Predictive Livestock Early Warning System (PLEWS): Monitoring forage condition and implications for animal production in Kenya

Abstract

Weather and climate extremes have impacted forage conditions and lead to loss of animal production and livelihood of livestock-dependent communities in Kenya. Monitoring of forage conditions and developing a reliable early warning system can reduce the loss of livestock and improve the resilience. In order to enhance resilience of affected populations, through a collaboration of multiple agencies in Kenya and beyond, a dynamic web-based Predictive Livestock Early Warning System (PLEWS) decision support tool was developed. The system combines the water balance, PHYGROW (Phytomass Growth Model) simulation model and spatial analysis tools to generate current and a 6-monthly forecast of forage conditions. Although in its pilot phase, the tool holds potentials to provide decision support with anticipatory actions by communities, regional and national governments. By utilizing the output and engaging such pre-emptive interventions, emergencies can be prevented by promoting proactive decision-making conditioned on advance information of forage conditions. Timely actions based on advanced information can reduce potential impacts of extreme weather and climate events on livestock. The pro-active actions can reduce the losses and response costs associated with the impacts of weather, climate extremes and can improve food security of most vulnerable populations. Keywords: Early warning, Livestock, Community resilience, Drought, Livelihoods