Humans have been around for only about 0.01% of Earth’s history, yet we’ve altered natural landscapes and processes that have remained stable for millions of years. A team of researchers from the University of Glasgow recently studied a formerly sandy beach in the UK that highlights how fast these changes can occur.

Industrial steel and iron furnaces operated extensively in the UK from 1856 until the 1980s. During these decades, workers dumped roughly 335 million cubic meters (90 billion gallons) of molten furnace waste, called slag, across the country. Of that, roughly 27 million cubic meters (6 million gallons) now sits on the coast of Derwent Howe in a massive 30-meter (100-foot), solidified cliff. 

The researchers analyzed this region to understand how man-made, or anthropogenic, materials influence the way rocks form. Rocks naturally form and change into different types of rocks over million-year timescales, through a continuous process called the rock cycle. When the team uncovered a soda can tab manufactured in 1989 within the hardened grains, or clasts, of slag, they concluded that the beach had solidified within the last 35 years. Based on this discovery, they proposed a new term for rocks formed from anthropogenic sediments: the anthropoclastic rock cycle. 

The team collected 1,300 grains of sediment from 13 sites in the study area and found that 83% were slag. Natural beach sediments, like quartz sand, comprised only about 17% of the grains. As wind and waves broke down the cliff, slag clasts fell off and became rounded by friction as tides transported them from the cliff to the beach. 

At the boundary where the slag touched the beach, the researchers also saw evidence that the slag had seeped into the underlying wet sediment. The rocks there resembled a type of rock called peperite, which forms when lava flows over wet, loose sediments.  They concluded that this peperite-like rock formed as the molten slag flowed over the still sandy beach. Slag is much thicker than wet sand, so the resulting rock looked like blobs of slag encased in sandy rock. 

The researchers then visually observed how the slag grains were arranged in the solidified rock to reconstruct the tidewater speeds at different points in the coast’s history. The different ways sediments are arranged within a rock are called sedimentary features, and they reflect the processes that formed the rock. For example, as water flows over sand, it forms small, dune-like ripples. When the sand beds harden into rock, the ripples are preserved as features known as trough cross-bedding. 

Faster water erases any ripple formations and instead forms horizontal layers in the sediment, known as planar lamination. The researchers observed both trough cross-bedding and planar laminations preserved in the slag beach rocks. These sedimentary features indicate that the beach at Derwent Howe turned from loose sediment into rock in a generation. 

To investigate why this beach rapidly solidified, the researchers scanned the surfaces of the beach rock with electron beams and X-rays using a scanning electron microscope, or SEM, equipped with an energy dispersive X-ray, or EDX. Every chemical element emits a unique set of X-rays with different wavelengths when hit with EDX, so the researchers could compare the X-rays from their samples to databases of known mineral X-ray signatures. They identified the primary binding agents as calcium- and iron-rich minerals like calcite, goethite, and brucite. These minerals are called cements because they bind grains of sediment together. 

The researchers expected the slag to produce these cement compositions, since extracting metal ores from rock enriches the resultant slag in calcium, magnesium, manganese, and iron, which readily dissolve in water. When water flowing between closely packed slag grains can no longer hold additional dissolved elements, those elements precipitate as solid mineral cements. Since cements only form when the water has very high concentrations of dissolved elements, the introduction of massive amounts of slag caused the cement to form faster than it would in waters with lower concentrations of elements.

The researchers suspected that the anthropoclastic rock cycle they observed at Derwent Howe is not uncommon. Since slag contains all the elements necessary to form rocks when in contact with seawater and air, slag deposits all over the world could be rapidly influencing their local environments. With this in mind, the team suggested that future researchers update geological models to account for human contributions to the natural rock cycle. 

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Nitrogen is an essential building block of proteins, amino acids, and DNA. Without nitrogen, cells can’t function or reproduce. Nitrogen is abundant in the atmosphere as dinitrogen gas, but plants and animals can’t access atmospheric nitrogen. Instead, we rely on biologically available forms like ammonia and nitrate. 

Specialized microbes can transform atmospheric nitrogen into ammonia via a process called biological nitrogen fixation. Nitrogen-fixing soil bacteria have a unique protein complex, the nitrogenase complex, that facilitates this nitrogen transformation. The nitrogenase complex is activated by a group of genes known as nif genes. 

Legume plants like peanuts, peas, and beans have nitrogen-fixing bacteria in the soil zone around their roots, called the rhizosphere. The symbiotic relationship between nitrogen-fixing soil bacteria and legume plants supplies most of the biologically available nitrogen to life on Earth.

Bacteria attached to plant roots “feed” nitrogen to plants through the soil, and in turn receive organic acids for energy from plants performing photosynthesis. Source: Wikimedia Commons

However, one piece of the puzzle remains unexplored: the role of soil viruses in these nitrogen transformations, referred to as the nitrogen cycle. Viruses are microscopic particles made up of genetic material and proteins, but they can’t reproduce without a host cell. Scientists consider viruses to be biological entities that are halfway between living and non-living.

To reproduce, viruses contact a host cell and inject their genetic material into it. The virus’s genetic material takes over the host cell’s genome and forces the cell to produce proteins that assemble into new viruses. As new viruses are created, they can incorporate genes from the host cell into their own genetic material. Genes that are transferred from a host cell to a virus are known as auxiliary metabolic genes (AMGs). Viruses can carry AMGs and pass them to other hosts or use them to increase their own ecological fitness. 

Scientists from China, Spain, and the Czech Republic set out to investigate whether viruses from legume roots could increase local soil nitrogen fixation by expressing nif AMGs or by transferring nif genes to other bacteria. First, they determined the global distribution of viral nitrogen-fixing genes by analyzing about 8.6 million viral genomes from the Integrated Microbial Genomes/Virus database. They looked for the DNA sequences of known nitrogen-fixing genes and the locations where the viruses were sampled. They found that only 0.003% of the viruses in the database had at least 1 nitrogen-fixing gene, but they clustered in the same locations as nitrogen-fixing bacteria. 

The team also found 3 types of viruses that most commonly carried nitrogen-fixing genes: Kyanoviridae, Nudiviridae, and Bronfenbrennervirinae. Kyanoviridae viruses carried a nif gene called nifU. The researchers used a computer program called DRAM-v to confirm that nifU was a fully functional gene and a real tool that viruses could use. 

Next, the team collected soil samples from a cowpea field in Nanjing, China, to test whether the cowpea roots influenced the abundance of viruses using nitrogen-fixing genes. They collected soil from the cowpea rhizospheres and soil away from the plants. They analyzed both viral and bacterial RNA in the soil samples to identify active genes, using a sequencing process called metatranscriptomics. They found that the viral nifU gene was actively expressed in the cowpea rhizosphere samples more than in the non-crop soil. Although about 96% of nifU genes were being expressed by bacteria, viruses contributed about 4%. 

The researchers then assessed whether rhizospheric viruses changed the amount of nitrogen being fixed in these soils. They set up small, enclosed containers of sterile soil and added either bacteria or a mixture of bacteria and viruses extracted from the cowpea rhizospheres. They found that soil with viruses had higher total nitrogen (36 milligrams per kilogram, or mg/kg) than soil without viruses (17 mg/kg). 

Finally, they adjusted the air in each container to have a different form of dinitrogen gas. Atoms of the same element that have different atomic masses are known as isotopes. Nitrogen has 2 stable isotopes: lighter nitrogen-14 and heavier nitrogen-15. Bacteria or viruses that fix nitrogen at natural isotope abundances will take up nitrogen-14. But scientists can track who in the population fixes nitrogen by adding nitrogen-15 to the air, a process called nitrogen-15 stable isotope probing. Nitrogen-fixers will incorporate the heavy nitrogen-15 into their biomass over time and increase their weight, allowing researchers to separate and identify them.

The team grew the bacteria and viruses with nitrogen-15 for 35 days, then used stable isotope probing to separate the nitrogen fixers. They detected viral nifU AMGs among the heavier biomass, confirming that rhizospheric viruses were fixing nitrogen. 

The team concluded that rhizospheric viruses and the viral nifU AMG can increase nitrogen fixation in cowpea soils. The team suggested that although viruses with nitrogen-fixing genes are rare, they can influence the soil nitrogen cycle. They recommended that future researchers further test the contribution of viral nifU genes to plant nitrogen fixation with controlled infection experiments.

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In March 2021, the carcasses of at least 260 marine organisms from 81 species, including large animals called megafauna, washed ashore in South Africa. Scientists questioned whether this event was the result of an extreme temperature drop that can happen when deep, cold water rises to the surface along coastlines. Scientists refer to these rapid cooling events as coastal upwelling. 

Climate change is making oceans warmer, but it’s also making coastal upwelling stronger, with unknown consequences for marine megafauna. Scientists recently studied 2 boundary currents that are rapidly warming and creating strong upwelling near the edges of sharks’ geographic ranges: the Agulhas Current in southern Africa and the East Australian Current in eastern Australia. They wanted to determine whether climate-driven changes in upwelling zones are making cold-shock events more frequent and intense, and how these events are pushing sharks beyond their temperature limits. 

First, the researchers analyzed sea surface temperature data from satellites to see if rapid cooling from upwelling caused the mass marine die-off in 2021. They also obtained hourly temperature recordings from temperature loggers to measure subsurface temperature changes during the event. They found that during the March 2021 event, sea surface temperatures along the coast dropped by up to 7°C (12°F) in less than 48 hours, from 24°C (75°F) to below 17°C (63°F). Subsurface temperatures dropped faster, by more than 9°C (16°F) in 24 hours, from 21°C (70°F) to 12°C (54°F). 

Bullsharks experience physiological stress at temperatures below 19°C (66°F), which is near their lower thermal limit, when migrating through rapid cooling zones. Therefore, the researchers deduced that during the 2021 cold-shock event, the sharks were exposed to temperatures several degrees below their thermal limit, possibly more than 5°C (or 10°F) colder. 

The researchers also tagged 66 bull sharks with acoustic and satellite transmitters – including 41 at the Agulhas Current in South Africa and 25 at the East Australian Current in eastern Australia – to determine how they responded near their lower thermal limits in these zones. The acoustic tags record when sharks pass underwater receivers, providing information on their movements, locations, and water depths at those specific locations. In contrast, satellite tags continuously record the water temperatures and depths the sharks experience over time. 

The researchers used these data to compare sharks living in warm subtropical waters with those living in cooler waters at the edge of their temperature range. The researchers found that low temperatures that persisted for long periods prevented the sharks and other megafauna from physiologically recovering. They saw that some sharks try to swim to shallower depths and look for warmer water, but cooling sometimes happened faster than they could respond. 

The researchers also obtained wind records from the South African Weather Service to determine if upwelling-favorable winds happened before the 2021 event. They reported strong easterly winds pushing cold water on the surface along the coastline immediately before the event occurred. Because the cooling, strong winds, and animal deaths happened at the same time and place, the researchers inferred that upwelling was the main reason for the die-off.

Finally, the researchers examined 41 years of sea surface temperature data and used mathematical models to compute changes in the frequency and intensity of these events. Their analysis showed that rapid cooling events linked to upwelling can last a lot longer than the usual 1 to 3 days. For example, the March 2021 event lasted for 7 days. 

They found that these events have increased in both frequency and intensity in the past decades, and produce more extreme temperature drops than typically happen within 24 hours. Their results suggested that the 2021 die-off was part of an increasing trend, where warming oceans allow species to move into different areas, but intense upwelling can suddenly expose them to fatal cold events. This pattern is what scientists call a climate bait-and-switch. 

The researchers concluded that climate change is making coastal upwelling stronger, which can push marine megafauna beyond their thermal limits, even when initial warming appears to be beneficial. Their findings highlight an understudied aspect of climate change in the context of how temperature and upwelling cause shifts in species survival. They concluded their findings could help predict how marine ecosystems respond to future changing ocean conditions.

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When you think of an asteroid impact, you’re probably imagining something like the cataclysmic event that nearly wiped out the dinosaurs. In an astonishingly rare event, a rock the size of the island of Manhattan could come hurtling from deep space towards Earth and destroy the world.

On the contrary, asteroids are generally leftover debris from the primordial solar system that didn’t become part of a larger body, like a planet or moon, and they’re not particularly rare. Scientists estimate that there are about 1 billion asteroids and comets classified as near-Earth objects, or NEOs. NEOs are generally much smaller than the asteroid that killed the dinosaurs. They range from weakly held-together piles of rubble 200 meters (700 feet) across, to the minuscule 2024 BX1, approximately 44 centimeters (17 inches) across. 

For several decades, astronomical surveys of the sky have looked for these asteroids. NASA’s Center for Near-Earth Object Studies (CNEOS) Fireball and Bolide Database has records of over 1,000 incidents of objects colliding with our planet since the mid-1990s. Among these is a set of 11 objects that scientists detected before they hit Earth, known as imminent impactors. Finding imminent impactors allows scientists unique opportunities to study the smallest building blocks of the solar system, enabling them to learn more about asteroid composition, structure, and history.

A team of scientists recently conducted a study on how the newly built Vera Rubin Observatory could detect more imminent impactors before they strike Earth. They examined the CNEOS Fireball and Bolide Database impact records spanning February 1, 1994, to January 1, 2026, for records of the asteroids’ coordinates, velocities, and the energy they released at the time of collision. 

They found that 343 NEOs met this criterion, including 5 known imminent impactors. Using these recorded data, they reconstructed the objects’ pre-impact characteristics. The team predicted the asteroids’ orbital paths from the recorded coordinates and velocity. Assuming the objects were spherical, they estimated the size from velocity and impact energy. From this information about the asteroids’ state before impact, the team could then simulate whether the Rubin Observatory would have detected them. 

When small asteroids hit Earth, they mostly burn up in the atmosphere, producing a bright flash that is relatively easy to spot compared to when they are in space. The Rubin Observatory can see objects up to 10 billion times dimmer than the brightest star in the night sky, Sirius. To predict if the Rubin Observatory can detect dim NEOs, the team used the solar system simulator SORCHA. SORCHA takes an observatory’s specifications and the physical properties of the NEOs and uses these to determine whether the observatory could detect them. It also estimates the measured sizes and speeds of the NEOs, and predicts when the observatory would have seen them. 

At the Rubin Observatory, an imminent impactor is considered discovered if it’s observed at least 3 separate times over 15 days before hitting Earth. So this team applied this same criterion to their simulation. They found that of their 343 impactors, SORCHA estimated that the Rubin Observatory would have discovered 14 of them before impact. 

They also found that SORCHA predicted 4 additional impactors that could have been observed at least once, potentially allowing scientists to search other telescope data for evidence of their existence in pre-collision images. Based on these results, the team estimated that the Rubin Observatory could find 4% of all objects longer than 1 meter (3 feet) before they hit Earth. This percentage of discovery translates to 1 to 2 imminent impactors detected every year, at least double their current discovery rate.

The ability to more consistently find imminent impactors would allow researchers to study the smallest pieces of the solar system in detail and to draw general conclusions about the properties of objects that could potentially collide with Earth. This would also allow scientists to more accurately calculate the orbits of imminent impactors, determine where more meteorites land to recover them, and keep tabs on the extremely rare but more hazardous large impactors for planetary defense initiatives. So, humanity can learn more about the ancient solar system, and hopefully avoid going the way of the dinosaurs while doing so!

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Nearly 170 billion tons of ice melt off the Greenland Ice Sheet every year, but scientists don’t fully understand the process by which this melting occurs. Researchers in the past suggested that liquid water forms at the glacier’s surface, where warm air and sunlight melt the ice. This meltwater travels down through cracks in the glacier and along the bedrock beneath it and flows out to sea. 

However, some scientists view this model as too simple because it assumes water only flows downward and ignores how temperature affects water movement. They argue that an oversimplified melting model is unreliable for predicting how future ice sheets will behave.

One group of researchers tested this by investigating how water movement across Greenland is controlled by lakes beneath the ice sheet, called subglacial lakes. They monitored a newly discovered subglacial lake using high-resolution satellite images taken from 2012 to 2019 and 3D surface maps generated from the images. They focused on ice sheet changes from July 22 to August 1, 2014, during a suspected subglacial lake drainage event. A drainage event is like a water balloon that’s too full, bursting from excess pressure. 

They examined images of the Greenland ice sheet taken from Landsat-8, 3D surface maps from the Polar Geospatial Center, and data from ICESat and ICESat-2 taken in the summer of 2014. Based on these data, the researchers identified a 2-square-kilometer (0.8-square-mile) region of ice rising 10 to 15 meters (about 30 to 50 feet), forming a dome on the ice sheet’s surface. They suggested that this dome formed when a large, meltwater-fed lake developed on the bedrock beneath the ice sheet, pushing the ice upward. 

They also saw that on July 22, 2014, the dome began to collapse. Over the next 10 days, it dropped by 85 meters (about 280 feet), forming a basin. Using the dome’s dimensions, the researchers estimated that 90 million cubic meters, or about 3 billion cubic feet, of water drained from the lake at an average rate of 100 cubic meters, or about 3500 cubic feet, per second over the 10 days. This is roughly equivalent to 36,000 Olympic swimming pools draining at a rate of 1 pool every 25 seconds! 

The researchers also found that during the collapse, 40-meter-high (130-foot) ice blocks were uprooted about 1 kilometer (0.6 mile) downstream from the basin, followed by 6 square kilometers (about 2 square miles) of smooth ice. The researchers hypothesized that these features formed when water burst through the ice, flowed along its surface, and then reentered the ice sheet.

Next, they used data from Landsat 5, Landsat 9, the National Snow and Ice Data Center, and the U.S. Geological Survey to demonstrate that the drainage event also affected the surrounding environment. When the water reentered the ice sheet, it flowed beneath the Harding Glacier downstream. This influx of fast-moving water reduced pressure at the glacier’s base, slowing its movement. Simultaneously, the increased drainage beneath the Harding Glacier caused 500 to 600 meters (about 1,600 to 2,000 feet) of ice to break off its end. 

In response to these changes, the researchers hypothesized that subglacial waters rose to the surface rather than sinking to the bedrock because the ice sheet was frozen to it. To test this, they simulated temperatures at the base of the ice sheet using computer-generated thermal models. They input a range of likely bedrock temperatures and ice thicknesses to simulate possible conditions under the ice sheet. They found that all the simulations predicted the glacier’s base would remain below -5°C (23°F). At such low temperatures, the ice would be frozen to the bedrock before subglacial water could drain out. Since water couldn’t flow under the glacier, it was forced to travel upward. 

The researchers used these findings to develop a new conceptual model of how glacial meltwater moves. First, surface ice melts and flows into a subglacial lake. As meltwater accumulates, pressure builds at the base of the ice sheet, forming a dome on the surface. A drainage event causes the dome to collapse. As water moves downward through the glacier, it is blocked from reaching the base because the ice is frozen to the bedrock. The water then moves upward, bursts through the surface, travels across it, and eventually reenters the glacier before draining to the ocean.

The team concluded that water movement above, through, and below glaciers is interconnected. Destructive upward flow of meltwater, followed by downward flow beneath glaciers, can weaken ice sheet structure and alter downstream glacier dynamics. Their work highlights the need for more scientists to consider the processes driving glacial ice loss.

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Many volcano scientists spend their time monitoring volcanoes to predict if, or when, they’ll next erupt. The challenge for these scientists is to forecast the exact probability of an eruption and the moment it will occur. 

To address this problem, a team of researchers developed an early-detection system to determine when to issue alerts about volcanic eruptions. Their motivation was that previous alert systems weren’t accurate enough because they couldn’t detect underground volcanic processes that occur right before an eruption. 

From 2014 to 2023, the researchers conducted a series of tests to accurately detect temporary, low-frequency vibrations using an instrument called a seismometer. The researchers focused on these transient signals because they come from earthquakes and other ground phenomena, which scientists often rely on to predict volcanic eruptions. These phenomena include ground tilting caused by fracturing from the movement of magma and volcanic gases. The scientists named these signals the “Jerk” signals because they occur due to sudden movements. 

The team set up their experiment at Piton de la Fournaise, a volcano at La Réunion Island off the east coast of Madagascar. They discovered the Jerk signals by detecting and analyzing mysterious short-term signals from existing and experimental seismic data. During real-time experiments, they detected signals 8 kilometers (about 5 miles) from the volcano at the Rivière de l’Est seismic station. These signals resulted from changes in ground elevation as magma moved, and they preceded eruptions by minutes and sometimes hours. 

The researchers measured the Jerk signals in units of newton-meters per second, which conveys how fast physical changes occurred in or around the volcano. In addition to real-time experiments, the team checked the Jerk signals’ accuracy by analyzing the station’s past data to determine when these signals would have occurred before an eruption.

To avoid false alarms during their experiments, the researchers needed to distinguish between the signal amplitudes of ocean tides and the transient Jerk signals. So, they used computational software to predict the signals from ocean tides. This was necessary because the instruments that record ground phenomena are also sensitive to tidal movements.  

The Jerk system sent its first automatic alarm in June 2014, 1 hour before the first volcanic tremor, signalling that magma was at the Earth’s surface. The team recorded the last signal in their study on July 2, 2023, 40 minutes before the eruption, at a slow 1.5 newton-meters per second. From 2014 to 2023, other Jerk detections occurred between a few minutes and up to 8 hours before an eruption.

To further assess the strength of the Jerk signals, the team examined previous eruption records at Piton de la Fournaise. They found that for the 24 eruptions between 1998 and 2010, a Jerk alarm would have gone off 83% of the time. Of the 48 eruptions that occurred between 1998 and 2023, including the eruptions during their real-time tests, about 42 Jerk alarms would have occurred. However, they found that the Jerk signals were more accurate during their real-time analysis than they would have been for the eruptions 20 years earlier. 

Although the researchers successfully detected pre-eruption signals, they noted that the Jerk alarms occasionally arrived too late due to the data processing time, which takes at least 10 to 15 minutes. They reported 2 late alarms: one on June 11, 2019, and the other on February 10, 2020. Therefore, after 10 years of tracking the Jerk signals, the team evaluated their success rates at 22 successful alarms out of 24 eruptions, for a 92% positive rate. 

Before using the Jerk signals, many volcanologists struggled to predict the exact moment a volcano erupts. The team concluded that, in addition to the usual methods for detecting pre-eruption earthquakes, observatory scientists could now use Jerk signals to confidently notify authorities in advance of volcanic eruptions, so they can alert people living near volcanoes worldwide. 

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