TS4.1 | Global tectonics and the biosphere: Backdrop or driver?
EDI
Global tectonics and the biosphere: Backdrop or driver?
Co-organized by SSP4
Convener: Marissa Betts | Co-conveners: Elizabeth Dowding, Luke Strotz

Plate tectonics has had a profound influence on Earth’s biosphere, possibly from its inception. Tectonic processes can directly affect ecosystem evolution by impacting available habitats and controlling changes in nutrient flux through oceanic rifting, or weathering and erosion of the continents, which sheds nutrients and raw materials necessary for biological processes into the oceans. Collision and break-up of tectonic plates also affects the distribution of marine organisms, whether by altered ocean circulation patterns or by the creation and destruction of physical barriers (e.g. mountain ranges, land bridges, seaways). While it is relatively easy to reproduce palaeogeographic and tectonic configurations for more recent time periods (e.g. Jurassic to the present day), reconstructing the spatial relationships of more ancient tectonic blocks can be challenging. Nevertheless, reliable palaeogeographic models and/or full tectonic global plate models (GPMs) are the cornerstone for testing the relationships between global tectonics and the biosphere.

This session aims to bring together a broad spectrum of researchers investigating how Precambrian–Phanerozoic tectonics has impacted biological processes. Because tackling such questions leans heavily on multi-disciplinary approaches, we encourage submissions from researchers utilizing data and methods across a variety of research fields. We welcome submissions covering a wide range of topics, including, but not limited to; palaeomagnetism, palaeogeography, palaeontology/palaeobiology, macroevolution, palaeoclimatology, geochemistry, sedimentology and geochronology. We would also like to showcase studies that emphasise the FAIR (findable, accessible, interoperable, reusable), CARE (collective benefit, authority to control, responsibility, ethics) and Open Science principles when it comes to leveraging data at both model-development and model-application stages.