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Mapping current and future distribution of bat species probable reservoirs of Ebolavirus in Democratic Republic of Congo
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  • Yannick Mugumaarhahama,
  • Marcellin Cokola,
  • Arsène Mushagalusa,
  • Nadège Cirezi,
  • Espoir Bagula,
  • Katcho Karume,
  • Gustave Mushagalusa
Yannick Mugumaarhahama
Université Evangélique en Afrique

Corresponding Author:[email protected]

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Marcellin Cokola
Université Evangélique en Afrique
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Arsène Mushagalusa
Université Evangélique en Afrique
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Nadège Cirezi
Université Evangélique en Afrique
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Espoir Bagula
Université Evangélique en Afrique
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Katcho Karume
Université Evangélique en Afrique
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Gustave Mushagalusa
Université Evangélique en Afrique
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Abstract

Aim: In recent studies, three species of bat, Hypsignathus monstrosus, Myonycteris torquata and Epomops franqueti were identified as the most likely candidates to be reservoir for Ebolavirus. To help in epidemic preparedness and surveillance, species distribution modeling techniques are useful for predicting where these species are likely to occur in DR Congo. Methods: MaxEnt software was used to model the current and future distribution of the three species in DR Congo based on the occurrence data collected from global biodiversity information facility and environmental covariates collected from Worldclim and USGS. The future distribution were obtained based on two scenario (RCP4.5 and RCP 8.5) of the HadGEM2-CC an IPPC5 climate projections from global climate models (GCMs). Results: The suitable habitat of H. monstrosus, M. torquata and E. franqueti are essentially located from latitude -5° to 5° and longitude 17° to 30°. Overall, their favourable living areas are located in the territories along the entire northern border and the entire northern part of the eastern border of the DR Congo with varying degrees of importance depending on the territories and species. Three bioclimatic variables have shown to play major role in their spread, the precipitation of the driest quarter, the precipitation of coldest quarter and the temperature annual range. In the future, the suitable area of these species will be decreasing and being essentially located in the Kivu provinces. The change in the ecological niche of these species will differ with respect to future climate scenario. Climate of RCP 8.5 has shown to induce major decrease of their suitable habitat in DR Congo. Main conclusions: The MaxEnt model is potentially useful for forecasting the future adaptive distribution of the three bat species under climate change, and it provides important guidance for comprehensive management of the Ebolavirus risk.