Browsing by Author "Anemone, Robert L."
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- The first Miocene fossils from coastal woodlands in the southern East African RiftPublication . Bobe, René; Aldeias, Vera; Alemseged, Zeresenay; Anemone, Robert L.; Archer, Will; Aumaître, Georges; Bamford, Marion K.; Biro, Dora; Bourlès, Didier L.; Doyle Boyd, Melissa; Braun, David R.; Capelli, Cristian; d’Oliveira Coelho, João; Habermann, Jörg M.; Head, Jason J.; Keddadouche, Karim; Kupczik, Kornelius; Lebatard, Anne-Elisabeth; Lüdecke, Tina; Macôa, Amélia; Martínez, Felipe I.; Mathe, Jacinto; Mendes, Clara; Paulo, Luis Meira; Pinto, Maria; Presnyakova, Darya; Püschel, Thomas A.; Regala, Frederico; Sier, Mark; Ferreira da Silva, Maria Joana; Stalmans, Marc; Carvalho, SusanaThe Miocene was a key time in the evolution of African ecosystems witnessing the origin of the African apes and the isolation of eastern coastal forests through an expanding arid corridor. Until recently, however, Miocene sites from the southeastern regions of the continent were unknown. Here, we report the first Miocene fossil teeth from the shoulders of the Urema Rift in Gorongosa National Park, Mozambique. We provide the first 1) radiometric ages of the Mazamba Formation, 2) reconstructions of paleovegetation in the region based on pedogenic carbonates and fossil wood, and 3) descriptions of fossil teeth. Gorongosa is unique in the East African Rift in combining marine invertebrates, marine vertebrates, reptiles, terrestrial mammals, and fossil woods in coastal paleoenvironments. The Gorongosa fossil sites offer the first evidence of woodlands and forests on the coastal margins of southeastern Africa during the Miocene, and an exceptional assemblage of fossils including new species.
- Unsupervised learning of satellite images enhances discovery of late Miocene fossil sites in the Urema Rift, Gorongosa, MozambiquePublication . d’Oliveira Coelho, João; Anemone, Robert L.; Carvalho, SusanaPaleoanthropological research focus still devotes most resources to areas generally known to be fossil rich instead of a strategy that first maps and identifies possible fossil sites in a given region. This leads to the paradoxical task of planning paleontological campaigns without knowing the true extent and likely potential of each fossil site and, hence, how to optimize the investment of time and resources. Yet to answer key questions in hominin evolution, paleoanthropologists must engage in fieldwork that targets substantial temporal and geographical gaps in the fossil record. How can the risk of potentially unsuccessful surveys be minimized, while maximizing the potential for successful surveys?
- Using remote sensing and machine learning to reconstruct paleoenvironmental features in the Koobi Fora FormationPublication . Dorans, Elizabeth R.; Coelho, Joao D'Oliveira; Anemone, Robert L.; Bobe, Rene; Carvalho, Susana; Forrest, Frances; Braun, David R.Advances in Geographic Information Systems and Remote Sensing technologies have the potential to revolutionize archaeological and paleontological fieldwork. Machine learning models have been effective in identifying conditions ideal for preservation, exposure, and discovery of fossils in a range of geographic contexts. Researchers working in the Koobi Fora Formation of northern Kenya have long inquired about the geographic patterning of extinct fauna and their respective paleoenvironments. This project is the first attempt to use machine learning techniques to capture paleoecological patterns utilizing topographical and spectral variables that may be predictive of the input of aquatic components in the paleoenvironments of the Koobi Fora Formation.