Saturday, May 17, 2025

 

Scientists use fossils to assess the health of Florida’s largest remaining seagrass bed. Surprisingly, it’s doing well!



Florida Museum of Natural History
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Seagrasses stabilize sediment, reducing erosion and enhancing the accumulation of nutrient-rich biomatter. They’re so good at doing this that even though seagrass meadows cover only 0.2% of the ocean floor, they’re responsible for 50% of marine carbon burial.

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Credit: Ben Jones / Ocean Image Bank





The seagrass is greener along Florida’s Nature Coast … figuratively, that is. A new study published in the journal Marine Ecology Progress Series shows that seagrass ecosystems along the northern half of Florida’s Gulf Coast have remained relatively healthy and undisturbed for the last several thousand years.

This is not the case for most other seagrass ecosystems the world over, nearly 30% of which have disappeared since 1879. An estimated 7% of seagrass beds were lost each year between 1990 and 2009. Those that remain are generally not faring well, and the discovery of a healthy refugium is a rare event.

“Nothing is really pristine today, because humans have altered all of Earth’s environments, but this is about as good as it gets,” said Michal Kowalewski, senior author of the study and the Thompson chair of invertebrate paleontology at the Florida Museum of Natural History.

Figuring this out wasn’t easy, though. The extraordinary changes humans have made to the planet not only jeopardized the health of entire ecosystems, but they’ve also made it nearly impossible for us to know what a healthy ecosystem should look like in the first place.

“Most of the contemporary biological data we have postdates the Industrial Revolution,” Kowalewski said. “If you think about any type of real-time instrumentation that collects physical and chemical information about an environment, or if you think about the rigorous bio-inventory surveys, all of those things are from the last 50 to 100 years at most.”

In other words, humans have been altering their surroundings much longer than they’ve been systematically observing them. Fortunately, we aren’t the only thing that keeps a record of the past. The Earth does a pretty good job of it, too.

That’s the idea behind a relatively new branch of science called conservation paleobiology, which uses the most recent fossil record to reconstruct past ecosystems. For this method to work well, scientists need to analyze a large number of fossils, but there are only a few types of organisms that are preserved in sufficient quantities. Seagrasses, which are entirely composed of soft tissues that rapidly decompose after death, are not one of them.

This isn’t a hindrance to paleobiologists, though. Unlike modern grass lawns, which are ecologically barren and in which hardly anything lives but the grass itself, seagrass meadows are underwater oases for coastal marine organisms. This includes a variety of animals that produce hard shells, which are disproportionately represented in the fossil record. The shells of oysters, clams and other mollusks disintegrate so slowly that they stay around the ocean floor from hundreds to millions of years.

Kowalewski and his colleagues have previously conducted extensive research showing that the fossils of mollusks and other marine organisms with tough exteriors are so tightly connected and dependent on their environments that they can be used as a surrogate for species that don’t normally get preserved. If mollusks are doing well, it’s likely that everything else is too.

To find out if seagrass communities along Florida’s Nature Coast have recently degraded, the study authors sampled from 21 locations in six estuaries, from the mouth of the Steinhatchee River in the north to that of the Weeki Wache in the south. At each site, they used a long hose made from PVC pipe to suction up sections of the seafloor.

“We collect sediment samples while scuba diving, and then we sieve those samples and extract all that we find in it,” Kowalewski said. “The samples are dominated by dead material, because it has accumulated there over many centuries. Typically, for every live bivalve or snail, we find thousands of dead specimens.”

The odious task of counting and identifying the specimens took his team members several years to complete. Once they’d crunched the numbers, their results showed that mollusk diversity — and the health of seagrass meadows, by extension — hasn’t changed much over the last several millennia, including the most recent one in which humans have left their mark on even the most challenging and inhospitable environments.

“Only rarely do we find historical evidence that can make us optimistic about the current state of a local ecosystem,” Kowalewski said. “Most conservation paleobiology studies tell depressing stories about shrinking habitats, declining biodiversity and diminishing ecosystem services. For once, at least, this is not the case. What’s thrilling to me is we can show this system is still in very good condition, which makes it even more important to protect it.”

Establishing that the seagrass meadows found along the Nature Coast are relatively unchanged is also important because they can be now used with more confidence as a benchmark for assessing the state of heavily altered seagrass habitats and guiding their restoration.

Just 50 miles south of the study’s sampling area, seagrass communities haven’t been as lucky. Between 1950 and 1980, the city of Tampa’s population increased from about 125,000 people to 270,000. During that same period, 46% of seagrass meadows in Tampa Bay disappeared. Aggressive nutrient reduction efforts in the region led to water quality improvements and the recovery of seagrass in Tampa Bay between 1999 and 2018 — however, recent assessments have again shown significant reductions in seagrass followed by modest recoveries. On the opposite coast, a survey from 1999 indicated as much as 60% of seagrass coverage had been lost in a 56-mile stretch of the Indian River Lagoon.

These die-offs are primarily caused by nutrient pollution from inland farms and coastal cities. Plumes of single-celled microalgae and photosynthetic bacteria feast on excess nutrients and multiply in the water column, creating what are, in effect, marine clouds. This significantly reduces the amount of light that reaches the seafloor, which seagrasses don’t tolerate well.

The Nature Coast, which was designated an aquatic preserve in 2020, has largely avoided these challenges.

“There’s not a lot of development in those watersheds, particularly from the area around Weeki Wachee all the way up into the Panhandle, so the effects of excess nutrient delivery are not as pronounced as is in other places that have suffered as a consequence,” said study co-author Thomas Frazer, dean and professor of biological oceanography at the University of South Florida College of Marine Science.

The good news is, many of the meadows have since rebounded with the aid of pollution mitigation and habitat restoration efforts. But in many places across Florida, algal blooms are now an annual occurrence, and these will continue to have negative effects on seagrasses.

Climate change creates additional challenges, particularly for species along the Nature Coast. Though they’re doing well now, temperate and subtropical species are being pushed toward the planet’s poles by increasing global temperatures. But Florida species in Gulf waters can only migrate so far before they hit land.

“There’s nowhere for them to go,” Frazer said.

Backed up against the Panhandle, Florida’s Gulf Coast seagrasses will encounter marine climate refugees from further south. This has the potential to disrupt the tenuous balance within seagrass ecosystems. A single seagrass leaf can host a bazaar of tentacled hydroids, encrusting bryozoans, olive-shaped sea squirts, bacterial colonies and algal fuzz. In fact, as little as half of what you see when looking at seagrass is actual plant.

In a healthy seagrass meadow, these seagrass dwellers are kept in check by grazing fish and invertebrates, but as these ecosystems change along with the Earth’s climate, the continued diversity and existence of grazers is far from guaranteed.

“We’re already seeing range extensions of mobile fauna,” Frazer said. “A number of fishes, for example, are moving up north along the Gulf Coast, and they may either eat seagrass or consume grazers that help keep seagrasses clean of organisms that live on them.”

Seagrass ecosystems were around before the dinosaurs went extinct, and the consequences of losing something this old and diverse are not trivial.

In her 1955 book “The Edge of the Sea,” Rachel Carson wrote that “thrusting their roots into the sand and shifting coral debris, the seagrasses achieve a firmer attachment than the rootless algae do; where they grow thickly, they help to secure the offshore sands against the currents, as on the land the dune grasses hold the dry sands against the winds.”

Seagrasses stabilize sediment, reducing erosion and enhancing the accumulation of nutrient-rich biomatter. They’re so good at doing this that even though seagrass meadows cover only 0.2% of the ocean floor, they’re responsible for 50% of marine carbon burial.

All of these tightly packed resources attract animals. Sea turtles, manatees and fish eat seagrass, while countless other species make the meadows their home.

“They provide very important nursery habitat,” Frazer said. “In Florida alone, more than 80% of the fish caught by commercial fisherman and recreational anglers spend some part of their life history in those seagrass beds.”

Their deep roots and slender green tongues also protect coastal environments on land. Most seagrasses average only a foot or two in length, but a bunch of them together creates a substantial amount of drag. In near-shore environments, where the water is shallow, seagrasses can reduce wave energy by up to 40%.

“They’re a front line for storm protection,” Frazer said.

For now, that protection remains in place. Florida’s Nature Coast Aquatic Preserve has the largest seagrass bed in the Gulf. With good management, it may stay that way.

Louis Grimmelbein and Sahale Casebolt of the Florida Museum of Natural History and Savanna Barry, Katherine Cummings and Alexander Hyman of the University of Florida are also coauthors of the study.

 

Human activity reduces plant diversity hundreds of kilometres away



Nature has published the international study in which the Biodiversity and Evolution research group of the University of the Basque Country (UPV/EHU) was involved. Its authors describe the results as “alarming”



University of the Basque Country

Idoia Biurrunresearching during the pandemic 

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Idoia Biurrunresearching during the pandemic

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Credit: UPV/EHU





The study, in which the Biodiversity and Evolution Research Group of the UPV/EHU’s Faculty of Science and Technology participated, was carried out within the framework of the international DarkDivNet network and focused on nearly 5,500 locations in 119 regions across the world. In each location studied, the research teams analysed all the plant species present in different habitats to identify dark diversity. This innovative methodology for studying biodiversity made it possible to estimate the potential plant diversity in each study site and compare it with the plants actually present. 

The results reveal a hitherto unknown effect of human activities on biodiversity. In regions with little human impact, natural habitats contain on average one third of the potential species, mainly because not all the species can spread throughout the area naturally. By contrast, in regions with a high human impact, habitats tend to include only one fifth of the potential species. Traditional methods for estimating biodiversity, based on counting the number of species present without taking potential species into consideration, tend to underestimate the true effect of human impact.

The Gorbeia Nature Reserve

Based on the original idea of Professor Meelis Pärtel of the University of Tartu and lead author of the study, the DarkDivNet network was launched in 2018. Since then, research groups from all over the world have been gradually joining in order to gather samples in as many regions of the planet as possible. A case in point was the UPV/EHU’s scientific team formed by Idoia Biurrun-Galarraga and Juan Antonio Campos-Prieto, lecturers in the Botany section of the Department of Plant Biology and Ecology; they chose the Gorbeia Nature Reserve as the setting for sampling 55 study sites, targeting beech forests and moors as habitats. The work took five years to complete and had to contend with the COVID-19 pandemic and political crises in many countries within the network.

The degree of human impact in each region was measured using the Human Footprint Index, based on factors such as population density, changes in land use and infrastructure construction (roads). The study showed that the human footprint index negatively affects plant diversity in a locality within a radius of several hundred kilometres. The authors pointed out that the results “are alarming because they show that human disturbance exerts a much greater impact than initially thought, even reaching protected areas far from the source of human impact. Pollution, deforestation, overgrazing and forest fires can exclude plant species from their natural habitats, preventing them from recolonising”. The researchers also pointed out that “the negative influence of human activity was less pronounced when at least one third of a region's area remained well preserved, which supports the global goal of protecting 30% of the planet's surface”.

In conclusion, this study highlights the importance of maintaining healthy ecosystems beyond nature reserves and emphasises the concept of dark diversity as a useful tool for assessing the status of ecosystems undergoing restoration, identifying species that have a preference for a particular habitat but are not yet present in it.

Reference

Pärtel, M., R. Tamme, C. P. Carmona, K. Riibak, M. Moora, … I. Biurrun, … J.A. Campos,… and M. Zobel (2025) "Global impoverishment of natural vegetation revealed by dark diversity." Nature. DOI: https://www.nature.com/articles/s41586-025-08814-5

 

Navigating financial uncertainty: How AI nudges can curb overdraft costs



The Hebrew University of Jerusalem





A new study reveals that AI-powered email reminders can significantly reduce overdraft fees by helping users pay closer attention to their finances. The randomized field experiment, conducted with over 39,000 users of a personal finance app, found that simplified and strategically framed messages—especially those emphasizing loss avoidance—were the most effective. While users with higher income and credit scores were more likely to act on the alerts, the findings highlight both the potential and limitations of AI-based financial nudges. The research offers valuable insights into the intersection of behavioral finance, financial technology, and human decision-making.

A new study co-authored by Prof. Orly Sade, Dean of the Hebrew University Business School together with Daniel Ben-David and Ido Mintz from Intuit, demonstrates how artificial intelligence (AI) can help consumers avoid overdraft fees—potentially saving households millions in avoidable charges.
AI-driven financial tools are changing the way people manage their money, providing real-time support that goes beyond traditional budgeting. From predictive alerts that flag potential overdrafts to systems that automatically transfer funds to prevent shortfalls, these technologies offer practical solutions for everyday financial challenges. While they hold promise in helping users avoid unnecessary fees and build better habits, their impact depends on understanding what motivates individuals to use them and follow through on the guidance they provide.

Overdraft fees remain a costly burden for many. The researchers conducted a large-scale field experiment using data from over 39,000 users of Mint, a popular personal financial management platform in the U.S. and Canada. The goal was to test whether AI-generated reminders could reduce the likelihood of users overdrawing their bank accounts.

The AI system used in the study predicted when users were likely to incur overdraft fees and sent email reminders accordingly. These reminders varied in complexity and tone, allowing researchers to test both the impact of the alerts and the influence of message framing.

Key findings include:
•    Any reminder helped: Users who received an alert were less likely to incur overdraft charges.
•    Simplicity matters: Clear, concise messages were significantly more effective than complex ones.
•    Framing counts:
o    Messages framed negatively (e.g., “Avoid overdraft fees”) led to a 9% reduction in overdrafts the following week.
o    These users saved an average of $25 over four months.
o    Positively framed messages (“Save money”) also worked, but were slightly less effective.
•    Who responded best: Alerts were most effective for users with fair to good credit and mid-to-high incomes—those more able to act on the information.
•    Limits of nudging: Financially vulnerable users, such as those with low liquidity or maxed-out credit, were less able to benefit from the reminders, showing that behavioral nudges alone aren't always enough.

“Our study provides evidence that AI-based, tailored communication can positively influence financial behavior—but it must be accessible and actionable,” said Prof. Sade. “Simple, timely messages have the power to help people make better decisions, but we also need to consider broader systemic barriers for those in more challenging financial situations.”

This research contributes to the growing literature on human-computer interaction, digital nudging, and the use of AI for financial wellbeing. It also underscores the importance of designing interventions that are both behaviorally informed and grounded in real-world financial constraints.
The study demonstrates the potential of technology to improve lives when paired with behavioral insights—and raises important questions about how digital tools can be made more inclusive for those who need them most.
 

 

AI predicts bacterial resistance to cleaning agents



With the help of artificial intelligence and DNA decoding, a new method can predict how well disease-causing bacteria such as Listeria tolerate disinfectants. This research may become a valuable weapon in the fight against harmful bacteria.




Technical University of Denmark





A group of researchers, including scientists from the DTU National Food Institute, have developed a method that, with the help of artificial intelligence and DNA decoding, can predict how well disease-causing bacteria such as Listeria tolerate disinfectants. This research may become a valuable weapon in the fight against harmful bacteria in the food industry.

 

The study, published in Scientific Reports, a peer-reviewed journal from the Nature Portfolio, demonstrates that machine learning can be used to predict whether a bacterial strain will survive cleaning. The research paves the way for smarter hygiene strategies and faster responses when there is a risk of pathogenic bacteria being present in a food production.

The hidden threat in clean environments

Listeria monocytogenes is a foodborne bacterium that thrives in the cold and damp environments, that are often found in food processing facilities. One of the major challenges posed by listeria is its ability to form biofilms—a slimy layer that adheres to surfaces—which can, over time, lead to resistance against the disinfectants that are used to eliminate it. Until now, detecting this resistance has required time-consuming laboratory tests.

“The danger lies in the fact that a surface may appear clean, yet resistant bacteria can still be hiding in cracks and corners,” says senior researcher at the DTU National Food Institute Pimlapas Shinny Leekitcharoenphon.

DNA and AI— a powerful duo

In the study, researchers analysed the entire genome of over 1,600 listeria strains. These DNA profiles were used to train a machine learning model that learned to identify genetic patterns associated with resistance to disinfectants commonly used in the food industry.

Three different disinfectants were tested: two pure chemical compounds—benzalkonium chloride (BC) and didecyldimethylammonium chloride (DDAC)—as well as a commercial product, Mida San 360 OM.

“It’s like teaching a computer to read the bacteria’s manual, and then letting it tell us whether the bacterium is likely to survive cleaning with a particular disinfectant,” says Pimlapas Shinny Leekitcharoenphon.

The AI model achieved an accuracy of up to 97% and was able to predict tolerance to both the pure chemical substances and the commercial product.

“It is promising that the models work not only for the pure chemical substances, but also for a product that is actually used in the food industry. This suggests that the method could be applied in real-world settings,” says Pimlapas Shinny Leekitcharoenphon.

In addition to known resistance genes, the researchers also discovered several new genes that may play a role in the bacteria’s ability to survive disinfectants. This improves the predictive power of the model and may provide new insights into how bacteria develop and spread resistance.

Do we need new disinfectants?

The researchers suggest that their method can initially help the food industry use existing disinfectants more efficiently—by selecting the right product for the right bacterium based on its DNA profile.

“AI does not provide us with a recipe for new disinfectants, but it does tell us which bacteria are likely to survive which chemicals. This enables swift and precise action,” says Pimlapas Shinny Leekitcharoenphon. “

At the same time, the discovery of new resistance genes may inspire the future development of improved disinfectants that exploit the bacteria’s vulnerabilities.

A breakthrough for food safety

Testing bacterial resistance in the laboratory can take days. This method shows that, with DNA data and machine learning, accurate predictions can be made in minutes. When pathogenic bacteria emerge in a food production facility, it is crucial to act swiftly to prevent the spread of disease.

“We hope our method will become a valuable tool in the fight against disease-coursing bacteria and contribute to making food production even safer,” says Pimlapas Shinny Leekitcharoenphon.

The current standard for cleaning in the food industry is not based on genome sequencing, and, as with any other new technology, it will take time to incorporate a new method.

‘We have just received funding to continue the work, and the goal of the research is for the method to be easily usable by employees in a food production site,” says Pimlapas Shinny Leekitcharoenphon.

About the research

Original title of the scientific article: Quantitative prediction of disinfectant tolerance in Listeria monocytogenes using whole genome sequencing and machine learning | Scientific Reports 

Published in Scientific Reports, Nature Portfolio. Authors: Gmeiner A et al. (2025).

DOI: 10.1038/s41598-025-94321-6 

The research was funded by Karl Pedersen og Hustrus Industrifond (DI-2019-07020), the Danish Dairy Research Foundation, the Milk Levy Fund, and Arla Foods.

 

Researchers virtually freeze time to capture clear images of fast-spinning objects



Technique enables continuous monitoring of components like turbine and jet engine blades, which could help detect early signs of wear or damage



Optica

Experimental results 

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To demonstrate the system, the researchers showed that it could reconstruct real-time high-quality still images of a model jet engine rotating at about ∼2170 rpm (top images) and a CPU cooling fan rotating at ~14,700 rounds per minute (bottom images).

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Credit: Zibang Zhang, Jinan University in China




WASHINGTON — Researchers have developed a real-time imaging system that can capture images of fast-spinning objects over long durations. Real-time monitoring of rotating parts such as the turbine blades used in power plants or the fan blades of jet engines is critical for detecting early signs of damage — such as wear or cracks — helping prevent serious failures and reducing maintenance needs.

“Capturing clear images of fast-spinning objects is challenging because they tend to blur or look grainy,” said research team member Zibang Zhang from Jinan University in China. “Although high-speed cameras can help, they’re expensive and can’t be used for long periods. Our method overcomes this challenge by virtually freezing time by exploiting the repetitiveness of the object’s motion.”

In the Optica Publishing Group journal Optics Letters, the researchers describe their new imaging system, which is based on a single-pixel detector. They show that it can capture images of an object spinning at around 14,700 rounds per minute (rpm).

“The system could detect wear or cracks that can develop in high-speed metal cutting and grinding tools over time — without stopping the machines — improving safety and extending the equipment’s lifespan,” said Zhang. “In the future, this technology could be integrated into smart manufacturing systems, aircraft maintenance platforms or even home appliances like car engines, blenders, fans, air conditioners and hard drives, making these devices smarter and safer.”

Freezing time

Imaging fast-spinning objects is not an easy task for conventional imaging techniques because rotation leads to severe motion blur. Although reducing exposure time can ease the problem, this tends to create noisy images because fewer photons are captured. High-speed cameras can also be used to capture fast-spinning objects but are prohibitively expensive and cannot be used continuously over long time periods.

As part of a project aimed at developing an optical system for online engine inspection, the researchers developed a new system that overcomes many of the challenges of imaging fast-spinning objects by using structured illumination and single-pixel detection. This imaging approach projects patterned light onto a scene and captures the resulting intensity variations with a single-pixel detector, allowing a computer to reconstruct a detailed image without needing a traditional camera sensor. Single-pixel detectors are photodiodes with only one pixel available. Compared to traditional camera sensors, single-pixel detectors have higher sensitivity, a wider dynamic range and faster response, making them suitable for imaging fast-spinning objects.

“The key to the method is synchronization, which essentially freezes time by keeping the target object stationary compared to the pattern projection,” explained Zhang. “By using synchronized illumination, we converted a dynamic imaging problem into a static imaging problem.”

The imaging system captures clear images of rotating objects by aligning with their repetitive motion. This is much like painting a sunrise over several days, where each time the sun rises, the artist paints a small part of the scene. Even though the sun moves continuously it is possible to capture the whole picture by setting an alarm to sync with the sun's daily return.

Capturing a spinning object

For the imaging setup, the researchers used a high-speed projector — specifically, a digital micromirror device enabling projection speeds of up to 22,000 Hz — to illuminate the rotating object with a series of patterns. The single-pixel detector acquires a measurement for each pattern projection. Once the object spins around once, the projector switches to the next pattern.

To synchronize the projection, the researchers “set an alarm clock” by aiming a laser at one blade of the spinning object, creating backscattered pulses. When the number of pulses matches the number of blades, it signals the projector to switch patterns — like setting off the alarm — allowing clear imaging of the rotating object using just a single-pixel detector.

To demonstrate the system, the researchers showed that it could reconstruct real-time high-quality still images of a model jet engine 11 cm in diameter rotating at about ∼2170 rpm and a CPU cooling fan rotating at ~14,700 rounds per minute. The researchers said that the method, which requires no prior knowledge about an object, can also be used to image objects with unstable rotation speed.

Next, the researchers plan to improve the system’s portability and make it easier to integrate into a real aircraft engine.

Paper: S. Long, Z. Zhang, M. Yao, Z. Wu, C. Li, J. Zhong, “Single-pixel real-time monitoring system for a high-speed rotating object,” Opt. Lett., 50, 3449-3452 (2025).
DOI: 10.1364/OL.555872

Credit

Zibang Zhang, Jinan University in China

 

Conservatives privately support several firearm policies, but don’t publicly demand them



A Rutgers Health study highlights that conservatives who support firearm policies are no less likely than liberals to believe their peers support those same policies



Rutgers University





Surveys have repeatedly shown bipartisan support for a number of firearm policies, including universal background checks. Despite this private support, there is little public demand by conservatives that such policies be enacted on the state or federal level.

A study, conducted by the New Jersey Gun Violence Research Center at Rutgers University and appearing in Preventive Medicine Reports, asked whether the gap between private support and public demand could be explained by a sense among conservatives that their community may alienate them if they publicly vocalize their support. But the researchers found that the answer is no.

“It might simply be that while many conservatives support these policies, they simply are not as high of a priority for them as they are for more liberal individuals,” said Michael Anestis, executive director of the New Jersey Gun Violence Research Center and lead author of the study

Rutgers Health researchers examined this question in a representative sample in mid-2023 of 7,529 adults from nine states: New Jersey, Pennsylvania, Ohio, Minnesota, Florida, Mississippi, Texas, Colorado and Washington.

The authors assessed nine different policies: licensing laws, universal background checks, extreme risk protection orders, secure storage laws, assault weapons bans, high-capacity magazine bans, allowing teachers to carry firearms at school, allowing individuals to carry firearms publicly without a permit and tax incentives for purchasing firearm locks. Overall, 32% of the sample identified as conservative, 40.4% as moderate and 27.6% as liberal.

Three policies were supported by a majority of members of all political groups: licensing (70.1% of conservatives, 77.4% of moderates, 94.3% of liberals), universal background checks (86% of conservatives, 87.2% of moderates, 96.1% of liberals) and extreme risk protection orders (64.5% of conservatives, 75.3% of moderates, 90.8% of liberals). Another, secure storage laws, nearly did so as well (49.7% of conservatives, 66.8% of moderates, 84.6% of liberals). All remaining policies demonstrated substantial partisan differences in levels of support.                               

“Consistent with prior research and public polls, our findings demonstrate that the majority of Americans support a range of firearm policies,” Anestis said. “The issue is that more conservative communities tend to support these policies in private, but not demand them in public.”

What stood out as surprising to the authors was that conservatives who supported various firearm policies were no less likely than moderate or liberal supporters to believe that their peers support those same policies as strongly as they do. Given this, the data doesn’t support the notion that the lack of public conservative support for these policies is explained by conservative fears of alienating their communities.

“In the meantime, defeating these policies is an enormous priority for firearm lobbyists and, because of this, the only pressure felt by conservative elected officials comes from individuals with a financial interest in preventing these policies from passing,” Anestis said.