vital signs: an integrated monitoring system for agricultural landscapes
DESCRIPTION
Presented by Roseline Remans, Columbia University at the Africa RISING–CSISA Joint Monitoring and Evaluation Meeting, Addis Ababa, Ethiopia, 11-13 November 2013TRANSCRIPT
Vital SignsAn Integrated Monitoring System for Agricultural Landscapes
Africa RISING–CSISA Joint Monitoring and Evaluation Meeting, Addis Ababa, Ethiopia, 11-13 November 2013
Roseline Remans, Columbia University
An Integrated Monitoring System for Agricultural Landscapes• Ecosystem Services• Agricultural Production• Human Wellbeing
Vital Signs isstarting in
SubSaharan Africa
ETHIOPIAGHANA
TANZANIA
UGANDA
RWANDA
MOZAMBIQUE
Regions of impending agricultural change
For decision making
Co – location of data in space and time – to assess tradeoffs and synergies
Use of existing systems and data as much as possible – often adding the environmental components
Ownership by governments to link with national data collection efforts
Build national capacity on data collection, storage, analysis and use
Integrated Monitoring of Agricultural Landscapes
6
decisionlayer
analytical layer
measurement layer
development agencies, private sector, donors,
NGOs, farmer associations, national governments
analytics engine(models and trade off analysis + algorithms)
analytical outputs
data + metadata
archive and management
decision support dashboard
other networks and data sources
LSMS, AfSIS, FAO,
GEO.....
remotely sensed + in situ
Vital Signs Approach - 1. Analysis threads
VITAL SIGNS DECISION INDICATORS CATEGORIES
Thread Indicator Agriculture Human wellbeing
Ecosystems Services
Climate Forcing Net AFOLU Climate Forcing XBiodiversity Biodiversity Security XWood Fuel Wood fuel Energy Security X X
LivestockRangeland degradation XForage Adequacy X X
Water Water Security X X XResilience Resilience or buffering index X X XInclusive Wealth Sustainability index X X XFood Security Food Security Index X XSoil Health Soil Health Index X XAg. Intensification Yield Target (%) XPoverty Poverty X
Health Prevalence of malaria, diarrhea, anemia X
Nutrition % overweight, under weight, stunting, and wasting X
GLOBALFacilitating comparisons among different regions
REGIONProviding insights and information at the scale on which agricultural investment decisions are made
LANDSCAPEMeasuring relationships between agricultural intensifications, ecosystem services and human wellbeing
FIELD/PLOTTracking agricultural production, including inputs and outputs
HOUSEHOLDUsing surveys on health, nutritional status, income and assets
Tiers 1 and 2 Tiers 3 and 4
Vital Signs Approach - 2. Sampling framework and Measurement scales
Sampling Framework
• Tier 1 – simple measures, complete regional coverage at moderate resolution, based on models and remote sensing– Land cover, vegetation type, biomass, modeled NPP – yields
• Tier 2A -1 ha plots, in situ detail, statistically valid sample - to validate Tier 1 and measure things not ‘seen’ by RS (250-500 plots sampled;
• Tier 2B: 500+ HHs depending on national surveys• Population, disaggregated national statistics
• Tier 3 – Flow based, continuous sampling – weather station, hydrological flows
• Tier 4 – Process-oriented studies at high resolution- – Five to ten 10X10 km landscapes per region – 30-40 households per landscape with associated fields
Tanzania SAGCOT development clusters and protected areas
Ghana Tier 2a plots and Tier 4 landscapes
Natural Systems
Slash & Burn Agriculture; shortened
fallows
Degraded Systems
Rehabilitation through
intensification
Intensive Management
Time and Population Density
Bonsaaso, Ghana`
Mbola, Tanzania
Koraro, Ethiopia
Sauri, KenyaRuhiira, Uganda
Ecos
yste
m s
tock
s, fu
nctio
ns, s
ervi
ces
Regions of impending agricultural change
SAGCOT DEVELOPMENT CLUSTERSAND PROTECTED AREAS