Paleoclimatic and paleoecological inferences of the Family Anemiaceae: A palynological investigation from variable spatial and temporal strata in some lithostratigraphic units of Brazil, India and France

• Published in: Review of palaeobotany and palynology Vol. 285; p. 104316
• Main Authors: Duarte, Sarah Gonçalves, da Silva, Francisco José, Arai, Mitsuru, da Silva Sylvestre, Lana, Wanderley, Maria Dolores, Jha, Neerja, Joshi, Harinam, Masure, Edwige, El Atfy, Haytham
• Format: Journal Article
• Language: English
• Published: Elsevier B.V 01.02.2021; Elsevier
• Subjects: Anemiaceae; Brazil; Cicatricosisporites; Earth Sciences; France; India; Multivariate analysis; Paleontology; Sciences of the Universe; Brazil; Multivariate analysis; France; Cicatricosisporites; Anemiaceae; India
• ISSN: 0034-6667; 1879-0615
• DOI: 10.1016/j.revpalbo.2020.104316

The study of the interaction of cicatricose spores related to the family Anemiaceae with other botanical groups in the palynological record contributes to a better understanding of the paleoecological, paleoclimatic and paleoenvironmental aspects of this family through geological times. The present work based on the investigation of Anemiaceae fossil spores and other contemporary palynomorphs in different geological rock units and time windows from Brazil, France and India. For the purpose to fulfill the objectives of this study, detailed statistical analyses are applied in order to trace the adaptation of Anemiaceae in variable conditions throughout its geological existence, especially that this family is distributed spatially through a large regional scale of the world and was not limited to warm and humid paleoclimates. Results show that fossil Anemiaceae has been survived interacting among a diverse community of plants in a wide spectrum of paleoenvironments and paleoclimates. •Inferences of paleoclimatic conditions under which Anemiaceae survived during diverse sptial and temporal scales.•New integration of palynological data from different sedimentary basins.•Multivariate statistical analyses reprenst a reliable basis to interpret paleoenvironments.