ABSTRACT
Slow slip events (SSEs) accommodate a significant proportion of tectonic plate motion at subduction zones, yet little is known about the faults that actually host them. The shallow depth (<2 km) of well-documented SSEs at the Hikurangi subduction zone offshore New Zealand offers a unique opportunity to link geophysical imaging of the subduction zone with direct access to incoming material that represents the megathrust fault rocks hosting slow slip. Two recent International Ocean Discovery Program Expeditions sampled this incoming material before it is entrained immediately down-dip along the shallow plate interface. Drilling results, tied to regional seismic reflection images, reveal heterogeneous lithologies with highly variable physical properties entering the SSE source region. These observations suggest that SSEs and associated slow earthquake phenomena are promoted by lithological, mechanical, and frictional heterogeneity within the fault zone, enhanced by geometric complexity associated with subduction of rough crust.
ABSTRACT
The fossil record provides empirical patterns of morphological change through time and is central to the study of the tempo and mode of evolution. Here we apply likelihood-based time-series analyses to the near-continuous fossil record of Neogene planktonic foraminifera and reveal a morphological shift along the Truncorotalia lineage. Based on a geometric morphometric dataset of 1,459 specimens, spanning 5.9-4.5 Ma, we recover a shift in the mode of evolution from a disparate latest Miocene morphospace to a highly constrained early Pliocene morphospace. Our recovered dynamics are consistent with those stipulated by Simpson's quantum evolution and Eldredge-Gould's punctuated equilibria and supports previous suppositions that even within a single lineage, evolutionary dynamics require a multi-parameter model framework to describe. We show that foraminiferal lineages are not necessarily gradual and can experience significant and rapid transitions along their evolutionary trajectories and reaffirm the utility of multivariate datasets for their future research.