Ecological niche modeling for predicting the habitat suitability of fascioliasis based on maximum entropy model in southern Caspian Sea littoral, Iran

Abstract

The present study aimed to determine the number of cases of animal fascioliasis per district in the southern littoral of Caspian Sea and to model suitable ecological niches for Fasciola infection in the region. Stool samples (n = 2688) were collected from cattle and sheep in Guilan, Mazandaran and Golestan provinces. The samples were tested using flotation method, and the number of parasite eggs per gram (EPG) of feces was recorded for each sample. Occurrence-only data of Fasciola were collected from the field. A total of 96 points/locations were used to model the ecological niche of Fasciola in maximum entropy (MaxEnt) and geographical information system (GIS). The spatial layers were compiled from 23 bioclimatic and biophysical variables for modeling analysis. Jackknife analysis was used to determine the relative importance of all variables in the model. In the present study, the proportion of fascioliasis in both hosts was highest in Guilan province (sheep: 12.34%, cattle: 15.16%), followed by Mazandaran (sheep: 7.3%, cattle: 6.25%) and Golestan (sheep: 0%, cattle: 0.94%) provinces. The Area Under Curve (AUC) value of the model was 0.909, indicating a good predictive power of the model. Our modeling results indicate that four variables, which were markedly incorporated into the model, are the major predictors of the presence probability of Fasciola spp. in the region: Bio17 (Precipitation of driest quarter; 45.5%), Bio14 (Precipitation of driest month; 24.8%), aspect (9%), and altitude (7.2%). The data presented herein show expansion of the potential high-risk areas of fascioliasis in the northern part of Iran, located at the southern littoral of Caspian Sea, especially in Guilan province. However, the extent of the predicted risk zones varied between the different areas of the region and within provinces, such that at the present, many parts of Golestan province are less environmentally suitable for Fasciola distribution than other areas in the region.

Keywords: Bioclimatic variables; Fascioliasis; Geographic information system (GIS); Maximum entropy model; Southern Caspian Sea littoral; Topographic variables.