Global quieting of high-frequency seismic noise due to COVID-19 pandemic lockdown measures.

Human activity causes vibrations that propagate into the ground as high-frequency seismic waves. Measures to mitigate the coronavirus disease 2019 (COVID-19) pandemic caused widespread changes in human activity, leading to a months-long reduction in seismic noise of up to 50%. The 2020 seismic noise quiet period is the longest and most prominent global anthropogenic seismic noise reduction on record. Although the reduction is strongest at surface seismometers in populated areas, this seismic quiescence extends for many kilometers radially and hundreds of meters in depth. This quiet period provides an opportunity to detect subtle signals from subsurface seismic sources that would have been concealed in noisier times and to benchmark sources of anthropogenic noise. A strong correlation between seismic noise and independent measurements of human mobility suggests that seismology provides an absolute, real-time estimate of human activities.

Classifying elephant behaviour through seismic vibrations.

Seismic waves - vibrations within and along the Earth's surface - are ubiquitous sources of information. During propagation, physical factors can obscure information transfer via vibrations and influence propagation range [1]. Here, we explore how terrain type and background seismic noise influence the propagation of seismic vibrations generated by African elephants. In Kenya, we recorded the ground-based vibrations of different wild elephant behaviours, such as locomotion and infrasonic vocalisations [2], as well as natural and anthropogenic seismic noise. We employed techniques from seismology to transform the geophone recordings into source functions - the time-varying seismic signature generated at the source. We used computer modelling to constrain the propagation ranges of elephant seismic vibrations for different terrains and noise levels. Behaviours that generate a high force on a sandy terrain with low noise propagate the furthest, over the kilometre scale. Our modelling also predicts that specific elephant behaviours can be distinguished and monitored over a range of propagation distances and noise levels. We conclude that seismic cues have considerable potential for both behavioural classification and remote monitoring of wildlife. In particular, classifying the seismic signatures of specific behaviours of large mammals remotely in real time, such as elephant running, could inform on poaching threats.

Density structure of Earth's lowermost mantle from Stoneley mode splitting observations.

Advances in our understanding of Earth's thermal evolution and the style of mantle convection rely on robust seismological constraints on lateral variations of density. The large-low-shear-wave velocity provinces (LLSVPs) atop the core-mantle boundary beneath Africa and the Pacific are the largest structures in the lower mantle, and hence severely affect the convective flow. Here, we show that anomalous splitting of Stoneley modes, a unique class of free oscillations that are perturbed primarily by velocity and density variations at the core-mantle boundary, is explained best when the overall density of the LLSVPs is lower than the surrounding mantle. The resolved density variations can be explained by the presence of post-perovskite, chemical heterogeneity or a combination of the two. Although we cannot rule out the presence of a ∼100-km-thick denser-than-average basal structure, our results support the hypothesis that LLSVPs signify large-scale mantle upwelling in two antipodal regions of the mantle.