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Learning from the past to predict the future: inferring responses of the Pernambuco Center of Endemism (PCE) avifauna to climate changes with comparative phylogeography and species distribution models

Grant number: 20/16065-8
Support type:Scholarships in Brazil - Post-Doctorate
Effective date (Start): March 01, 2021
Effective date (End): February 28, 2023
Field of knowledge:Biological Sciences - Zoology
Principal researcher:Luís Fábio Silveira
Grantee:Fernanda Bocalini
Home Institution: Museu de Zoologia (MZ). Universidade de São Paulo (USP). São Paulo , SP, Brazil
Associated research grant:17/23548-2 - Evaluation, recovering and conservation of endangered animal species from the Pernambuco Centre of Endemism, AP.TEM

Abstract

The Pernambuco Center of Endemism (PCE) in Northeastern Brazil is the most threatened area of the Atlantic Forest (AF) biodiversity hotspot. Understanding the processes responsible for generating and maintaining the exceptionally high diversity of the Neotropical region is fundamental and long-term conservation measures must ensure that these processes continue to occur. Recent studies identified that PCE endemic birds presented a pervasive relationship with populations from Southern and Central AF and demographic model comparisons indicated a stable demographic history without population size shifts. This result points towards the environmental stability in a refugium to explain the PCE high species diversity, nevertheless, the idiosyncratic pattern of divergence could be indicative of the putative role of species-specific ecological traits. Although previous studies have detailed the population structure, phylogeographic relationships, and demographic history of some PCE endemic species, responses to past climate changes have not been addressed with comparative phylogeography along with spatially explicit approaches. Here, we aim to use SNP data from ultraconserved elements from PCE populations to i) verify if the current patterns of genomic diversity reflect multitaxa responses congruent to the historical environmental changes that affected AF during late Pleistocene, and ii) use molecular data to calculate demographic history parameters for each species and use them in conjunction with the distribution of suitable areas from ecological niche modeling to develop models for the distribution of genetic diversity under future climates. The demographic parameters will be used to build demographic and spatial genetic models of future landscapes and quantify the expected impact of climate change on the spatial distribution of genetic diversity.

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