Estrutura genética e parâmetros ecológicos em populações de Scinax nebulosus (Spix, 1824) (ANURA: HYLIDAE) - Oliveira, Rosa Hermina de (2020)
The Neotropical region has the largest abundance of anuran amphibians in the world with 7166 species currently described, of which 1193 are registered for Brazil. Studies involving population ecology help to understand abundance and distribution processes of species, their relationships with environmental characteristics, interactions and phylogenetic proximity. Morphological similarity of some animal populations hinders their identification, causing confusion between their actual distribution, mainly when there is geographic variation between populations. Our aim was to describe the genetic structure, analyze morphometric, bioacoustic variation and genetic parameters in populations of Scinax nebulosus in areas of North and Northeast region of Brazil. For this, sequences of the mitochondrial Gene 16S rDNA were obtained from 23 samples of the muscle tissue of S. nebulosus. The singing of 12 specimens was analyzed. For ecological parameters: we analyzed a total of 167 specimens regarding composition of helminths and parasitological descriptors among populations of S. nebulosus. The phylogenetic tree based on Bayesian inference of population structure confirmed distinct strains between North and Northeast of Brazil. The result of morphology separated the samples into two distinct groups (North and Northeast), with significant variables. The acoustic structures of populations analyzed were similar, but the result did not identify any significance in the data, which may be related to low number of samples analyzed. Lineage distinction between Northeast and North was analyzed and from it a new species was described for Scinax genus, found in Santarém state of Pará. The variation in helminths composition was analyzed and showed 13 species of helminths infecting S. nebulosus. Our results suggest that S. nebulosus populations are actually a complex of species, requiring further studies using integrative taxonomy to understand their actual distribution and identity.