOD-SICHRA data management, SPAM, DREAMZHE GUO
GIS coordinator, market accessIVY ROMERO administrative coordinator
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