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. 2019 Oct 2;9(1):14187.
doi: 10.1038/s41598-019-50765-1.

Modeling the global distribution of Culicoides imicola: an Ensemble approach

Affiliations

Modeling the global distribution of Culicoides imicola: an Ensemble approach

Samson Leta et al. Sci Rep. .

Abstract

Culicoides imicola is a midge species serving as vector for a number of viral diseases of livestock, including Bluetongue, and African Horse Sickness. C. imicola is also known to transmit Schmallenberg virus experimentally. Environmental and demographic factors may impose rapid changes on the global distribution of C. imicola and aid introduction into new areas. The aim of this study is to predict the global distribution of C. imicola using an ensemble modeling approach by combining climatic, livestock distribution and land cover covariates, together with a comprehensive global dataset of geo-positioned occurrence points for C. imicola. Thirty individual models were generated by 'biomod2', with 21 models scoring a true skill statistic (TSS) >0.8. These 21 models incorporated weighted runs from eight of ten algorithms and were used to create a final ensemble model. The ensemble model performed very well (TSS = 0.898 and ROC = 0.991) and indicated high environmental suitability for C. imicola in the tropics and subtropics. The habitat suitability for C. imicola spans from South Africa to southern Europe and from southern USA to southern China. The distribution of C. imicola is mainly constrained by climatic factors. In the ensemble model, mean annual minimum temperature had the highest overall contribution (42.9%), followed by mean annual maximum temperature (21.1%), solar radiation (13.6%), annual precipitation (11%), livestock distribution (6.2%), vapor pressure (3.4%), wind speed (0.8%), and land cover (0.1%). The present study provides the most up-to-date predictive maps of the potential distributions of C. imicola and should be of great value for decision making at global and regional scales.

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Conflict of interest statement

The authors declare no competing interests.

Figures

Figure 1
Figure 1
Beanplot illustrating performance in terms of TSS and ROC values over the 30 prediction models (10 algorithms × three runs). The lite horizontal lines indicate the overall averages.
Figure 2
Figure 2
Beanplot of environmental and livestock demographic characteristics of C. imicola occurrence localities (N = 1039). Tmin = Mean annual minimum temperature (°C), Tmax = Mean annual maximum temperature (°C), Tavg = Mean annual temperature (°C), Prec = Mean annual precipitation (mm/year), Srad = Solar radiation (kJ m−2 day−1), Wind = wind speed (m s−1), Vapr = water vapor pressure (kPa), Livestock = Livestock population (livestock population/5 arc minute).
Figure 3
Figure 3
Predicted potential distribution of C. imicola. The scale indicates less suitable environment (cooler colors) and most suitable environment (warmer colors).
Figure 4
Figure 4
The estimated committee averaging across the selected predictions. The scale indicates unsuitable environment with certain prediction (cooler colors), less suitable with uncertain prediction (light colors), and most suitable environment with certain prediction (warmer colors).
Figure 5
Figure 5
The Estimated ‘clamping mask’ value. Warmer colors indicate areas where models predictions are uncertain.

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