JOURNAL ARTICLE
Andean uplift, climatic events, and rainforest bridges determined the spatiotemporal evolution of the cumaru and tonka beans (Dipterygeae: Leguminosae).
Published In: Botanical Journal of the Linnean Society, 2024, v. 206, n. 2. P. 126 1 of 3
Database: Academic Search Ultimate 2 of 3
Authored By: Carvalho, Catarina S; Lima, Haroldo C; Lemes, Maristerra R; Cardoso, Domingos 3 of 3
Abstract
This article focuses on the biogeographical history, diversification, and evolutionary adaptations of the Dipterygeae, an early-branching papilionoid legume clade of neotropical tree species. Using molecular phylogenetics and ancestral area reconstruction, the study finds that Dipterygeae originated in Amazonia during the Middle Eocene (~46 Mya) and primarily diversified in situ there, with multiple independent dispersal events into other Neotropical biomes such as the Brazilian Atlantic Forest, Cerrado savannas, Caatinga dry forests, and Chocó + Central America rainforests. The evolution of distinct fruit types—dehiscent legumes, drupes, and cryptosamaras—correlates with dispersal syndromes (animal or wind dispersal) and facilitated colonization of different habitats, with cryptosamara fruits linked to open habitats like the Cerrado. Geological events (e.g., Andean uplift), climatic shifts, and biome connectivity shaped the diversification and distribution patterns observed in Dipterygeae, highlighting Amazonia’s central role as a source of lineages for other Neotropical biomes.
Additional Information
- Source:Botanical Journal of the Linnean Society. 2024/10, Vol. 206, Issue 2, p126
- Document Type:Article
- Subject Area:Earth and Atmospheric Sciences
- Publication Date:2024
- ISSN:0024-4074
- DOI:10.1093/botlinnean/boae015
- Accession Number:180266991
- Copyright Statement:Copyright of Botanical Journal of the Linnean Society is the property of Oxford University Press / USA and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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