Coccidiosis is a gastrointestinal disease caused by parasites of the genus Eimeria. To produce the ecological niche model for the geographic distribution of Eimeria species, the maximum entropy algorithm (MaxEnt) was ...Coccidiosis is a gastrointestinal disease caused by parasites of the genus Eimeria. To produce the ecological niche model for the geographic distribution of Eimeria species, the maximum entropy algorithm (MaxEnt) was used and 19 bioclimatic variables with a spatial resolution of 30 arc-seconds (approximately 1 km2) were downloaded from the World Climate Database. These were reduced to BIO2, BIO3, BIO4, BIO7 and BIO15 for each species after examining cross-correlations among them to account multicollinearity. A jackknife analysis was included to assess the contribution of five bioclimatic variables and the fit of the model was evaluated with the area under receiver operating characteristic curve (AUC). Under a current climate scenario, the jackknife evaluation of the MaxEnt model showed that BIO4 (temperature seasonality) made the greatest contribution to the distribution model for 22 Eimeria species;whereas BIO7 (temperature annual range) was the most important factor that contributes to the distribution model of 10 species. The habitat suitability model based on the maximum entropy theory was supported by AUC values higher than 0.9 and predicted that the suitable habitats for different species of Eimeria are present in southern, eastern and western areas of Mexico. Our study may support future studies exploring factors that constrain the distribution of Eimeria as well as strategies aimed at reducing the disease prevalence.展开更多
文摘Coccidiosis is a gastrointestinal disease caused by parasites of the genus Eimeria. To produce the ecological niche model for the geographic distribution of Eimeria species, the maximum entropy algorithm (MaxEnt) was used and 19 bioclimatic variables with a spatial resolution of 30 arc-seconds (approximately 1 km2) were downloaded from the World Climate Database. These were reduced to BIO2, BIO3, BIO4, BIO7 and BIO15 for each species after examining cross-correlations among them to account multicollinearity. A jackknife analysis was included to assess the contribution of five bioclimatic variables and the fit of the model was evaluated with the area under receiver operating characteristic curve (AUC). Under a current climate scenario, the jackknife evaluation of the MaxEnt model showed that BIO4 (temperature seasonality) made the greatest contribution to the distribution model for 22 Eimeria species;whereas BIO7 (temperature annual range) was the most important factor that contributes to the distribution model of 10 species. The habitat suitability model based on the maximum entropy theory was supported by AUC values higher than 0.9 and predicted that the suitable habitats for different species of Eimeria are present in southern, eastern and western areas of Mexico. Our study may support future studies exploring factors that constrain the distribution of Eimeria as well as strategies aimed at reducing the disease prevalence.
