Early Warning System for Monitoring Nutrition and Livestock Health and the Food Security of Humans in
Eastern Africa (LEWS)
Early Warning System for Monitoring Nutrition and Livestock Health for Food Security of Humans in East Africa is a subproject (one of four
subprojects in East Africa) within the USAID funded Global Livestock Collaborative Research Support Program
(GL-CRSP). It is being implemented
by Texas A&M, and the complementary Crisis Mitigation Project by the Association for Strengthening Agricultural Research for East and Central
Africa (ASARECA), Livestock Network, managed by International Livestock Research Institute
(ILRI).
Famine and food security in East Africa have been a chronic issue for decades because of the weather variation, expansion of human populations,
political instability and changing land use/tenure policies in the region. For pastoralists in the region, survival of their livestock herds determines
their well being. Donor organizations have initiated a variety of activities designed to address the plight of pastoralists in the region. USAID's
Famine Early Warning System (FEWS) is one example along with a variety of regional drought preparedness programs and in-country early warning
programs throughout the Greater Horn of Africa. To respond to uncertainty, pastoralists in East Africa must be afforded more timely, quality
information about their local conditions and trends and be given options in both a spatial and temporal context.
An early warning system will be developed for East Africa to provide the capability of detecting changes in the well-being of free-ranging livestock
before they are normally detected by the pastoralist or crisis monitoring organizations. LEWS project has 6 validation sites set up in Eritrea, Uganda,
Tanzania, Kenya and Ethiopia (see map). The purpose of these sites is to make final adjustments in the models and fecal profiling technologies that
will be used in the livestock early warning system.
A series of tools, i.e., spatially explicit analyses and direct animal nutrition monitoring, developed in the Texas Agricultural Experiment Station, will
be integrated into the existing crisis monitoring infrastructure in 5 East African countries (Eritrea, Ethiopia, Kenya, Tanzania, Uganda). Information
on projected trends in livestock condition (e.g., weight, mortality, milk, reproduction), forage supply and crop stability will be provided in a timely
manner to supply the decision-making processes with information that is 6-8 weeks earlier than the present monitoring systems. This will allow more
timely and informed decisions relative to issuance of crisis warnings and interventions, as well as reduce environmental degradation. The spatial
monitoring and analysis system will be integrated with ASARECA to help identify mitigation research topics.
A series of in-country core teams have been formed to help design criteria to establish a classification system of the region which allows spatial
representation of "effective environments" using the weather, terrain, soil, and human and livestock datasets in the GIS-based Spatial
Characterization Tool (SCT). A set of criteria will be established to define the effective environments, sampling locations within the effective
environments and monitoring sites within a location. Location and site selection criteria will be based on the nature of infrastructure available to the
team and level of funding. However, we expect to identify sampling routes and actual sites within a location representing an effective environment
based on 1) accessibility, 2) institutional infrastructures (e.g., monitoring programs, schools, or
NGO/PVO activities), 3) existing governmental
infrastructure such (e.g., universities, extension offices and experiment stations), 4) degree of pastoral community-based organizations and 5)
personal security risk of the samplers. Nutritional well-being of free-ranging livestock will be assessed through fecal profiling via near infrared
reflectance spectroscopy (NIRS). The geo-referenced fecal profiles will be integrated with the
SCT, the livestock population surveys and continuous
10-day weather datasets from the USAID/USGS-NOAH FEWS program. This integration will provide a foundation dataset for a metamodeling
systems involving a multiple species plant growth/livestock production model (PHYGROW), a livestock nutrition model (NUTBAL), a mixed farming
crop model (APEX) and a modified El Nino/Southern Oscillation driven model calibrated for East Africa. Analyses will be disseminated within the
current communication infrastructure of regional, national, and international early warning systems.
Predictions from the LEWS project will be fed back into the FAO Global Information and Early Warning System
(GIEWS) and USAID Famine Early
Warning system (FEWS) reporting systems and the ASARECA Crisis Mitigation Office. The SCT system will serve as a visual reporting system for
emerging trends and potential hot spots.
The LEWS project intends to leave in place the analytical capacity and the human resources to sustain the monitoring and early warning system
linked to key policy makers and agencies capable of taking actions to mitigate crisis emerging from poor nutrition,
inadequate forage supply and lack of water.
