Development of the first georeferenced map of Rhipicephalus (Boophilus) spp. in Mexico from 1970 to date and prediction of its spatial distribution

• Published in: Geospatial health Vol. 13; no. 1; p. 624
• Main Authors: Alcala-Canto, Yazmin, Figueroa-Castillo, Juan Antonio, Ibarra-Velarde, Froylán, Vera-Montenegro, Yolanda, Cervantes-Valencia, María Eugenia, Salem, Abdelfattah Z M, Cuéllar-Ordaz, Jorge Alfredo
• Format: Journal Article
• Language: English; Italian
• Published: Italy PAGEPress Publications 07.05.2018
• Subjects: Animals; Cattle; Cattle Diseases - parasitology; Datasets as Topic; Georeference; GIS; Maxent; Maximum entropy method; Mexico; Mexico - epidemiology; Rhipicephalus; Rhipicephalus (Boophilus) spp; Spatial Analysis; Species distribution model; Tick Infestations - epidemiology; Mexico; GIS; Georeference; Species distribution model; Mexico; Maxent; Rhipicephalus (Boophilus) spp
• ISSN: 1827-1987; 1970-7096
• DOI: 10.4081/gh.2018.624

The tick genus Ripicephalus (Boophilus), particularly R. microplus, is one of the most important ectoparasites that affects livestock health and considered an epidemiological risk because it causes significant economic losses due, mainly, to restrictions in the export of infested animals to several countries. Its spatial distribution has been tied to environmental factors, mainly warm temperatures and high relative humidity. In this work, we integrated a dataset consisting of 5843 records of Rhipicephalus spp., in Mexico covering close to 50 years to know which environmental variables mostly influence this ticks' distribution. Occurrences were georeferenced using the software DIVA-GIS and the potential current distribution was modelled using the maximum entropy method (Maxent). The algorithm generated a map of high predictive capability (Area under the curve = 0.942), providing the various contribution and permutation importance of the tested variables. Precipitation seasonality, particularly in March, and isothermality were found to be the most significant climate variables in determining the probability of spatial distribution of Rhipicephalus spp. in Mexico (15.7%, 36.0% and 11.1%, respectively). Our findings demonstrate that Rhipicephalus has colonized Mexico widely, including areas characterized by different types of climate. We conclude that the Maxent distribution model using Rhipicephalus records and a set of environmental variables can predict the extent of the tick range in this country, information that should support the development of integrated control strategies.