The origin and evolution of open habitats in North America inferred by Bayesian deep learning models.
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s41467-022-32300-5.pdf
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3.72 MB
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Resource type
Journal article
Date published
August 17, 2022
Abstract
Some of the most extensive terrestrial biomes today consist of open vegetation, including temperate grasslands and tropical savannas. These biomes originated relatively recently in Earth’s history, likely replacing forested habitats in the second half of the Cenozoic. However, the timing of their origination and expansion remains disputed. Here, we present a Bayesian deep learning model that utilizes information from fossil evidence, geologic models, and paleoclimatic proxies to reconstruct paleovegetation, placing the emergence of open habitats in North America at around 23 million years ago. By the time of the onset of the Quaternary glacial cycles, open habitats were covering more than 30% of North America and were expanding at peak rates, to eventually become the most prominent natural vegetation type today. Our entirely data-driven approach demonstrates how deep learning can harness unexplored signals from complex data sets to provide insights into the evolution of Earth’s biomes in time and space.
Project(s)
Priority 2: Trait Diversity and Function
Funder
| Funder name | Awards |
SciLifeLab & Wallenberg Data Driven Life Science Program | Grant: KAW 2020.0239 |
National Science Foundation, United States | EAR-1253713 |
Vetenskapsrådet, Sweden | 2019-04739 - 2019-05191 |
Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung, Switzerland | PCEFP3_187012 |
Stiftelsen för Strategisk Forskning, Sweden | FFL15-0196 |
Royal Botanic Gardens, Kew, United Kingdom | |
Swedish National Infrastructure for Computing | |
Kempestiftelserna, Sweden | |
Knut och Alice Wallenbergs Stiftelse, Sweden | |
Uppsala Universitet, Sweden | |
Journal title
Nature Communications
Volume
13
Issue
1
Article number
4833
Publisher
Springer Science and Business Media LLC
Place of publication
Berlin/Heidelberg, Germany
eISSN
2041-1723
Date accepted
July 25, 2022
Official URL
Rights statement
In Copyright
Additional information
IF = 14.919 (2021-2022)