Keywords
sandflies
GARP
MaxEnt
models
How to Cite
Abstract
Spatial analyzes have prompted the development of models to predict the spatial distribution of species. These techniques estimate the potential geographical distribution areas by representing the occurrence of the species from the association between the presence records and environmental variables of the site. The aim of this study was to evaluate the efficiency of two models, MaxEnt and GARP, to predict the potential distribution of the main species of Lutzomyia in an endemic area of leishmaniasis in Venezuela. We use 190 georeferenced points of sandflies captured in the state of Merida, discriminated in 67 points for Lutzomyia youngi, 51 for Lutzomyia gomezi, 40 for Lutzomyia ovallesi and 32 for Lutzomyia walkeri. We take the climatic variables from the database Worldclim for area 23. The results show that both models had a good performance and their distribution ranges are consistent between themselves. Although GARP predicts a greater potential distribution for Lutzomyia youngi and Lutzomyia gomezi, MaxEnt generates more accurate predictions of probabilities of occurrence, determined by the bioclimatic variables that characterize the potential distribution of each species. It is considered better use MaxEnt because it presents a projection of the distribution according to contribution of bioclimatic variables as it provides important information for understanding the dynamics of distribution of Lutzomyia species and the risk of transmission of leishmaniasis in the state Merida–Venezuela, information relevant to the control entities.References
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