Knowledge about spatial distribution of organisms and the variables that influence this distribution are of great importance for understanding species ecology as well as biodiversity conservation and environmental management strategies. In recent years, modeling algorithms and software have been widely employed in order to model the potential geographic distribution of different organisms providing important information about species ecology contributing to more efficient species management and conservation strategies. However this approach is very scarce in relation to aquatic plant communities. Thus the aim of this study is to develop potential distribution models of submerged rooted macrophytes species in a coastal basin of the southern coast of São Paulo, and to identify predictors of this distribution. The hypothesis that in addition of the limnological variables, the spatial distribution of macrophytes in aquatic environments is also related to landscape variables will be tested. The species to be modeled are Egeria densa, Cabomba furcata and Potamogeton sp, abundant species of the basin rivers. The MAXENT modeling algorithm will be used to develop potential geographical distribution models. The models obtained will be evaluated and validated through statistical protocols and through field validation. The relationship between the presence of aquatic macrophytes in rivers and chemical, physical and landscape variables will also be evaluated statistically using Generalized Linear Models (GLM).
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