As our world is rapidly reshaped by climate change, glaciers have retreated and revealed new swaths of bare land. Throughout the coming decades to centuries, this rocky ground will become dappled with lichens and scrub, eventually giving rise to newborn forests in a process known as ecological succession. 

Ecologists have mapped out the stages of ecological succession for plant communities, observing which species are the first to colonize land and how these pioneer species promote secondary growth. Yet before any plants sink their roots into the soil, it is populated by thriving communities of single-celled microbes that prepare it for further habitation. Scientists study how these microbial communities arise to understand how healthy ecosystems develop.

Newly exposed land is nutrient-poor and subject to large temperature fluctuations, so the first species to settle there must overcome these challenges. Pioneer plant species are often habitat generalists, meaning they can thrive under a variety of environmental conditions. However, all plants convert water and sunlight into carbon and energy. Microbes can use many different energy sources, and often contain genes for multiple metabolisms in their genomes. Therefore, researchers wondered whether pioneer microbes could also be defined by their metabolic flexibility. 

A team of scientists based at Monash University in Australia tested this hypothesis by studying land left in the wake of 2 retreating glaciers: one on an island off the coast of Antarctica and one in the Swiss Alps. The researchers sampled soils along a path from the tip of the glacier outward, which had been exposed to the air for different amounts of time. By comparing the microbial communities within these soils, the researchers could track the different stages of ecological succession after glacial retreat.

The researchers extracted DNA from the soils and analyzed it using 2 sequencing methods. First, they sequenced a gene called 16S rRNA, which is like a microbial fingerprint for the different species present. They used this method to understand the diversity of these communities and track their species overlap, helping them to identify habitat generalists that thrived under different soil conditions. 

To understand the metabolic flexibility of these microbes, the researchers used a second method, known as metagenomics, which sequences all of the DNA in a sample rather than just a single gene. They used these data to reconstruct the entire genomes of microbes present in the soils, providing information on what kinds of metabolic activities they were capable of. The team also measured chemicals like ammonium and sulfide in the soils, as well as atmospheric gases like methane and carbon monoxide, to assess how the microbes used these compounds for growth.

The researchers found microbes inhabiting even the youngest soils, demonstrating the speed at which life takes hold in new environments. The abundance of microbes increased by approximately 8-fold in older soils, alongside a similar rise in species diversity, indicating that complex communities persisted over time. They also found the metabolic capabilities of microbes inhabiting Antarctic and Swiss glacial soils to be remarkably similar, suggesting common selective pressures drove the establishment of these new ecosystems.

They were surprised to discover that the most abundant microbes in younger soils were habitat specialists that were rare in older soils. These pioneer microbes, while still metabolically flexible, had adapted to utilize meager energy sources like atmospheric trace gases, including hydrogen, methane, and carbon monoxide. Many of these microbes could also derive energy from chemicals that dissolved out of rocks, like inorganic sulfur compounds. The researchers proposed that pioneer microbes could quickly take advantage of newly opened ecological niches, like soils exposed during a glacier’s retreat, because of their efficiency at using scant resources. 

They found that habitat generalists, on the other hand, tended to dominate older soils.  This result suggested that the habitat specialists were eventually outcompeted by the slow and steady growth of the habitat generalists in a real-life turtle-and-hare race.

The team concluded that using multiple growth strategies helps microbes adapt to new environments. However, they acknowledged that ecological succession could occur differently in other landscapes, such as in the aftermath of volcanic eruptions, meteorite impacts, or forest fires. They suggested that future researchers work to uncover how microbial communities lay the groundwork across these diverse ecosystems. 

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In 2011, miles of rock shifted deep underwater in the Japan Trench, causing an earthquake that deformed the seafloor and caused a devastating tsunami. Off the Eastern Coast of the Tōhoku region in Japan, a huge piece of the Earth’s crust carrying the Pacific Ocean, known as a tectonic plate, is forcing itself beneath Japan and into the Earth’s interior. Researchers think rock from this plate pushed against rock far beneath Japan, building pressure until it became too great. The lower plate slipped, spreading energy from the slip site and causing the earthquake. 

Plate slip can cause 2 types of outcomes. The first occurs kilometers deep in the Earth’s crust, causing earthquakes too small to trigger tsunamis. The second type causes extreme slip events that begin deep in the crust, like the 2011 event that extended into the Japan Trench and warped the seafloor. The moving seafloor displaces seawater, causing a tsunami. These events are referred to as slip-to-the-trench style earthquakes.

Researchers think this phenomenon is not unique to 2011, as Japan has a long history of tsunami-causing earthquakes. Charlotte Pizer and colleagues investigated sediment from the Japan Trench to unearth the geologic history of slip-to-the-trench style earthquakes.

In between earthquakes, Japanese islands continuously shed sediment that fills the trench, forming horizontal layers. Slip-to-the-trench earthquakes bend and fold these layers. The team hypothesized that if they found these folds in the Japan Trench and dated them, they could catalogue the record of slip-to-the-trench style earthquakes in the area.

Earthquakes like these occur repeatedly, meaning that younger ones can erase folds caused by older ones. To account for this overprinting, the researchers chose a study site within the Japan Trench about 100 kilometers (60 miles) north of where the most severe earthquakes occur. This site is only mildly deformed by slip-to-the-trench earthquakes since it’s so far from their source, making it easier for the team to identify individual events. 

Pizer and her group pieced together data collected from this site by previous researchers to reconstruct Japan’s earthquake history. They compiled 3 main types of data. Two of these were images of sediment layers in the trench constructed from reflections of vibrations sent into the ground, called seismic profiles. 

The first seismic profile captured the full trench, over 1 kilometer deep (about 0.6 miles), at 5-meter (16-feet) resolution. Using this method, any layers smaller than 5 meters thick won’t appear in the image. The second seismic profile captured only the top 40 meters (130 feet) of sediment, but could detect layers as thin as 10 centimeters (4 inches). 

The final type of data they used came from a 36-meter (120-foot) long cylinder of sediment extracted from the bottom of the trench, called a sediment core. Researchers in the past tied layers within this sediment core to historic earthquake events. They showed that it recorded 2 specific earthquakes in the area, the Kyotoku earthquake of 1454 CE, and the Jogan earthquake of 869 CE, both of which likely caused tsunamis. 

Pizer’s team could observe the depth of the Kyotoku and Jogan earthquake layers taken from the sediment core in their high-resolution seismic profile of the trench. In these high-resolution data, they noticed that deformation occurred in the sediment up to the layer marking the Jogan earthquake, but not above it, meaning deformation of the trench happened during this 869 CE event. 

The high-resolution data were only able to image sediments from recent earthquakes since 869 CE, but the low-resolution profile, which imaged the full trench, was able to capture the deeper, older record. When they looked deeper into the trench sediment, the researchers noticed that deformation from the 869 CE event had spread from where the tectonic plate is colliding with Japan. They saw at least 6 more similarly deformed layers, implying each was its own slip-to-the-trench event, although the dates of these events are unknown.

Pizer and colleagues concluded that slip-to-the-trench earthquakes are long-standing, common events in the Japan Trench. They hope future scientists will continue to research this site to better assess tsunami risks in Japan.

 

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Electric vehicles and other clean energy devices rely on batteries that use a metal called lithium. The expanded use of lithium has made lithium mining a rapidly growing industry. Lithium is most often found in volcanic rocks called pegmatites. Researchers have studied how much carbon and water pegmatite mining uses, but they don’t know how it affects local water quality. 

Pegmatite mining releases not only lithium but also other metals commonly found in pegmatite, such as rubidium and cesium. These trace metals are under-researched in terms of their environmental effects and possible human toxicity, though the EPA has linked high levels of lithium to adverse health effects in kidney function, neurological development, and thyroid function. As such, there’s currently no established safe level for lithium in drinking water, but the U.S. Geological Survey suggests a preliminary safety level of 10 micrograms per liter (μg/L). 

Researchers at Duke University recently tested how much pegmatite mining increased lithium levels in local waters, and how long those effects lingered after mining processes ended. To do so, they measured metal concentrations in waters downstream from 2 lithium mines and adjacent processing plants. They hypothesized that mining activities would increase interactions between rocks and the surrounding surface water and groundwater, impacting their lithium concentrations.

The researchers collected 99 water samples from surface streams and 93 samples from groundwater wells surrounding the Kings Mountain and Hallman Beam lithium mines, in a zone of about 40 kilometers (25 miles) along the border of South Carolina and North Carolina. The researchers took 51 surface water samples upstream of the mines to evaluate natural metal levels, and compared these with 48 downstream samples showing the mining-impacted metal levels. 

The researchers measured lithium and other trace elements, like rubidium, cesium, arsenic, and strontium, in the waters using an instrument called an inductively coupled plasma mass spectrometer. They found that lithium concentrations in the surface waters increased from a background of 0.2 to 79 μg/L to concentrations of 785 to 1,249 μg/L within 10 kilometers (6.2 miles) of the mines and processing facilities. The groundwater lithium levels were as high as 4,500 to 47,000 μg/L in the wells at the mines, but were not affected at downstream wells where lithium levels ranged from 0.5 to 890 μg/L. 

They suggested that lithium in the groundwater downstream from the mines came from natural interactions of the pegmatite rocks with the water, rather than from the mines themselves. This natural process was confirmed when the researchers noticed that lithium levels in the groundwater rose after rainfall, which caused more water-rock interaction.

The researchers also measured ions like calcium, sulfate, and chloride in the waters using a tool that can analyze compound molecules, called an ion chromatograph. They found that calcium and sulfate concentrations increased in surface waters within 10 kilometers (6.2 miles) downstream of the processing facilities. These downstream waters had 50 to 120 milligrams per liter (mg/L) of calcium and 100 to 300 mg/L of sulfate, compared to 5 to 20 mg/L of calcium and 3 to 10 mg/L of sulfate in the background surface waters. These ions are also byproducts of pegmatite processing, produced from a waste product made up of calcium sulfate, called gypsum. 

The team explained that active mining has been discontinued at this site for approximately 3 decades, meaning that the lithium concentrations they measured reflect the long-term release of lithium from inactive mines and mining waste. Drawing from historical data, they estimated that while the mines were active, they likely released 10 to 30 times the amount of trace metals they measured at the same location today. 

The researchers concluded that hard-rock processing impacts downstream metal and ion concentrations more than the mining itself. As lithium mining operations expand, the researchers suggested that future researchers examine lithium toxicity as well as the potential effects of its co-occurring metals, like rubidium and cesium. They also emphasized the need to find solutions for removing the trace metals and dissolved gypsum from water systems, or preventing them from leaking into the water systems to begin with.

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Brown rot is a common fungal disease in the Southeastern United States that affects stone fruits like peaches, cherries, and plums. Monilinia fructicola is a tan, fuzzy fungus that grows on tree flowers, twigs, and fruit, and is the most common cause of brown rot. Once brown rot infects a tree, the damage is irreversible, causing significant crop losses in commercial orchards. Farmers try to control the spread of M. fructicola by applying chemical sprays, called fungicides, to fruit trees in the spring.

In M. fructicola, a biosynthesis gene named MfCYP51 encodes a major protein critical to the fungi’s survival. Certain fungicides, called demethylation inhibitor (DMI) fungicides, stop M. fructicola from growing by targeting this protein. Over the last 20 years, DMI fungicides have become less effective against brown rot as M. fructicola becomes more resistant. 

Living microorganisms and their metabolites can control fungal diseases as an alternative to chemical fungicides, known as biofungicides. Many bacteria produce compounds like hydrogen cyanide and pyrrolnitrin that damage fungal cells. However, scientists have not found a biofungicide suitable for commercial production.​ A group of researchers at Clemson University in the USA and Huazhong Agricultural University in China set out to test whether the soil bacteria Pseudomonas chlororaphis and Bacillus subtilis could be effective biofungicides against brown rot. 

The researchers performed an incubation experiment to analyze how the fungal cells make their critical protein from the MfCYP51 gene, a process called gene expression, under different fungicide treatments. They used 3 M. fructicola strains sensitive to traditional DMI fungicides and 3 resistant strains. They tested these with 5 different fungicide treatments: a DMI fungicide, a mixture of P. chlororaphis metabolites, a mixture of living B. subtilis cells, a DMI fungicide + P. chlororaphis metabolites, and a DMI fungicide +  B. subtilis cells. They also set up a control treatment with sterile water instead of fungicide.  

After 6 hours, the researchers extracted the molecule that measures gene expression, called RNA, from the fungi. They found that both the P. chlororaphis treatment and the DMI fungicide + P. chlororaphis treatment substantially reduced MfCYP51 expression in both the sensitive and resistant isolates compared to the controls. In contrast, the DMI fungicide, B. subtilis, and DMI fungicide + B. subtilis treatments increased MfCYP51 expression in the resistant isolates. The researchers concluded that P. chlororaphis has a unique ability to reduce gene expression, unlike other biofungicides.

​To further investigate how the biofungicide treatments work, the team tested whether P. chlororaphis and B. subtilis produced the anti-fungal metabolite pyrrolnitrin. They added 1 milliliter of each treatment to a machine that separates and identifies liquid compounds using high pressure, called a high-performance liquid chromatograph. They found that the P. chlororaphis treatment contained pyrrolnitrin, so they hypothesized that it was responsible for reducing gene expression.

Additionally, the researchers tested their 5 treatments on brown rot in fruit. For each treatment, they took 10 Gala apples, washed and sterilized their surfaces, and sprayed them with the fungicides. After 24 hours, they poked holes in the apples with toothpicks and added 20 microliters of liquid containing M. fructicola cells to the poked holes. They placed the apples in a humid chamber for 5 days and measured the number and size of brown rot spots that developed on their surfaces. 

Despite decreasing MfCYP51 expression, ​the researchers found that P. chlororaphis treatment alone didn’t reduce brown rot disease compared to the control, but the DMI fungicide and B. subtilis treatments did. The mixed treatments of DMI fungicide + P. chlororaphis and DMI fungicide + B. subtilis both reduced brown rot disease compared to the control, but only the DMI fungicide + P. chlororaphis treatment prevented it. 

​The researchers concluded that although biofungicides may not be fully effective on their own, commercializing them could allow farmers to use less DMI fungicide. They explained that scaling back the use of DMI fungicides would slow M. fructicola resistance. Finally, they proposed that future researchers test biofungicide mixtures containing pyrrolnitrin in the field to observe real-world effects on stone fruit trees.

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Earth has many unique features for a planet, such as a magnetic field, a large moon, and plate tectonics. It’s also the only planet we know of that harbors life. These facts form the basis of the Rare Earth hypothesis, which posits that we haven’t found aliens because other planets in the Galaxy probably don’t have all the right conditions for life. 

Another characteristic of Earth is that about 30% of its surface is land and about 70% is ocean. Recently, Columbia University Assistant Professor David Kipping investigated whether the proportion of Earth’s surface covered by dry land versus ocean, or its land fraction, is another reason Earth is habitable not only for simple single-celled organisms, but also for intelligent species like humans. 

To test this hypothesis, Kipping created 4 statistical models of planets with different land fractions that intelligent aliens could potentially evolve on. First, he created an equation to describe the likelihood that a planet in its star’s habitable zone has a particular land fraction, known as a probability distribution. Kipping weighted this probability distribution toward the extreme ends, making it more likely that a planet would be covered by a single huge landmass or a single vast ocean than by a mix of both, as on Earth. 

Kipping then incorporated this land fraction probability distribution into his statistical models to calculate the probability that a random planet will have that land fraction and host intelligent life. The 4 scenarios Kipping tested were: 1) that intelligent life is more likely to emerge on land-dominated planets, 2) that it’s more likely to emerge on ocean-dominated planets, 3) that it’s more likely to emerge on planets with roughly equal amounts of land and ocean, and 4) that its emergence is independent of a planet’s land fraction. 

As a first step in determining the kinds of planets intelligent aliens would tend to emerge on, Kipping used each model to predict the probability that intelligent life would emerge on a planet with the same land fraction as Earth. He then compared these probabilities by calculating the ratios between each value. Because Earth is the only known planet with intelligent life, a model that predicted a greater probability for humanity’s existence on Earth would be more likely to reflect reality.

Kipping considered it strong evidence that a given model was more realistic than another if the ratio between 2 of them was greater than 10, meaning one model was 10 times more likely to predict the existence of Earth and humanity. Kipping found that no comparison of any 2 models passed this threshold. However, the models assuming that intelligent life prefers ocean-dominated planets or planets with a land-ocean balance were 2.5 and 3 times more likely to predict the existence of humanity than the model assuming that intelligent life prefers land-dominated planets. Additionally, the model assuming that intelligent life prefers a land-ocean balance was always more likely to predict humanity than any other model, though marginally. 

Kipping also addressed whether finding more planets with intelligent life would affect which model was deemed most realistic, for example, if scientists discovered conclusive evidence of life on Mars in its distant past. Here, Kipping identified 2 complications. First, it’s uncertain how much of Mars’s surface was once covered by water – some estimate it had a land fraction as high as 81%, while others estimate it was as low as 25%. Second, proving that Mars once had life would not prove it once had intelligent life.

Regardless, Kipping reran the models assuming that ancient Mars had a land fraction comparable to Earth’s. Adding this second data point produced ratios similar to those in the earlier Earth-only calculations, meaning it still didn’t make any single model 10 times more likely to predict the existence of humans and Martians, respectively. 

Kipping then took the 10-times threshold and reversed the calculations to find what conditions would exceed it. In doing so, he calculated that astronomers would need to find 14 other planets with intelligent life and known land fractions to robustly determine whether intelligent life is more likely to occur on desert planets, ocean planets, balanced planets, or without bias.

Kipping concluded that he can’t yet definitively state whether there is something special about Earth’s land fraction when it comes to producing intelligent species. However, Earth’s existence would suggest that intelligent life is unlikely to favor extreme desert planets, so the Milky Way probably isn’t filled with Tatooines and Jakkus. And while his analysis doesn’t debunk the Rare Earth hypothesis, it does undermine the argument that Earth’s ocean size explains why Earth is rare. 

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