Amphibians categorized as data deficient in the Brazilian list of threatened species: patterns of lack of information, issues on the use DD category and extinction risk prediction

Abstract

Amphibians are the most threatened vertebrates in the world, being 41% of them under threat. Indeed, 22.5% of the amphibians are classified as Data Deficient (DD), indicating that the proportion of threatened species could be even higher. Brazil is home to the largest number of the world's amphibians, accounting to 1,026 species recorded until mid 2014. There are 163 amphibians classified as DD in the current Brazilian list of endangered wildlife. The objective of this project is to investigate Brazilian amphibian species, classified as DD, in order to identify which information is lacking and tools that could help understand biological patterns of geographic distribution and extinction risks. The aim is also to understand issues related to the application of the category DD by extinction risk assessors. For this, a database will be organized from literature review, search in database of scientific collections and consultations with experts. Searching for patterns, database will be built and subjected to descriptive analyzes and exploratory statistics, using the Principal Component Analysis (PCA) and Canonical Correspondence Analysis (CCA). Geographic distribution of species models will be produced through the use of occurrence records, which will be organized conservatively, discarding incomplete, incorrect or questionable information. Climatic conditions will be gathered in the Worldclim platform, and physical conditions in AMBDATA system, with a resolution of 1 km2. Variable selection will be done through Pearson correlation analysis (e 0.7 correlation) and ACP, selecting variables with the greatest amount of variation in representative axes. To produce the model of geographical of species distribution Maxent algorithm and the Mahalanobis distance algorithm will be used, dedicating 30 % of the samples for testing. The suitability of the pixels will be calculated by bootstrapping ten times, and if the number of points is between 20:50, the Jackknife method will be preferred. The generated and validated geographical distribution models will be than used as predictor variables in classification models of species threatened of extinction, as well as natural history, taxonomic and threat. These classification predictive models will be generated according to the RandomForest classification method. IUCN criteria will be used in assessing models. All analyzes will be performed in the computing environment R. Evaluation of the use of DD category by different groups of experts will be determined by the application of semi-structured interviews followed by quantitative questionnaire, which will be evaluated by factorial analysis of correspondence (FAC). (AU)