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The rate and timing of hydrologically forced landslides is a complex function of precipitation patterns, material properties, topography, and groundwater hydrology. In the simplest form, however, slopes fail when subsurface pore pressure grows large enough to exceed the Mohr‐Coulomb failure criterion. The capacity for pore pressure rise in a landslide is determined in part by the thickness of the unsaturated zone above the water table, which itself is set by weathering patterns that should have predictable patterns across different lithologies. To investigate how this structure affects landslide behavior, we exploit a multi‐year record of precipitation, pore pressure, and velocity from Oak Ridge earthflow, a slow‐moving landslide set in Franciscan mélange, northern California, USA. In conjunction with electrical resistivity tomography and hydraulic conductivity measurements, these data show that Oak Ridge has a thin weathered profile that is comparable in thickness to other mélange landslides in California. We propose that due to the inherently thin vadose zone, mélange landscapes experience an unusually high water table that frequently brings them close to movement; however, the capacity to increase stress is limited by the small amount of dynamic storage available. Instead, excess pore pressure is shed via springs and saturation overland flow once the water table reaches the surface. Linkages between weathering patterns, hydrology, and deformation can explain behavior patterns exhibited by Franciscan mélange earthflows across a large precipitation gradient.

 

Like faults, landslides can slip slowly for decades or accelerate catastrophically. However, whereas experimentally derived friction laws provide mechanistically based explanations for similarly diverse behavior on faults, little monitoring exists over the temporal and spatial scales required to more clearly illuminate the mechanics of landslide friction. Here we show that displacement of an active slow landslide is accommodated primarily through mm‐scale stick‐slip events that recur on timescales of minutes to hours on asperities that are small (<100 m) relative to the landslide. The frequency of slip events tracks both landslide velocity and pore fluid pressure. The stick‐slip nature demonstrates by itself that slow slip is governed, at least in part, by velocity‐weakening frictional asperities. This observation, in combination with the sensitivity of slow slip to pore fluid pressure and the small relative scale of asperities, suggests similarities between slow slip in landslides and episodic slow slip along faults.

 

Abstract Laser wakefield accelerators promise to revolutionize many areas of accelerator science. However, one of the greatest challenges to their widespread adoption is the difficulty in control and optimization of the accelerator outputs due to coupling between input parameters and the dynamic evolution of the accelerating structure. Here, we use machine learning techniques to automate a 100 MeV-scale accelerator, which optimized its outputs by simultaneously varying up to six parameters including the spectral and spatial phase of the laser and the plasma density and length. Most notably, the model built by the algorithm enabled optimization of the laser evolution that might otherwise have been missed in single-variable scans. Subtle tuning of the laser pulse shape caused an 80% increase in electron beam charge, despite the pulse length changing by just 1%. 

Secondary production, the growth of new heterotrophic biomass, is a key process in aquatic and terrestrial ecosystems that has been carefully measured in many flowing water ecosystems. We combine structural equation modeling with the first worldwide dataset on annual secondary production of stream invertebrate communities to reveal core pathways linking air temperature and precipitation to secondary production. In the United States, where the most extensive set of secondary production estimates and covariate data were available, we show that precipitation-mediated, low–stream flow events have a strong negative effect on secondary production. At larger scales (United States, Europe, Central America, and Pacific), we demonstrate the significance of a positive two-step pathway from air to water temperature to increasing secondary production. Our results provide insights into the potential effects of climate change on secondary production and demonstrate a modeling framework that can be applied across ecosystems.