Padrões de distribuição espacial e temporal em comunidades de ácaros em seringueira (Hevea SPP.) no Brasil - Nuvoloni, Felipe Micali [UNESP] (2015)
The rubber tree, Hevea brasiliensis (Muell. Arg. Euphorbiaceae) is the main source of natural rubber in the world, being originated and constrained to the Amazon basin. In the last years, the study of species of mites associated with rubber crop have been focused due to the importance of Calacarus heveae Feres, and Tenuipalpus heveae Baker, which occasionally induce severe defoliation and losses on latex production. Although, most of studies has highlighted local results, being absent broadscale studies, and connected data analysis. We performed a compilation of literature data, and complemented it with field sampling, aiming to diminish the lack of knowledge about the mites associated with rubber trees in Brazil. Our results highlight the huge diversity of species (250) recorded on rubber trees, from which C. heveae, T. heveae and Phyllocoptruta seringueirae Feres were the most abundant. These species present a populational peak comprised between February to May. Native rubber trees from Amazon also can harbor a great diversity of Phytoseiidae species, since seven new species were described from there. Beyond that, based on the communities temporal dynamics, we verified that regardless of the locality, all the communities of mites follow the same strict patter of species accumulation through time. In this sense, the traditional approach, that relies on the species-time-relationship STR could not be applied to our data. As a result, we built a new approach based on the turnover rates, disentangling the Colonization and Extinction components from turnover metric (Sorensen). At least, the spatial structure of the communities was driven by the dispersion-based component, and in the environmental component autocorrelated with space, in a biogeographic scale. On the other hand, the effect of these components also changed according to the taxon. At least, number of species was also negatively modeled ...