TREMORS (NO WORMS DETECTED)

NEWS NATURE
18 APRIL 2019

Algorithms spot millions of California’s tiniest quakes in historical data
Project identifies reams of imperceptible tremors that can help to image fault lines in unprecedented detail.




Large earthquakes such as the magnitude-7.2 quake that hit Baja California in Mexico in 2010 are often surrounded by thousands of smaller tremors. Credit: Daniel Conejo/AFP/Getty

When it comes to earthquakes, large, destructive ones dominate the headlines. But seismologists have long known that small quakes, which are created by the near-constant slipping of fault lines and often go unnoticed even by scientists, can illuminate crucial details about all kinds of earthquakes, even really powerful ones.

Now, a team of researchers has used machine-learning and supercomputers to spot millions of these imperceptible quakes — as small as magnitude 0.3 — hiding in the seismological records of southern California, one of the most tectonically treacherous corners of the United States.

The data will allow researchers to improve their understanding of the physical processes that trigger hazardous earthquakes — ultimately boosting hazard-mitigation efforts.

This type of data mining is like gold-mining, says Ken Hudnut, a geophysicist at the US Geological Survey in Pasadena, California, who was not involved with the research. The project can extract ‘gold’ at record efficiencies, and might find riches that no one expected to dig up, he says. The results were published in Science1 on 18 April.

The team’s approach could also be applied elsewhere and to other geological features, such as volcanoes, say the researchers.
Exhuming quakes

The project, called Mining Seismic Wavefields (MSW), began in 2016, and involves researchers at Stanford University in California, the University of Southern California (USC) in Los Angeles, the California Institute of Technology in Pasadena and the Georgia Institute of Technology in Atlanta.

The researchers came up with the idea some time ago, but two key ingredients were missing: vast and detailed seismic data sets created with modern instrumentation, and powerful computer systems to process the data efficiently. The elements finally came together a few years ago, and teams began developing techniques to find small earthquakes in new records.

The Caltech MSW group analysed seismic data known as waveforms, which represent earthquakes, and used their distinctive features to create templates that could ‘show’ algorithms what to look for in a large data set. They fed the templates into supercomputers and used them to detect the elusive fingerprints of tiny quakes in an ocean of noise.
Signal vs noise

But distinguishing between sources of low-level ground shaking is “anything but trivial”, says Yehuda Ben-Zion, acting director of the Southern California Earthquake Center at USC and co-leader of the MSW project. His group, which was studying the anatomy of seismic faults, found that the California ground shakes constantly. Vibrations from planes, trees, houses and even antennas shaking in the wind generate rumbles that, to a seismograph, look like earthquakes and can make up up 10–50% of signals in a set of seismological data.

To separate them out, the team developed machine-learning models and fed them millions of examples of both real quake signals and non-tectonic shaking. The software could “learn to correctly identify never-seen-before waveforms”, says team member Christopher Johnson, a geoscientist at the Scripps Institute of Oceanography in La Jolla, California.

The team also found that seismic records are not always good enough to create sufficient templates for the software to learn what an earthquake in a particular region looks like. So the researchers developed another algorithm, called Fingerprinting and Similarity Thresholding (FAST), which is based on a method developed for audio recognition. But unlike apps such as Shazam that recognize for music on the basis of small clips, FAST doesn’t know what clips from the earthquake ‘song’ sound like. Instead, it looks for snippets in the entire data set that are similar to each other, and flags them as candidate quakes, says Karianne Bergen, a data scientist at Harvard University in Boston, Massachusetts, who co-developed the algorithm while doing her PhD at Stanford.

For the latest paper1, the MSW team applied these approaches to the entire continuous set of data recorded by the prolific Southern California Seismic Network, which has sensors all across the region.

The researchers found 1.81 million previously undetected quakes that took place in 2008–17 — a tenfold increase on the original number catalogued.

Ben-Zion suspects that with improvements in computing power and detection methods, MSW will be able to pick out many millions more quakes even tinier than those they are currently finding.

“We can expand the number of sensors, we can put them in boreholes deep underground to reduce the background noise levels, and we can improve our automated algorithms for finding these weak events in the data,” says lead author Zachary Ross, a geophysicist at Caltech.
Trembling volcanoes

The technique is “be limited by the quality and paucity of data when compared with the high-quality data we have now,” says Lucile Bruhat, an earthquake physicist at the École Normale Supérieure in Paris who is not involved with the project. But “we can, and should, revisit catalogues and past large earthquakes to better characterize what happened at the time”, she says.

Bruhat suggests the technique could also be used to observe mysterious types of earthquake such as ‘slow slip’ events, which take months or years to unfold and are hinted at by numerous miniature rumbles.

Jackie Caplan-Auerbach, a seismologist and volcanologist at Western Washington University in Bellingham, thinks the approach could be applied to volcanoes.

“We know that volcanoes are creaky, unstable things, and the vast majority of their seismic activity is very small”, which makes it difficult to detect, she says. If this work can help extract these rumblings, then researchers will gain insights into the magma and superheated fluids moving about inside them.
doi: 10.1038/d41586-019-01258-8

References

1.

Ross, Z. E., Trugman, D. T., Hauksson, E. & Shearer, P. M. Science https://doi.org/10.1126/science.aaw6888 (2019).

CRISPR CRITTERS
NATURE NEWS
23 APRIL 2019

CRISPR gene-editing creates wave of exotic model organisms

But the practical challenges of breeding and maintaining unconventional lab animals persist.

Sara Reardon

PDF version



The Hawaiian bobtail squid (Euprymna scolopes) alters the camouflage patterns on its skin based on what it sees.Credit: Eric Roettinger/Kahi Kai Images

Joseph Parker has wanted to know what makes rove beetles tick since he was seven years old. The entomologist has spent decades collecting and observing the insects, some of which live among ants and feed on their larvae. But without tools for studying the genetic and brain mechanisms behind the beetles’ behaviour, Parker focused his PhD research on Drosophila fruit flies — an established model organism.

Now, more than a decade later, the rise of the CRISPR gene-editing technique has put Parker’s childhood dream within reach. He is using CRISPR to study symbiosis in rove beetles (Staphylinidae) in his lab at the California Institute of Technology in Pasadena. By knocking out genes in beetles that live with ants and in those that do not, Parker hopes to identify how the insects’ DNA changed as their lifestyles diverged. “We’re designing a model system from scratch,” he says.

Biologists have embraced CRISPR’s ability to quickly and cheaply modify the genomes of popular model organisms, such as mice, fruit flies and monkeys. Now they are trying the tool on more-exotic species, many of which have never been reared in a lab or had their genomes analysed. “We finally are ready to start expanding what we call a model organism,” says Tessa Montague, a molecular biologist at Columbia University in New York City.

Montague works on the Hawaiian bobtail squid (Euprymna scolopes) and the dwarf cuttlefish (Sepia bandensis), species whose unusual camouflage acts as an outward display of their brain activity. The cephalopods project patterns onto their skin to match what they see around them. But probing how their brains process stimuli has been difficult. Researchers would normally do this by embedding electrodes or other sensors into the skull — but squid and cuttlefish are boneless.

Last year, Montague and her colleagues successfully injected CRISPR components into cuttlefish and bobtail-squid embryos for the first time. Now, they are trying to genetically modify the cephalopods’ neurons to light up when they fire.
Technical knock out

Other researchers are using CRISPR to study species’ distinctive social behaviours. Daniel Kronauer, a biologist at the Rockefeller University in New York City, has created raider ants (Ooceraea biroi) that cannot smell pheromones. In experiments, the genetically modified ants were not able to sustain the complex hierarchy seen in a normal raider-ant colony1. The scientists are now using CRISPR to alter genes thought to influence raider ants′ behaviour.

Then there are species that threaten human or environmental health — such as the pea aphid (Acyrthosphion pisum), an insect that attacks legume crops worldwide. To edit the aphid’s genome with CRISPR, a team led by Shuji Shigenobu, an evolutionary geneticist at the National Institute for Basic Biology in Okazaki, Japan, had to manipulate the insect’s complex life cycle. Female aphids born in summer reproduce asexually, by cloning themselves, whereas those born in autumn lay eggs.

Shigenobu’s team set up an incubator that simulated the cool temperatures and short days of autumn so their aphids would lay eggs that the scientists could inject with CRISPR components.

After four years, the team succeeded in editing a pigment gene as a proof of concept, Shigenobu announced last month during a conference at the Howard Hughes Medical Institute’s Janelia Research Campus in Ashburn, Virginia. He hopes that by modifying other parts of the aphid’s genome, researchers can learn more about how the insects interact with plants. That information could lead to the production of better pesticides.
Inching forward

Developing animal models requires immense amounts of time and money, and until recently there was little support for such work. In 2016, the US National Science Foundation launched a US$24-million programme to create model organisms — and in doing so, reveal the genetic and molecular mechanisms behind complex traits and behaviours.

The programme supports research to create tools for probing species’ genomes, study organisms’ life cycles and develop protocols to raise these species in the lab. This support has begun to pay off: in March, for instance, researchers at the University of Georgia in Athens said2 that they had used CRISPR to create the first genetically modified reptile, the brown anole (Anolis sagrei).

Despite such promising early results, the push to create model organisms with CRISPR has revealed how little is known about many species’ genomes, life cycles and habits. Researchers face practical challenges such as determining how to inject CRISPR components into embryos and coaxing finicky, fragile species to breed in the lab.

“The reason classic model systems were chosen was they’re basically pests. Nothing can stop them growing,” Montague says. “But if we take on this challenge of working on new organisms because they have an amazing feature, they’re often not happy to grow under [just] any conditions.”

This has forced scientists to weigh the effort required to study a particular trait against the potential rewards. Modifying a genome requires a deep understanding of a species’ behaviour and lifecycle — a tall order when that organism is studied by only a handful of people worldwide. “People are not choosing these model systems lightly,” says David Stern, a biologist at Janelia.

Stern knows this first hand: he and his colleagues succeeded in breeding one fruit-fly species only after discovering that the insects need an olfactory cue to lay eggs — the smell of a particular chemical made by plants.

Still, researchers’ interest in developing atypical animal models continues to grow. Montague and her colleagues have created a tool called CHOPCHOP, which allows them to design a CRISPR system for editing specific genes in any DNA snippet. So far, scientists have sent her genetic sequences from more than 200 different species, including plants, fungi, viruses and farm animals.

“I had this weekly reminder that these molecular tools do work in pretty much every organism on the planet,” Montague says. “It’s such an exciting time to work on any model organism — especially these new and weird creatures.”

Nature 568, 441-442 (2019)
doi: 10.1038/d41586-019-01300-9



References

1.

Trible, W. et al. Cell 170, 727–735.e10 (2017).
2.

Rasys, A. M. et al. Preprint at bioRxiv https://www.biorxiv.org/content/10.1101/591446v1 (2019).

Climate Crisis: 

South African And Global Democratic Eco-Socialist Alternatives

Vishwas Satgar
NYU Press, Feb. 28, 2018 - Political Science - 372 pages
Capitalisms addiction to fossil fuels is heating our planet at a pace and scale never before experienced. Extreme weather patterns, rising sea levels and accelerating feedback loops are a commonplace feature of our lives. The number of environmental refugees is increasing and several island states and low-lying countries are becoming vulnerable. Corporate-induced climate change has set us on an ecocidal path of species extinction. Governments and their international platforms such as the Paris Climate Agreement deliver too little, too late. Most states, including South Africa, continue on their carbon-intensive energy paths, with devastating results. Political leaders across the world are failing to provide systemic solutions to the climate crisis. This is the context in which we must ask ourselves: how can people and class agency change this destructive course of history? Volume three in the Democratic Marxism series, The Climate Crisis investigates eco-socialist alternatives that are emerging. It presents the thinking of leading climate justice activists, campaigners and social movements advancing systemic alternatives and developing bottom-up, just transitions to sustain life. Through a combination of theoretical and empirical work, the authors collectively examine the challenges and opportunities inherent in the current moment. This volume builds on the class-struggle focus of Volume 2 by placing ecological issues at the centre of democratic Marxism. Most importantly, it explores ways to renew historical socialism with democratic, eco-socialist alternatives to meet current challenges in South Africa and the world.

Neoliberalism and Climate Policy in the United States:
From market fetishism to the developmental state



This book explores how Washington’s efforts to act on climate change have been translated under conditions of American neoliberalism, where the state struggles to find a stable and legitimate role in the economy, and where environmental and industrial policy are enormously contentious topics.

This original work conceptualizes US climate policy first and foremost as a question of innovation policy, with capital accumulation and market domination as its main drivers. It argues that US climate policy must be understood in the context of Washington’s broader efforts over the past four decades to dominate and monopolize novel high-tech markets, and its use of immense amounts of state power to achieve this end. From this perspective, many elements of US climate politics that seem confusing or contradictory actually appear to have an obvious and consistent logic.

This book will be of particular interest to students and scholars of IPE, as well as individuals generally interested in gaining a stronger understanding of US climate politics and policy, and the role and influence of neoliberalism on contemporary economic governance.