After a group split, chimps killed their former friends

After the large Ngogo chimpanzee group in Kibale National Park, Uganda, split into two, individuals in one group attacked and killed more than 20 members of the other group—chimps who had been their former friends and allies.

Prior to its split, the Ngogo group was unusually large. Chimpanzee groups typically comprise about 50 members, according to John Mitani, professor emeritus of anthropology at the University of Michigan.

“…why did yesterday’s friend become today’s foe?”

When he first began observing the Ngogo group, there were well over 100 members. Over time, the group grew to about 200 individuals.

Mitani and Yale University professor David Watts started the Ngogo Chimpanzee Project in 1995.

From 1998 to 2014, the chimpanzees lived together in a single group. In 2015, aggression between individuals of two subgroups living in the center and west erupted, with members in each isolating themselves from each other. In 2016, the western group sent a territorial patrol to the central group, and the males fought. Then, in 2018, members of the western group killed a young adult male from the central group. After that event, individuals in the two groups separated and stopped interacting socially, spatially, and reproductively. Over the next seven years, members of the western group killed seven mature males and 17 infants.

Researchers have long known that chimpanzees will attack and kill their neighbors. But this finding, published in Science, was surprising because these chimpanzees were killing their former friends and allies, says Mitani, senior author of the study. For him, it highlights a key difference between chimpanzees and humans.

“Chimpanzees appear to consider outsiders as the enemy no matter who they are. One stark difference that exists between chimpanzees and humans is that we are an unusually prosocial and cooperative species,” Mitani says.

“We go out of our way to help and aid neighbors, some of whom may be total strangers.

“While aggression and wars break out among humans from time to time, for the most part, we live peaceably side-by-side with others now in a world of over 8 billion people. This difference between chimpanzees and humans is something that gives me hope, especially in this time of polarization.”

Why the split?

Several factors could have led to the 2018 split, Mitani says.

The group’s unusually large size is likely to have led to both increased feeding and reproductive competition. The deaths of several males in 2014 before aggressive interactions broke out in 2015 could have altered social dynamics within the group, creating hostilities that weren’t there previously. But none of these events in isolation explain the break to the researcher. In sum, a combination of factors most likely led to the split.

For Mitani, the split is difficult to come to grips with because for many years the Ngogo chimpanzees thrived due to their large group size. Previous studies found that they used their large numbers to work together collectively and cooperatively, benefiting in the process: They dominated their neighbors, took over areas previously occupied by those neighbors, gained more food, and obtained reproductive advantages.

“Given this, why did yesterday’s friend become today’s foe?” Mitani says. “It’s been hard to watch chimpanzees that I have studied for so long, know, and love turn on each other like this.”

Aaron Sandel, lead author of the study and anthropologist at the University of Texas, says that their findings may tell us something about the evolution of human warfare, challenging the hypothesis that human warfare, including civil war, is driven primarily by cultural markers of group identity such as ethnic or religious differences.

“In humans, we often attribute violent conflicts, including civil wars, to tensions that arise from ethnic, religious or political differences,” Sandel says. “We know this can’t be the case with chimps. They don’t have ethnicity or religion or political institutions. So this complex, violent conflict must be driven by more basic relational dynamics: Enduring social bonds, cliques, shifting alliances, rivalries.”

Lessons from data

Another unusual aspect of the split and its associated aggression is that the attacks and killings have been asymmetric, with members of the initially smaller group—the western group, with 76 members—attacking and killing members of the larger central group, which exited the split with 116 members. Typically, individuals in larger groups of chimpanzees use their numerical superiority to attack those in smaller groups. Members of the central group, however, failed to retaliate when the western chimpanzees started their killing spree.

“With these killings, the western group has flipped the tables on the central group,” Mitani says.

“At the outset of hostilities in 2015, the members of the smaller western group were quite afraid of the members of the larger central group, but something happened. They realized they could kill the central chimps and began doing so, to an obvious extreme.”

As of December 2025, the western group had 108 individuals while the central group’s numbers fell to 76.

“Findings like those in this paper are derived from long-term data collected over many, many years and have been supported by federal funds. I hope funds from our government will continue to be available for projects like this,” Mitani says.

“The Ngogo chimps have many more important and surprising stories to tell us.”

Additional coauthors are from the University of Michigan, the University of Utah and the Utah Natural History Museum, and Arizona State University.

Source: University of Michigan

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Primitive star could shed light on the dawn of the universe

On the fringes of the Milky Way, near a satellite galaxy called the Large Magellanic Cloud, researchers have discovered the most metal-poor, chemically primitive star ever found, according to new research.

Composed primarily of hydrogen and helium and containing less than 0.005% of the metals in the sun, the chemical makeup of the star SDSS J0715-7334 is the closest analog yet found to the first stars that formed in our universe.

“These pristine stars are windows into the dawn of stars and galaxies in the universe.”

Studying this low-mass, ultra-metal-poor star could help clarify astronomers’ ideas about this first generation of stars, called Population III stars, which astronomers cannot observe directly.

“No Population III stars have ever been observed, either because they were massive, lived fast and died young, or the lowest-mass Population III stars that could persist to the present day are extremely rare. Either way, the properties of this first stellar generation are some of the most important unknowns in modern astrophysics,” says coauthor Kevin Schlaufman, an associate professor of physics and astronomy at Johns Hopkins University.

Schlaufman originally identified SDSS J0715-7334 as a star of interest in 2014 for follow up as part of the current fifth generation of the Sloan Digital Sky Survey.

“While this star does not have a primordial composition itself, it is the closest astronomers have ever gotten to the Population III stellar generation on this particular metric,” he says.

SDSS J0715-7334 was formed from a gas cloud that had recently interacted with the material ejected by a Population III star’s supernova. Working backwards, astronomers can use the ratios of the elements in SDSS J0715-7334 to explore the mass of that Population III star and the energy of its supernova explosion.

“These pristine stars are windows into the dawn of stars and galaxies in the universe,” says first author Alexander Ji, an assistant professor of astronomy and astrophysics at University of Chicago.

A team of astronomers analyzed data gathered with the Magellan Clay Telescope and its high-resolution Magellan Inamori Kyocera Echelle spectrograph to determine that SDSS J0715-7334 is almost entirely hydrogen and helium with only trace amounts of carbon and iron.

The composition of SDSS J0715-7334 indicates that the Population III star that produced its carbon and iron was both unusually massive and exploded with uncommon vigor, the researchers say.

SDSS J0715-7334 is roughly 80,000 light years away in the vicinity of the Large Magellanic Cloud, the largest of the 100-200 small satellite galaxies that orbit the Milky Way. The Magellanic Clouds have only recently joined the Milky Way, and their long history of living alone has allowed them to ingest material from the cosmic web for a longer period than the Milky Way. Those conditions may have promoted the production of low-metallicity stars like SDSS J0715-7334.

“It’s possible that we’re going to find a relatively higher proportion of ultra-metal-poor stars in galaxies like the Magellanic Clouds than in our own Milky Way Galaxy,” Schlaufman says.

As part of the Sloan Digital Sky Survey, the researchers will continue to study the Milky Way’s formation and evolution, with Schlaufman leading an effort to study the oldest stars in the Milky Way.

“There is still lots to be done to understand what actually was going on in that era long, long ago when the Milky Way was young,” Schlaufman says. “We’ve only scratched the surface with this current phase of the Sloan Digital Sky Survey.”

Findings from the survey appear in the journal Nature Astronomy.

Additional coauthors are from the Harvard & Smithsonian Center for Astrophysics, the University of Chicago, the Max Planck Institute of Astronomy, Vanderbilt University, The Ohio State University, University of Florida, Monash University, Space Telescope Science Institute, Yale University, Universidad Católica del Norte, The University of Texas, Carnegie Institution for Science, Sorbonne Université, Heidelberg University, Eötvös Loránd University, Sean University of Illinois at Urbana-Champaign, Montana State University, the University of Colorado, and The Pennsylvania State University.

Support for the research came from from the National Science Foundation, Alfred P. Sloan Research Fellowship, Max Planck Society, European Research Council, NASA, Agence Nationale de la Recherche, Gruber Science Fellowship, ANID, Joint Committee ESO-Government of Chile, Hungarian Academy of Sciences, Kavli Institute for Cosmological Physics, UChicago Data Science Institute, and The University of Chicago.

Source: Johns Hopkins University

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City methane emissions are rising faster than estimated

Urban emissions of methane—a potent greenhouse gas—are rising faster than “bottom-up” accounting estimates anticipated, according to a new study.

The discrepancy was found with satellite measurements of methane over 92 major cities around the world. For 72 of the cities, there were sufficient data to track changes in methane emissions between 2019 and 2023. Overall, global urban methane emissions in 2023 were 6% higher than 2019 levels and 10% higher than 2020 levels, although they tended to decrease in European cities.

In contrast, accounting methods—which tally emission estimates of individual methane sources—suggest that urban methane emissions have only risen between 1.7% and 3.7% since 2020.

The study included over half of the C40 network, a group of 97 cities around the world aiming to reach net-zero emissions by 2050. Total methane emissions across all the studied C40 cities in 2023 were also 10% higher than 2020 levels, and the cities will have to contend with an extra 2 teragrams of methane emissions per year, which is about 30% of their emission reduction targets.

The gap between official estimates and satellite measurements warn that city policies designed with accounting estimates may not reduce methane emissions as desired.

“In order to reduce greenhouse gas emissions and set good emissions policy, cities need to know how much they are emitting and what those sources are. But there is quite a bit of uncertainty with that for methane,” says Eric Kort, corresponding author of the study in Proceedings of the National Academy of Sciences.

Kort advised the study’s lead author as a University of Michigan professor of climate and space sciences and engineering, and is now director of the atmospheric chemistry department at the Max Planck Institute for Chemistry.

The study continues Kort’s work identifying gaps in accounting of methane, which can enter the atmosphere from old or leaky natural gas infrastructure, landfills and wastewater treatment plants, and is 80 times more potent at warming the planet than carbon dioxide over a 20-year period.

With measurements from airplane surveys, Kort’s research group has shown that flaring at oil and gas production sites leaks 5 times more methane than previously estimated, and that the true climate impact of offshore oil and gas production is double the official estimates. The findings helped make flares an emissions-reduction target in the Inflation Reduction Act, leading to a $30 million Department of Energy call for new technology to reduce leaks from gas flaring.

In 2019, similar aerial measurements suggested that several large cities across the US were also emitting more methane than previously thought. The new study showed that this is a global problem.

“Cities have the motivation and power to reduce greenhouse gas emissions and therefore, present significant opportunities for impactful emissions reduction,” says Erica Whiting, a UM doctoral student in climate and space sciences and engineering and the study’s first author.

“However, there was not previously a method to quantify and monitor urban methane emissions around the globe and, therefore, no observation-based method to evaluate emission reduction strategies.”

The researchers’ global satellite measurements suggest that urban emissions accounted for 10% of all human methane emissions in 2023, and city methane emissions overall were nearly four times higher than the oil and gas “ultra emitters” that have been the focus of previous studies and emission policies.

The new findings come from the TROPOMI instrument, which was launched aboard the European Copernicus Sentinel-5 Precursor satellite in 2017 to track atmospheric pollution and climate change. TROPOMI measures the amount of sunlight reflected by the atmosphere back into space. It separately measures many wavelengths of light, each of which provides information on the concentration of a particular gas or pollutant, and it has sufficient spatial resolution to pinpoint individual cities.

TROPOMI’s resolution is too coarse to identify where exactly unreported methane is coming from within the city, however. The researchers think that higher-resolution measurements could help cities update their accounts and emission policies.

“We, and others in the field, are looking into higher-resolution satellite measurements so that we can tease apart the contribution of large localized sources,” Kort says.

“Those satellites can’t necessarily tell you the whole city’s emissions, but they could tell you what individual landfills or facilities are doing.”

Funding for this study came from NASA and the National Institute of Standards and Technology.

Source: University of Michigan

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‘Clean’ beauty products often have hidden hazards

Analysis reveals that in the absence of federal regulation, “clean” beauty labels often leave consumers guessing, particularly women of color.

As consumers increasingly pivot toward safer, non-toxic personal care routines, the “clean beauty” market has exploded. However, the new research suggests that for consumers with textured hair, the “clean” label may not always equal “chemical-free.”

“…’clean’ is often nothing more than a marketing term.”

In a new study that will appear in the Journal of Exposure Science and Environmental Epidemiology, researchers analyzed the landscape of products marketed as “clean” for textured hair (curly, coily, and wavy) at a major retailer.

The findings highlight a significant regulatory gap: despite retailer efforts to curate safer options, the lack of a standardized federal definition for “clean” means consumers must still navigate a complex and often opaque marketplace.

The study, led by the University of California, Santa Barbara’s Environmental Studies Program and Columbia University Mailman School of Public Health, in partnership with Black Women for Wellness and Silent Spring Institute, utilized a specific Target store in South Los Angeles as a case study. Researchers web-scraped ingredient lists for 150 hair products labeled as “Target Clean” to assess their safety profiles using the Environmental Working Group’s (EWG) Skin Deep database.

While retailers like Target are leaders in the sustainability space—investing millions in green chemistry and creating internal standards to restrict certain chemicals—the study indicates that voluntary retailer efforts cannot fully substitute for federal regulation.

“As we looked at general products, there was a large range from safe to extremely hazardous. We were hoping that the ‘clean’ products would lean toward the safer side, but we were surprised to see that the majority were still moderate hazards,” says lead author Joaquín Madrid Larrañaga, a researcher at UC Santa Barbara.

“It shows that ‘clean’ is often nothing more than a marketing term.”

The analysis revealed that even within the “clean” aisle, significant data gaps and potential hazards remain. Seventy percent of the products analyzed listed “fragrance” or “parfum” as an ingredient. This umbrella term can legally hide a mixture of undisclosed chemicals, some of which are linked to endocrine disruption and allergic reactions, due to “trade secret” protections. Only 41% of the products analyzed were found in the EWG database. Of those that were listed, more than 90% were classified as a “moderate” risk to human health (hazard scores between 3 and 6) rather than “low” risk.

While many products carried “free-from” claims (e.g., “sulfate-free”), inconsistent labeling practices were observed. For instance, while 14.6% of products contained sulfates, only roughly half of the products carried the retailer’s “Formulated without Sulfates” badge, leaving over one-third of products inconsistently labeled.

The study focuses on textured hair products because they are disproportionately used by women of color, who already bear a heavier burden of exposure to endocrine-disrupting chemicals. The researchers describe this as the “environmental injustice of beauty”—where interlocking systems of oppression lead to unequal chemical exposures.

“It’s a no-win situation for women of color, particularly Black women. In their desire to avoid using chemical relaxers, they might seek out ‘clean’ branded natural hair products that still expose them to toxic chemicals,” says coauthor Lariah Edwards, a researcher at Columbia University Mailman School of Public Health.

Community partners emphasize that this confusion creates an unfair burden on the consumer.

“It is deeply upsetting that even ‘clean’ beauty labels can offer a false sense of safety and Black women are forced to work so hard just to protect their health from toxic chemicals in everyday hair products,” says Janette Robinson-Flint, executive director of Black Women for Wellness.

“This study shows that we need policy change that meaningfully regulates cosmetics and personal care products with enforceable standards.”

The researchers emphasize that the findings are not an indictment of a single retailer, but a call for industry-wide reform.

“The burden of proof to show a chemical is harmful usually comes when someone gets sick, and that is the reverse incentive that we should have,” says senior author Bhavna Shamasunder, professor of environmental studies and chair in Racially Just, Resilient, and Sustainable City Futures at UC Santa Barbara.

“This isn’t necessarily a retailer issue; it’s a manufacturing and regulatory problem.”

Until federal regulations are standardized, the researchers suggest consumers look out for and avoid the following ingredients often found in hair products: fragrances and parfum, sulfates, parabens, and phthalates.

Additional coauthors are from UC Santa Barbara, the Columbia University Mailman School of Public Health, the Silent Spring Institute, and Black Women for Wellness.

This work was supported by the Rose Foundation Consumer Products Funding Board, the California Breast Cancer Research Program, the National Institutes of Environmental Health Sciences, the Passport Foundation, and the Forsythia Foundation.

Source: UC Santa Barbara

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AI leans on autism stereotypes when giving social advice

Users who disclose autism to artificial intelligence agents when seeking social advice raise complex questions about bias, stereotypes, and trustworthiness, according to a new study.

When people ask ChatGPT and other artificial intelligence models for advice, they often share deeply personal details in hopes of getting better answers: their age, their gender, their mental health history, even medical diagnoses like autism.

But the new research suggests those disclosures may change artificial intelligence (AI) models’ advice in ways that track closely with common stereotypes about people with autism.

Up to 70% of the time, AI discourages those with autism to avoid socializing. Some users disapproved of that in strong terms.

In April, second-year Virginia Tech computer science department doctoral student Caleb Wohn presented his paper at the Association for Computing Machinery’s Conference on Human Factors in Computing Systems, better known as CHI.

The research he led explored what happens when users with autism disclose their diagnosis to an AI model before asking for social advice. The findings raise difficult questions about whether AI is personalizing its responses, or if it’s giving biased advice that reinforces stereotypes.

“I was thinking about my experiences growing up with autism,” Wohn says. “It would have been very tempting for me, at certain times, to want to just be able to talk with something that’s not a person that seems objective and feel like I’m getting objective advice.”

But as a computer scientist, he worried that many users might not realize how much AI systems can change their answers based on identity-related information.

“For someone like me as a kid, or someone who isn’t in AI and doesn’t have all this technical knowledge, I wanted to know: How are its responses going to change if I disclose autism?” Caleb says.

The work builds on earlier research from the lab of Eugenia Rho, assistant professor of computer science, which found that autistic users frequently turn to AI tools for emotional support, interpersonal communication help, and social advice.

Other Virginia Tech researchers on the project include computer science PhD students Buse Carik and Xiaohan Ding and Associate Professor Sang Won Lee. Young-Ho Kim, a research scientist at the South Korea-based NAVER Corporation, also collaborated on the study.

This study comes at a critical moment, as more people use AI systems—technically called large language models (LLMs)—for highly personal decisions.

“People are really looking to personalize LLMs,” Rho says. “But if a user tells the model that they’re autistic, or a woman, or any other self-identification, what assumptions will it make?”

And how will those assumptions color its responses, and what impacts could that have on users?

To answer those questions, the team first identified 12 well-documented stereotypes associated with autism and created hundreds of decision-making scenarios around them. The researchers tested six major large language models, including GPT-4, Claude, Llama, Gemini, and DeepSeek, using thousands of scenarios where users requested advice—”Should I do A or B?”—about social scenarios, including events, confrontations, new experiences, and romantic relationships.

After generating 345,000 responses, they measured how advice shifted when users explicitly described themselves with stereotypical traits and when they simply disclosed that they were autistic. Researchers found that disclosing autism often shifted the models’ recommendations toward stereotypical assumptions about autistic people being introverted, obsessive, socially awkward, or uninterested in romance.

For example, one model recommended declining a social invitation nearly 75% of the time when autism was disclosed, compared with about 15% of the time when it was not. In dating scenarios, another model recommended avoiding romance or staying single nearly 70% of the time after autism disclosure, compared with roughly 50% when autism was not mentioned.

The results showed that 11 of the 12 stereotype cues significantly shifted model decisions across at least four of the six AI systems tested.

But the researchers did not stop with statistics.

The team interviewed 11 AI users with autism and showed them examples of how the models responded with and without autism disclosure. Some of them were shocked that the results showed how reliant on stereotypes the LLMs were in giving advice.

One exclaimed: “Are we writing an advice column for Spock here?”—invoking the iconic TV show Star Trek and its half-human, half-Vulcan character, who prioritized logic and reason over emotion. Others described it as restrictive, patronizing, or infantilizing, occasionally in pretty strong language.

But some participants says the more cautious, disclosure-based advice felt validating and supportive.

“One user’s bias could be another user’s personalization,” Rho says.

The same participant could react positively in one situation and negatively in another. That tension led the researchers to what they call a “safety-opportunity paradox.” Advice that feels protective to one user may feel limiting to another.

For Wohn, one of the most troubling discoveries was how difficult it can be for users to see these patterns in real time.

“AI is very good at seeming reliable,” he says. “Its responses are very clean and professional, and they sound right. But when you think about it being deployed systematically, when you think about the kind of systematic biases that are actually shaping its responses, that’s when it starts to get a lot more concerning.”

He compared the problem to AI-generated images.

“They look really clean and polished, and then when you look at the details, things fall apart,” Caleb says. “The surface gloss is beautiful, but looking deeper is getting harder and harder, because models are getting better at masking.”

Team members hope the research will encourage developers to build more transparent AI systems that give users greater control over how personal information shapes responses.

As one participant told the researchers: “I want to have control over how my identity is used.”

Source: Virginia Tech

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Brain stimulation improves PTSD symptoms

A study finds a targeted form of non-invasive brain stimulation can calm the brain’s fear center and significantly improve symptoms of post-traumatic stress disorder, with benefits lasting months after treatment.

Transcranial magnetic stimulation (TMS) is an FDA-approved treatment for several conditions including depression, though not for post-traumatic stress disorder (PTSD). It uses magnetic pulses to influence activity in specific brain regions.

PTSD has been linked to heightened activity in the amygdala, the brain region involved in processing fear.

In this clinical trial, investigators in the Emory University psychiatry and behavioral sciences department examined whether two weeks of low-frequency TMS could reduce amygdala reactivity to threat and improve PTSD symptoms. They used MRI scans to precisely identify where on the head to apply stimulation, allowing the treatment to be personalized for each participant.

Fifty adults with PTSD symptoms enrolled in the study, and 47 completed it. Most participants were recruited through the Grady Trauma Project, a large-scale clinical research program studying civilian trauma based at Grady Health System and the Emory University School of Medicine. Participants were randomly assigned to receive either active TMS or a placebo treatment in a blinded design so they would not know which treatment they received. MRI scans measured amygdala responses to threat before and after treatment.

The researchers found that active TMS reduced right amygdala reactivity to threat. Participants who received active TMS showed significant improvement in PTSD symptoms. Clinical benefit was observed after just two weeks of treatment and lasting at least six months, the full period examined in the study.

Seventy-four percent of individuals in the active TMS group experienced clinically meaningful symptom reduction.

“This study shows that we can directly target the brain circuits involved in PTSD and produce measurable changes in both brain function and symptoms,” says principal investigator Sanne van Rooij, PhD, associate professor of Psychiatry and Behavioral Sciences, Emory University School of Medicine.

“By using MRI to guide stimulation, we are moving toward more precise, individualized treatments that address the biology of the disorder.”

Unlike traditional talk therapy, TMS treatment does not require patients to recount traumatic experiences, which may reduce a barrier to care for some people. Participants reported changes in how they emotionally experienced their trauma, including improved management of nightmares. Some described the treatment as “life changing,” saying it “gave me back my life.”

According to the researchers, this is the first study to use MRI scans to individualize TMS for PTSD. By demonstrating a specific change in the amygdala, a region known to function differently in PTSD, they say the findings advance understanding of the neurobiology of recovery and suggest a new direction for treatment of PTSD locally, nationally, and internationally.

The findings appear in The American Journal of Psychiatry.

Additional contributors to the study are from Emory, Harvard Medical School, Wayne State University, and Dartmouth College and the National Center for PTSD.

The study was funded by the National Institutes of Health and the Brain and Behavior Research Foundation.

Source: Emory University

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Planets need more water for life than scientists thought

Unfortunately for science fiction fans, desert worlds outside our solar system are unlikely to host life, according to new research.

The new work shows that an Earth-sized planet needs at least 20 to 50% of the water in Earth’s oceans to maintain a critical natural cycle that keeps water on the surface.

“This has implications for a lot of the potentially habitable real estate out there.”

Scientists believe that there are billions of planets outside our solar system. More than 6,000 of these exoplanets are confirmed, but only some of them are candidates for life.

The search for life has focused on planets in the “habitable zone,” a sweet spot that is neither too close nor too far from a central star. Planets in this zone are considered viable because they can maintain liquid surface water.

“When you are searching for life in the broad landscape of the universe with limited resources, you have to filter out some planets,” says lead author Haskelle White-Gianella, a University of Washington doctoral student of Earth and space sciences.

Water, although essential, does not guarantee the existence of life. With this study, researchers worked to further narrow the search by investigating planets with just a small amount of water.

“We were interested in arid planets with very limited surface water inventory—far less than one Earth ocean. Many of these planets are in the habitable zone of their star, but we weren’t sure if they could actually be habitable,” White-Gianella says.

The team’s results in Planetary Science Journal show that habitability hinges on the geologic carbon cycle—a water-driven process that exchanges carbon between the atmosphere and interior over millions of years, stabilizing surface temperatures.

Carbon dioxide, which comes from volcanoes in a natural system, accumulates in the atmosphere before falling back to Earth dissolved in rainwater. Rain erodes and chemically reacts with rocks on the Earth’s surface and runoff transports carbon to the ocean, where it sinks to the seafloor. Plate tectonics drives carbon-rich oceanic plates below continental land. Millions of years later, carbon resurfaces as mountains form.

If water levels drop too low for rainfall, carbon removal—from weathering—can’t keep up with emissions from volcanic eruptions and carbon dioxide levels in the atmosphere spike, trapping water. Rising temperatures evaporate the remaining surface water, initiating runaway warming that makes the planet too hot to support life.

“So that unfortunately makes these arid planets within habitable zones unlikely to be good candidates for life,” White-Gianella says.

Although scientists have instruments that can measure surface water, rocky exoplanets are difficult to observe directly. In this study, the researchers ran a series of complex simulations to better understand how water might behave in these desert worlds.

Previous efforts to model the carbon cycle focused on cooler, perhaps wetter planets. The models factored in evaporation from sunlight, but didn’t include other drivers, such as wind. White-Gianella adapted existing models to drier planets by refining evaporation and precipitation estimates.

“These sophisticated, mechanistic models of the carbon cycle have emerged from people trying to understand how Earth’s thermostat has worked—or hasn’t—to regulate temperature through time,” says senior author Joshua Krissanen-Totton, a UW assistant professor of Earth and space sciences.

However, the function of the geologic carbon cycle on arid planets was largely unexplored. The results show that even planets that form with surface water could lose it, transitioning from potentially habitable to uninhabitable due to carbon cycle disruption.

One such planet exists far closer to home: Venus. The planet of love is roughly the same size as Earth, likely formed around the same time and may have started with a similar amount of water.

Yet today, the surface of Venus rivals the temperature of a wood-fired pizza oven. Standing on the surface would feel like being crushed by 10 blue whales, White-Gianella says.

Many theories attempt to explain why Earth and Venus are so different. White-Gianella and Krissanen-Totton propose that Venus, being closer to the sun, may have formed with slightly less water than Earth, which imbalanced the geologic carbon cycle. As surface temperatures rose with atmospheric carbon dioxide levels, Venus lost its water—and any life it may have hosted.

Upcoming missions to Venus will attempt to understand what happened to the planet and whether it ever hosted life. The findings could also offer insight into planets much farther away.

“It’s very unlikely that we will land something on the surface of an exoplanet in our lifetime, but Venus—our nextdoor neighbor—is arguably the best exoplanet analog,” White-Gianella says.

The researchers hope that results from future missions will help validate the results of their modeling.

“This has implications for a lot of the potentially habitable real estate out there,” Krissanen-Totton says.

This study was funded by the National Science Foundation, the NASA Astrobiology Program, and the Alfred P. Sloan Foundation.

Source: University of Washington

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