Spatial Data and Analysis in Support of Improved Policy and Planning

Christopher Auricht chris@auricht.com

John DixonJohn.Dixon@aciar.gov.au

ACIARCanberra 21 June 2012

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Talk outline Context and Background Needs Issues and status of spatial data Methodology used in developing an updated

farming systems dataset and analysis for Sub-Saharan Africa

Status and future work

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Facts According to CGIAR analysis

One billion of the worlds poor within Africa and Asia (those living on less than $1 per day) are fed primarily by: hundreds of millions of small-holder farmers (often

with less than 2 ha of land, several crops, and a cow or two), or

Herders (most with fewer than five large animals)

Solution Develop sustainable farming systems that

improve efficiency gains to produce increased food production

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One Billion People Suffer Chronic Hunger and Poverty

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Scale of Rural Hunger Nearly one billion people experience debilitation,

health-threatening hunger each year 4 out of 5 of these people are rural farmers

Trends in maize shortage in ZambiaPercentage of farm households with maize shortage

The Hunger Period

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Hunger Hotspots Superimposed on Farming Systems

Source: InterACADEMY Council 2004

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Background Business as usual investments in agriculture unlikely

to deliver sustainable solutions in many countries Numerous issues often identified as barriers to

progress e.g. inefficiencies in program delivery, political uncertainty etc. These are not the only problem!

Existing systems (often under stress) have been, and are expected to continue to accommodate large increases in population, increasing urbanisation, rising demand for animal products and competition for land and water

Forecasts suggesting that current practices will not stay abreast with population growth, environmental change and increasing demand for animal products.

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Needs Requires a strategic approach, an appreciation of

scale, and an understanding of the interactions between and within systems

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The current ACIAR project Builds on the work of Dixon et al 2001

www.fao.org/farmingsystems/

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2001 Farming Systems and Poverty Global study – part of the World Bank Rural Sector

Review Widely accepted as pioneering body of work – looked at

things as a ‘surface’ across landscape not confined by country borders

Largely driven by LGP/AEZ and market access, supplemented by expert opinion

Extensively used to guide investment at the program level and frame analysis in numerous global studies

Approach focused on high level farming systems within six developing regions

Involved use of various thematic data layers to underpin the delineation, characterisation / description and subsequent analysis of systems

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Kenya

Tanzania

Zimbabwe

Zambia

Moz

ambiqu

e

Uganda

Rwanda

Malawi

#

900 0 900 Kilometers

N

Major Farming Systems

1. Irrigation

2. Tree crop

3. Forest based

4. Rice-tree crop

5. Highland perennial

6. Highland temperate mixed

7. Root crops

8. Cereal-root crops mixed

9. Maize mixed

11. Agro-pastoral millet/sorghum

12. Pastoral

13. Sparse (arid)

14. Coastal artisanal fishing

Major Lakes

National Boundaries

Major rivers

Regional ProgrammeCountries

10. Large commercial and smallholder

Program Application

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Hunger Hotspots and Farming Systems

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Sub-Saharan Update Farming systems website in FAO still one of

the most visited sites within the organisation

Previous study 10 years old Consistent seamless datasets somewhat

limited in original work In need of updating as spatial extent of

systems and frame conditions changed e.g. climate, population, urbanisation, market access etc.

Many updated and new datasets available

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Current Situation 2012 – Large quantity of potential datasets – approx. 300

alone in the Harvest Choice database longitudinal and some predictive data now available

GAEZ 3.0 - 1,000’s of datasets representing 100’s of thematic layers

Challenge – which ones to use and how Strategic approach

Access and collation Assess (fit-for-purpose) and Prioritise (currency, coverage,

scale etc) Process Products Disseminate

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Methodology Work in collaborative fashion with authors and other large

data providers e.g. IFPRI – Harvest Choice, UN-FAO, ILRI, ICRAF, IIASA, CGIAR others

.

Spatial and Tabular Data

Delineate new Farm-ing System Boundar-ies – Iterative pro-cess based on concept of central tendancy

Statistics and Anal-ysis

Characterise and describe systems

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Approach Integration of new datasets –

LGP and Market access Supporting Datasets

Population (rural, urban, total) Livestock – cattle, sheep, goats, poultry, LU and

TLU Crop areas and production Yield gaps Protected areas Poverty $2.00 and $1.25 /day Nutrition

ElevationSlope, aspect, drainageSettlements, ports, marketsRoad, rail, river, ICT networksMarket travel times & costs

Hunger, Poverty & Productivity Spatial Covariates/Proxies & Analytical Flow

Port travel times & costs

Terrain, Demography,

Infrastructure, Admin Units

ProductionEnvironment &

Constraints

ProductionSystems &

Performance

Interventions/Responses

Agroecological ZonesCropland extent & intensityPests & Diseases (Maize Stem Borer)Drought Incidence & SeverityRunoffAdministrative Units Farming SystemsCrop Suitability: Rainfed WheatCrop Distribution & YieldsValue of Production per Rural Person

NA

010

2030

40

0

1

2

3

4

5

6

7

100 80 60 40 20 0

IrrigationThreshold

% of AvailableSoil Water

MaizeYield

Potentialt[DM]/ha

Fertilizer Application Ratekg[N]/ha

Yield Responses to Inputs, Management, CCProfitability of small scale irrigationQuantity of Nutrients RemovedFertilizer ProfitabilityDistribution of Welfare Benefits

Linkage toMacroModels

Aggregate to FPUs

Source: HarvestChoice 2010

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Changes between 2001 and 2012

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Updated FS Boundaries and LGP

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Yield Gap – Aggregate of Major Crops

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Big questions for management and policy

What is it? Where is it? What are its characteristics and how does it

operate ? What are the risks/threats ? What are the opportunities (Research / Extension)

? How changing with time ? Evaluation and Performance

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Spatial data Tool to support process Understand Analyse Develop interventions Monitor Not the answer in itself

has limitations Fit for purpose Complement with expert knowledge

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Thanks Acknowledgements

ACIAR IFPRI – Harvest Choice CGIAR ILRI ICRAF FAO IIASA others

Questions & Discussion