Introduced species have the potential to become invasive and jeopardize entire ecosystems. The success of species establishing viable populations outside their original extent depends primarily on favorable climatic conditions in the invasive ranges. Species distribution modeling (SDM) can thus be used to estimate potential habitat suitability for populations of invasive species. Here we review the status of six amphibian species with invasive populations in Brazil (four domestic species and two imported species). We (i) modeled the current habitat suitability and future potential distribution of these six focal species, (ii) reported on the disease status of Eleutherodactylus johnstonei and Phyllodytes luteolus, and (iii) quantified the acoustic overlap of P. luteolus and Leptodactylus labyrinthicus with three co-occurring native species. Our models indicated that all six invasive species could potentially expand their ranges in Brazil within the next few decades. In addition, our SDMs predicted important expansions in available habitat for 2 out of 6 invasive species under future (2100) climatic conditions. We detected high acoustic niche overlap between invasive and native amphibian species, underscoring that acoustic interference might reduce mating success in local frogs. Despite the American bullfrog Lithobates catesbeianus being recognized as a potential reservoir for the frog-killing fungus Batrachochytrium dendrobatidis (Bd) in Brazil, we did not detect Bd in the recently introduced population of E. johnstonei and P. luteolus in the State of São Paulo. We emphasize that the number of invasive amphibian species in Brazil is increasing exponentially, highlighting the urgent need to monitor and control these populations and decrease potential impacts on the locally biodiverse wildlife.
Automatic identification of animals is extremely useful for scientists, providing ways to monitor species and changes in ecological communities. The choice of effective audio features and classification techniques is a challenge on any audio recognition system, especially in bioacoustics that commonly uses several algorithms. This paper presents a novel software architecture that supports multiple feature extraction and classification algorithms to help on the identification of animal species from their recorded sounds. This architecture was implemented by the WASIS software, freely available on the Web.
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