The study, published in the Personality and Social Psychology Bulletin, assessed 767 people over three times in May 2020. The researchers took a mixed-method approach that allowed them to look at several indicators of well-being while also asking people in an open-ended question to reflect on the role of pets from their point of view. Pet owners reported that pets made them happy. They claimed pets helped them feel more positive emotions and provided affection and companionship. They also reported negative aspects of pet ownership like being worried about their pet’s well-being and having their pets interfere with working remotely.

However, when their happiness was compared to nonpet owners, the data showed no difference in the well-being of pet owners and nonpet owners over time. The researchers found that it did not matter what type of pet was owned, how many pets were owned or how close they were with their pet. The personalities of the owners were not a factor.

“People say that pets make them happy, but when we actually measure happiness, that doesn’t appear to be the case,” said William Chopik, an associate professor in MSU’s Department of Psychology and co-author of the study. “People see friends as lonely or wanting companionship, and they recommend getting a pet. But it’s unlikely that it’ll be as transformative as people think.”

The researchers explored several reasons why there is not a difference between the well-being of pet owners and nonpet owners. One of them being that nonpet owners may have filled their lives with a variety of other things that make them happy.

In late September of this year, flash-flooding surged down neighborhood streets and subway stairways in New York City, as a historic rainfall led to canceled flights and closed roads and city officials urged people to stay at home or shelter in place. Some areas of the city saw up to 2.58 inches of rain in one day, nearly 50% more than the city sewer system’s maximum capacity, causing wastewater problems for many low-lying homes and businesses.

Intuitively, when an extreme weather event hits a city, the more residents it has, the larger number of people are affected. Currently, 83% of the United States population lives in urban settings, according to the U.S. Census. This number is expected to grow over the coming decades, rendering urban climate resilience extraordinarily important. As a result, many people have the impression that the growing sizes of cities are making weather extremes worse for the people who live there.

However, cities are designed and built by people. So, it stands to reason that if some methods of land development increase population exposures to extreme weather conditions, others might hold the potential to moderate or even reduce population exposures as the climate changes over the coming decades.

To explore this idea, University of Delaware researcher Jing Gao, assistant professor in the College of Earth, Ocean and Environment and a resident faculty member in the Data Science Institute, and colleague Melissa Bukovsky, associate professor in the Haub School of Environment and Natural Resources at the University of Wyoming, investigated how changes in urban land and population will affect future populations’ exposures to weather extremes under climate conditions at the end of the 21st century.

The researchers looked at urban areas across the continental United States, including cities large and small, with various development densities and in different climate regions. They used a data-driven model developed by Gao to predict how urban areas across the country will grow by 2100, based on development trends observed over the past 40 years. The research team considered how these urban land changes might affect weather extremes like heat waves, cold waves, heavy rainfalls and severe thunderstorms. They then analyzed how many people would be exposed to these extremes under different climate and urban development conditions at the end of the century.

The research team’s simulations showed that at the end of the 21st century, how a city is laid out or organized spatially, often called an urban land pattern, has the potential to reduce population exposures to future weather extremes, even for heat waves under very high urban expansion rates. Further, how the urban landscape is designed — meaning how buildings are clustered or dispersed and how they fit into the surrounding environment — seem to matter more than simply the size of a city. This is true even while climate change is increasing population exposures.

These findings apply to all cities, from large metropolitan areas like New York City to smaller towns in more rural contexts, such as Newark, Delaware.

“Regardless of the size of a city, well planned urban land patterns can reduce population exposures to weather extremes,” Gao said. “In other words, cities large and small can reduce their risks caused by weather extremes by better arranging their land developments.”

These findings differ from current common perceptions. For example, existing literature in this area has almost exclusively focused on limiting the amount of urban land development, Gao said.

In contrast, the new findings from this research encourage researchers and practitioners from a wide range of related fields to reconsider how cities are designed and built so that they can be in harmony with their regional natural surroundings and more resilient to potential climate risks over the long run.

Gao likened the effects of climate change and urban land patterns on extreme weather risks to the effects of a person’s diet and activity level on their risk for health problems. Properly designed urban land patterns, she said, are like physical exercises that work to counteract poor dietary choices, contributing to a reduced risk for disease, while helping a person become more fit in general.

“Carefully designed urban land patterns cannot completely erase increased population exposures to weather extremes resulting from climate change, but it can generate a meaningful reduction of the increase in risks,” Gao said.

And the cost to start is small, Gao said. No extravagant measure, such as leveling and rebuilding a large area at once, is required.

“Instead, when building new and renovating existing parts of a city, we should adjust our mindset to consider how the new development and renovation will change the way the city as a whole situates in its natural surroundings, and how the city and its surrounds can be one integrated human-environment system at large scales over the long run,” Gao said. “The key is to start adjusting how we think about development now.”

Next steps in the work

The researchers are working to identify specific characteristics about the spatial arrangement of a city that can make it more — or less — resilient to future weather extremes. Identifying these patterns can help guide development that is more sustainable in the face of increasing instances of extreme weather. Through their efforts, the research team hopes to provide actionable suggestions for how to design and build urban areas that reduce their residents’ exposures to weather extremes in the long run.

Importantly, the researchers emphasized that these characteristics will likely vary from region to region, now and as climate changes. For instance, what works in arid Phoenix, Arizona, will probably differ from what will work in humid New Orleans, Louisiana. Likewise, what might work today for a city could differ from what will work in the future, as climate conditions evolve.

“Eventually, we want our work to be directly useful to urban design and planning efforts, offering insights and tools for decision makers to influence long-term social and environmental well-being at scale,” Bukovsky said. “First, though, we need to identify what development patterns can improve various cities’ long-term climate resilience. We will continue collaborating in the future.”

Although previous researchers have collected water and microbial samples from the cave entrances and easily accessible sinkholes, the Northwestern-led team reached the deep, dark passageways of unlit waters to better understand what can survive inside this unique underground realm.

After analyzing the samples, the researchers noted a system rich with diversity, organized into distinct patterns. Similar to a stereotypical high school lunchroom, microbial communities within the cave system tend to cluster into well-defined cliques. But one family of bacteria (Comamonadaceae) acted as a popular social butterfly — appearing at nearly two-thirds of the “cafeteria tables.” The findings hint that Comamonadaceae is the ecological linchpin of the broader community.

The research was published late last week (Nov. 2) in the journal Applied and Environmental Microbiology.

“This is certainly the most expansive microbial survey across this part of the world,” said Northwestern’s Magdalena R. Osburn, who led the study. “These are incredibly special samples of underground rivers that are particularly difficult to obtain. From those samples, we were able to sequence the genes from microbial populations that live in these sites. This underground river system provides drinking water for millions of people. So, whatever happens with the microbial communities there has the potential to be felt by humans.”

A geobiology expert, Osburn is an associate professor of Earth and planetary sciences at Northwestern’s Weinberg College of Arts and Sciences. Northwestern alumnus Matthew Selensky led this project as a part of his dissertation when he was a graduate student in Osburn’s laboratory. Study co-author Patricia Beddows,professor of Earth and planetary sciences at Weinberg, led the cave-diving expedition and leveraged her decades of experience working on these caves. Other Northwestern co-authors include Andrew Jacobson, professor of Earth and planetary sciences, and former graduate student Karyn DeFranco, who focused on the geochemistry.

Located primarily in southeastern Mexico, the extensive Yucatán carbonate aquifer is pockmarked by numerous sinkholes leading to a complex web of underwater caves. Hosting a diverse, yet understudied microbiome, the underwater network contains areas of freshwater, seawater and mixtures of both. The system also includes a variety of zones — from pitch-black, deep pits with no direct openings to the surface to shallower sinkholes sparkling with sunlight.

“The Yucatan platform is essentially a Swiss cheese of cave conduits,” Osburn said. “We were curious which microbes are found together when we look across the whole system versus which microbes are found within one ‘neighborhood.'”

To explore this question, a team of cave divers collected 78 water samples from 12 individual sites within the cave system near the Caribbean coast in Quintana Roo, Mexico. The sample collection spanned from the Xunaan Ha system at the north end to inland and coastal portions of the Sac Actun system (including a distinctive, 60-meter-deep pit) to the Ox Bel Ha system to the south.

Back in a dive-shop-turned-science lab, researchers filtered cells out of each sample and analyzed its chemistry. Next, back at Northwestern, they identified microbial communities by sequencing their DNA. Then, Selensky developed a new computational program to perform network analysis on the data set. The resulting networks showed which species tend to live together. For each site, the researchers considered the environmental context of each microbial community, including cave type (pit or conduit), cave system, distance from the Caribbean coast, geochemistry and position in the water column.

Although water from the Gulf of Mexico flows into the Yucatán aquifer, the aquifer’s microbiome varies substantially from the nearby sea, the researchers found. The microbiomes also vary throughout the cave system — from cave to cave and from shallow water to deep water.

“The microbial communities form distinct niches,” Osburn said. “There is a varying cast of characters that seem to move around, depending on where you look. But when you look across the whole data set, there’s a core set of organisms that seem to be performing key roles in each ecosystem.”

Osburn and her team found that Comamonadaceae, a family of bacteria typically found in groundwater systems, lived in several niches. They also discovered that a deep, pit-like sinkhole with a surface opening (allowing sunlight to spill in) housed the most microbial communities — segregated into layers of distinct niches throughout the water column.

“It seems that Comamonadaceae performs slightly different roles in different parts of the aquifer, but it’s always performing a major role,” Osburn said. “Depending on the region, it has a different partner. Comamonadaceaeand its partners probably have some mutualistic metabolism, maybe sharing food.”

Most T cells only work in the person who made them. Your T cells fight threats by responding to molecular fragments that belong to a pathogen — but only when these molecules are bound with markers that come from your own tissues. Your influenza-fighting T cells can’t help your neighbor, and vice versa.

“However, we all have T cells that do not obey these rules,” says LJI Professor and President Emeritus Mitchell Kronenberg, Ph.D. “One of these cell types is mucosal-associated invariant T (MAIT) cells.”

Now Kronenberg and his LJI colleagues have uncovered another MAIT cell superpower: MAIT cells can recognize the same markers whether they come from humans or mice. Kronenberg calls this finding “astounding.” “Humans diverged from mice in evolution 60 million years ago,” he says.

This new research, published in Science Immunology, sheds light on the genes and nutrients that give MAIT cells their fighting power. The findings are an important step toward one day harnessing these cells to treat infectious diseases and improve cancer immunotherapies.

“Because MAIT cells are the same across individuals, they could more easily be used in cell therapies, where, in principle, my MAIT cells could be given to you,” says Kronenberg.

The new study also opens the door to exploiting MAIT cells to improve cellular therapies. “If we could make normal T cells more like MAIT cells, maybe we could make them act faster and more vigorously to combat any type of infection or cancer,” says study co-first author Gabriel Ascui, a UC San Diego graduate student in LJI’s Kronenberg Lab.

Why MAIT cells are special

Kronenberg was initially interested in MAIT cells because of their unexpected response speed. Typical T cells need a few days to develop in the thymus and only adapt to fighting new threats after leaving the thymus — and after several days of stimulation from a pathogen. MAIT cells are much faster because they can respond to more generic markers of infection, rather than hunting for very specific tissue-type markers. For MAIT cells, a red flag is a red flag, no matter who is waving it.

This broad specificity makes MAIT cells similar to the immune system’s first-responder cells, such as macrophages and neutrophils, which make up the “innate” immune system. “MAIT cells have this ‘innate-like’ characteristic,” says Ascui. “They’re like your first line of defense.” In fact, MAIT cells tend to gather in tissues like the lungs and intestines, where the body is under constant threat from airborne and foodborne pathogens.

The new study shows that MAIT cells don’t just recognize a range of markers within one person. Instead, these odd T cells can “see” markers shared between humans — and even between species. Scientists call these kinds of shared markers “conserved.” There has been no reason for the markers to change over the eons, so they remain the same across related species.

But just because these MAIT cells look the same between species, doesn’t mean they fight pathogens — or make energy — in exactly the same ways.

Why look at mouse cells?

Comparing human and mouse MAIT cells is important for guiding future studies where mice can serve as useful animal models to study exactly how these cells combat pathogens.

Kronenberg, Ascui, and their colleagues used single-cell sequencing and other tools to compare differences in gene expression pathways between human and mouse MAIT cells. The scientists found that mice have two different kinds of MAIT cells, which produce different inflammatory molecules, called cytokines. One kind of MAIT cell, which the scientists call MAIT1, produces a lot of a cytokine called interferon-gamma. The other kind of the MAIT cell, called MAIT 17, produces a lot of a cytokine called interleukin-17.

A recent Nature Cell Biology study from the Kronenberg Lab, co-led by LJI Instructor and Immunometabolism Core Director Tom Riffelmacher, Ph.D., shows that after a bacterial infection, MAIT1 and MAIT17 cells persist but become super-charged, or capable of having greater protective function for months. These cytokines help the MAIT cells take aim at different threats. MAIT1 cells target viruses such as influenza, while MAIT17 cells are better at targeting bacteria.

In the new study, the team found that MAIT cells from both species are more capable of taking up and storing fat, compared with typical T cells. This finding suggests MAIT cells are more dependent on this nutrient for energy. This discovery is also in line with previous work in the Kronenberg Lab showing that some MAIT cells depend on fat to fight pathogens. The key difference between the species was that human MAIT cells can produce interferon-gamma and IL-17, but not evidently by separate cell populations.

When mice live like us

The scientists needed to know — was this difference in human and mouse MAIT cells linked to genetic differences or to our different habitats? Lab mice, such as those cared for at LJI, are housed in ultra-clean vivariums. Their food is blasted in an autoclave to kill pathogens, and their water, toys, and cages are kept as sterile as possible.

Kronenberg and Ascui were curious — do mice living in less-controlled environments show differences in MAIT cell function? The team collaborated with UC San Diego scientists to study MAIT cells from mice kept in so-called “dirty” or less sterile conditions, similar to a pet store environment. Their research suggests MAIT cells from these mice have even more in common with human MAIT cells, especially when it came to having more MAIT1 cells, which produced more interferon-gamma than lab mouse MAIT1 cells.

“Pet stores aren’t dirty in the conventional sense,” says Kronenberg. “But part of the idea is that the ‘dirty’ mice are living in an environment — with more microbes and immune system challenges — that’s a little closer to human environments.”

The team also compared MAIT cells found in different parts of the body, such as the blood, thymus (where T cells, including MAIT cells, develop), and the lung and spleen (where MAIT cells camp out). They discovered that MAIT cells still in the thymus look very similar between humans and mice (“dirty” or not); however, MAIT cells from the lungs and blood are more different between humans and lab mice.

MAIT cells from the “dirty” mice fell between the two groups, adding to the evidence that more natural-like environments change how MAIT cells develop and learn to target disease.

“Environmental, as well as genetic differences, shape the species differences in these cells,” says Kronenberg.

What does this mean for clinical research?

The new study gives scientists a sort of answer key, a list of genetic signatures to tell MAIT cells apart depending on the species and tissues they come from. Going forward, the team is interested in whether they can prompt typical T cells to express similar genetic signatures.

“If we could make normal cells more ‘innate,’ like MAIT cells, perhaps we could improve T cell therapy for cancer,” says Ascui. “That’s one avenue we’re looking at.”

Kronenberg is also interested in whether scientists can modify MAIT cells to actually decrease levels of IL-17 in the body. Although IL17 helps fight infections, some T cells produce IL-17 against the wrong targets, triggering harmful inflammation and even autoimmune disease.

“There are cases where IL-17 can be a bad actor,” says Kronenberg. “So although there are cases where we might want to induce more MAIT17 cells, expand their population, but we’d also like to find ways to prevent them from arising in situations where they might not be what we want.”

Additional authors of the study, “Transcriptomes and metabolism define mouse and human MAIT cell populations,” include co-first authors Shilpi Chandra and Thomas Riffelmacher, and Ashu Chawla, Ciro Ramírez-Suástegui, Viankail C. Castelan, Gregory Seumois, Hayley Simon, Mallory P. Murray, Goo-Young Seo, Ashmitaa L. R. Premlal, Benjamin Schmiedel, Greet Verstichel, Yingcong Li, Chia-Hao Lin, Jason Greenbaum, John Lamberti, Raghav Murthy, John Nigro, Hilde Cheroutre, Christian H. Ottensmeier, Stephen M. Hedrick, Li-Fan Lu, and Pandurangan Vijayanand.

“I’m hopeful that policymakers will rely on this work as motivation and support for the scale-up of beneficial fire as a key strategy in preventing wildfire catastrophes,” said study co-author Michael Wara, director of the Climate and Energy Policy Program at the Stanford Woods Institute for the Environment. “Beneficial fire is not without its own risks — but what our study shows is just how large and long-lasting the benefits are of this crucial risk reduction strategy.”

Significant risk reduction

The study, which focused on California, comes almost exactly five years after the state suffered its deadliest wildfire on record, the Camp Fire. Hotter weather and a history of fire suppression have allowed the build up of tinder-dry trees and brush, which fuel increasingly destructive wildfires. It wasn’t always that way. For millennia, Indigenous people allowed wildfires to burn, and intentionally applied fire to the land for reasons ranging from ceremony to subsistence. As a result, pre-colonial forests across California contained less fuel for hungry flames and were better able to retain moisture — keys to fire and drought resilience.

It’s no secret that wildfire-prone regions need to shift from a single-minded focus on suppression to one that includes much more controlled burning and forest resilience. Previous Stanford-led research has shown that California alone needs fuel treatments — whether prescribed burns or vegetation thinning — on about 80,000 square kilometers or nearly 20% of the state’s land area.

However, until now, studies assessing the beneficial effects of prescribed and low-intensity fires have been limited to relatively small areas, such as a single wilderness area or watershed. For this paper, the researchers reviewed 20 years of satellite monitoring of wildfires across more than 100,000 square kilometers of California forests.

The team — fire policy experts, public health scientists, and statistical and machine learning researchers — harmonized multiple state-wide datasets on fuel characteristics and fire behavior, including fire intensity (measured by the amount of energy released) and fire severity (measured by the ecosystem impacts of large fires). Previous studies have shown that prescribed fires and unplanned low-intensity wildfires have similar risk-reduction effects. Both remove surface fuels and smaller diameter trees, thereby helping forests achieve a more fire-resilient mix of trees and preventing fires from growing too intense. Both also leave tree canopies intact due to relatively low flame heights.

The authors measured the protective effect of low-intensity fires using a method that assembled unburned areas into a synthetic landscape closely resembling the burned landscapes’ attributes, such as weather patterns, elevation, vegetation type, and disturbance history. This approach allowed them to assess how these burned landscapes might have evolved had they not burned in that same year — and compare these counterfactuals to their actual evolution throughout time.

Using this approach, the researchers were able to quantify the reduced risk of high-intensity fires after a low-intensity fire burns in a forestland, and then see how long the protective effect lasts. They found that low-intensity fire in mixed conifer forests in California initially provides a 60% reduction in risk of catastrophic fire, and this effect lasts at least six years but diminishes over time. They also found a smaller but still significant reduction in risk in oak-dominated forests.

Good timing

Policymakers could use the study’s results as a foundation for future evaluation of wildland fuel treatments by comparing the quantified benefits to potential costs and risks associated with its implementation. The timing is good: The U.S. Forest Service has proposed treating nearly 200,000 square kilometers (about 50 million acres) over the next decade through a mixture of fuel treatment strategies. California has proposed increasing the amount of land it treats for wildfires to 2,000 square kilometers (about 500,000 acres) annually.

To be effective, wildland fuel treatments, including prescribed burning, have to be ongoing, periodic maintenance rather than a one-time intervention for forests that are adjacent to communities or critical infrastructure, the researchers write. The risk mitigation benefit of low-intensity burning will depend heavily on careful selection and targeting of the intervention to provide maximum protection for people, communities, and ecosystems.

“This study exemplifies how data science can contribute to climate mitigation through a highly multidisciplinary collaboration,” said study lead author Xiao Wu, an assistant professor of biostatistics at Columbia University who worked on the paper as a Data Science Fellow at Stanford. “Wildfires present substantial threats to both our ecosystems and human well-being. As scientists, our constant goal is to find practical solutions.”

Wara is also senior director of policy for the Sustainability Accelerator at the Stanford Doerr School of Sustainability.

Coauthors of the study include Erik Sverdrup, a postdoctoral scholar in Stanford’s Graduate School of Business; Michael Mastrandrea, associate director of policy at the Sustainability Accelerator, research director of the Climate and Energy Policy Program and a senior research scholar at the Stanford Woods Institute for the Environment; and Stefan Wager, an associate professor of operations, information and technology in Stanford’s Graduate School of Business and an associate professor of statistics (by courtesy) in Stanford’s School of Humanities and Sciences.

The study was funded by Stanford Data Science and the National Institutes of Health.

In a new Science Advances publication, the JILA team — along with collaborators from universities in Sweden, Greece, and Germany — probed the spin dynamics within a special material known as a Heusler compound: a mixture of metals that behaves like a single magnetic material. For this study, the researchers utilized a compound of cobalt, manganese, and gallium, which behaved as a conductor for electrons whose spins were aligned upwards and as an insulator for electrons whose spins were aligned downwards.

Using a form of light called extreme ultraviolet high-harmonic generation (EUV HHG) as a probe, the researchers could track the re-orientations of the spins inside the compound after exciting it with a femtosecond laser, which caused the sample to change its magnetic properties. The key to accurately interpreting the spin re-orientations was the ability to tune the color of the EUV HHG probe light.

“In the past, people haven’t done this color tuning of HHG,” explained co-first author and JILA graduate student Sinéad Ryan. “Usually, scientists only measured the signal at a few different colors, maybe one or two per magnetic element at most.” In a monumental first, the JILA team tuned their EUV HHG light probe across the magnetic resonances of each element within the compound to track the spin changes with a precision down to femtoseconds (a quadrillionth of a second).

“On top of that, we also changed the laser excitation fluence, so we were changing how much power we used to manipulate the spins,” Ryan elaborated, highlighting that that step was also an experimental first for this type of research.

Along with their novel approach, the researchers collaborated with theorist and co-first author Mohamed Elhanoty of Uppsala University, who visited JILA, to compare theoretical models of spin changes to their experimental data. Their results showed strong correspondence between data and theory. “We felt that we’d set a new standard with the agreement between the theory and the experiment,” added Ryan.

Fine Tuning Light Energy

To dive into the spin dynamics of their Heusler compound, the researchers brought an innovative tool to the table: extreme ultraviolet high-harmonic probes. To produce the probes, the researchers focused 800-nanometer laser light into a tube filled with neon gas, where the laser’s electric field pulled the electrons away from their atoms and then pushed them back. When the electrons snapped back, they acted like rubber bands released after being stretched, creating purple bursts of light at a higher frequency (and energy) than the laser that kicked them out. Ryan tuned these bursts to resonate with the energies of the cobalt and the manganese within the sample, measuring element-specific spin dynamics and magnetic behaviors within the material that the team could further manipulate.

A Competition of Spin Effects

From their experiment, the researchers found that by tuning the power of the excitation laser and the color (or the photon energy) of their HHG probe, they could determine which spin effects were dominant at different times within their compound. They compared their measurements to a complex computational model called time-dependent density functional theory (TD-DFT). This model predicts how a cloud of electrons in a material will evolve from moment to moment when exposed to various inputs.

Using the TD-DFT framework, Elhanoty found agreement between the model and the experimental data due to three competing spin effects within the Heusler compound. “What he found in the theory was that the spin flips were quite dominant on early timescales, and then the spin transfers became more dominant,” explained Ryan. “Then, as time progressed, more de-magnetization effects take over, and the sample de-magnetizes.”

The phenomena of spin flips happen within one element in the sample as the spins shift their orientation from up to down and vice versa. In contrast, spin transfers happen within multiple elements, in this case, the cobalt and manganese, as they transfer spins between each other, causing each material to become more or less magnetic as time progresses.

Understanding which effects were dominant at which energy levels and times allowed the researchers to understand better how spins could be manipulated to give materials more powerful magnetic and electronic properties.

“There’s this concept of spintronics, which takes the electronics that we currently have, and instead of using only the electron’s charge, we also use the electron’s spin,” elaborated Ryan. “So, spintronics also have a magnetic component. The reason to use spin instead of electronic charge is that it could create devices with less resistance and less thermal heating, making devices faster and more efficient.”

From their work with Elhanoty and their other collaborators, the JILA team gained a deeper insight into spin dynamics within Heusler compounds. Ryan said: “It was really rewarding to see such a good agreement with the theory and experiment when it came from this really close and productive collaboration as well.” The JILA researchers are hopeful to continue this collaboration in studying other compounds to understand better how light can be used to manipulate spin patterns.