I used mantle convection simulations to investigate the controlling factors for the magnitude of lithospheric net rotation (LNR) and to find the statistical predictability of LNR in a fully self-consistent convective system. We find that high lateral viscosity variations are required to produce Earth-like values of LNR. When the temperature dependence of viscosity is lower, and therefore slabs are softer, other factors such as the presence of continents and a viscosity gradient at the transition zone are also important for determining the magnitude of net rotation. We find that, as an emergent property of the chaotic mantle convection system, the evolution of LNR is too complicated to predict in our models. However, we find that the range of LNR within the simulations follows a Gaussian distribution, with a correlation time of 5 Myr. The LNR from the models needs to be sampled for around 50 Myr to produce a fully Gaussian distribution. This implies, that within the time frames considered for absolute plate motion reconstructions, LNR can be treated as Gaussian variable. This provides a new geodynamic constraint for absolute plate motion reconstructions.
The Conclusions
I used mantle convection simulations to investigate the controlling factors for the magnitude of lithospheric net rotation (LNR) and to find the statistical predictability of LNR in a fully self-consistent convective system. I find that high lateral viscosity variations are required to produce Earth-like values of LNR. When the temperature dependence of viscosity is lower, and therefore slabs are softer, other factors such as the presence of continents and a viscosity gradient at the transition zone are also important for determining the magnitude of net rotation. I find that, as an emergent property of the chaotic mantle convection system, the evolution of LNR is too complicated to predict in our models. However, I find that the range of LNR within the simulations follows a Gaussian distribution, with a correlation time of 5 Myr. The LNR from the models needs to be sampled for around 50 Myr to produce a fully Gaussian distribution. This implies, that within the time frames considered for absolute plate motion reconstructions, LNR can be treated as Gaussian variable. This provides a new geodynamic constraint for absolute plate motion reconstructions.
Using the same set of data, I also studied the effect of changing plate configuration on carbon storage in the crust. This is an element of the carbon cycle, locking away carbon from the surface and atmospheric carbon reservoir for tens of millions of year, before it is either degassed through volcanoes or locked away for much longer periods in the Earth's interior. I found that volatile storage increase when mid-ocean ridges form or change direction. The primary driver of changes in flux of volatile for degassing or subduction is the state of the ridge system 10s of millions of years previously, rather than the rate of subduction.
In the process of investigating measures of net rotation, I developed a machine learning tool that accelerates the calculation of seismic anisotropy as result of mantle flow. This was developed as a side project and is currently being used by research groups in Lyon and Montpellier. An article about the tool is in preparation and the tool will be released as open source software at the same time.
