A Digitally Integrated Africa Soil Information Service (AfSIS)

Grantee institution:The International Centre for Tropical Agriculture (CIAT)

Budget: US$ 18.1 m

Implementing Institution:Tropical Soil Biology & Fertility (TSBF) Institute of (CIAT)

Partners:Columbia University’s Earth Institute

World Soil Information (ISRIC)World Agro-forestry Centre (ICRAF)

5 initial NARS in Africa (Kenya, Tanzania, Malawi, Mali & Nigeria)

22 other African countries

Presentation Outline

• Background• Foreseen Impact• Project Activities• AfSIS Data Systems• Soil Surveys• Fertility trials• Capacity building, user outreach, policy &

dissemination

Background

Numbers

• About 500 million hectares of sub-Saharan Africa’s agricultural land are moderately or severely degraded

• African farmers are able to apply only 10 percent of the nutrients that farmers in the rest of the world return to the soil

• soils in southwestern Kenya, for example, lose an estimated 100 kilograms of nitrogen per hectare each year

Nutrient depleted soils reason for poor crops & low productivity

Large scale land degradation due to soil erosion: How to address?

Impact

Foreseen Impact• Provide accurate & spatially explicit soil database for 42

African countries

• Contribute to the reversal of soil degradation in Africa

• Contribute to increased crop yields & improved livelihoods for approximately 1 to 2 million poor African households

• Prepare material and evidence to guide policy and action that enhances Africa’s soil & crop productivity

• Contribute to the development of African institutions capacity to be able to map, disseminate and use soils information to plan natural resource management in their countries & in the continent

The Sahelian DrylandsArea: 1.2 million km2

Population: 38 millionMillet & sorghum belt: 23 million ha

Humid Forest ZoneArea: 5.8 million km2

Population: 168 millionCassava belt: 18 million haNERICA potential: 2 million ha

Moist Savanna and Woodland Zones

Area: 4.4 million km2

Population: 157 millionMaize belt: 32 million haCA potential: 7 million ha

S

N

EW

0 1000 2000

kilometers

Initial Impact Initial Impact zones zones targeted by targeted by AfSISAfSIS

Nigeria

Kenya

Malawi

Tanzania

Mali

Project Activities

AfSIS Objectives

Objective 1: Global efforts to fund raise & prepare the GlobalSoilMap.net & collecting soil pedology legacy data for the African node (AfSIS)

Coordinated by ISRIC

Objective 2: Cyber Infrastructure & soils databaseCoordinated by CIESIN at Earth Institute

Objective 3: Soil survey covering 18.1 sq km using unbiased statistical sampling and soil properties prediction modeling from 60 sentinel sites in 27 sub-African countries

Coordinated by TROPAG at Earth Institute

AfSIS ObjectivesObjective 4: • Implementing field management trials in 5 countries• Collecting & analyzing legacy experimental data

Coordinated by CIAT-TSBF

Objective 5: Capacity building, serving end users, defining use cases,

dissemination, articulating policy, & articulating impact pathways

Coordinated by CIAT-TSBF

Objective 6: M & E plan and overall project management

Project Director –Dr. Pedro Sanchez

Some details about the AfSIS Activities

AfSIS Data Systems

Objective 2: CIESIN

Sonya Ahamed, Tor V, Jubal, P. Okoth

Dissemination

• Project Website

• http://www.AfricanSoils.net

• Map Servers

• Global plus AfSIS Databases

• Global soil data models

• Capability for on-line updates with walking sticks for off-line access & use

Soil Surveys

Objective 3

Markus Walsh, Tor Vagen, Keith Shepherd, Jerome Tondoh, Luseged

AfSIS Sentinel Sampling

• ~17.5 million km2 of continental SSA

• ~0.6 million km2 of Madagascar

• Spatially stratified random sampling approach consisting of 60 sites

• Each 100 km2 • 42 countries with 95% of

human population• ~9,600 new geo-referenced

soil profiles• 38,000 individual soil

samples

One Sentinel Site

10 km

10 km

Total of 160 sampling Points per site

4 soil samples per point

Example of a digital soil carbon condition map of Segou in Mali

Low resolution-wider coverage High resolution-less coverage

Fertility Trials

Objective 4Jeroen Huising Cheryl Palm,

Generose Nguziheba, Shamie Zingore & P. Okoth

The yield gap and the limitations that cause it

0

500

1000

1500

2000

2500

3000

3500

4000

4500

Maize Soybean Cowpea

Gra

in y

ield

(t h

a-1

)

Farmer

Researcher

Derived Savanna

Potential yield

(Experimentation)

Actual yield

Yield gap

Biophysical limitations- Soil fertility- Water- Variety, etc

Socio economic and policy limitations- Knowledge- Credit availability-Inputs-Output Markets

Which inputs are lacking?

Why inputs are not used?

Our aim: prevention, restoration & productivity

AfSIS Impact Target Zones

• Soil fertility recommendation trials installed in 5 countries marked in yellow

• Soil management recommendation framework developed from past experimental legacy data and from new management recommendation trials

Capacity building, user outreach & dissemination

Objective 5

Peter Okoth, Policy Economist, Extension, Market, other PIs, etc

Activities under Objective 5

• Capacity building

• Use Cases

• Impact pathways

• Policy formulation

• Partnerships

• Dissemination

• Monitoring & Evaluation

Training & Capacity building

• Training for capacity building in:– Soil Survey (numbers trained on the job)– NIR/MIR scanning, analysis & interpretations

(numbers trained on the job)– Management & recommendation trials

(numbers trained on the job)– ISFM and targeting recommendations

(numbers trained on the job)– Formal training ( numbers of graduate level

training at MSc & PhD)

Dissemination

Peter Okoth, Extension (Public, Private, NGOs), Agro-dealers,

Media

Questions

• Dissemination: Which tools are currently available for this? How do we maximize out-scaling of

knowledge and data? Which are the incentives to ensure adoption

and sustenance of technology use once disseminated?

Who does what? How do they do it? Who pays for it?

Steps towards dissemination

soil fertility ISFMmanagement

trialspossible spatial

interventiondomains

geo-referencedspatial soils data

& information

cyberspace

ana

lysi

s &

inte

rpre

tatio

n

diag

nost

ic d

educ

tions

other dissemination

media

analysis & interpretation

diagnostic deductions

managementrecommendationsPolicy guidelines

& Briefs

1

23

45

6

7

8

9

10

F

F

Obj 3

Obj 4Obj 4

Objs 4 & 5

F

Objs 2 & 5 legacydata

analysis

AfSIS dissemination construction & user

concerns

object location

geometricattributes

soilattributes

HA

RD

WA

RE

SOFTWARE

KN

OW

LED

GE

WH

O?

HOW

? WH

ERE?

WH

AT?

USERS

USERS

USER

S

USE

RS

GIS system interface

User concerns & project objectives response interface

3,4

3,4,5

2,5

2,5

object

Specific objectiveattention domains

Who?International National Local

HarvestChoice Agro-dealers Researchers

HarvestPlus Fertilizer buyers Local public extension service providers

Fertilizer manufacturers Fertilizer blenders CBOs/NGOs

AGRA Public extension service providers

Agri-business

African CGIAR scientists Seed companies Media

Regional networks Private advisory services Local policy makers

Un agencies Policy makers & regulators NUANCES-farmers

NEPAD Agricultural investors Breeders

Development partners Researchers & students Watershed managers

Global climate modelers Ecosystem modelers & land use planners

WhatThemes Measured attributes Predicted attributes

Keith obj3 soil samples spectral signatures

inherent soil properties

Markus obj3 Field and sampled soil properties

Functional soil properties

Jeroen obj4 yield responses to different management treatments

Decision framework to arrive at predicted responses for different management scenarios

CovariatesCovariates

Legacy & Legacy & new datanew data

1. Data Input1. Data Input

2. Soil properties2. Soil properties

Soil MapSoil Map

ClayClay

OCOC

pHpH

BD Water Water storagestorage

Al toxicityAl toxicity

FertilizerFertilizer responseresponse

ErosionErosion

CarbonCarbonManagementManagement

3. Soil functions3. Soil functionsSpatial Spatial

inferencinferenc

ee

modelsmodels Pedotransfer

Pedotransferfunctionsfunctions

Social Social CovariatesCovariates

Legacy dataLegacy data

4. Management4. Management InputsInputs

5. Management5. Management recommendations recommendations

FertilizerFertilizerapplicationapplication

ErosionErosion controlcontrol

ClimateClimate mitigationmitigation

Crop Crop selectionselection

IrrigationIrrigation

6. End Users6. End Users

Policy-makersPolicy-makers

ExtensionExtension

ScientistsScientists

Farmers

Agro-business

Decision Decision

analysisanalysis

Dec

isio

nan

alys

is

TrainingTrainingDisseminationDisseminationCyber-Cyber-

infrastructureinfrastructure

What?

• Structured content (tables, narratives, figures, pictures, video clips, trends) from objectives 3 & 4

• Decisions on what to avail for access by the different levels of users

Where

• Geo-referenced geometric as well as thematic attributes of the soil properties

• Political boundaries (national, district, location, sub-location, etc)

• Geomorphologic boundaries and the corresponding landform units

• Road networks with centers and towns

Dissemination tools in AfSIS

Tools Target Audience

Project Website & Blogs Global

Google Earth et al. Global

Publications Global Scientists

Workshops International, national, district, local

Extension (public, private, NGOs, etc)

Farmers indirectly, Local & National

Wireless and mobile phones Extension & farmers

CDs, DVDs, Mailing list

TV, Radio, Print Media Local, national

AFSISPROJECT

DATABASE

WEATHERCHANNEL

AGRO DEALERSDIGITAL MAP

COMMODITYTRADERS

FARMERS, AGRO-DEALERS

REGISTER &DATABASE

NU

AN

CE

S

EX

TE

NS

ION

SE

RV

ICE

NA

TIO

NA

LP

OL

ICY

MA

KE

RS

DE

VE

LO

PM

EN

T

PA

RT

NE

RS

INV

ES

TO

RS

GSM NETWORKS

PRIVATE IT COMPANY

FARMERS & AGRO-DEALERS

FARMER’S & AGRODEALERS

REQUESTS

SOILWEATHER

PRICESMARKETSE-CREDIT

COMPANIESNGOSCBOS

SC

IEN

TIF

IC C

OM

MU

NIT

Y

GOOGLE EARTH

IMPACT ORIENTED DISSEMINATION

POSSIBLE END USERS

Impact!-How?

FARMER SUPPORTSERVICES

COMPANY RESPONSE

Achievements so far• Launch on 13th January 2009• Promotion in over 50 media houses including print, audio and blogs• Visited 3 node countries to install necessary infrastructure• Purchased vehicles • Purchased computer hardware• Purchased 20 GPSs• Recruited 1 MSc student already in Aberdeen University• Hired Scientist for West & Southern Africa (Objective 3)• Hired Socio-economist• Conducted interviews for an M&E position• Taken on board Southern Africa TSBF scientists• Worked on 2009 project workplan• Initiated experimental work in Mali• Process of getting the Arusha office operational• Ordered Spectrometers & GPS equipment• Implemented www.Africasoils.net• Initiated discussions with AGcommons on Use Case definition

Thank you!Ahsante sana!

Use cases

• Which uses of soil data and information can we think of?

• How do we capture the variety of potential users?

• Which tools are available to do this?• Which soil variables are most relevant?• Which decisions can be made from AfSIS

soil information • Which kind of decisions can be made?

Impact Pathways

• Partnerships: Which kind of partnerships do we need to

have for maximum impact? How do we structure the partnerships? How do we sustain the partnerships?