From PBS NOVA: “What’s up with Jupiter’s wandering magnetic field?”

In 2018 and 2019, data from NASA’s Juno mission revealed new discoveries about Jupiter’s bizarre magnetic field.

Introduction

In 2018, astronomers were on the hunt for Planet Nine, a mysterious and powerful celestial body thought to dwell billions of miles beyond Neptune. They found 12 new moons orbiting Jupiter instead.

Then, in October of this year, astronomers made another astonishing moon discovery: 20 tiny “new” satellites around Saturn, allowing the ringed giant to unseat Jupiter as the planet in our solar system with the most moons. But as 2019 comes to a close, Jupiter, the largest and oldest planet in our solar system, is back in the spotlight for a new reason: its shape-shifting magnetic field.

This still from an animation illustrates Jupiter’s magnetic field at a single moment in time. The Great Blue Spot, an-invisible-to-the-eye concentration of magnetic field near the equator, stands out as a particularly strong feature. Credit: NASA/JPL-Caltech/Harvard/Moore et al.

In a recent study [Nature Astronomy], researchers compared observations of Jupiter’s magnetic field from NASA’s Juno spacecraft with those taken by Pioneer 10, Pioneer 11, Voyager 1, and Ulysses. They found that Jupiter’s field had changed in just a few short decades.

How is this possible? And could it have happened if Jupiter’s core was more like our own planet’s?

Kelvinsong

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Sometimes the best way to find something is by not looking for it at all.

Astronomers looking for Planet Nine—a celestial body predicted to orbit in the outer reaches of our solar system—stumbled upon 12 new moons orbiting Jupiter. By this latest count, our solar system’s largest planet now has 79 moons, more than any other.

Astronomers made the discoveries using the Blanco telescope at the Cerro Tololo Inter-American Observatory in Chile and the Subaru telescope on Mauna Kea, Hawaii.

NOAO/CTIO Victor M Blanco 4m Telescope which houses the DECam at Cerro Tololo, Chile, housing DECam at an altitude of 7200 feet

NAOJ/Subaru Telescope at Mauna Kea Hawaii, USA,4,207 m (13,802 ft) above sea level

It took the team a while to make the required observations to confirm each moon’s existence. The smallest moon is just over a half-mile across, while the largest is about three miles in diameter. Some slipped in and out of view, complicating the task.

Here’s Ben Guarino, reporting for the Washington Post:

“Jupiter’s moons range in size from shrimpy satellites to whopping space hulks. Galileo discovered the first four of Jupiter’s moons, all huge, in 1610. The largest Galilean moon, Ganymede, is bigger than the planet Mercury. Those moons orbit close to Jupiter and travel in the same direction as the planet spins.

The moons Sheppard spied are farther-flung and tiny, each no more than two miles in diameter. One moon detected by Sheppard and his colleagues is the smallest Jovian moon ever discovered. They named it Valetudo, after a daughter of Jupiter and the Roman goddess of hygiene and personal health.”

The orbits of Jupiter’s moons

Most of the newly discovered moons orbit opposite to Jupiter’s spin, what’s known as a retrograde orbit. But Valetudo, in addition to being the smallest discovered, orbits in prograde, or the same direction as the planet’s spin. That puts it on a possible collision course with a retrograde moon.

Photo credits: NASA, Roberto Molar-Candanosa/Carnegie Institution for Science

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NOVA is the highest rated science series on television and the most watched documentary series on public television. It is also one of television’s most acclaimed series, having won every major television award, most of them many times over.

From PBS NOVA: “How polar bear guards protect the largest Arctic expedition ever”

From PBS NOVA

November 21, 2019
Katherine J. Wu
@KatherineJWu

A glimpse into the lives of the MOSAiC mission’s polar bear guards—and the powerful predators they watch for.

Working with polar bears “isn’t about what you do when you have a bad encounter,” says polar bear researcher Eric Regehr, “but what you do to prevent them.” Image Credit: Michael Ginzburg

Michael Ginzburg was 20 when he met his first polar bear.

It was October 2008, and Ginzburg—a student at the time—was aboard a small research vessel northwest of the Svalbard archipelago when his mentor shouted that she’d spotted a bear on the coastline. Ginzburg scrambled up to the deck and sprinted to the front of the boat, forgetting both gloves and boots.

Shivering in his slippers, he studied the animal 1,000 feet away (a male, he would later learn, identifiable by its thick neck and short, pointed tail). Over the soft whir of clicking cameras, he heard its playful grunts and growls as it fussed with a fishing net that had washed ashore. As Ginzburg’s hands and feet went numb, his nose tingled with the bear’s heavy musk, wafted out to sea by strong Arctic winds.

Ginzburg, who is from Russia, had been in closer proximity to bears in zoos. But this peaceful encounter on the animal’s home turf felt different. “It had this certain intimacy,” he says. “It wasn’t this loud, crowded moment.”

That first polar bear, he says, made him sure he didn’t want it to be his last.

Now a photojournalist and polar adventurer based in Germany, Ginzburg has made good on that vow. His next expedition may be his most challenging yet: As one of several polar bear guards for the ongoing Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) expedition, he’ll be drawing on his close encounters with bears to ensure other people don’t have them.

Not only the science behind MOSAiC is a huge endeavour that needs the expertise of multiple nations and scientific disciplines, but also the logistics face unparalleled challenges.

Over the course of a pair of 2-month stints aboard the icebreaker RV Polarstern, a research vessel currently frozen into a slab of Arctic ice, Ginzburg will spend his days scouring the horizon for bears. It will be his job to watch them, in the hopes of safeguarding the ship, its equipment, and the hundreds of people on board. It will be his job to scare them, if and when the curious creatures come too close. And, under the direst of circumstances, it will be his job to shoot and kill them, should it be necessary to save a human life.

RV Polarstern

Polarstern approaches Akademik Fedorov, a supporting icebreaker, to exchange people and scientific equipment. Image Credit: Esther Horvath

The German research aircrafts Polar 5 and Polar 6 will be operated to complement the measurements at the central MOSAiC site. A landing strip will be built especially for these research planes and for resupply flights in spring 2020.

Research and supply cruises by icebreakers from MOSAiC partners will provide support for the AWI research vessel Polarstern. They will further extend the geographical coverage of the observations and will link the measurements to the larger scales of the Arctic climate system and explore global feedbacks.

In addition, helicopters will be employed. Fuel depots for long-range helicopters have been set up on Bolshevik Island to broaden the spectrum of response options to potential emergency situations during the expedition.

The Arctic is warming faster than any other place on Earth. MOSAiC will document an entire year of the physical, geochemical, and biological changes taking place in this shifting landscape in the hopes of improving global climate models and preserving what’s left of Earth’s fragile crown of ice.

The questions the MOSAiC team is asking about this region have never been more urgent, says Katie Florko, a polar bear researcher at the University of British Columbia. As temperatures rise, Arctic ice is fading, imperiling the countless creatures that depend on it—and fueling weather extremes farther south. “It’s all reliant on the sea ice,” Florko says. “It all comes full circle.”

That makes the risks worth it, she says, for polar bears and people alike. This is about their future—and ours.

Constant vigilance

Since mid-October, Polarstern has been moored into an ice floe that’s creeping past the North Pole at about 4 miles per day. Over the next year, some 300 scientists will reside on the ship in 2-month rotations. They’ll anchor encampments and equipment directly into the floe, sampling everything from the air swirling miles above the ice to the microscopic sea life teeming thousands of feet below.

This base camp, which extends about half a mile from Polarstern itself, is the heart of the expedition, and the most critical area to protect. Teams of polar bear guards—six to eight on each leg of the trip—will spend most of their days on watch, either scouring the horizon from the ship or patrolling a tripwire fence encircling the camp. When researchers need to collect samples from stations off-site, some up to 30 miles away, they’ll take guards with them.

A polar bear feasts on a fresh kill. Image Credit: Michael Ginzburg

Unlike their grizzly cousins, polar bears (Ursus maritimus) are tailor-made for the punishing habitats of the north. Swaddled in inches-thick layers of fat and dense white fur, these behemoths can weigh more than 1,300 pounds. Their skull-crushing jaws and clawed feet can disembowel a 4-foot seal. Polar bears have even been known to go after walruses twice their size.

Behind the bears’ black noses—able to smell prey from miles away—are minds as sharp as their teeth: They’re calculating hunters, capable of snaring seals when they breach the sea ice to breathe. They communicate with each other through scents, sounds, and subtle body language. And they can navigate journeys of hundreds, if not thousands, of miles with their senses alone. “Polar bears are very smart animals,” says University of Alberta’s Ian Stirling, who’s been studying polar bears for almost 50 years. “You can practically see the wheels turning in their heads.”

As far as bear fare goes, humans aren’t high on the list: Our lack of substantive blubber makes us an impractical snack for an animal that fasts for up to eight months at a time. “By and large, polar bears don’t actually like coming around people,” Stirling says.

But out here, people are interlopers, and even mild curiosity from something this strong can spell trouble, Ginzburg says. Like a child touching the wings of a butterfly, tactile investigation from a polar bear can be a death sentence. “That’s purely because of their enormous size and weight,” he says. “By feeling you, unfortunately, they break you.”

Photojournalist and polar explorer Michael Ginzburg, a former researcher now serving as a polar bear guard on the MOSAiC Arctic expedition. Image Credit: Julia Hager

Should a bear cross the tripwire fence, a flare will be triggered to, in theory, frighten the animal away. But the mechanical barrier alone isn’t enough. Flares are reactionary, not proactive. That’s where Ginzburg and the rest of the safety team comes in: Their eyes and ears are needed to sense the bears; their voices, to raise the alarm. Around bears, “the hardest job of all is maintaining vigilance,” Stirling says.

On his daily patrol, Ginzburg will use binoculars to scan the sea ice—not just for fur, but for the signs that might precede or follow a bear’s presence: the alluring silhouette of a seal, or a fat set of footprints in the snow. A keen nose also helps. “Bears are very smelly,” he says. “You can tell if they’re coming downwind.”

But it can still be surprisingly easy to miss a thousand-pound bear. “They’re huge, but they are also very well camouflaged,” he says. “Sometimes the bear is 100 meters in front of you, but in the shade…it will just look like a pile of dirty snow.” To human eyes, subtle differences in light can transform a lump of ice into a living, breathing predator. Polarstern guards will also monitor a suite of thermal cameras that can detect heat emanating from beneath the bears’ vast white coats.

Key to guarding is also a good understanding of animal behavior, Ginzburg says. If a bear is well-fed and healthy, there’s little reason for it to stop. But that’s not always the case. If the animal gets within a few hundred feet and Ginzburg senses a threat, he’ll ready his flare gun—a handheld version of the scare tactic deployed by the tripwire fence.

Not all bears scare easy, though.

The absolute last resort is the .308 caliber rifle carried by each guard. If it comes to it, Ginzburg says, there’s a protocol: Once the bear’s within 100 feet, take aim just below the head. One shot is usually enough to take down a smaller female or a juvenile. Multiple shots might be necessary for a healthy adult male. “If we shoot, we shoot to kill,” Ginzburg says.

A male polar bear lounging in the snow. Image Credit: Michael Ginzburg

In the past 10 years, Ginzburg has seen many hundreds, if not thousands, of bears. He’s never had to fire at one. (Neither have any of the other eight people interviewed for this story, guards, researchers, or otherwise.)

In reality, being a successful polar bear guard is less about being good with guns than it is about awareness and communication, says Åshild Rye, a Norwegian polar bear guard who will join Ginzburg on the second leg of the trip next month. “It’s about trying to be as present as possible,” she says. Rye’s strategy is to think in hypotheticals: Where is the bear coming from? How is the bear behaving? Am I at a good vantage point? What will I do if the bear comes close?

Armed guards will lead any MOSAiC scientific teams that travel far from the ship, and will be the first to venture into any new terrain. While they scout, ideally from high ground, vehicles will be kept running to maintain an easy escape route; equipment won’t be set up until there’s a solid all-clear. Near Polarstern, there are plenty of places to retreat. But the farther away the researchers get from their temporary civilization, the more vulnerable they are.

“I don’t know a single Arctic scientist who isn’t always thinking about safety,” says Kristin Laidre, an Arctic ecologist and polar bear expert at the University of Washington. “If you don’t do it that way, you don’t keep doing it.”

The full North Pole experience

Scientists Gunnar Spreen (center) and Matthew Shupe (right) exam a potential ice floe for MOSAiC in September 2019. Image Credit: Esther Horvath

The second leg of the trip will be the most difficult, Ginzburg says. As Earth’s North Pole tilts completely out of the reach of the sun, the Polarstern team will be working in continuous darkness for several months—the Arctic’s polar night. It’s the graveyard shifts to end all graveyard shifts.

This will be Ginzburg’s fourth extended polar night. For him, it’s a draw, not a deterrent. “It’s about as Arctic as it gets,” he says. “The full North Pole experience.” (He’ll be joining MOSAiC on a later leg, too, where he’ll be privy to the opposite effect: midnight sun.)

Visibility during these months will be poor, and even with top-of-the-line night vision goggles, Ginzburg and his colleagues may only be able to spot bears when they’re just hundreds of feet away—a paltry distance, he says, compared to the mile or more that binoculars afford. The guards will also have to be conscious of the length of their shifts. Long stints with the goggles, Ginzburg says, have a way of wearing on the eyes and mind. “You’re in pitch black, you’re on your own, you start to get cold,” he says. After a couple hours, he says, “your imagination and your brain start messing with you.”

A changing of the guard will occur every two hours or so, with personnel rotating between shifts on the ship and out on the ice. There are accommodations aplenty on board, but things quickly get less luxurious in the field. A big conundrum, Ginzburg says, is how to safely pee while on patrol amid strong winds and temperatures that can plunge to minus 50 degrees Fahrenheit.

A male (left) and female (right) polar bear on the Arctic ice. Image Credit: Michael Ginzburg

Privacy isn’t a problem, but on a mission where pristine ice samples are key, contaminating the snow is a big no-no. Instead, Ginzburg uses a Nalgene bottle that’s a different size and color from the one carrying his drinking water. “When you’re exhausted, tired, and cold…it is really easy to grab the wrong [container],” he says. “That’s not such a big problem for the toilet urge, but at some point later on the mistake will become very evident.” (The protocol is similar for Ginzburg’s female colleagues, but with an extra piece of equipment: a female urination device.)

During polar night especially, the guarding job will come down to mental grit, says Rye, who’s weathered several winters in Svalbard. Like Ginzburg, though, she’s looking forward to the challenge—in part because it’ll bring the team on Polarstern closer together. Members of the expedition’s safety team hail from all around the world, and many of the guards have yet to meet each other in person. “With so many people in one place…this will be the most social time,” Rye says. “That will make the darkness a welcome season for me.”

Rye will also be the only female polar bear guard on her leg of the trip, though it’s a distinction she’s used to. “A lot of the work I’ve done before has also been dominated by men,” she says. Her love of the outdoors is what keeps her coming back. “We have distanced ourselves too far from nature,” she says. “We think we are something separate. But people are nature.”

Like Rye, Ginzburg leapt at the chance to participate in what he calls “the biggest expedition in the history of humankind.” When you get an offer like that, he says, “it’s hard to say no.”

A male polar bear. Most polar bears “are very risk averse” and don’t want much to do with humans, says polar bear researcher Eric Regehr. But every so often, one might approach out of curiosity. Image Credit: Michael Ginzburg

But Ginzburg’s polar expeditions have become bittersweet since the birth of his son, who will celebrate his second birthday while his father is wintering aboard Polarstern. Packed alongside Ginzburg’s clothes and tools is a set of skis, painted by his son, that he’ll wear most days he’s patrolling. “He did some very abstract drawings, right on the front,” Ginzburg says. “With those drawings ahead of me…all I have to do is look down. They’re a reminder for me to not do anything stupid.”

The most dangerous game

A few years back, Ginzburg had his closest call yet. While on a job in the Arctic, he lost track of his surroundings and was startled to spot a large male bear just a few hundred feet away ambling toward him and his crew. He scrambled for his flare gun, loaded a cartridge, and fired. The bear was unfazed. So Ginzburg shot off another flare—and then another. But the bear plowed on.

Heart pounding, Ginzburg slowly began to load his rifle. “When an animal looks that dedicated, walking to you…it was a scary situation,” he says. “I was ready to shoot.”

The bear was a little more than 200 feet away when Ginzburg took aim. But in an instant, the bear seemed to change its mind. It turned and lumbered away.

In retrospect, Ginzburg and his crew weren’t in any real danger, he says. Their unexpected visitor had probably just been curious—lured in, perhaps, by the scent of another group of bears nearby while Ginzburg’s attention had drifted. “I neglected my surroundings,” he says. “It was my fault.”

Safety engineer Bjela König watches a group of scientists from the bridge of Polarstern. Image Credit: Esther Horvath

Ginzburg doesn’t expect such close calls during MOSAiC’s yearlong expedition. Though all guards will carry a rifle and ammunition, “their whole job is to do everything they can so that weapon never has to be used,” Laidre says.

Polarstern has already been visited by a handful of bears, including a mother and her young cub.

A polar bear and her cub passed close to the Polarstern, a German icebreaker that’s on a yearlong expedition in the Arctic. Esther Horvath/@MOSAiCArctic/Twitter

Ginzburg estimates that the mission will glimpse several dozen more—perhaps even 100—before its 13 months in the Arctic are up.

For MOSAiC to be successful, it must put humans in polar bear territory. That means exercising respect and caution—and identifying priorities ahead of time, says Florko. If it comes down to protecting a piece of equipment or an animal, there’s no question about what comes first, she says. Most measurements can be salvaged; the same can’t be said for an endangered life.

The human-polar bear relationship is complex, but it doesn’t have to be contentious, says Katya Wassillie, who is Alaska Native (specifically Yup’ik/Iñupiaq) and executive director of the Alaska Nannut Comanagement Council (ANCC). Indigenous populations native to the Arctic have been sustainably harvesting bears (called nanuq in Inuit languages) for food and clothing for millennia, Wassillie points out. This longstanding relationship, she says, is built on respect and a mutual sense of boundaries. Even when not tracking the bears, human hunters will cross paths with them on the ice because they often seek the same prey. And bears can benefit from the bone piles left behind by whaling communities. The two species, Wassillie says, have spent generations growing alongside each other.

“Most people see…a dangerous, aggressive animal,” Ginzburg says. “But I see way more bears being gentle and curious, and funny and intelligent.”

A male (right) and female (left) polar bear tussle before mating. Image Credit: Michael Ginzburg

Polar bears have no natural enemies. But the global changes wrought by human-driven climate change have made them some of the most vulnerable creatures in the Arctic—the only place they live. Perhaps the greatest threat humans pose to polar bears’ existence isn’t one carried out by bullets or guns, but the continued warming of the world.

Unlike other bears, polar bears are considered marine mammals, spending most of their lives atop sea ice, where they hunt, mate, and often raise their cubs. Recent melts have displaced bears from the habitats where they make their highest-calorie kills, driving them onto land before they’ve had the chance to build up enough fat to endure months-long fasts. With fewer platforms to hunt from, bears are now traveling greater distances for less food, putting serious strains on their health, says Anthony Pagano, a polar bear researcher at the University of California, Santa Cruz.

More time spent ashore also brings bears into closer contact with people, leading to conflict—and even a handful of fatalities. As they lose their habitats, bears are also being visited more and more by tourists and researchers. The exposure makes Wassillie worry that some of these dangerous predators are becoming habituated to humans and important deterrents like flares—the same ones that MOSAiC’s polar bear guards carry. “The bears know when they’re not in mortal peril,” she says. “Now certain methods are not as effective as they used to be.”

A polar bear on sea ice. Photojournalist Michael Ginzburg snapped this photo when the bear wandered by, seeming curious. Image Credit: Michael Ginzburg

Roughly 26,000 bears currently inhabit the Arctic, but several populations are experiencing precipitous declines, says Eric Regehr, a polar bear expert at the University of Washington. But the disappearing sea ice is “changing rapidly and dramatically in only one direction,” he says. “If climate change isn’t addressed…a century from now, this species won’t be around as we know it today.”

What happens in the Arctic doesn’t stay in the Arctic, Laidre says. The changes happening up north—the ones affecting bears now—have already begun to trickle down to the rest of the planet, fueling floods, storms, and temperature fluctuations worldwide.

That puts polar bears and people on the same side. What’s between us and them isn’t about animosity, or the hierarchy of predator and prey, Ginzburg says. It’s about finding a way to coexist—to share the Arctic, and its ice, while it’s still there.

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From PBS NOVA: “To predict the next infectious disease outbreak, ask a computer”

From PBS NOVA

October 15, 2019
Katherine J. Wu

Lyle’s flying fox (Pteropus lylei), one of several bat species known to carry Nipah virus, which can cause serious illness in people. Animal health and human health go hand in hand, researchers say. Image Credit: asawinimages, iStock

On December 26, 2013, a two-year-old boy named Emile Ouamouno fell ill in the village of Meliandou in Guinea, West Africa. For two days, his tiny body was wracked with fever as he vomited and passed black stool. By December 28, he was dead.

Within weeks, his sister, mother, and grandmother were, too—the first casualties of what would eventually become thousands. The largest Ebola outbreak in history had begun.

It would be many months, however, before a team of researchers would pinpoint the probable source of the epidemic: a colony of Angolan free-tailed bats (Mops condylurus) that had roosted in a hollow cola tree less than 200 feet from Emile’s home. The locals called them lolibelo, or flying mice, for their distinctive smell and long tails. They were common targets for children at play, who would rouse them from sleep with sticks and roast them as snacks.

By the time ecologists and veterinarians arrived in Meliandou in April 2014, the tree in question had been burned and the bats were long gone. But the winged, mouse-sized mammals are still considered some of the likeliest candidates for Ebola’s so-called animal reservoirs, maintaining the virus in the wild before it makes each of its fateful hops into humans.

The disease’s devastating trajectory is a familiar one. Ebola, like SARS, Lyme disease, HIV, and most of the other infections known to plague people, got its start in another species. It’s in these creatures that pathogens can also hide between epidemics, biding time before they re-emerge.

By the time most reservoir species are identified, the pathogens in question have already spilled over into people. In the wake of an outbreak, that leaves just one course of action: mitigation—the frantic attempt to halt the collapse of a line of dominos after they’ve already begun to fall.

For Barbara Han, a disease ecologist at the Cary Institute, this reactive approach isn’t enough. “The fact is, you’ve already waited until people got sick,” she says. “You don’t want to hand out umbrellas after the rain falls. You want to forecast the rain before it starts.”

To get ahead of the curve, researchers need better tools that can predict these outbreaks before they happen, says David Redding, a disease ecologist at University College London. That means searching for the ecological and epidemiological patterns that precede spillovers—the harbingers of outbreaks that flicker to life in the wild, then trickle into humans.

Most of these warning signs aren’t readily discernible by human brains alone. So scientists like Han and Redding have turned to computational models that can scour gobs of ecological and demographic data in their stead, hunting for clues to where the next infectious leak might spring.

The border between Guinea and Liberia, during the 2014 Ebola outbreak. Frequent boat travel, as well as other modes of transport, can help Ebola virus hop from one country to another. Image Credit: CDC Global, flickr

Into the wild, and back out again

Out in the wild, infection is a given—a reality Barbara Han, who got her scientific start in animal ecology, became intimately familiar with while tracking fungal pathogens [PLOS|ONE] in amphibians.

But the bugs that lurk in wildlife don’t always stay there.

Of the new and emerging infectious diseases documented by the Centers for Disease Control (CDC) over the past couple decades, 75 percent are zoonotic, or capable of spreading from animals to humans. And while scientists have amassed a good deal of data on animal reservoirs over the years, they’ve long struggled to uncover the crucial commonalities among them—the traits that make a species ideally suited to pass a pathogen to people.

That’s why Han has turned to a tool that could accomplish what human researchers can’t on their own. Several years ago, she and her team trained a computer model [PNAS] to pick out new rodent species with high disease-carrying potential, based on the traits they shared with 217 previously identified carriers of disease. Han compares the approach to Pandora’s strategy for recommending songs: An algorithm learns the trends that dictate musical taste or vulnerability to infection, then offers up a comparable band or animal that hasn’t been considered before. Using this tactic, Han’s model scanned through the 2,277 rodent species that exist worldwide and homed in on 58 not previously designated as reservoirs.

The list was diverse, spanning much of the rodent family tree. But its members did seem to have a couple things in common, like brief lifespans, early sexual maturity, and large numbers of offspring. “These rodents basically have a ‘live fast, die young’ approach to life,” Han says. It’s possible they prioritizing reproduction over other resource-heavy pursuits like, say, an ironclad immune system, she says. But unlike rats and mice, long-lived, slow-maturing humans have more to lose by ignoring infections.

A northern grasshopper mouse (Onychomys leucogaster), one of several species pinpointed by a machine learning model trained to detect rodents at risk of carrying infectious diseases. Image Credit: Weber, iStock

Predictions aren’t guarantees. And it’s likely that many of these disease-carrying candidates will never harbor a problematic pathogen at all. But when done well, “modeling studies are great for hypothesis generation—they demonstrate what could happen,” says Inger Damon, Director of the CDC’s Division of High-Consequence Pathogens and Pathology.

And in certain instances, they seem spot on, Han says. While her team’s paper was being prepped for publication, two [Parasitology International] of the voles [PLOS] on their computer-generated list were confirmed to harbor parasites.

A similar story has played out in other animal groups, too. In 2016, Han and her colleagues published a list of bat species [PLOS] that could play host to filoviruses [Emerging Infectious Diseases], the group that includes Ebola. Less than a year later, a team of virus hunters uncovered filoviruses lurking in China’s fruit bats, including a couple species from Han’s paper.

Around the same time, a colleague at Columbia University phoned Han, bursting with excitement: He’d discovered a new ebolavirus [Nature Biotechnology] in Sierra Leone. It wasn’t yet clear if the virus could cause disease in humans, but it had been detected in two types of bats. One of them was the Angolan free-tailed bat—another species high on Han’s list of potential reservoirs. The same species suspected of infecting Emile Ouamouno years before.

Bridging the divide

Reservoirs aren’t reservoirs until they’re tapped. For a disease to jump into a human population, it needs access—a region where infected animals and people overlap.

At University College London, David Redding and ecologist Kate Jones have taken their own computational approach to uncover the dynamics of infection at these ports of entry. Their newest model, described in a paper published today in the journal Nature Communications, is what Redding calls a hybrid approach, borrowing from both ecology and epidemiology to predict areas at high risk of Ebola spillover and subsequent outbreak in Africa.

“We know where animal hosts are,” he says. (In Ebola’s case, that almost certainly means bats, and possibly great apes and duikers—a type of antelope—as well.) “And we also know where people are. Where you have both, you have likely contact, and risk of disease.”

Workers in Guinea, West Africa, shortly after Ebola was confirmed to have hit the region. Image Credit: EU Civil Protection and Humanitarian Aid, flickr

That might sound simple enough. But a bevy of other variables make dynamics of a spillover far more complex, Redding says. Land use, for instance, can have a big impact on a reservoir’s range, and how much the members of different populations mix. On the human side, the size of an ensuing outbreak depends on connectivity—how easy it is for people to physically get around and mingle with others—and regional wealth, which often dictates the amount of money allocated to health care.

From the virus’ perspective, “the ideal situation would probably include a human population situated in a forested area with animal hosts, near a big transportation hub, near a big city,” Redding says. “That’s where you would expect large outbreaks to occur.”

While these are many of the critical variables that affect zoonotic disease, Damon says, there are always more variables to consider. Only some spillovers turn into outbreaks. And the likelihood of that transition can hinge on aspects of human behavior that Redding’s model didn’t capture, like the prevalence of funerary practices that may increase contact with infected bodies, she says.

By definition, computational modeling will always be a bit reductionist, says Sadie Ryan, a disease ecologist at the University of Florida. Programs have to accurately and efficiently capture the complexities of the real world with a limited set of data. That’s a huge challenge—and a high stakes one, she says. “If you’re doing massive spatial computational simulations without real information, you’re just making video games.”

But models like these, which take animals, humans, and their environments into account, effectively capture the “biological realism of these spillover events,” Ryan says.

The largest Ebola outbreak in history may have begun when an Angolan free-tailed bat (Mops condylurus) passed the virus to a toddler in Meliandou, Guinea, West Africa in 2013. Children in the village often roused bats from tree hollows to play with cook eat them. Image Credit: Jakob Fahr, iNaturalist

In its current iteration, Redding’s model has proven powerful. With the data it was fed, it correctly identified several areas that had already experienced Ebola outbreaks, such as the Democratic Republic of Congo (DRC), Gabon, and regions in West Africa hit by the epidemic that began in Meliandou.

When the simulation originally ran in 2018, it also flagged several other regions—including Nigeria, Ghana, Rwanda, and Kenya—that, at the time, had been mostly untouched by the virus. In the months since, two of its outbreak predictions in the DRC have come true.

Cloudy with a chance of infection

West Africa’s Ebola epidemic ended in June of 2016. In the two and a half years after Emile Ouamouno fell ill in Meliandou, at least 28,646 people had been infected and at least 11,323 had died—more than all previous Ebola outbreaks combined.

The virus has since re-emerged. And with so many available hiding places in the wild, it’s likely to do so again, Redding says.

This is where outbreak predictions can be powerful, Han says. They can inform where health care resources are diverted next, or how ecologists and conservationists can protect and monitor (rather than villainize) reservoir species in their natural habitats, she says.

Acting on the numbers churned out by these models, however, is another issue entirely, Damon says. Predicting spillover isn’t the same as preventing it—a process that requires increased surveillance, or an infusion of resources that can quash outbreaks before they have a chance to grow.

An infection control supervisor (left) demonstrates proper hand washing techniques during a field supervision visit to a small clinic in N’Zérékoré, Guinea. Image Credit: Lindsey Horton, CDC Global, flickr

These interventions will become increasingly complicated to execute in a rapidly changing world, Ryan says. As temperatures rise and habitats disappear, reservoir species—among many others—will be forced to uproot and adopt new behaviors, rejiggering their potential to transmit disease. “Climate change impacts literally everything,” says Han, who’s now collaborating with researchers at NASA to incorporate climate data into her team’s predictions.

In the case of Ebola, one trend may already be clear: The worse climate change gets, the more outbreaks we’ll have, Redding says. Projecting into the year 2070, his team’s simulations show that warmer, wetter conditions will raise the risk of spillovers across the African continent. Some of these effects can be mitigated by reducing carbon emissions and increasing sustainable development, Redding says—but only if the world takes action soon.

“This is about getting the concept of intervention out there ahead of time,” Ryan says. “If this is how the future is unfolding, let’s be there before it happens. And let’s be ready.”

See the full article here .

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From Fermi National Accelerator Lab: “MINERvA successfully completes its physics run”

FNAL Art Image by Angela Gonzales

From Fermi National Accelerator Lab , an enduring source of strength for the US contribution to scientific research world wide.

April 5, 2019
Caitlyn Buongiorno

FNAL MINERvA front face Photo Reidar Hahn

On Feb. 26, a crowd of engineers, technicians and analysts crowded around a computer screen as Fermilab scientist Deborah Harris pressed “stop” on the data collection for the MINERvA neutrino experiment.

“We’re all just really excited by what we’ve accomplished,” said Harris, MINERvA co-spokesperson and future professor at York University. “The detector worked wonderfully, we collected the data we need, and we did it on schedule.”

MINERvA studies how neutrinos and their antimatter twins, antineutrinos, interact with the nuclei of different atoms. Scientists use that data to help discover the best models of these interactions. Now, after nine years of operation, the data taking has come to an end, but the analysis will continue for a while. MINERvA scientists have published more than 30 scientific papers so far, with more to come. As of today, 58 students have obtained their master’s or Ph.D. degrees doing research with this experiment.

Neutrinos could hold the answer to one of the most pressing mysteries in physics: why matter was not completely annihilated by antimatter after the Big Bang. That imbalance from 13.7 billion years ago led the universe to develop into what we see today. Studying neutrinos (and antineutrinos) could uncover the mystery and help us understand why we are here at all.

The MINERvA collaboration gathers to celebrate the end of data taking. MINERvA co-spokesperson Laura Fields, kneeling at center, holds a 3-D-printed model of the MINERvA neutrino detector. Photo: Reidar Hahn

A number of neutrino experiments investigate this mystery, including Fermilab’s NOvA experiment and the upcoming international Deep Underground Neutrino Experiment, hosted by Fermilab.

FNAL LBNF/DUNE from FNAL to SURF, Lead, South Dakota, USA

To be as successful as possible, these experiments need precise models that describe what happens before and after a neutrino collides with an atom.

Every time a neutrino collides with part of an atom inside a detector, a spray of new particles flies off and travels through the rest of the detector. In order to understand the nuances of neutrinos, scientists need to know the energy of the neutrino when it first enters the detector and the energy of all the particles produced after the interaction. This task is complicated by the fact that some of the outgoing particles are invisible to the detector — and must still be accounted for.

Imagine you’re playing pool and you shoot the cue ball at another ball. You can easily predict where that second ball will go. That prediction, however, gets much more complex when your cue ball strikes a collection of balls. After the break shot, they scatter in all directions, and it’s hard to predict where each will go. The same thing is true when a neutrino interacts with a lone particle: You can easily predict where the lone ball will go. But when a neutrino interacts with an atom’s nucleus — a collection of protons and neutrons — the calculation is much more difficult because, like the pool balls, particles may go off in many different directions.

“It’s actually worse than that,” said Kevin McFarland, former MINERvA co-spokesperson and professor of physics at the University of Rochester. “All the balls in the break shot are also connected by springs.”

MINERvA provides a neutrino-nucleus interaction guidebook for neutrino researchers. The experiment measured neutrino interactions with polystyrene, carbon, iron, lead, water and helium. Without MINERvA’s findings, researchers at other experiments would have a much tougher time understanding the outcomes of these interactions and how to interpret their data.

“I really am proud of what we’ve been able to accomplish so far,” said Laura Fields, Fermilab scientist and co-spokesperson for MINERvA. “Already the world has a much greater understanding of these interactions.”

See the full article here.

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Fermi National Accelerator Laboratory (Fermilab), located just outside Batavia, Illinois, near Chicago, is a US Department of Energy national laboratory specializing in high-energy particle physics. Fermilab is America’s premier laboratory for particle physics and accelerator research, funded by the U.S. Department of Energy. Thousands of scientists from universities and laboratories around the world collaborate at Fermilab on experiments at the frontiers of discovery.

FNAL Short-Baseline Near Detector under construction

Dark Energy Camera [DECam], built at FNAL

FNAL MINOS Far Detector in the Soudan Mine in northern Minnesota

From Fermi National Accelerator Lab: “ICARUS neutrino detector installed in new Fermilab home”

FNAL Art Image by Angela Gonzales

From Fermi National Accelerator Lab , an enduring source of strength for the US contribution to scientific research world wide.

August 16, 2018
Leah Hesla

For four years, three laboratories on two continents have prepared the ICARUS particle detector to capture the interactions of mysterious particles called neutrinos at the U.S. Department of Energy’s Fermi National Accelerator Laboratory.

On Tuesday, Aug. 14, ICARUS moved into its new Fermilab home, a recently completed building that houses the large, 20-meter-long neutrino hunter. Filled with 760 tons of liquid argon, it is one of the largest detectors of its kind in the world.

With this move, ICARUS now sits in the path of Fermilab’s neutrino beam, a milestone that brings the detector one step closer to taking data.

It’s also the final step in an international scientific handoff. From 2010 to 2014, ICARUS operated at the Italian Gran Sasso National Laboratory, run by the Italian National Institute for Nuclear Physics. Then the detector was sent to the European laboratory CERN, where it was refurbished for its future life at Fermilab, outside Chicago. In July 2017, ICARUS completed its trans-Atlantic trip to the American laboratory.

The second of two ICARUS detector modules is lowered into its place in the detector hall. Photo: Reidar Hahn

“In the first part of its life, ICARUS was an exquisite instrument for the Gran Sasso program, and now CERN has improved it, bringing it in line with the latest technology,” said CERN scientist and Nobel laureate Carlo Rubbia, who led the experiment when it was at Gran Sasso and currently leads the ICARUS collaboration. “I eagerly anticipate the results that come out of ICARUS in the Fermilab phase of its life.”

Since 2017, Fermilab, working with its international partners, has been instrumenting the ICARUS building, getting it ready for the detector’s final, short move.

“Having ICARUS settled in is incredibly gratifying. We’ve been anticipating this moment for four years,” said scientist Steve Brice, who heads the Fermilab Neutrino Division. “We’re grateful to all our colleagues in Italy and at CERN for building and preparing this sophisticated neutrino detector.”

Neutrinos are famously fleeting. They rarely interact with matter: Trillions of the subatomic particles pass through us every second without a trace. To catch them in the act of interacting, scientists build detectors of considerable size. The more massive the detector, the greater the chance that a neutrino stops inside it, enabling scientists to study the elusive particles.

ICARUS’s 760 tons of liquid argon give neutrinos plenty of opportunity to interact. The interaction of a neutrino with an argon atom produces fast-moving charged particles. The charged particles liberate atomic electrons from the argon atoms as they pass by, and these tracks of electrons are drawn to planes of charged wires inside the detector. Scientists study the tracks to learn about the neutrino that kicked everything off.

Rubbia himself spearheaded the effort to make use of liquid argon as a detection material more than 25 years ago, and that same technology is being developed for the future Fermilab neutrino physics program.

“This is an exciting moment for ICARUS,” said scientist Claudio Montanari of INFN Pavia, who is the technical coordinator for ICARUS. “We’ve been working for months choreographing and carrying out all the steps involved in refurbishing and installing it. This move is like the curtain coming down after the entr’acte. Now we’ll get to see the next act.”

ICARUS is one part of the Fermilab-hosted Short-Baseline Neutrino program, whose aim is to search for a hypothesized but never conclusively observed type of neutrino, known as a sterile neutrino. Scientists know of three neutrino types. The discovery of a fourth could reveal new physics about the evolution of the universe. It could also open an avenue for modeling dark matter, which constitutes 23 percent of the universe’s mass.

ICARUS is the second of three Short-Baseline Neutrino detectors to be installed. The first, called MicroBooNE, began operating in 2015 and is currently taking data. The third, called the Short-Baseline Near Detector, is under construction. All use liquid argon.

Fermilab’s powerful particle accelerators provide a plentiful supply of neutrinos and will send an intense beam of the particle through the three detectors — first SBND, then MicroBooNE, then ICARUS. Scientists will study the differences in data collected by the trio to get a precise handle on the neutrino’s behavior.

“So many mysteries are locked up inside neutrinos,” said Fermilab scientist Peter Wilson, Short-Baseline Neutrino coordinator. “It’s thrilling to think that we might solve even one of them, because it would help fill in our frustratingly incomplete picture of how the universe evolved into what we see today.”

Members of the crew that moved ICARUS stand by the detector. Photo: Reidar Hahn

The three Short-Baseline Neutrino experiments are just one part of Fermilab’s vibrant suite of experiments to study the subtle neutrino.

NOvA, Fermilab’s largest operating neutrino experiment, studies a behavior called neutrino oscillation.

FNAL NOvA detector in northern Minnesota

The three neutrino types change character, morphing in and out of their types as they travel. NOvA researchers use two giant detectors spaced 500 miles apart — one at Fermilab and another in Ash River, Minnesota — to study this behavior.

Another Fermilab experiment, called MINERvA, studies how neutrinos interact with nuclei of different elements, enabling other neutrino researchers to better interpret what they see in their detectors.

Scientists at Fermilab use the MINERvA to make measurements of neutrino interactions that can support the work of other neutrino experiments. Photo Reidar Hahn

“Fermilab is the best place in the world to do neutrino research,” Wilson said. “The lab’s particle accelerators generate beams that are chock full of neutrinos, giving us that many more chances to study them in fine detail.”

The construction and operation of the three Short-Baseline Neutrino experiments are valuable not just for fundamental research, but also for the development of the international Deep Underground Neutrino Experiment (DUNE) and the Long-Baseline Neutrino Facility (LBNF), both hosted by Fermilab.

DUNE will be the largest neutrino oscillation experiment ever built, sending particles 800 miles from Fermilab to Sanford Underground Research Facility in South Dakota. The detector in South Dakota, known as the DUNE far detector, is mammoth: Made of four modules — each as tall and wide as a four-story building and almost as long as a football field — it will be filled with 70,000 tons of liquid argon, about 100 times more than ICARUS.

The knowledge and expertise scientists and engineers gain from running the Short-Baseline Neutrino experiments, including ICARUS, will inform the installation and operation of LBNF/DUNE, which is expected to start up in the mid-2020s.

“We’re developing some of the most advanced particle detection technology ever built for LBNF/DUNE,” Brice said. “In preparing for that effort, there’s no substitute for running an experiment that uses similar technology. ICARUS fills that need perfectly.”

Eighty researchers from five countries collaborate on ICARUS. The collaboration will spend the next year instrumenting and commissioning the detector. They plan to begin taking data in 2019.

See the full article here .

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Fermi National Accelerator Laboratory (Fermilab), located just outside Batavia, Illinois, near Chicago, is a US Department of Energy national laboratory specializing in high-energy particle physics. Fermilab is America’s premier laboratory for particle physics and accelerator research, funded by the U.S. Department of Energy. Thousands of scientists from universities and laboratories around the world
collaborate at Fermilab on experiments at the frontiers of discovery.

From NOVA: “NASA’s TESS Spacecraft Will Scan the Sky For Exoplanets”

From NOVA

13 Apr 2018 [Just now in social media.]
Allison Eck

NASA/TESS will identify exoplanets orbiting the brightest stars just outside our solar system.

The era of big data is here—not just for life on Earth, but in our quest to find Earth-like worlds, too.

Next Monday, April 16, NASA’s $200-million Transiting Exoplanet Survey Satellite, or TESS, will surge skyward on a SpaceX Falcon 9 rocket. If all goes well, over the next two years, it will search space for signs of exoplanets, or planets beyond our own solar system. So far, scientists have found around 4,000 such celestial bodies freckled across the face of the universe, including seven Earth-sized planets orbiting the dwarf star Trappist-1 about 235 trillion miles away. NASA’s Kepler spacecraft, launched in 2009, has led this revolutionary effort—but now it’s running out of fuel.

TESS, its replacement, will document close-by exoplanets circling bright stars (as opposed to the more distant ones Kepler surveyed). These data points will give scientists more information about the planets ripest for scientific exploration—and which may harbor life.

“TESS’s job is to find an old-fashioned address book of all the planets spread out around all the stars in the sky,” said Sara Seager, astrophysicist and planetary scientist at MIT and deputy science director for the TESS mission.

George Ricker, principal investigator for TESS, estimates that the spacecraft will be able to find some 500 super-Earths, or planets that are one-and-a-half to two times the size of Earth, and several dozen Earth-sized planets. Many of these likely orbit red dwarf stars, which are smaller and cooler than our Sun. TESS will watch for transits—the slight dimming of stars as planets pass in front of them from our vantage point on Earth.

Since red dwarfs are cooler than the Sun, habitable zone planets that revolve around them will orbit closer to their host star, making transits more frequent—and thus more scientifically useful.

“The transits are a repeating phenomenon. Once you’ve established that a given host star has planets, you can predict where they will be in the future,” Ricker said. “That’s really going to be one of the lasting legacies from TESS.”

Stephen Rinehart, project scientist for TESS, says that with Kepler, the goal was to get a narrow, deep look at one slice of the cosmos. By contrast, TESS will take an expansive look at the most promising candidates for future research—and compare and contrast them.

“It’s changing the nature of the dialogue,” Rinehart said. “So far, the nature of our conversations about exoplanets have really been statistical. With TESS, we’ll find planets around bright stars that are well-suited to follow-up observations, where we can talk not just about what the population is like, but we can start talking about what individual planets are like.”

TESS will gaze upon 20 million stars in the solar neighborhood. Kepler was only able to look at about 200,000. “We’ve got a factor of a hundred more stars that we’re going to be able to look at,” Ricker said. “These are the objects that people are going to want to come back to centuries from now.”

The spacecraft will act as a bridge to future projects, too, like the James Webb Telescope, which is set to launch in May of 2020. That telescope will study every phase in the history of our universe—and it’ll act as the “premier observatory of the next decade.”

Our history with exoplanets is surprisingly brief. While we had dreamt of them for centuries, it was only 25 years ago that we confirmed their existence. Now, we know that nearly every red dwarf in the Milky Way has a family of planets, and that maybe 20% of those planets lie with the habitable zone. With so much variety and many to choose from, scientists hope that by studying their atmospheres, they’ll be able to detect signs of life.

“[Habitability] is one of the philosophical questions of our time,” Rinehart said. “Can we find evidence that there’s even a possibility of other life nearby us in the universe? TESS isn’t going to quite get us there. TESS is an important step forward.”

Paul Hertz, director of astrophysics for NASA, echoes Rinehart’s optimism.

“After TESS is done, you’ll be able to go outside at night, take your grandchild by the hand, and point to a star and say, ‘I know there’s a planet around that star. Let’s talk about what that planet might be like,’” Hertz said. “Nobody’s ever been able to do that in the history of mankind.”

See the full article here .

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From NOVA: “Does Dark Matter Ever Die?”

From NOVA

30 May 2018 [Just found in social media]
Kate Becker

Dark matter is the unseen hand that fashions the universe. It decides where galaxies will form and where they won’t. Its gravity binds stars into galaxies and galaxies into galaxy clusters.

Dark matter cosmic web and the large-scale structure it forms The Millenium Simulation, V. Springel et al

Caterpillar Project A Milky-Way-size dark-matter halo and its subhalos circled, an enormous suite of simulations . Griffen et al. 2016

And when two galaxies merge, dark matter is there, sculpting the product of the merger. But as for what dark matter actually is? No one knows.

Here’s the short list of what we do know about dark matter. Number one: There’s a lot of it, about five times more than “ordinary” matter. Two: It doesn’t give off, reflect, or absorb light, but it does exert gravity, which is what gives it a driver’s-seat role in the evolution of galaxies. Three: It’s stable, meaning that for almost 13.8 billion years—the current age of the universe—dark matter hasn’t decayed into anything else, at least not enough to matter much. In fact, the thinking goes, dark matter will still be around even when the universe is quintillions (that’s billions of billions) years old—maybe even forever.

Though invisible, dark matter exerts gravity just like other matter. No image credit.

Theoretical physicists dreaming up new ideas about dark matter typically start with these three basic principles. But what if the third—the requirement that dark matter be stable over the cosmic long haul—is wrong? That’s the renegade idea behind a new dark matter proposal called “Dynamical Dark Matter.” Though it’s still on the fringe of dark matter physics (“It’s as far as you can get from the traditional approaches,” says physicist Keith Dienes of the University of Arizona, who first developed the idea with Lafayette College theorist Brooks Thomas), it’s been gaining traction and attracting collaborators from particle physics, astrophysics, and beyond.

And dark matter is a field that could use some new ideas. While astronomers have been picking up dark matter’s fingerprints all over the universe for at least a century, physicists can’t seem to get a fix on a single dark matter particle. It’s not for lack of trying. Particle hunters have looked for signs of them in flurries of particles set loose by colliders like the Large Hadron Collider (LHC). They have buried germanium crystals and tanks of liquid xenon and argon deep underground—beneath mountains and in old gold mines—and looked for dark matter particles pinging off the atomic nuclei inside. The result: Nothing, at least not anything that physicists can agree on.

DARWIN Dark Matter experiment. A design study for a next-generation, multi-ton dark matter detector in Europe at the University of Zurich

Lux Dark Matter 2 at SURF, Lead, SD, USA

DEAP Dark Matter detector, The DEAP-3600, suspended in the SNOLAB deep in Sudbury’s Creighton Mine

Inside the ADMX experiment hall at the University of Washington Credit Mark Stone U. of Washington

Meanwhile, the astrophysical evidence for dark matter keeps building up. Take one universal mystery: Astronomers, after clocking how fast stars are circling around in galaxies, have found that stars skimming a galaxy’s perimeter are going just about as fast as closer-in stars. But based on everything we know about how gravity works, they should actually be going a lot slower—unless there is some invisible mass pulling on them. Then, there are galaxy clusters: Galaxies within them are jouncing around so quickly that they should fly apart, absent some invisible mass is holding them all together. Noticing a theme here? Even the cosmic microwave background radiation, the closest thing we have to a baby picture of the newborn universe, has patterns in it that can only really be explained by dark matter. So, if dark matter is so ubiquitous, why can’t we find it?

Gravity from Huchra’s Lens causes light from the quasar Einstein Cross to bend around it..No image credit.

Some researchers are beginning to wonder if they’ve been searching for the wrong thing all along. Most (though not all) dark matter detectors are designed to find hypothetical particles called WIMPs—short for “weakly interacting massive particles.” WIMPs are an appealing dark matter candidate because they emerge naturally from a beyond-the-standard-model theory called supersymmetry, which posits that the all the fundamental subatomic particles have as-yet-undiscovered partners.

As physicists worked out the properties of those still unseen particles, they noticed that one was a startlingly good match for dark matter. It would interact with other particles via gravity and something called the weak force, which only works when particles get within a proton’s-width of each other. Plus, it would be stable, and there could be just enough of it to account for the missing mass without upsetting with the evolution of the universe.

The appeal of WIMPs is “almost aesthetic,” says Jason Kumar, a physicist at the University of Hawaii: it speaks to physicists’ love of all that is simple, symmetrical, and elegant. But, Kumar says, “It’s now becoming very hard to get these models to fit with the data we’re seeing.” That doesn’t mean that the WIMP model is wrong, but it does put researchers in the mood to consider ideas that, ten years ago, might have been brushed off as theoretical footnotes. Like, for instance, the idea that dark matter that isn’t stable after all.

A Destabilizing Influence

Dienes and Thomas were newcomers to dark matter when they first hatched the idea of Dynamical Dark Matter. They were so new to the field that, at first, they didn’t even worry about stability. Together, they began sketching a new kind of dark matter. First, they thought, what if dark matter weren’t just one kind of particle, but a whole bunch of different kinds? Second, what if those particles could decay? Some might disappear within seconds, but others could stick around for trillions of years. The trick would be getting the balance right, so that the bulk of the dark matter would linger until at least the present day.

Dienes and Thomas called their new framework “Dynamical Dark Matter,” and started sharing it at talks and academic conferences. The reaction, according to Dienes: “A boatload of skepticism.”

“People kept asking about stability,” Dienes remembers. “But we were not thinking about stability in the traditional way.”

Why are physicists so sure that dark matter is stable, anyway? Galaxies from long ago—the ones astronomers see when they look billions of light years out into the universe—aren’t more weighed-down by dark matter than our nearby, present-day specimens, at least not at the level of precision that astronomers can measure. Plus, if dark matter decayed into lighter, detectable particles, the little shards would fly out into space with a lot of energy, which we would be able to measure on Earth. And if the decay started in the universe’s baby days, it would disrupt the formation of the elements, shifting the chemistry of the cosmos.

Galaxies far away from Earth aren’t any more massive than those nearby. No image credit.

Dynamical Dark Matter resolves the stability problem through a balancing act. If most of dark matter is tied up in particles that live a long time—longer than the age of the universe—that leaves room for a small share of dark matter to be made up of particles that vanish quickly. “It’s a balancing between lifetimes and abundances,” Dienes says. “This balancing is the new underlying principle that replaces mere stability.”

At first glance, this might sound contrived. Why should everything work out just so? But Dienes, Thomas, and their collaborators have discovered several scenarios that naturally produce just the right combination of particles. “It turns out there are a lot of interesting ways in which these things can come about,” Thomas says. Dynamical Dark Matter remains agnostic about what the dark matter particles are or how they came to be. “It’s not just a single model for dark matter, like a particle that’s a candidate,” he says. “It’s a whole new framework for thinking about what dark matter could be.”

Dynamical Dark Matter is one of a growing number of “multi-component” dark matter models that welcome in multiple particles. “The key differentiator for Dynamical Dark Matter is that it’s not just a random collection of particles,” Kumar says. “There are just a couple of parameters that describe everything about it.”

A Shrinking Slice of Pie

Today, dark matter makes up about 85% of the “stuff” in the universe, out-massing regular matter by a factor of five to one. But if the Dynamical Dark Matter framework is right, one day, dark matter will fizzle out entirely. The process will start slowly. Then, as a larger share of dark matter hits its expiration date, the die-out will speed up until, ultimately, dark matter goes extinct.

That won’t happen for a long, long time—long after dark energy, that other cosmic mystery force, stretches the universe to the brink of nothingness. (But that’s another story.) So one might ask: Who cares if a teeny weeny bit of dark matter goes “poof” if no one misses it?

Scientists searching for dark matter particles do.

That’s because, at dark matter detectors, Dynamical Dark Matter particles should leave a more complicated set of fingerprints than WIMPs. While WIMPs should make a relatively simple “clink” against the ordinary particles inside a detector, Dynamical Dark Matter (or any other brand of multiplex dark matter) would make a jumbled-up jangle. “If there is only one dark-matter particle, there is a well-known ‘shape’ for this recoil spectrum,” says Dienes, describing the detector read-out. “So seeing such a complex recoil spectrum would be a smoking gun of a multi-component dark-matter scenario such as Dynamical Dark Matter.”

Particle collider experiments could also distinguish Dynamical Dark Matter from WIMPs. “Dynamical dark matter basically provides a very rich spectrum of very different types of collider signatures, some very different from conventional dark matter,” says Shufang Su, a physicist at the University of Arizona. With Dienes and Thomas, Su is trying to predict the traces Dynamical Dark Matter would leave in data from particle colliders like the LHC.

Su was attracted to the dynamical dark matter model by the idea that dark matter could be a whole panoply of particles instead of just one, which would leave a distinctive signature on the visible particles produced in the LHC’s smash-ups. “These changes could be very dramatic and very different from what would occur if there is only a single dark matter species,” Su says. “If one dark matter particle leads to a single peak, Dynamical Dark Matter could lead to multiple peaks and perhaps even peculiar kinks.”

Then there’s the decay factor. Depending on how long Dynamical Dark Matter particles live, some might fall apart almost as soon as they are created. Others might last long enough to travel some length of the detector, or escape entirely. “Even though it’s still dark matter, it could have a totally different signature,” Su says.

While Su is thinking about how to detect Dynamical Dark Matter at colliders here on Earth, Kumar is thinking about whether it could explain something that has been puzzling astronomers: a mysterious excess of high-energy positrons in space. Dark matter researchers have suggested the positrons could be coming from WIMPs, which spit them out as they collide with and annihilate other WIMPs. The trouble, Kumar says, is that this process should only produce positrons up to a certain maximum energy before shutting down; so far, astronomers haven’t found such a cut-off. Dynamical dark matter just might be able to make positrons at the energy levels astronomers observe.

Of course, Dynamical Dark Matter is just one of many alternatives to WIMPs. There are also SIMPS, RAMBOs, axions, sexaquarks—the list goes on. Until physicists make a clear-cut detection, theorists will have plenty of headroom to dream up new ideas.

“The main message is that this is an interesting alternative. We are not claiming that it is necessarily better,” Dienes says. “The field is wide open, and data will eventually tell us.”

See the full article here .

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From NOVA: “How Dust Built the Universe”

NOVA

28 Jul 2017
Samia Bouzid

If you’ve ever driven into the sunset with a dirty windshield or taken a drive after a snowstorm, your windshield caked with salt, you can probably relate to one of astronomers’ ongoing frustrations: seeing through dust.

Cosmic dust, which collects in galaxies in loose fogs or thick clouds, has often plagued astronomers. The tiny grains, each 10,000 times smaller than the eye of a needle, absorb light, scatter it, or change change its wavelength so it’s invisible to the eye. In doing so, dust steals some of the few clues we have to understand the nature of the universe.

But astronomers are discovering that dust plays important roles in both creating our universe and helping us understand it. It plants the seeds for stars, planets, and life as we know it. In the past two decades, astronomers studying dust have pulled back the curtain on important pieces of the universe that were hiding in plain sight. The more we learn about dust, the more we realize that it is part of the puzzle—not the rascal hiding the puzzle pieces.

Fertilizing the Universe

In the clouds of swirling gas that produce stars and planets, dust serves as a wingman for hydrogen. As a cloud condenses under its own gravity, star formation begins when hydrogen atoms meet and form molecules. But the compressing gas raises temperatures to the point where hydrogen begins whizzing around too fast to form bonds. It’s easier for the atoms to latch onto a piece of relatively big, slow dust. There, on the dust’s surface, two atoms can form a bond, making forming the first building blocks of a star. But dust is more than a matchmaker. As nearby stars blaze hot and bright in the ultraviolet, clouds of dust can act as a shield, sheltering stars-to-be from the barrage of radiation, which can break their chemical bonds and thwart their path to stardom.

The stars and dust clouds of the Milk Way. No image credit.

When the obstacles are finally overcome, a new star blossoms out of a cloud. Some of the remaining dust and gas begins to spin around the star and flatten into a disk. Specks of dust collide, and as their gravity increases, they pull more dust and gas onto their surface, accreting material. Over time, they become pebbles, then boulders and, sometimes, a few million years later, planets.

Xuening Bai, a research associate at the Harvard Center for Astrophysics, studies the processes that create planets and the stuff of life. Without dust, he says, the world would be a different place.

Seeing the Universe in a New Light

Indeed, most of what we see in space—not to mention all that we are, all that we eat, all that we breathe—owes its existence, in some way, to a grain of dust that formed the seed of a star or planet. But despite its fundamental importance, astronomers have only begun to understand what dust really is and how it affects the way we see the universe.

Dust itself is a mishmash of mostly carbon-based ashes cast off from dying stars. “It’s a catch-all term for what we would refer to on Earth as soot,” says Caitlin Casey, an astronomer at the University of Texas at Austin. Until recently, this “soot” was poorly understood. For centuries, the practice of astronomy was limited to what people could observe at visible wavelengths—in other words, what people could actually see. Dust absorbs light that can be seen by the naked eye and re-emits it at longer, infrared wavelengths, which are invisible to us. As a result, for most of history, dust was seen only as dark blobs, riddling galaxies with holes.

Then, in the 1960s, the first infrared telescopes pioneered the study of dust emissions. But these telescopes were not able to detect all radiation from dust. Very distant galaxies, such as the ones Casey studies some 10 billion light-years away, are receding so quickly that the light re-emitted by their dust gets stretched, shifting its wavelength into the submillimeter range and making the galaxies practically invisible, even in infrared telescopes.

NASA Infrared Telescope facility Mauna Kea, Hawaii, USA

It wasn’t until 1998 that a group of astronomers in Mauna Kea, Hawaii, pointed a submillimeter telescope at a blank field of sky and made a discovery that rocked the field. A few years earlier, the Hubble Space Telescope had revealed that this blank sky was swarming with distant galaxies, but now, an entirely new population of galaxies lit up in submillimeter wavelengths. It was like turning on a light in a room where astronomers had fumbled in the dark for centuries. Galaxies glowed with dust, and the earliest, most distant galaxies, showed the most dust of all.

East Asia Observatory James Clerk Maxwell telescope, Mauna Kea, Hawaii, USA

Dust Bunnies in the Edges of the Universe

Submillimeter wavelengths were the last piece of the electromagnetic spectrum to be observed by astronomers, so in some ways, the 1998 discovery seemed to complete a picture of the universe. Large swaths of the sky were now imaged at every wavelength. Dust, the quiet catalyst behind star formation, had been unmasked.

But in another way, astronomers had merely stumbled upon more pieces to a puzzle they thought they had completed. Because if dust comes from stars, the universe should get dustier the more stars have lived and died. What business did the earliest galaxies have being so dusty? The universe has been around for nearly 14 billion years, but most of these dusty galaxies formed when the universe was a tender 2 or 3 billion years old. By then, only a few generations of stars had ever existed. So where did all that dust come from?

Desika Narayanan, an astronomer at the University of Florida, probes for answers by developing numerical simulations to model the early universe. He says that one clue lies in the earliest galaxies, which were probably ungainly, messy galaxies a far cry from the elegant spiral that is our Milky Way. Galaxies like ours pop out a star about once or twice a year. But these old, dusty galaxies were firecrackers, bursting with up to 1,000 to 2,000 new stars a year. As the first stars died, dust billowed from them and filled the galaxy—perhaps enough to account for the levels of dust seen today.

But telescope data can only confirm so much. In the short lifetime of submillimeter astronomy, Narayanan says, telescope sensitivity has drastically improved, outpacing even camera phone technology, which has raced from blurry images taken by flip-phones to the latest, sharpest shots on iPhones in roughly the same period.

Still, even the greatest telescopes strain against the vastness of the universe. They have to be extremely large to detect and resolve light from the most distant galaxies. At 15 meters in diameter, the world’s largest submillimeter dish belongs to the James Clerk Maxwell Telescope at the summit of Mauna Kea, Hawaii. It was the first telescope to detect these galaxies in 1998. In Chile, the Atacama Large Millimeter Array/Submillimeter Array, or ALMA, is made up of 66 dishes that can be arranged to span nearly 10 miles in an attempt to resolve the universe’s faintest, most distant galaxies.

ESO/NRAO/NAOJ ALMA Array in Chile in the Atacama at Chajnantor plateau, at 5,000 metres

It’s no coincidence that both of these observatories were built in extreme environments, both well above 10,000 feet and in dry places where the air is thin. Water vapor in the air soaks up most of the infrared radiation passing through it that’s so critical to observing dust. Meanwhile, the Earth itself radiates enthusiastically in the infrared, creating a noisy background for any signal that does get through. “Doing infrared astronomy from the ground is like trying to observe a star in the daylight out of a telescope made of light bulbs,” George Rieke, an infrared astronomer, once said.

For now, this difficulty has left some mysteries intact. Although astronomers are better able to observe galaxies and create simulations, some galaxies remain too old and too dusty to fit into existing models. The size, peculiar structure, and dustiness of early galaxies is not fully explained.

The next surge in science, expected to help explain some of the mysteries surrounding dusty, star-forming galaxies, will come from the James Webb Space Telescope, a massive instrument with a six-and-a-half-meter dish—a piece of highly polished metal as wide as a giraffe is tall—set to for launch in 2018.

Free from the interfering atmosphere, this telescope will peer into the dusty edges of space in finer detail than any other telescope.

Narayanan says that the astronomy community is excited for these new measurements, and expect it will reveal new avenues for exploration. “Immediately, you start to open up as many questions as you think you’re going to answer,” he says.

Twenty Years of Dusty Galaxies

On July 31, astronomers will meet in Durham, U.K., to celebrate the 20th anniversary of the discovery of dusty star-forming galaxies and share what they have learned over the last two decades. But the elusiveness of hard data has left many questions about ancient dusty galaxies still open for debate. “I suspect we’re still going to walk away from this meeting saying, ‘Theorists still haven’t figured out where they come from,’” Narayanan says.

But the mystery is part of what fascinates him. Twenty years ago, “We had no idea these things existed,” he says. “Then they just lit up in the infrared and have posed a huge challenge ever since then.”

Despite all the research on dust, it is only a small fraction of the universe. Even in moderately dusty galaxies like our own, dust accounts for less than 1% of the mass. Yet its ability to transform the light passing through it completely changes the way we see the universe.

For astronomers like Casey and Narayanan, this leaves plenty of mysteries to probe. “It’s really cool to me that something that is so negligible in terms of the mass budget of the universe can have such a tremendous impact on how we perceive it,” Casey says. “There is so much to discover and rediscover.”

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From NOVA: “Cancer Biology Reproducibility Project Sees Mixed Results” Read it and Weep

NOVA

18 Jan 2017 [Don’t know how I missed this, or maybe they never put it up in social media before?]
Courtney Humphries

How trustworthy are the findings from scientific studies?

A growing chorus of researchers says there’s a “reproducibility crisis” in science, with too many discoveries published that may be flukes or exaggerations. Now, an ambitious project to test the reproducibility of top studies in cancer research by independent laboratories has published its first five studies in the open-access journal eLife.

“These are the first public replication studies conducted in biomedical science, and that in itself is a huge achievement,” says Elizabeth Iorns, CEO of Science Exchange and one of the project’s leaders.

Cancer biology is just one of many fields being scrutinized for the reproducibility of its studies.

The Reproducibility Project: Cancer Biology is a collaboration between the non-profit Center for Open Science and the for-profit Science Exchange, which runs a network of laboratories for outsourcing biomedical research. It began in 2013 with the goal of repeating experiments from top-cited cancer papers; all of the work has been planned, executed, and published in the open, in consultation with the studies’ original authors. These papers are the first of many underway and slated to be published in the coming months.

The outcome so far has been mixed, the project leaders say. While some results are similar, none of the studies looks exactly like the original, says Tim Errington, the project’s manager. “They’re all different in some way. They’re all different in different ways.” In some studies, the experimental system didn’t behave the same. In others, the result was slightly different, or it did not hold up under the statistical scrutiny project leaders used to analyze results. All in all, project leaders report, one study failed to reproduce the original finding, two supported key aspects of the original papers, and two were inconclusive because of technical issues.

Errington says the goal is not to single out any individual study as replicable or not. “Our intent with this project is to perform these direct replications so that we can understand collectively how reproducible our research is,” he says.

Indeed, there are no agreed-upon criteria for judging whether a replication is successful. At the project’s end, he says, the team will analyze the replication studies collectively by several different standards—including simply asking scientists what they think. “We’re not going to force an agreement—we’re trying to create a discussion,” he says.

The project has been controversial; some cancer biologists say it’s designed to make them look bad bad at a time when federal research funding is under threat. Others have praised it for tackling a system that rewards shoddy research. If the first papers are any indication, those arguments won’t be easily settled. So far, the studies provide a window into the challenges of redoing complex laboratory studies. They also underscore the need that, if cancer biologists want to improve the reproducibility of their research, they have to agree on a definition of success.

An Epidemic?

A recent survey in Nature of more than 1,500 researchers found that 70% have tried and failed to reproduce others’ experiments, and that half have failed to reproduce their own. But you wouldn’t know it by reading published studies. Academic scientists are under pressure to publish new findings, not replicate old research. There’s little funding earmarked toward repeating studies, and journals favor publishing novel discoveries. Science relies on a gradual accumulation of studies that test hypotheses in new ways. If one lab makes a discovery using cell lines, for instance, the same lab or another lab might investigate the phenomenon in mice. In this way, one study extends and builds on what came before.

For many researchers, that approach—called conceptual replication, which gives supporting evidence for a previous study’s conclusion using another model—is enough. But a growing number of scientists have been advocating for repeating influential studies. Such direct replications, Errington says, “will allow us to understand how reliable each piece of evidence we have is.” Replications could improve the efficiency of future research by winnowing out false hypotheses early and help scientists recreate others’ work in order to build on it.

In the field of cancer research, some of the pressure to improve reproducibility has come from the pharmaceutical industry, where investing in a spurious hypothesis or therapy can threaten profits. In a 2012 commentary in Nature, cancer scientists Glenn Begley and Lee Ellis wrote that they had tried to reproduce 53 high-profile cancer studies while working at the pharmaceutical company Amgen, and succeeded with just six. A year earlier, scientists at Bayer HealthCare announced that they could replicate only 20–25% of 47 cancer studies. But confidentiality rules prevented both teams from sharing data from those attempts, making it difficult for the larger scientific community to assess their results.

‘No Easy Task’

Enter the Reproducibility Project: Cancer Biology. It was launched with a $1.3 million grant from the Laura and John Arnold Foundation to redo key experiments from 50 landmark cancer papers from 2010 to 2012. The work is carried out in the laboratory network of Science Exchange, a Palo Alto-based startup, and the results tracked and made available through a data-sharing platform developed by the Center for Open Science. Statisticians help design the experiments to yield rigorous results. The protocols of each experiment have been peer-reviewed and published separately as a registered report beforehand, which advocates say prevents scientists from manipulating the experiment or changing their hypothesis midstream.

The group has made painstaking efforts to redo experiments with the same methods and materials, reaching out to original laboratories for advice, data, and resources. The labs that originally wrote the studies have had to assemble information from years-old research. Studies have been delayed because of legal agreements for transferring materials from one lab to another. Faced with financial and time constraints, the team has scaled back its project; so far 29 studies have been registered, and Errington says the plan is to do as much as they can over the next year and issue a final paper.

“This is no easy task, and what they’ve done is just wonderful,” says Begley, who is now chief scientific officer at Akriveia Therapeutics and was originally on the advisory board for the project but resigned because of time constraints. His overall impression of the studies is that they largely flunked replication, even though some data from individual experiments matched. He says that for a study to be valuable, the major conclusion should be reproduced, not just one or two components of the study. This would demonstrate that the findings are a good foundation for future work. “It’s adding evidence that there’s a challenge in the scientific community we have to address,” he says.

Begley has argued that early-stage cancer research in academic labs should follow methods that clinical trials use, like randomizing subjects and blinding investigators as to which ones are getting a treatment or not, using large numbers of test subjects, and testing positive and negative controls. He says that when he read the original papers under consideration for replication, he assumed they would fail because they didn’t follow these methods, even though they are top papers in the field.. “This is a systemic problem; it’s not one or two labs that are behaving badly,” he says.

Details Matter

For the researchers whose work is being scrutinized, the details of each study matter. Although the project leaders insist they are not designing the project to judge individual findings—that would require devoting more resources to each study—cancer researchers have expressed concern that the project might unfairly cast doubt on their discoveries. The responses of some of those scientists so far raise issues about how replication studies should be carried out and analyzed.

One study, for instance, replicated a 2010 paper led by Erkki Ruoslahti, a cancer researcher at Sanford Burnham Prebys Medical Discovery Institute in San Diego, which identified a peptide that could stick to and penetrate tumors. Ruoslahti points to a list of subsequent studies by his lab and others that support the finding and suggest that the peptide could help deliver cancer drugs to tumors. But the replication study found that the peptide did not make tumors more permeable to drugs in mice. Ruoslahti says there could be a technical reason for the problem, but the replication team didn’t try to troubleshoot it. He’s now working to finish preclinical studies and secure funding to move the treatment into human trials through a company called Drugcendr. He worries that replication studies that fail without fully exploring why could derail efforts to develop treatments. “This has real implications to what will happen to patients,” he says.

Atul Butte, a computational biologist at the University of California San Francisco, who led one of the original studies that was reproduced, praises the diligence of the team. “I think what they did is unbelievably disciplined,” he says. But like some other scientists, he’s puzzled by the way the team analyzed results, which can make a finding that subjectively seems correct appear as if it failed. His original study used a data-crunching model to sort through open-access genetic information and identify potential new uses for existing drugs. Their model predicted that the antiulcer medication cimetidine would have an effect against lung cancer, and his team validated the model by testing the drug against lung cancer tumors in mice. The replication found very similar effects. “It’s unbelievable how well it reproduces our study,” Butte says. But the replication team used a statistical technique to analyze the results that found them not statistically significant. Butte says it’s odd that the project went to such trouble to reproduce experiments exactly, only to alter the way the results are interpreted.

Errington and Iorns acknowledge that such a statistical analysis is not common in biological research, but they say it’s part of the group’s effort to be rigorous. “The way we analyzed the result is correct statistically, and that may be different from what the standards are in the field, but they’re what people should aspire to,” Iorns says.

In some cases, results were complicated by inconsistent experimental systems. One study tested a type of experimental drug called a BET inhibitor against multiple myeloma in mice. The replication found that the drug improved the survival of diseased mice compared to controls, consistent with the original study. But the disease developed differently in the replication study, and statistical analysis of the tumor growth did not yield a significant finding. Constantine Mitsiades, the study’s lead author and a cancer researcher at the Dana-Farber Cancer Institute, says that despite the statistical analysis, the replication study’s data “are highly supportive of and consistent with our original study and with subsequent studies that also confirmed it.”

A Fundamental Debate

These papers will undoubtedly provoke debate about what the standards of replication should be. Mitsiades and other scientists say that complex biological systems like tumors are inherently variable, so it’s not surprising if replication studies don’t exactly match their originals. Inflexible study protocols and rigid statistics may not be appropriate for evaluating such systems—or needed.

Some scientists doubt the need to perform copycat studies at all. “I think science is self-correcting,” Ruoslahti says. “Yes, there’s some loss of time and money, but that’s just part of the process.” He says that, on the positive side, this project might encourage scientists to be more careful, but he also worries that it might discourage them from publishing new discoveries.

Though the researchers who led these studies are, not surprisingly, focused on the correctness of the findings, Errington says that the variability of experimental models and protocols is important to document. Advocates for replication say that current published research reflects an edited version of what happened in the lab. That’s why the Reproducibility Project has made a point to publish all of its raw data and include experiments that seemed to go awry, when most researchers would troubleshoot them and try again.

“The reason to repeat experiments is to get a handle on the intrinsic variability that happens from experiment to experiment,” Begley says. With a better understanding of biology’s true messiness, replication advocates say, scientists might have a clearer sense of whether or not to put credence in a single study. And if more scientists published the full data from every experiment, those original results may look less flashy to begin with, leading fewer labs to chase over-hyped hypotheses and therapies that never pan out. An ultimate goal of the project is to identify factors that make it easier to produce replicable research, like publishing detailed protocols and validating that materials used in a study, such as antibodies, are working properly.

Access mp4 video here .

Beyond this project, the scientific community is already taking steps to address reproducibility. Many scientific journals are making stricter requirements for studies and publishing registered reports of studies before they’re carried out. The National Institutes of Health has launched training and funding initiatives to promote robust and reproducible research. F1000Research, an open-access, online publisher launched a Preclinical Reproducibility and Robustness Channel in 2016 for researchers to publish results from replication studies. Last week several scientists published a reproducibility manifesto in the journal Human Behavior that lays out a broad series of steps to improve the reliability of research findings, from the way studies are planned to the way scientists are trained and promoted.

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From NOVA: “Remnants of Earth’s Original Crust Found in Canada”

NOVA

16 Mar 2017
Annette Choi

Two geologists studying North America’s oldest rocks have uncovered ancient minerals that are remnants of the Earth’s original crust which first formed more than 4.2 billion years ago.

These rocks appear to preserve the signature of an early Earth that presumably took shape within the first few hundred million years of Earth’s history.

Jonathan O’Neil and Richard Carlson uncovered the samples on a trek to the northeastern part of Canada to study the Canadian Shield formation, a large area of exposed continental crust underlying, centered on Hudson Bay, which was already known to contain some of the oldest parts of North America. O’Neil calls it the core or nucleus of the North American continent. “That spot on the shore of Hudson Bay has this older flavor to it, this older chemical signature.”

A view of 2.7 billion-year-old continental crust produced by the recycling of more than 4.2 billion-year-old rocks. Image credit: Alexandre Jean

To O’Neil, an assistant professor of geology at the University of Ottawa, rocks are like books that allow geologists to study their compositions and to learn about the conditions in which they form. But as far as rock records go, the first billion years of the Earth’s history is almost completely unrepresented.

“We’re missing basically all the crust that was present about 4.4 billion years ago. The question we’re after with our study is: what happened to it?” said Carlson, director of the Carnegie Institution for Science. “Part of the goal of this was simply to see how much crust was present before and see what that material was.”

While most of the samples are made up of a 2.7 billion-year-old granite, O’Neil said these rocks were likely formed by the recycling of a much older crust. “The Earth is very, very good at recycling itself. It constantly recycles and remelts and reworks its own crust,” O’Neil said. He and Carlson arrived at their conclusion by determining the age of the samples using isotopic dating and then adding on the estimate of how long it would have taken for the recycled bits to have originally formed.

O’Neil and Carlson’s estimate relies on the theory that granite forms through the reprocessing of older rocks. “That is a possibility that they form that way, but that is not the only way you can form these rocks,” said Oliver Jagoutz, an associate professor of geology at the Massachusetts Institute of Technology. “Their interpretation really strongly depends on their assumption that that is the way these granites form.

The nature of Earth’s first crust has largely remained a mystery because there simply aren’t very many rocks that have survived the processes that can erase their signature from the geologic record. Crust is often forced back into the Earth’s interior, which then melts it down, the geologic equivalent of sending silver jewelry back into the forge. That makes it challenging for geologists to reconstruct how the original looked.

These new findings give geologists an insight into the evolution of the oldest elements of Earth’s outer layer and how it has come to form North America. “We’re recycling extremely, extremely old crust to form our stable continent,” O’Neil said.

See the full article here .

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