Famine and food security in East Africa have been a chronic issue for decades given the weather variation, expansion of human populations, political instability and changing land use/tenure policy 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, of which 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 The 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. 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 inform current decision-making processes with information that is 6-8 weeks earlier than current 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 the coordinating organization for agriclutural research in East Africa (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 Cahracterization 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 based on the nature of infrastructure available within a location representing an effective environment based on;
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 along with livestock population surveys and continuous 10-day weather datasets from the USAID/USGS-NOAH FEWS program to provide a foundation dataset for a meta-modeling system 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 Niño/Southern Oscillation driven model calibrated for East Africa.
Analyses will be disseminated within the current communication infrastrcture of regional, national amnd international early warning systems.
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Technology
Department of Rangeland Ecology & Mgmt
Texas A&M University College Station, Texas
For comments or suggestions contact aajama@cnrit.tamu.edu