Spatial Distribution and Abundance of Chrysomya bezziana in Jazan Province, Saudi Arabia Using GIS
Myiasis caused by Calliphorid and Oestrid flies constitute a major threat to the development of livestock industry in Kingdom of Saudi Arabia. Increased veterinary concerns recently paid to the frequent reports on enteric pathogens caused by the larvae of these flies. Although the importance of shee...
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Veröffentlicht in: | Journal of Entomological Research Society 2023-04, Vol.25 (2), p.439-453 |
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creator | Alahmed, Azzam Nasser, Mohamed Kheir, Salah Sallam, Mohamed Dawah, Hassan Alashaal, Sara Hosni, Eslam M |
description | Myiasis caused by Calliphorid and Oestrid flies constitute a major threat to the development of livestock industry in Kingdom of Saudi Arabia. Increased veterinary concerns recently paid to the frequent reports on enteric pathogens caused by the larvae of these flies. Although the importance of sheep and goats in Saudi Arabia, the geographic distribution limits of Calliphorid and Oestrid infestation in caprine livestock has never been highlighted. ArcGIS software was used to assess the spatial distribution of myiasis causing flies in Jazan Province, Saudi Arabia. Implemented Evolutionary algorithms in maximum entropy (MaxEnt) was used to predict the distribution map for myiasis causing flies. Bioclimatic and topographic data layers from Worldclim was analyzed to estimate the percent contribution of variables predicting suitable habitats of flies causing myiasis. Field validation was occurred to evaluate the habitat suitability produced by the model. The predictive ecological niche model was found high with an AUC value of 0.95 and 0.93 for train and test occurrence records, respectively, with a standard deviation equal 0.032. About eighteen variables were found to Contribute in spatial predictive occurrence of myiasis causing flies. Precipitation variables enhanced the model predictive power with (57.7%) in Jackknife test. Besides, elevation, NDVI and tree cover shared reduced effect in predicting myiasis causing flies distribution. |
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Increased veterinary concerns recently paid to the frequent reports on enteric pathogens caused by the larvae of these flies. Although the importance of sheep and goats in Saudi Arabia, the geographic distribution limits of Calliphorid and Oestrid infestation in caprine livestock has never been highlighted. ArcGIS software was used to assess the spatial distribution of myiasis causing flies in Jazan Province, Saudi Arabia. Implemented Evolutionary algorithms in maximum entropy (MaxEnt) was used to predict the distribution map for myiasis causing flies. Bioclimatic and topographic data layers from Worldclim was analyzed to estimate the percent contribution of variables predicting suitable habitats of flies causing myiasis. Field validation was occurred to evaluate the habitat suitability produced by the model. The predictive ecological niche model was found high with an AUC value of 0.95 and 0.93 for train and test occurrence records, respectively, with a standard deviation equal 0.032. About eighteen variables were found to Contribute in spatial predictive occurrence of myiasis causing flies. Precipitation variables enhanced the model predictive power with (57.7%) in Jackknife test. 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The predictive ecological niche model was found high with an AUC value of 0.95 and 0.93 for train and test occurrence records, respectively, with a standard deviation equal 0.032. About eighteen variables were found to Contribute in spatial predictive occurrence of myiasis causing flies. Precipitation variables enhanced the model predictive power with (57.7%) in Jackknife test. 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Increased veterinary concerns recently paid to the frequent reports on enteric pathogens caused by the larvae of these flies. Although the importance of sheep and goats in Saudi Arabia, the geographic distribution limits of Calliphorid and Oestrid infestation in caprine livestock has never been highlighted. ArcGIS software was used to assess the spatial distribution of myiasis causing flies in Jazan Province, Saudi Arabia. Implemented Evolutionary algorithms in maximum entropy (MaxEnt) was used to predict the distribution map for myiasis causing flies. Bioclimatic and topographic data layers from Worldclim was analyzed to estimate the percent contribution of variables predicting suitable habitats of flies causing myiasis. Field validation was occurred to evaluate the habitat suitability produced by the model. 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subjects | Bioclimatology Ecological niches Entropy Evolutionary algorithms Flies Generalized linear models Genetic algorithms Geographic information systems Geographical distribution Goats Industrial development Larvae Livestock Livestock industry Maximum entropy Myiasis Precipitation Sample size Sheep Software Spatial distribution Topography Variables Vegetation |
title | Spatial Distribution and Abundance of Chrysomya bezziana in Jazan Province, Saudi Arabia Using GIS |
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