Natural fabrics of a hornblende-rich amphibolite: Implications for hornblende crystallographic preferred orientation and seismic anisotropy of the lower crust

The relation of seismic anisotropy to the deformation and flow of the lower crust relies on the intrinsic properties of the minerals in the crust and on the formation of crystallographic preferred orientation (CPO). Hornblende is an important constituent of the continental and oceanic lower crust and often exhibits a strong CPO. However, the formation of CPO in hornblende is not well understood, and it is difficult to uniquely relate its texture and anisotropy to conditions of metamorphism-deformation. We present a petrofabric analysis, using electron backscatter diffraction, of two hornblende-rich amphibolites from the Mamonia complex (Cyprus) with peak pressure and temperature of 0.6 GPa and 610 +/- 40 degrees C. We distinguish between microstructures with varied strains and show that, while the common hornblende CPO-in which the [001] is aligned with lineation-is independent of strain, its symmetry does depend on strain: it is hexagonal (axial-[001]) under low strains but becomes orthorhombic ([001] and (100) parallel to the lineation and foliation normal of the deformation, respectively) under increasing strains. This transition is correlated with a decrease in the shape-preferred orientation and an increase in the intragrain misorientation, whose rotation is consistent with the easy slip system (100)[001] of hornblende. Thus, we interpret the hexagonal CPO to represent a metamorphic fabric (a texture formed under quasi-static conditions) and the orthorhombic CPO to represent a solid-state deformation fabric (a texture formed by strain accommodated via dislocation-mediated deformation). We consider the seismic anisotropy of the natural hornblende textures and compare two tectonic scenarios of lower crust deformation -crust thickening and channel flow with marked differences in the expected seismic anisotropy between the two scenarios. Taken together, the dataset presented here can be used as a new framework for understanding and interpreting natural textures and seismic anisotropy from the lower crust.