GIS @ILRI

A quick overview and some examples

GIS at ILRI

• Research:

Wide variety of projects

Within the different “themes”

• Services:

Part of RMG (Research Methods Group)

SW and data management

Advice and services

Capacity Building

Data sourcing and sharing

Some exciting GIS outputs anno 2008• Poor Livestock Keepers / Value of Production

SSA and SA An Notenbaert, Patrick Kariuki, Abisalom Omolo

• USLE Based Potential Erosion Map Nile Basin Paulo van Breugel, A. Notenbaert, L. Claessens, J. VdSteeg

• Livestock water productivity and crop water use Nile Basin Paulo van Breugel

• Simplified productions systems map (4 classes) + projection to 2030 Global An Notenbaert, R. Kruska, P. Thornton, M. Herrero

• Projections for crops, livestock, livestock products, water use, malnutrition Developing world Mario Herrero, An Notenbaert

• Climate Change hotspots + VOPs ASARECA Jeannette Van de Steeg, M. Herrero, P. Thornton

• Vulnerability indicators GHA James Kinyangi, A. Notenbaert, M. Herrero

• Composite Risk maps COMESA An Notenbaert, Stella Massawe

• GOBLET and the “development domains tool” Global Carlos Quiros, An Notenbaert

• Avian Influenza Risk maps Africa, Asia, Indonesia Wachira Theuri, Russ Kruska, Acho Okiko

• Innovation successes Ethiopia Patrick Kariuki, R. Puskur

• Updated poverty maps Uganda Patrick Kariuki

• M&E Site selection – chilling plants and hubs for small-holder dairy. East Africa Pamela Ochungo

• Kitengela Atlas (Wildlife and livestock, fences) Kitengela Shem Kifugo, Mohamed Said

What is planned for 2009 (and beyond)• LS production systems toolbox (incl. standard classifications) and LS productivity

An Notenbaert, M. Herrero, P. Thornton, R. Kruska

• Length Growing Period and Cereal production under different scenarios / GCMs Philip Thornton

• Global rangeland model + carbon sinks + responses to CC Stefano Disperati / Joseph Maitima, M. Herrero

• Dynamic vulnerability for SSA (+ Mali & Mozambique) An Notenbaert, M. Herrero, P. Thornton, N. Johnson

• Intensification thresholds and nutrient balances (global) Jeannette Van de Steeg, M. Herrero

• Ecosystem services in the pastoral areas (+ links with food/environmental security) Stefano Disperati, J. van de Steeg, M. Said, M. Herrero

• Methane emissions from livestock (global) Mario Herrero, P. Thornton, R. Kruska

• Feed supply (crops, forages, rangelands) & feed demand + impacts CC + Feed markets (global) Mario Herrero, Michael Blummel, A. Notenbaert

• Integration of livestock in LU and economic models Mario Herrero, P Thornton

• Water poverty and vulnerability in the Nile Basin James Kinyangi, T. Ouma, A. Notenbaert

• Climate – Land use interactions in East-Africa Joseph Maitima, Jenny Olson

• Evaluation of Arid Lands Resource Management Program Abisalom Omolo, A. Notenbaert

• Landscape genomics Steve Kemp

• East Coast Fever (risk mapping, spatial targeting of delivery), RVF and bird flue Phil Toye, Frank Hansen, Jeff Mariner

• Value chains and market access (distance to markets and services; collection and distribution of market information, risks and diseases) Steve Staal, Derek Baker

1. SLP drivers of change

Drivers of change in crop-livestock systems and their potential impacts on agro-ecosystem

services and human well-being to 2030

Herrero, M., Thornton, PK, Notenbaert, A., Msangi, S., Wood,S., Kruska, R., Dixon, J., Bossio, D., van de Steeg, J.,Freeman, H.A., Li, X. and Parthasarathy Rao, P.

CGIAR Systemwide Livestock Programme.

SLP drivers of change

…. can the poor benefit from these changes?…. can we change without compromising food security, ecosystems services and livelihoods?

PR

OB

LEM

Population increasing, Urbanisation, Increased demand for LS products, Intensification, Climate change, Technology shifts, Globalisation, ….

Systems are changing:

SLP drivers of change

FRA

MEW

OR

K

SLP drivers of change

MET

HO

DS

4 Scenarios:

Reference

Bio-fuels Scenario

Irrigation Expansion

Low meat Demand

SLP drivers of change

SOM

E K

EY F

IND

ING

S1. Mixed intensive systems in the developing world are under significant

pressure From 2.5 to 3.4 billion people, from 150 to 200 million cattleSustaining most of the pigs and poultry and still increasing by 30-40%Most of the crops yields as well as areas stagnatingWater and soil fertility problems

Important productivity gains could be made in the more extensive systems

Annual changes in Cereal Production

2000 - 2030

0

1

2

3

4

5

6

CSA EA SA SEA SSA WANA Total

%

AgroPastoral Mixed Extensive Mixed Intensive Other Developed countries

Rates of growth of mixed intensive similar to developed

countriesCatching up

Rates lower than those of population growth

Rate of Change - Cereal Production

2000 - 2030

SLP drivers of change

SOM

E K

EY F

IND

ING

S2. Growth rates of cereal production are diminishing due to water and other

constraints… while LS production is growing at significantly faster rates

Annual rates of change - milk production 2000-2030

0

1

2

3

4

5

6

7

8

9

CSA EA SA SEA SSA WANA Total

%

AgroPastoral Mixed Extensive Mixed Intensive Other Developed countries

Annual rates of change - pork production

-4

-2

0

2

4

6

8

CSA EA SA SEA SSA WANA Total

%

AgroPastoral Mixed Extensive Mixed Intensive Other Developed countries

Annual rates of change - poultry production

0

2

4

6

8

10

12

14

CSA EA SA SEA SSA WANA Total

%

AgroPastoral Mixed Extensive Mixed Intensive Other Developed countries

Annual rates of change - beef production 2000-2030

0

1

2

3

4

5

6

7

8

CSA EA SA SEA SSA WANA Total

%

AgroPastoral Mixed Extensive Mixed Intensive Other Developed countries

Increases in: Income, Demand, Pressure on resources, Demand for grains

SLP drivers of change

SOM

E K

EY F

IND

ING

S3. “Moving megajoules” - fodder markets are likely to expand as demand for

meat and milk increases

4. Expansion of bio-fuels will likely reduce household food consumption in all systems

5. Some systems may need to de-intensify or stop growing to ensure sustainability of agro-ecosystems services

Better understanding of intensification thresholds: regulatory framework and M&E system

Incentives to protect environment / equitable “smart” schemes for payment of eco-system services

We need significant efficiency gains (in crops, livestock and other sectors alike)

2. Epidemiology

Thrusfield, M. (1995): Veterinary Epidemiology. Blackwell Science

Distribution of diseases in populations as well as factors

influencing their occurrence

spatial

- epidemiology is the ecology of diseases

„Unter Oecologie verstehen wir die gesamte Wissenschaft von den

Beziehungen des Organismus zur umgebenden Außenwelt.“

Ernst Haeckel 1866

German ecologist

“ecology is the science of the relationships of

the organism to the surrounding world”

space

Epidemiology is a spatial discipline

yet study of spatial interactions is often neglected

What’s happening in ILRI?

- disease risk mapping

- spatially explicit, agent based dynamic system modelling

- Bird flue in 5 countries in Africa and Indonesia

- East Coast Fever in East Africa

- Rift Valley Fever in Kenya

Epidemiology

Risk map for Avian Influence in Nigeria (Acho Okike ILRI Ibadan))

Epidemiology

A transport model for the spread of Avian Influenza in Nigeria

- AI mainly spread by transport of infected chicken or equipment

- Model calculates how far infection can maximally spread based on time

to cross a grid cell

Distribution of Ripicephalus appendiculatus the vector of Theileria parva

the causative agent of East Coast Fever

www.nhc.ed.ac.uk

www.fao.org

In planning:

- derive habitat model

- predict habitat under climate change

scenarios

- predict future distribution of vector

and disease

- targeting control measures

- huge economic losses in cattle

- native breeds more resistant

- exotic and mixed breeds increase productivity

but are very susceptible to ECF

http://outreach.eos.nasa.gov

Rift Valley Fever

- Mosquito-borne disease of cattle and humans

- periodic outbreaks can be predicted by weather conditions

- risk-based Decision Support Tool to plan intervention (vaccination, vector control..)

- in planning: revise Decision Support Tool and include economic measures

Thank you

Crops: You and Wood

Ag.Pot: LGP>180days or equipped for irrigation

MA: less than 8 hours to >250K