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    Scientists are racing to save the Last Ice Area, an Arctic Noah’s Ark

    It started with polar bears.

    In 2012, polar bear DNA revealed that the iconic species had faced extinction before, likely during a warm period 130,000 years ago, but had rebounded. For researchers, the discovery led to one burning question: Could polar bears make a comeback again?

    Studies like this one have emboldened an ambitious plan to create a refuge where Arctic, ice-dependent species, from polar bears down to microbes, could hunker down and wait out climate change. For this, conservationists are pinning their hopes on a region in the Arctic dubbed the Last Ice Area — where ice that persists all summer long will survive the longest in a warming world.

    Here, the Arctic will take its last stand. But how long the Last Ice Area will hold on to its summer sea ice remains unclear. A computer simulation released in September predicts that the Last Ice Area could retain its summer sea ice indefinitely if emissions from fossil fuels don’t warm the planet more than 2 degrees Celsius above preindustrial levels, which is the goal set by the 2015 Paris Climate Agreement (SN: 12/12/15). But a recent report by the United Nations found that the climate is set to warm 2.7 degrees Celsius by 2100 under current pledges to reduce emissions, spelling the end of the Arctic’s summer sea ice (SN: 10/26/21).

    Nevertheless, some scientists are hoping that humankind will rally to curb emissions and implement technology to capture carbon and other greenhouse gases, which could reduce, or even reverse, the effects of climate change on sea ice. In the meantime, the Last Ice Area could buy ice-dependent species time in the race against extinction, acting as a sanctuary where they can survive climate change, and maybe one day, make their comeback.

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    Ecosystem of the frozen sea

    The Last Ice Area is a vast floating landscape of solid ice extending from the northern coast of Greenland to Canada’s Banks Island in the west. This region, roughly the length of the West Coast of the United States, is home to the oldest and thickest ice in the Arctic, thanks to an archipelago of islands in Canada’s far north that prevents sea ice from drifting south and melting in the Atlantic.

    As sea ice from others part of the Arctic rams into this natural barrier, it piles up, forming long towering ice ridges that run for kilometers across the frozen landscape. From above, the area appears desolate. “It’s a pretty quiet place,” says Robert Newton, an oceanographer at Columbia University and coauthor of the recent sea ice model, published September 2 in Science. “A lot of the life is on the bottom of the ice.”

    The muddy underbelly of icebergs is home to plankton and single-celled algae that evolved to grow directly on ice. These species form the backbone of an ecosystem that feeds everything from tiny crustaceans all the way up to beluga whales, ringed seals and polar bears.

    These plankton and algae species can’t survive without ice. So as summer sea ice disappears across the Arctic, the foundation of this ecosystem is literally melting away. “Much of the habitat Arctic species depend on will become uninhabitable,” says Brandon Laforest, an Arctic expert at World Wildlife Fund Canada in Montreal. “There is nowhere else for these species to go. They’re literally being squeezed into the Last Ice Area.”

    The Last Ice Area extends across national borders, making it especially challenging to protect the last summer sea ice in the Arctic. The extent of the ice is predicted to shrink considerably by 2039.WWF CanadaThe Last Ice Area extends across national borders, making it especially challenging to protect the last summer sea ice in the Arctic. The extent of the ice is predicted to shrink considerably by 2039.WWF Canada

    The last stronghold of summer ice provides an opportunity to create a floating sanctuary —an Arctic ark if you will — for the polar bears and many other species that depend on summer ice to survive. For over a decade, WWF Canada and a coalition of researchers and Indigenous communities have lobbied for the area to be protected from another threat: development by industries that may be interested in the region’s oil and mineral resources.

    “The tragedy would be if we had an area where these animals could survive this bottleneck, but they don’t because it’s been developed commercially,” Newton says.

    But for Laforest, protecting the Last Ice Area is not only a question of safeguarding arctic creatures. Sea ice is also an important tool in climate regulation, as the white surface reflects sunlight back into space, helping to cool the planet. In a vicious cycle, losing sea ice helps speed up warming, which in turn melts more ice.

    And for the people who call the Arctic home, sea ice is crucial for food security, transportation and cultural survival, wrote Inuit Circumpolar Council Chair Okalik Eegeesiak in a 2017 article for the United Nations. “Our entire cultures and identity are based on free movement on land, sea ice and the Arctic Ocean,” Eegeesiak wrote. “Our highway is sea ice.” 

    The efforts of these groups have borne some fruit. In 2019, the Canadian government moved to set aside nearly a third of the Last Ice Area as protected spaces called marine preserves. Until 2024, all commercial activity within the boundaries of the preserves is forbidden, with provisions for Indigenous peoples. Conservationists are now asking these marine preserves to be put under permanent protection.

    Rifts in the ice

    However, there are some troubling signs that the sea ice in the region is already precarious. Most worrisome was the appearance in May 2020 of a Rhode Island—sized rift in the ice at the heart of the Last Ice Area. Kent Moore, a geophysicist at the University of Toronto, says that these unusual events may become more frequent as the ice thins. This suggests that the Last Ice Area may not be as resilient as we thought, he says.  

    This is something that worries Laforest. He and others are skeptical that reversing climate change and repopulating the Arctic with ice-dependent species will be possible. “I would love to live in a world where we eventually reverse warming and promote sea ice regeneration,” he says. “But stabilization seems like a daunting task on its own.”

    Still, hope remains. “All the models show that if you were to bring temperatures back down, sea ice will revert to its historical pattern within several years,” says Newton.

    To save the last sea ice — and the creatures that depend on it — removing greenhouse gases from the atmosphere will be essential, says oceanographer Stephanie Pfirman of Arizona State University in Tempe, who coauthored the study on sea ice with Newton. Technology to capture carbon, and prevent more carbon from entering the atmosphere, already exists. The largest carbon capture plant is in Iceland, but projects like that one have yet to be implemented on a major scale.

    Without such intervention, the Arctic is set to lose the last of its summer ice before the end of the century. It would mean the end of life on the ice. But Pfirman, who suggested making the Last Ice Area a World Heritage Site in 2008, says that humankind has undergone big economic and social changes — like the kind needed to reduce emissions and prevent warming — in the past. “I was in Germany when the [Berlin] wall came down, and people hadn’t expected that to happen,” she says.

    Protecting the Last Ice Area is about buying time to protect sea ice and species, says Pfirman. The longer we can hold on to summer sea ice, she says, the better chance we have at bringing arctic species —from plankton to polar bears — back from the brink.    More

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    Climate change may be shrinking tropical birds

    In a remote corner of Brazil’s Amazon rainforest, researchers have spent decades catching and measuring birds in a large swath of forest unmarred by roads or deforestation. An exemplar of the Amazon’s dazzling diversity, the experimental plot was to act as a baseline that would reveal how habitat fragmentation, from logging or roads, can hollow out rainforests’ wild menagerie.

    But in this pristine pocket of wilderness, a more subtle shift is happening: The birds are shrinking.

    Over 40 years, dozens of Amazonian bird species have declined in mass. Many species have lost nearly 2 percent of their average body weight each decade, researchers report November 12 in Science Advances. What’s more, some species have grown longer wings. The changes coincide with a hotter, more variable climate, which could put a premium on leaner, more efficient bodies that help birds stay cool, the researchers say.

    “Climate change isn’t something of the future. It’s happening now and has been happening and has effects we haven’t thought of,” says Ben Winger, an ornithologist at the University of Michigan in Ann Arbor who wasn’t involved in the research but has documented similar shrinkage in migratory birds. Seeing the same patterns in so many bird species across widely different contexts “speaks to a more universal phenomenon,” he says.

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    Biologists have long linked body size and temperature. In colder climates, it pays to be big because having a smaller surface area relative to one’s volume reduces heat loss through the skin and keeps the body warmer. As the climate warms, “you’d expect shrinking body sizes to help organisms off-load heat better,” says Vitek Jirinec, an ecologist at the Integral Ecology Research Center in Blue Lake, Calif. 

    Many species of North American migratory birds are getting smaller, Winger and colleagues reported in 2020 in Ecology Letters. Climate change is the likely culprit, Winger says, but since migrators experience a wide range of conditions while globe-trotting, other factors such as degraded habitats that birds may encounter can’t be ruled out.

    To see if birds that stay put have also been shrinking, Jirinec and colleagues analyzed data on nonmigratory birds collected from 1979 to 2019 in an intact region of the Amazon that spans 43 kilometers. The dataset includes measurements such as mass and wing length taken from 1979 to 2019 for over 11,000 individual birds of 77 species. The researchers also examined climate data for the region.

    By taking careful measurements of tropical birds, such as this white-crowned manakin (Pseudopipra pipra), researchers tracked shifts in body size over 40 years.Cameron Rutt

    All species declined in mass over this period, the researchers found, including birds as different as the Rufous-capped antthrush (Formicarius colma), which snatches insects off the forest floor, and the Amazonian motmot (Momotus momota), which scarfs down fruit up in trees. Species lost from about 0.1 percent to nearly 2 percent of their average body weight each decade. The motmot, for example, shrunk from 133 grams to about 127 grams over the study period.

    These changes coincided with an overall increase in the average temperature of 1 degree Celsius in the wet season and 1.65 degrees C in the dry season. Temperature and precipitation also became more variable over the time period, and these short-term fluctuations, such as an especially hot or dry season, better explained the size trends than the steady increase in temperature.

    “The dry season is really stressful for birds,” Jirinec says. Birds’ mass decreased the most in the year or two after especially hot and dry spells, which tracks with the idea that birds are getting smaller to deal with heat stress.

    Other factors, like decreased food availability, could also lead to smaller sizes. But since birds with widely different diets all declined in mass, a more pervasive force like climate change is the likely cause, Jirinec says.

    Wing length also grew for 61 species, with a maximum increase of about 1 percent per decade. Jirinec thinks that longer wings make for more efficient, and thus cooler, fliers. For instance, a fighter jet, with its heavy body and compact wings, takes enormous power to maneuver. A light and long-winged glider, by contrast, can cruise along much more efficiently.

    “Longer wings may be helping [birds] fly more efficiently and produce less metabolic heat,” which can be beneficial in hotter conditions, he says. “But that’s just a hypothesis.” This body change was most pronounced in birds that spend their time higher up in the canopy, where conditions are hotter and drier than the forest floor.

    Whether these changes in shape and size represent an evolutionary adaptation to climate change, or simply a physiological response to warmer temperatures, remains unclear (SN: 5/8/20). Whichever is the case, Jirinec suggests that the change shows the pernicious power of human activity (SN: 10/26/21).

    “The Amazon rainforest is mysterious, remote and teeming with biodiversity,” he says. “This study suggests that even in places like this, far removed from civilization, you can see signatures of climate change.” More

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    AI helps design the perfect chickpea

    A massive international research effort has led to development of a genetic model for the ‘ultimate’ chickpea, with the potential to lift crop yields by up to 12 per cent.
    The research consortium genetically mapped thousands of chickpea varieties, and the UQ team then used this information to identify the most valuable gene combinations using artificial intelligence (AI).
    Professor Ben Hayes led the UQ component of the project with Professor Kai Voss-Fels and Associate Professor Lee Hickey, to develop a ‘haplotype’ genomic prediction crop breeding strategy, for enhanced performance for seed weight.
    “Most crop species only have a few varieties sequenced, so it was a massive undertaking by the international team to analyse more than 3000 cultivated and wild varieties,” Professor Hayes said.
    The landmark international study was led by Dr Rajeev Varshney from the International Crops Research Institute for the Semi-Arid Tropics in Hyderabad, India. The study confirmed chickpea’s origin in the Fertile Crescent and provides a complete picture of genetic variation within chickpea.
    “We identified 1,582 novel genes and established the pan-genome of chickpea, which will serve as a foundation for breeding superior chickpea varieties with enhanced yield, higher resistance to drought, heat and diseases,” Dr Varshney said. More

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    Machine learning refines earthquake detection capabilities

    Researchers at Los Alamos National Laboratory are applying machine learning algorithms to help interpret massive amounts of ground deformation data collected with Interferometric Synthetic Aperture Radar (InSAR) satellites; the new algorithms will improve earthquake detection.
    “Applying machine learning to InSAR data gives us a new way to understand the physics behind tectonic faults and earthquakes,” said Bertrand Rouet-Leduc, a geophysicist in Los Alamos’ Geophysics group. “That’s crucial to understanding the full spectrum of earthquake behavior.”
    New satellites, such as the Sentinel 1 Satellite Constellation and the upcoming NISAR Satellite, are opening a new window into tectonic processes by allowing researchers to observe length and time scales that were not possible in the past. However, existing algorithms are not suited for the vast amount of InSAR data flowing in from these new satellites, and even more data will be available in the near future.
    In order to process all of this data, the team at Los Alamos developed the first tool based on machine learning algorithms to extract ground deformation from InSAR data, which enables the detection of ground deformation automatically — without human intervention — at a global scale. Equipped with autonomous detection of deformation on faults, this tool can help close the gap in existing detection capabilities and form the foundations for a systematic exploration of the properties of active faults.
    Systematically characterizing slip behavior on active faults is key to unraveling the physics of tectonic faulting, and will help researchers understand the interplay between slow earthquakes, which gently release stress, and fast earthquakes, which quickly release stress and can cause significant damage to surrounding communities.
    The team’s new methodology enables the detection of ground deformation automatically at a global scale, with a much finer temporal resolution than existing approaches, and a detection threshold of a few millimeters. Previous detection thresholds were in the centimeter range.
    In preliminary results of the approach, applied to data over the North Anatolian Fault, the method reaches two millimeter detection, revealing a slow earthquakes twice as extensive as previously recognized.
    This work was funded through Los Alamos National Laboratory’s Laboratory Directed Research and Development Office.
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    First quantum simulation of baryons

    A team of researchers led by an Institute for Quantum Computing (IQC) faculty member performed the first-ever simulation of baryons — fundamental quantum particles — on a quantum computer.
    With their results, the team has taken a step towards more complex quantum simulations that will allow scientists to study neutron stars, learn more about the earliest moments of the universe, and realize the revolutionary potential of quantum computers.
    “This is an important step forward — it is the first simulation of baryons on a quantum computer ever,” Christine Muschik, an IQC faculty member, said. “Instead of smashing particles in an accelerator, a quantum computer may one day allow us to simulate these interactions that we use to study the origins of the universe and so much more.”
    Muschik, also a physics and astronomy professor at the University of Waterloo and associate faculty member at the Perimeter Institute, leads the Quantum Interactions Group, which studies the quantum simulation of lattice gauge theories. These theories are descriptions of the physics of reality, including the Standard Model of particle physics. The more inclusive a gauge theory is of fields, forces, particles, spatial dimensions and other parameters, the more complex it is — and the more difficult it is for a classical supercomputer to model.
    Non-Abelian gauge theories are particularly interesting candidates for simulations because they are responsible for the stability of matter as we know it. Classical computers can simulate the non-Abelian matter described in these theories, but there are important situations — such as matter with high densities — that are inaccessible for regular computers. And while the ability to describe and simulate non-Abelian matter is fundamental for being able to describe our universe, none has ever been simulated on a quantum computer.
    Working with Randy Lewis from York University, Muschik’s team at IQC developed a resource-efficient quantum algorithm that allowed them to simulate a system within a simple non-Abelian gauge theory on IBM’s cloud quantum computer paired with a classical computer.
    With this landmark step, the researchers are blazing a trail towards the quantum simulation of gauge theories far beyond the capabilities and resources of even the most powerful supercomputers in the world.
    “What’s exciting about these results for us is that the theory can be made so much more complicated,” Jinglei Zhang, a postdoctoral fellow at IQC and the University of Waterloo Department of Physics and Astronomy, said. “We can consider simulating matter at higher densities, which is beyond the capability of classical computers.”
    As scientists develop more powerful quantum computers and quantum algorithms, they will be able to simulate the physics of these more complex non-Abelian gauge theories and study fascinating phenomena beyond the reach of our best supercomputers.
    This breakthrough demonstration is an important step towards a new era of understanding the universe based on quantum simulation.
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    A personalized exosuit for real-world walking

    People rarely walk at a constant speed and a single incline. We change speed when rushing to the next appointment, catching a crosswalk signal, or going for a casual stroll in the park. Slopes change all the time too, whether we’re going for a hike or up a ramp into a building. In addition to environmental variably, how we walk is influenced by sex, height, age, and muscle strength, and sometimes by neural or muscular disorders such as stroke or Parkinson’s Disease.
    This human and task variability is a major challenge in designing wearable robotics to assist or augment walking in real-world conditions. To date, customizing wearable robotic assistance to an individual’s walking requires hours of manual or automatic tuning — a tedious task for healthy individuals and often impossible for older adults or clinical patients.
    Now, researchers from the Harvard John A. Paulson School of Engineering and Applied Sciences (SEAS) have developed a new approach in which robotic exosuit assistance can be calibrated to an individual and adapt to a variety of real-world walking tasks in a matter of seconds. The bioinspired system uses ultrasound measurements of muscle dynamics to develop a personalized and activity-specific assistance profile for users of the exosuit.
    “Our muscle-based approach enables relatively rapid generation of individualized assistance profiles that provide real benefit to the person walking,” said Robert D. Howe, the Abbott and James Lawrence Professor of Engineering, and co-author of the paper.
    The research is published in Science Robotics.
    Previous bioinspired attempts at developing individualized assistance profiles for robotic exosuits focused on the dynamic movements of the limbs of the wearer. The SEAS researchers took a different approach. The research was a collaboration between Howe’s Harvard Biorobotics Laboratory, which has extensive experience in ultrasound imaging and real-time image processing, and the Harvard Biodesign Lab, run by Conor J. Walsh, the Paul A. Maeder Professor of Engineering and Applied Sciences at SEAS, which develops soft wearable robots for augmenting and restoring human performance. More

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    When algorithms get creative

    Our brains are incredibly adaptive. Every day, we form new memories, acquire new knowledge, or refine existing skills. This stands in marked contrast to our current computers, which typically only perform pre-programmed actions. At the core of our adaptability lies synaptic plasticity. Synapses are the connection points between neurons, which can change in different ways depending on how they are used. This synaptic plasticity is an important research topic in neuroscience, as it is central to learning processes and memory. To better understand these brain processes and build adaptive machines, researchers in the fields of neuroscience and artificial intelligence (AI) are creating models for the mechanisms underlying these processes. Such models for learning and plasticity help to understand biological information processing and should also enable machines to learn faster.
    Algorithms mimic biological evolution
    Working in the European Human Brain Project, researchers at the Institute of Physiology at the University of Bern have now developed a new approach based on so-called evolutionary algorithms. These computer programs search for solutions to problems by mimicking the process of biological evolution, such as the concept of natural selection. Thus, biological fitness, which describes the degree to which an organism adapts to its environment, becomes a model for evolutionary algorithms. In such algorithms, the “fitness” of a candidate solution is how well it solves the underlying problem.
    Amazing creativity
    The newly developed approach is referred to as the “evolving-to-learn” (E2L) approach or “becoming adaptive.” The research team led by Dr. Mihai Petrovici of the Institute of Physiology at the University of Bern and Kirchhoff Institute for Physics at the University of Heidelberg, confronted the evolutionary algorithms with three typical learning scenarios. In the first, the computer had to detect a repeating pattern in a continuous stream of input without receiving feedback about its performance. In the second scenario, the computer received virtual rewards when behaving in a particular desired manner. Finally, in the third scenario of “guided learning,” the computer was precisely told how much its behavior deviated from the desired one.
    “In all these scenarios, the evolutionary algorithms were able to discover mechanisms of synaptic plasticity, and thereby successfully solved a new task,” says Dr. Jakob Jordan, corresponding and co-first author from the Institute of Physiology at the University of Bern. In doing so, the algorithms showed amazing creativity: “For example, the algorithm found a new plasticity model in which signals we defined are combined to form a new signal. In fact, we observe that networks using this new signal learn faster than with previously known rules,” emphasizes Dr. Maximilian Schmidt from the RIKEN Center for Brain Science in Tokyo, co-first author of the study. The results were published in the journal eLife.
    “We see E2L as a promising approach to gain deep insights into biological learning principles and accelerate progress towards powerful artificial learning machines,” says Mihai Petrovoci. “We hope it will accelerate the research on synaptic plasticity in the nervous system,” concludes Jakob Jordan. The findings will provide new insights into how healthy and diseased brains work. They may also pave the way for the development of intelligent machines that can better adapt to the needs of their users.
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    Adding sound to quantum simulations

    When sound was first incorporated into movies in the 1920s, it opened up new possibilities for filmmakers such as music and spoken dialogue. Physicists may be on the verge of a similar revolution, thanks to a new device developed at Stanford University that promises to bring an audio dimension to previously silent quantum science experiments.
    In particular, it could bring sound to a common quantum science setup known as an optical lattice, which uses a crisscrossing mesh of laser beams to arrange atoms in an orderly manner resembling a crystal. This tool is commonly used to study the fundamental characteristics of solids and other phases of matter that have repeating geometries. A shortcoming of these lattices, however, is that they are silent.
    “Without sound or vibration, we miss a crucial degree of freedom that exists in real materials,” said Benjamin Lev, associate professor of applied physics and of physics, who set his sights on this issue when he first came to Stanford in 2011. “It’s like making soup and forgetting the salt; it really takes the flavor out of the quantum ‘soup.'”
    After a decade of engineering and benchmarking, Lev and collaborators from Pennsylvania State University and the University of St. Andrews have produced the first optical lattice of atoms that incorporates sound. The research was published Nov. 11 in Nature. By designing a very precise cavity that held the lattice between two highly reflective mirrors, the researchers made it so the atoms could “see” themselves repeated thousands of times via particles of light, or photons, that bounce back and forth between the mirrors. This feedback causes the photons to behave like phonons — the building blocks of sound.
    “If it were possible to put your ear to the optical lattice of atoms, you would hear their vibration at around 1 kHz,” said Lev.
    A supersolid with sound
    Previous optical lattice experiments were silent affairs because they lacked the special elasticity of this new system. Lev, young graduate student Sarang Gopalakrishnan — now an assistant professor of physics at Penn State and co-author of the paper — and Paul Goldbart (now provost of Stony Brook University) came up with the foundational theory for this system. But it took collaboration with Jonathan Keeling — a reader at the University of St. Andrews and co-author of the paper — and years of work to build the corresponding device. More