Abstract
Predictive studies project the geographic distribution of species and can be used to infer climatic niches. However, only a few studies have been conducted on mites. This approach helps map areas with potential for the occurrence of endemic, threatened, or potentially invasive species. Panonychus ulmi (Tetranychidae) is of global economic importance, commonly associated with apple orchards and grapevines. Potential distribution modeling is used to predict areas with environmental suitability for the distribution of a species and/or group. Considering that predictive models on national or regional scales present better data reliability, the present study aimed to analyze the distribution of P. ulmi in Brazil through bioclimatic inferences. The presence of species, bioclimatic variables, and MaxEnt algorithm were used to define a predictive model. The median performance rate of the model was 0.992, indicating its robustness. The variable that made the greatest contribution to the model was the average temperature of the coldest quarter (Bio11). The predictive model of the ecological niche indicated that the southern region of Brazil is environmentally favorable for the adaptation of this mite. The data obtained helped us understand the geographical distribution of P. ulmi in Brazil, and climatically suitable areas for its occurrence were inferred. We believe that this tool can offer indirect assistance to the agricultural sector, especially the producers of apples and grapes in Brazil regarding the presence of P. ulmi.
Publisher
Universidade Estadual de Maringa