| Grant number: | 20/16162-3 |
| Support Opportunities: | Regular Research Grants |
| Start date: | March 01, 2022 |
| End date: | August 31, 2024 |
| Field of knowledge: | Biological Sciences - Genetics |
| Principal Investigator: | Isabel Aparecida da Silva Bonatelli |
| Grantee: | Isabel Aparecida da Silva Bonatelli |
| Host Institution: | Instituto de Ciências Ambientais, Químicas e Farmacêuticas (ICAQF). Universidade Federal de São Paulo (UNIFESP). Campus Diadema. Diadema , SP, Brazil |
| Associated researchers: | Bryan Charles Carstens ; Danilo Trabuco do Amaral ; Evandro Marsola de Moraes ; Fernando de Faria Franco ; Marcelo Coelho Miguel Gehara |
| Associated scholarship(s): | 22/08676-2 - Automated survey and management of ecological and genetic data available in public databases, BP.TT |
Abstract
The understanding of many evolutionary processes begins with the investigation of species current geographical occurrence. One of the main findings is that the climatic changes over the past 21,000 years has led to substantial changes in the distribution of biodiversity on a global scale. However, most studies are based on descriptive narratives and interpretation of results for single taxa, which is insufficient. The exceptional increase in genetic and georeferenced data in public repositories offers an opportunity to refine the inferences proposed for a few species, making them accessible to larger taxonomic and geographical scales. Another approach that is established in the field of phylogeography is the exploration of phenotypic traits capable of explaining discordant phylogeographic patterns in the face of climatic events. The present project aims to understand the demographic responses of different neotropical species to the climatic changes of the Last Glacial Maximum using data available in digital repositories and a comparative and predictive phylogeography approach. Georeferenced genetic data will be collected and analyzed for different demographic changes based on species distribution modeling and approximate Bayesian computation (ABC). The association of abiotic and biotic traits with the demographic response will be investigated using machine learning. The results of the present work should offer a broader perspective for understanding the different demographic responses observed in species in the Neotropical region and encourage the reuse of available data from an automated approach. Additionally, it must provide support for conservation strategies and allow the development of new hypotheses to be tested using genomic data. (AU)
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