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Dimensions US-BIOTA-Sao Paulo: traits as predictors of adaptive diversification along the Brazilian Dry Diagonal

Grant number: 18/03428-5
Support type:BIOTA-FAPESP Program - Thematic Grants
Duration: September 01, 2018 - August 31, 2023
Field of knowledge:Biological Sciences - Genetics
Cooperation agreement: NSF - Dimensions of Biodiversity and BIOTA
Principal Investigator:Vera Nisaka Solferini
Grantee:Vera Nisaka Solferini
Principal investigator abroad: Scott Vernon Edwards
Institution abroad: Harvard University, United States
Home Institution: Instituto de Biologia (IB). Universidade Estadual de Campinas (UNICAMP). Campinas , SP, Brazil
Co-Principal Investigators:Fábio Sarubbi Raposo do Amaral
Assoc. researchers:Célio Fernando Baptista Haddad ; Danon Clemes Cardoso ; Evandro Marsola de Moraes ; Fernando de Faria Franco ; Guarino Rinaldi Colli ; José Paulo Leite Guadanucci ; Luciano Antonio Digiampietri ; Luciano Nicolas Naka ; Maykon Passos Cristiano ; Thiago Gonçalves Souza
Associated scholarship(s):19/04350-2 - Dimensions US-BIOTA-São Paulo: traits as predictors of adaptive diversification along the Brazilian Dry Diagonal, BP.IC


The Dry Diagonal (DD) contains a number of environments including the Caatinga and Cerrado that span over 1/3 the area of Brazil, as well as the Chaco of northern Argentina. Because of its perceived lower biodiversity for many taxa than in better known biomes such as the Amazon basin and the Atlantic forest, evolutionary processes in the DD have received much less attention from biologists, even though the DD, in particular the Cerrado, is likely the most endangered major biome in Brazil. The Dry Diagonal Dimensions Project will take a multilevel trait-based approach to understanding the origins and adaptive processes of plants, animals and fungi in the Brazilian DD. We will use a machine-learning approach to identify traits that facilitate or retard speciation for lineages entering the DD. We will then determine how DD biomes act to filter communities from species pools in adjacent habitats (Amazon, AF and others) using a trait-based community-phylogenetic framework that accounts for random assembly, competition, and habitat filtering. Finally, using next-generation sequencing, we will conduct comparative phylogeographic surveys of multiple lineages, whole-genome re-sequencing and transcriptomics to identify genomic drivers of trait divergence in the DD. Together these studies will identify functional, phylogenetic and genomic drivers of adaptation and phenotypic divergence in one of the most poorly understood but consequential habitats in Brazil. (AU)

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