Maximum Entropy Ecological Niche Prediction of the Current Potential Geographical Distribution of <i>Eimeria</i> Species of Cattle, Sheep and Goats in Mexico

Abstract

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 km 2) 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.

Similar Pattern of Potential Distribution of Pinus yunnanensis Franch and Tomicusyunnanensis Kirkendall under Climate Change in China

“…In this study, the nonparametric estimation of the Jackknife method was used to evaluate the contribution rate of each environmental factor and the receiver operating characteristic (ROC) curve of the influence of each environmental variable on the distribution of P. yunnanensis and T. yunnanensis. The area under the ROC curve (AUC) was used to evaluate the accuracy of model predictions [40,41]. AUC values range from [0.5, 1], and typically, model performance was classified as failing (0.5-0.6), poor (0.6-0.7), fair (0.7-0.8), good (0.8-0.9) or excellent (0.9-1.0).…”

“…Previous studies have revealed the problem of multicollinearity among variables of environmental factors [21,40,41]. In order to avoid excessive fitting of the model and multiple linear relationships among variables, environmental factors were pretreated in this study.…”

Projecting the Potential Distribution of Glossina morsitans (Diptera: Glossinidae) under Climate Change Using the MaxEnt Model

“…Maxent software is based on the maximum-entropy approach for modeling species niches and distributions. From a set of environmental grids and georeferenced occurrence localities, the model expresses a probability distribution where each grid cell has a predicted suitability of conditions for the species [ 28 ]. In this study, Maxent software and R language (version 3.6.0) were employed to analyze the relationship between occurrence records and climatic variables and to project the potentially suitable habitat of G. morsitans in historical and future periods.…”

Prevalence and Associated Risk Factors of Eimeria bovis and Eimeria zuernii in Kacha Bira District, Central Ethiopia

“…The prevalence of the disease has revealed statistically significant ( p < 0.05) differences among the months of the year. As discussed earlier in this manuscript, a higher rain is favorable for the survival of Eimeria oocyst as the oocyst does not survive in dry climates [ 72 – 74 ].…”