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Prediction of breeding regions for the desert locust Schistocerca gregaria in East Africa

Authors :
Keith Cressman
Mehari Tesfayohannes
Chrysantus M. Tanga
Henri E. Z. Tonnang
Thomas Dubois
Elfatih M. Abdel-Rahman
Emily Kimathi
Menale Kassie
Baldwyn Torto
Sevgan Subramanian
Saliou Niassy
Segenet Kelemu
Sunday Ekesi
David Miano Mwangi
Source :
Scientific Reports, Vol 10, Iss 1, Pp 1-10 (2020), Scientific Reports
Publication Year :
2020
Publisher :
Nature Publishing Group, 2020.

Abstract

Desert locust outbreak in East Africa is threatening livelihoods, food security, environment, and economic development in the region. The current magnitude of the desert locust invasion in East Africa is unprecedented and has not been witnessed for more than 70 years. Identifying the potential breeding sites of the pest is essential to carry out cost-effective and timely preventive measures before it inflicts significant damage. We accessed 9,134 desert locust occurrence records and applied a machine-learning algorithm to predict potential desert locust breeding sites in East Africa using key bio-climatic (temperature and rainfall) and edaphic (sand and moisture contents) factors. Ten days greenness maps from February 2020 to April 2020 were overlaid in model outputs to illustrate the temporal evolution of breeding site locations. This study demonstrated that vast areas of Kenya and Sudan, north eastern regions of Uganda, and south eastern and northern regions of South Sudan are at high risk of providing a conducive breeding environment for the desert locust. Our prediction results suggest that there is need to target these high-risk areas and strengthen ground surveillance to manage the pest in a timely, cost-effective, and environmentally friendly manner.

Details

Language :
English
ISSN :
20452322
Volume :
10
Issue :
1
Database :
OpenAIRE
Journal :
Scientific Reports
Accession number :
edsair.doi.dedup.....8309458fd750aec67b8b8971aa0de398
Full Text :
https://doi.org/10.1038/s41598-020-68895-2