Landscape evolution over the last 100 million years. Credit: Dr Tristan Salles, University of Sydney / AAAS
Advanced digital tools help us understand the past and predict the evolution of the Earth’s surface.
The interplay of climate, tectonic activity, and the passage of time provide formidable forces shaping the Earth’s appearance. Gentle erosion by rivers only adds to this, turning what appears to be an unchanging rock into an ever-changing surface.
However, our understanding of this complex process is limited at best. Scientists have released a new study revealing a detailed and dynamic model of the Earth’s surface over the past 100 million years. In collaboration with French scientists, geoscientists at the University of Sydney have published this new model in a prestigious journal.
Animation of a landscape dynamics model over the last 100 million years. It shows landscape erosion and sediment deposition. Credit: Dr. Tristan Salles, The[{” attribute=””>University of Sydney
For the first time, it provides a high-resolution understanding of how today’s geophysical landscapes were created and how millions of tonnes of sediment have flowed to the oceans.
Lead author Dr. Tristan Salles from the University of Sydney School of Geosciences, said: “To predict the future, we must understand the past. But our geological models have only provided a fragmented understanding of how our planet’s recent physical features formed.
“If you look for a continuous model of the interplay between river basins, global-scale erosion, and sediment deposition at high resolution for the past 100 million years, it just doesn’t exist. So, this is a big advance. It’s not only a tool to help us investigate the past but will help scientists understand and predict the future, as well.”
Using a framework incorporating geodynamics, tectonic and climatic forces with surface processes, the scientific team has presented a new dynamic model of the past 100 million years at high resolution (down to 10 kilometers), broken into frames of a million years.
Second author Dr. Laurent Husson from Institut des Sciences de la Terre in Grenoble, France, said: “This unprecedented high-resolution model of Earth’s recent past will equip geoscientists with a more complete and dynamic understanding of the Earth’s surface.
“Critically, it captures the dynamics of sediment transfer from the land to oceans in a way we have not previously been able to.”
A world map animation of landscape evolution over the past 100 million years.Credit: Dr Tristan Salles, University of Sydney
Dr. Salles said understanding the flow of terrestrial sediments into the marine environment is essential to understanding current ocean chemistry.
“Given that ocean chemistry is rapidly changing due to human-induced climate change, a more complete picture will help us understand the marine environment,” he said. The model allows scientists to test different theories about how the Earth’s surface responds to changing climate and tectonic forces.
Furthermore, this study provides an improved model for understanding how terrestrial sediment transport regulates the global carbon cycle over millions of years.
“Our findings provide a dynamic and detailed context for preparing and testing hypotheses by scientists in other fields, such as biochemical cycles and biological evolution.”
See also: Tristan Salles, Laurent Hasson, Patrice Ray, Clare Mallard, Sabin Zahirovic, Beatrice Hadler Boggiani, Nicolas Cortiz, and Maelis Arnold, 100 Million Year Landscape Dynamics from the Catchment to the Global Scale, 2 March 2023, Available here. chemistry.
DOI: 10.1126/science.add2541
This research was funded by the Australian Government and the Australian Research Council.
Authors Dr. Salles, Dr. Claire Mallard, and Ph.D. student Beatriz Hadler Boggiani are members of the EarthColab Group, and Associate Professors Patrice Rey and Dr. Sabin Zahirovic are members of the EarthByte Group. Both groups belong to the Department of Earth Sciences, University of Sydney.
The study was conducted in collaboration with French geoscientists from CNRS, University of Lyon, France, and ENS Paris.
