Phylogeographic structure and population connectivity of neotropical fish from the Amazon basin

• Grant number: 23/15984-8
• Support Opportunities: Scholarships in Brazil - Scientific Initiation
• Start date: February 01, 2024
• End date: January 31, 2025
• Field of knowledge: Biological Sciences - Genetics
• Principal Investigator: Isabel Aparecida da Silva Bonatelli
• Grantee: Isadora de Almeida Barboza Moreira
• Host Institution: Instituto de Ciências Ambientais, Químicas e Farmacêuticas (ICAQF). Universidade Federal de São Paulo (UNIFESP). Campus Diadema. Diadema , SP, Brazil

Abstract

Studies that focus on a deeper understanding of environmental and historical factors that shaped the exceptional biodiversity of the Neotropical region are still scarce and substantially smaller in relation to other global regions. Furthermore, this incredible richness is increasingly threatened and therefore, works that elucidates its underlying causes and maintenance is essential for its conservation over time. Neotropical freshwater fishes (NFFs) are the most diverse vertebrate fauna on Earth and excellent models for the study of broader biogeographical issues, as their population dynamics and genetics generally reflect historical and environmental changes in river basins. However, they were only included in discussions about Neotropical biodiversity recently and their diversification is still poorly understood. When analyzing co-distributed species, comparative phylogeography is a powerful tool for revealing distribution patterns and their underlying processes, as well as presenting increasingly valuable applications in the field of conservation biology. Therefore, the present work aims to analyze the genetic structure and connectivity of neotropical fish populations in the Amazon basin, which has the greatest wealth of freshwater fish in the world and is an important primary source of Neotropical biodiversity. To this end, genetic and occurrence data from different species retrieved from the literature and public databases, such as GBIF and Genbank, will be used, which will be applied to automated comparative phylogeography methods and tests of demographic models using approximate Bayesian computation.