Constraining the Range and Variation of Lithospheric Net Rotation Using Geodynamic Modeling

Lithospheric net rotation (LNR) is the movement of the lithosphere as a solid body with respect to the mantle. Separating the signal of LNR from plate tectonic motion is therefore an important factor in producing absolute plate motion models. Net rotation is difficult to constrain because of uncertainties in geological data and outstanding questions about the stability of the mantle plumes used as a reference frame. We use mantle convection simulations to investigate the controlling factors for the magnitude of 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 a Gaussian variable. This provides a new geodynamic constraint for absolute plate motion reconstructions.

Automated summary

High lateral viscosity variations are required to produce Earth-like values of lithospheric net rotation (LNR). Other factors such as the presence of continents and a viscosity gradient at the transition zone also play important roles in determining the magnitude of net rotation. Additionally, the evolution of LNR is too complicated to predict in models, but the range of LNR within simulations follows a Gaussian distribution with a correlation time of 5 Myr.