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Reconstruction of Atlantic Rainforest vegetation dynamics since the Late Pleistocene at southeastern (Espírito Santo State coast and Minas Gerais eastern) and northeastern (Bahia Southern) Brazil

Grant number: 13/15768-1
Support type:Scholarships in Brazil - Doctorate
Effective date (Start): October 01, 2013
Effective date (End): September 30, 2017
Field of knowledge:Physical Sciences and Mathematics - Geosciences
Principal Investigator:Luiz Carlos Ruiz Pessenda
Grantee:Mariah Izar Francisquini Correia
Home Institution: Centro de Energia Nuclear na Agricultura (CENA). Universidade de São Paulo (USP). Piracicaba , SP, Brazil
Associated research grant:11/00995-7 - Interdisciplinary paleoenvironmental studies in the Espirito Santo State coast, AP.PFPMCG.TEM

Abstract

This research project proposal is associated to the FAPESP 2011/0095-7 thematic project,"Interdisciplinary palaeoenviromental studies at Espirito Santo coast" and to Fapesp Research Program about Climate Global Change (PFPMCG-FAPESP). The main objectives are: to characterize the late Pleistocene connection between Atlantic and Amazonia rainforest and its possible routes of interaction (coast, /continent or both); to identify environmental characteristics that indicates the northeastern Espírito Santo coast as forest refuge since the late Pleistocene; to characterize the relative sea level (RSL) variations and its influence in the vegetation dynamics at Espírito Santo coast. At least three sedimentary cores will be collected: at Espirito Santo state, southern Bahia coast and eastern Minas Gerais State. Carbon and nitrogen isotope analyses and bioindicators (pollen, diatom, sponge spicules and phytoliths) in sediments, soils and peat etc., chronologically determined by radiocarbon dating, will contribute to the palaeoenvironmental reconstruction of the dynamic and the interactions between aquatic and terrestrial systems on the study sites. Moreover, pollen and phytoliths can reveal the Amazon specimen influences, confirming its presence in the past. The association of the data base from previous studies in the region and those in development, and compared with others in distinct Brazilian regions will support the enlargement of climatic models database, besides enabling the understanding of this environment and assist in future forecasts.