More than just larks and owls!

Research team led by Göttingen University use AI to discover when different forest birds sing

University of Göttingen

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The green woodpecker (Picus viridis) can be heard particularly frequently in the forest in the mornings from mid-March to April.

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Credit: David Singer

Everyone knows that if you want to enjoy the full experience of the dawn chorus in the forests of Central Europe, or carry out scientific research on bird species, you have to get up very early in the morning. Until now however, detailed data about daily and seasonal patterns in birdsong have only been available for a few species, as the observations required are time-consuming. A research team from the University of Göttingen and the Northwest German Forest Research Institute has now, for the first time, analysed the song and calls of 53 European forest bird species during a breeding season with the help of artificial intelligence. They were able to show that singing behaviour recorded with automatic audio recorders differs from previous expert knowledge. The findings were published in the Journal of Ornithology.

 

The researchers collected data at 256 forest locations in Lower Saxony in Germany. They recorded bird calls with small audio recorders around the clock for 30 seconds every 10 minutes from March to May. They then used AI to identify the bird species based on their calls and songs. The researchers checked the AI's suggestions to ensure that only reliable identifications of species were included in the analysis.

 

High-resolution analysis of a total of 6.4 million recorded sounds revealed that forest bird species have individual patterns of activity. “Our data show that there are far more activity types among forest bird species than just ‘larks’ and ‘owls’,” explains David Singer, lead author of the study and PhD student in Forest Nature Conservation at the University of Göttingen. In addition to a large group of species who are active during the hours of daylight, some species – such as blackbirds and woodcocks – were active around dawn and twilight and could in fact be heard twice a day. Blackbirds were also heard significantly more often in the evening than in the morning, a result that had not shown up in previous bird counts. There were also subgroups within the group of species active in the day. While many species of tit and the black woodpecker were most active in early spring and were heard significantly less from the end of April onwards, species such as the dunnock and the wren became active in April. Nocturnal species were in their own group, as were migratory birds, which do not arrive in Central Europe until May.

 

The researchers then went on to compare their results with previous recommendations for methods to carry out surveys of breeding birds. They were able to demonstrate that the recommended times to carry out surveys for many species often did not even overlap with their phases of peak song activity. For example, it was previously assumed that the great spotted woodpecker could be easily detected throughout the morning. However, according to the latest data, this species is significantly less likely to be heard around two hours after sunrise than shortly after sunrise. For other typical forest bird species such as the blue tit and the chiffchaff, song activity remained high beyond the recommended recording period in the morning, meaning that these species can still be reliably counted later in the day.

 

“By combining traditional methods of counting birds with the new AI-supported methods of analysing birdsong, we can significantly improve our knowledge and understanding of bird behaviour,” says Göttingen University forest ecologist Professor Andreas Schuldt, who jointly supervised the work. “In particular, measurements of species with short peaks of activity are improved by this new method.” For example, grey-headed and lesser spotted woodpeckers, which can only be heard during a relatively short time window, can be recorded particularly well with the new method, whereas ornithologists would be very lucky indeed to observe these species.

 

Working together with the Dachverband Deutscher Avifaunisten (DDA), the results of the study have already been incorporated into the latest edition of the book “Methodenstandards zur Erfassung der Brutvögel Deutschlands” (Methodological Standards for Recording Breeding Birds in Germany), so that strategies for carrying out research on birds can be better planned in future. A comparable evaluation for bird species in agricultural landscapes will be possible in the future thanks to ongoing research projects.

 

The study is part of the biodiversity monitoring programme of the Nordwestdeutsche Forstliche Versuchsanstalt together with the University of Göttingen’s Forest Nature Conservation, and Conservation Biology research groups. Information on the project (in German): www.nw-fva.de/wir/aktuelles/pm-biodiversitaetsmonitoring.

 

Original publication: D Singer et al “Diel and seasonal vocal activity patterns revealed by passive acoustic monitoring suggest expert recommendations for breeding bird surveys need adjustment.” Journal of Ornithology (2025). DoI: 10.1007/s10336-025-02307-y

 

Small audio recording devices were used to record bird songs in the forest around the clock.

Credit

David Singer

Journal

Journal of Ornithology

DOI

10.1007/s10336-025-02307-y 

Method of Research

Observational study

Subject of Research

Not applicable

Article Title

Diel and seasonal vocal activity patterns revealed by passive acoustic monitoring suggest expert recommendations for breeding bird surveys need adjustment.

Article Publication Date

19-Jul-2025

 

Collaboration rewarded for work to further deployment of batteries in emerging economies

Swansea University

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From left to right: Dr Darren Ould, Dr Marcin Orzech, Dr Sajad Kiani, and Dr Ashley Willow of Swansea University, alongside Dr Emma Freeman, Dr Brent De Boode, and Dr Dan Jones from Batri Ltd — key members of the collaborative team driving the innovative StamiNa project forward.

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Credit: StamiNa projec

Technology developed at Swansea University has won funding to help deliver better battery systems to Sub-Saharan Africa.

The StamiNa – Sustainable Transport and Affordable Mobility through Innovation in Na-ion technology project—led by Swansea University in partnership with Coventry University, Batri Ltd, Strathmore University (Kenya), AceOn Group, and Federal University of Technology Owerri (Nigeria)—is one of five collaborations to receive valuable investment from the Faraday Institution.

The projects all seek to optimise and validate battery systems to maximise performance and improve efficiency and lifetime. In doing so, they will advance the technologies a step closer to commercialisation.

This investment is the second phase of the Ayrton Challenge on Energy Storage (ACES) R&D programme, which the Faraday Institution is leading.

StamiNa is led by Professor Serena Margadonna, Chair in Materials Engineering at Swansea University, and it aims to demonstrate and validate a new sodium-ion battery (SIB) technology through a prototype swappable battery pack designed for e-mobility applications in East Africa.

Professor Margadonna said: “We’re proud to lead the StamiNa project, which brings together state-of-the-art sodium-ion battery technology developed at Swansea University with a shared vision for sustainable, equitable innovation.

“This collaboration goes beyond technology advances—it’s about delivering environmentally responsible, locally sourced solutions that are accessible to all. Together, we aim to accelerate commercialisation while supporting the growth of an African-led battery ecosystem with a local supply chain.”

SIBs could offer an alternative to lithium iron phosphate (LFP) batteries for the transition to electric mobility in Sub-Saharan Africa – they are easier to transport and do not have the same supply chain vulnerabilities.

In collaboration, Batri Ltd and Swansea University have developed a SIB technology employing Prussian White cathodes and coal-derived hard carbon anodes with a predicted energy density that exceeds commercially available SIBs, making it competitive with LFP.

Unlike alternatives, Prussian White is synthesised in water under mild conditions and is free of nickel and cobalt. This enables an energy-efficient production process that significantly reduces environmental impact and opens the potential to establish local supply chains.

The StamiNa project aims to:

• Optimise and scale up the production of the two active materials;
• Refine electrode fabrication and cell assembly processes and manufacture multilayer pouch cells and 18650 cylindrical cells at Coventry University;
• Demonstrate and validate cell performance in real-world applications. Cylindrical cells will be integrated into AceOn’s swappable battery pack and battery management system and field testing will be conducted on e-bikes at Strathmore University (Kenya);
• Evaluate pack performance at FUTO (Nigeria) and compare data with LFP and commercially available SIB alternatives; and,
• Evaluate cost, supply chain feasibility, recyclability, and sustainability of the SIB technology for the Sub-Saharan e-mobility market.

This project seeks to accelerate the commercialisation of UK SIB technology and establish a sustainable, African-led energy storage ecosystem that supports clean mobility and broader electrification efforts.

 

Scientists will use a $1M grant to build a support system addressing sea level rise and flooding in South Florida

University of Florida

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A team of University of Florida scientists has been awarded a $1 million grant from the National Science Foundation to tackle one of South Florida’s most urgent environmental threats: groundwater flooding and saltwater intrusion caused by sea level rise.

During the three-year project, scientists on a multidisciplinary team at UF’s Institute of Food and Agricultural Sciences (UF/IFAS), will develop a decision-support system to help local leaders make science-based, cost-effective choices about land use, infrastructure, climate adaptation and flooding mitigation.

“This is about getting ahead of the problem,” said Young Gu Her, an associate professor of hydrology and water resources engineering at the UF/IFAS Tropical Research and Education Center and leader of the project. “We aim to empower local governments with clear options that reflect both environmental and community realities before today’s risks become tomorrow’s emergencies.”

The highly specialized team brings expertise in urban stormwater management (Eban Bean), biochemistry (Ashley Smith), agroecology (Zachary Brym) and food and resource economics (Edward Evans). Together, they’ll explore how nature-based strategies can reduce flood risk and protect groundwater, alongside traditional infrastructure such as canals and seawalls. Examples of these nature-based strategies include mangrove restoration and natural or semi-natural systems known as green infrastructures such as rain gardens, porous pavement and cisterns that use vegetation, soils and landscape features to manage water and provide environmental and community benefits,

Southeast Florida is especially vulnerable due to its flat topography, porous limestone bedrock and a century of development that left the region with a naturally high groundwater table. Saltwater intrusion is already threatening freshwater supplies and farmland.

“Saltwater intrusion isn’t just a future concern—it’s already happening,” said Her. “Because of our geology, elevation and development patterns, our region is on the frontlines. It’s not just a science problem—it’s a people, food and land problem.”

What sets this project apart is its emphasis on real-world application. The decision-support system will be co-developed with local governments and will include groundwater simulations, sea level and climate projections, as well as detailed economic trade-off analysis.

“Unlike many academic models that remain theoretical, our approach brings together groundwater and soil sciences, ecology, economics, policy and community voices into a single, practical decision-support tool,” said Her.

The tool will allow users to test “what-if” scenarios to see how different investments, such as restoring wetlands versus expanding stormwater systems, perform under future conditions.

Critically, the team will also address a key tension in coastal water management: the mitigation of groundwater flooding that may come at the cost of increased saltwater intrusion, and vice versa. The tool will help identify optimal strategies that strike a balance or trade-off between the two, ensuring that solutions in one area do not inadvertently create new risks elsewhere.

“Mangroves act like coastal shields,” said Her. “They reduce storm surge and help prevent saltwater from pushing into freshwater. Meanwhile, wetlands and green spaces absorb excess water and recharge the aquifer. These solutions can be more affordable than hard infrastructure, and they build long-term resilience.”

Economic modeling will guide local governments in choosing strategies that offer the best return on investment.

“Economics helps communities make smart, cost-effective choices,” said Her. “We calculate how much each option reduces risk, what it costs and how it performs over time.”

The project runs from September 2025 through August 2028 and includes opportunities for community engagement, public input and local planning integration. While focused on Southeast Florida, the team expects the framework to be useful in other vulnerable coastal areas across the U.S. and beyond.

 

Inhaled agricultural dust disrupts gut health

UC Riverside study highlights need for protective measures for agricultural workers

University of California - Riverside

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RIVERSIDE, Calif. -- Inhaling agricultural dust may pose significant risks to gut health for workers in animal agriculture, a University of California, Riverside, study has found. 

Led by Declan McCole, a professor of biomedical sciences in the UCR School of Medicine, the study expands on prior findings that hog farm dust causes airway inflammation. The researchers now report in the Journal of Applied Toxicology that inhaling this dust also alters the gut microbiome and impairs intestinal function, including increased “leaky gut” or intestinal permeability. Leaky gut is associated with a range of chronic diseases, including inflammatory bowel disease, celiac disease, and type 1 diabetes.

“Exposure to swine farm dust, which contains high levels of bacteria and endotoxins, caused both airway inflammation and increased passage of gut bacterial products into the bloodstream in our mouse models,” said Meli’sa Crawford, a former postdoctoral researcher in McCole’s lab and the paper’s first author. “But what’s especially striking is the impact we observed on the gut microbiome and metabolism.”

The researchers exposed mice intranasally to hog dust extract for three weeks. The mice showed a significant drop in beneficial bacterial species, including Akkermansia muciniphila, Clostridium sp. ASF356, and Lachnospiraceae bacterium. 

The research team also found decreased levels of critical compounds in the gut of the mice, such as riboflavin, nicotinic acid, inosine, and leucine — key players in energy metabolism, immune regulation, and gut barrier maintenance.

“While most research has focused on the respiratory effects of farm dust, our findings clearly show that inhaled pollutants can have systemic consequences,” McCole said. “This research underscores the importance of considering the gut–lung axis when assessing the health risks of bioaerosol exposure in agriculture.”

The study builds on growing evidence that pollution from concentrated animal feeding operations can impact multiple organ systems. 

“Agricultural dust is rich in fine particulate matter and resistant bacteria, presenting a complex threat to farmworkers’ health,” McCole said. “Our earlier work showed that inhaled hog dust extract leads to neutrophilic lung inflammation. We now show the link to intestinal barrier dysfunction and microbial imbalance, highlighting the need for improved workplace protections for agricultural workers to mitigate long-term health consequences.”

The study was supported by grants from the National Institutes of Health; University of California, Davis-Western Center for Agricultural Health and Safety; and University of California Presidential Postdoctoral Fellowship Program. Crawford is now an assistant professor in the Department of Animal Sciences at Rutgers University in New Jersey.

The title of the research paper is “Respiratory Exposure to Agriculture Dust Extract Alters Gut Commensal Species and Key Metabolites in Mice.”

The University of California, Riverside is a doctoral research university, a living laboratory for groundbreaking exploration of issues critical to Inland Southern California, the state and communities around the world. Reflecting California's diverse culture, UCR's enrollment is more than 26,000 students. The campus opened a medical school in 2013 and has reached the heart of the Coachella Valley by way of the UCR Palm Desert Center. The campus has an annual impact of more than $2.7 billion on the U.S. economy. To learn more, visit www.ucr.edu.

 

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Journal

Journal of Applied Toxicology

DOI

10.1002/jat.4808 

Method of Research

Experimental study

Subject of Research

Animals

Article Title

Respiratory Exposure to Agriculture Dust Extract Alters Gut Commensal Species and Key Metabolites in Mice

 

Machine learning reveals historical seismic events in the Yellowstone caldera

Researchers detect, designate 10 times more earthquakes than previously recorded

Peer-Reviewed Publication

University of Western Ontario

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The Grand Prismatic hot spring in Yellowstone National Park is sourced from a magma chamber beneath it. The bright colours are produced by hydrophilic bacteria in the mineral-rich water.

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Credit: Bing Li / Western University

Yellowstone, a popular tourist destination and namesake of an equally popular TV show, was the first-ever national park in the United States. And bubbling beneath it – to this day – is one of Earth’s most seismically active networks of volcanic activity.

In a new study, published July 18 in the high impact journal Science Advances, Western engineering professor Bing Li and his collaborators at Universidad Industrial de Santander (Industrial University of Santander) in Colombia and the United States Geological Survey used machine learning to re-examine historical earthquake data from the Yellowstone caldera over a 15-year period. The team was able to retroactively detect and assign magnitudes to approximately 10 times more seismic events, or earthquakes, than previously recorded.

A caldera – like the one at Yellowstone Park spanning parts of Wyoming, Idaho and Montana – is a large depression or hollow formed when a volcano erupts and the magma chamber beneath it empties, leading to the collapse of the land above. This is different than a volcanic crater, which is formed by outward blasting.

The historical catalogue for the Yellowstone caldera now contains 86,276 earthquakes spanning the years 2008 to 2022, significantly improving previous understanding of volcanic and seismic systems through better data collection and systematic analyses.

A key finding in the study is that more than half of the earthquakes recorded in Yellowstone were part of earthquake swarms – groups of small, interconnected earthquakes that spread and shift within a relatively small area over a relatively short period of time. This is unlike an aftershock, which is a smaller earthquake that follows a larger mainshock in the same general area.

“While Yellowstone and other volcanoes each have unique features, the hope is that these insights can be applied elsewhere,” said Li, an expert in fluid-induced earthquakes and rock mechanics. “By understanding patterns of seismicity, like earthquake swarms, we can improve safety measures, better inform the public about potential risks, and even guide geothermal energy development away from danger in areas with promising heat flow.”

Molten-detecting machines

Prior to the application of machine learning, earthquakes were generally detected through manual inspection by trained experts. This process takes time, is cost-intensive and often detects fewer events than possible now with machine learning. Machine learning has sparked a data-mining gold rush in recent years as seismologists revisit the wealth of historical waveform data stored in datacenters across the world and learn more about current and previously unknown seismic regions around the world.

“If we had to do it old school with someone manually clicking through all this data looking for earthquakes, you couldn’t do it. It’s not scalable,” said Li.

The study also shows that earthquake swarms beneath the Yellowstone caldera have occurred along relatively immature, rougher fault structures, compared to more typical mature fault structures seen in regions such as southern California and even immediately outside the caldera.

The roughness was measured by characterizing earthquakes as fractals, which are geometric shapes that exhibit self-similarity, meaning they appear similar at different scales. First visualized by Benoit Mandelbrot in 1980, fractal patterns are seen in coastlines, snowflakes, broccoli, and even the branching of blood vessels. The fractal-based models, targeting roughness versus regularity, were able to characterize these earthquake swarms, which the researchers believe were caused by the mix of slowly moving underground water and sudden bursts of fluid.

“To a large extent, there is no systematic understanding of how one earthquake triggers another in a swarm. We can only indirectly measure space and time between events,” said Li. “But now, we have a far more robust catalogue of seismic activity under the Yellowstone caldera, and we can apply statistical methods that help us quantify and find new swarms that we haven’t seen before, study them, and see what we can learn from them.”

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Journal

Science Advances

DOI

10.1126/sciadv.adv6484 

Method of Research

Computational simulation/modeling

Subject of Research

Not applicable

Article Title

Long-term dynamics of earthquake swarms in the Yellowstone caldera

Article Publication Date

18-Jul-2025

Curved fault slip captured on CCTV during Myanmar earthquake

Seismological Society of America

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Dramatic CCTV video of fault slip during a recent large earthquake in Myanmar thrilled both scientists and casual observers when it was posted to YouTube. But it was on his fifth or sixth viewing, said geophysicist Jesse Kearse, that he spotted something even more exciting.

When Kearse and his colleague Yoshihiro Kaneko at Kyoto University analyzed the video more carefully, they concluded that it had captured the first direct visual evidence of curved fault slip.

Earthquake geologists often observe curved slickenlines, the scrape marks created by blocks of rock moving past each other during faulting. But until now there has been no visual proof of the curved slip that might create these slickenlines.

The video confirmation of curved fault slip can help researchers create better dynamic models of how faults rupture, Kearse and Kaneko conclude in their paper published in The Seismic Record.

The video comes from a CCTV security camera recording along the trace of Myanmar’s Sagaing Fault, which ruptured 28 March in a magnitude 7.7 earthquake. The camera was placed about 20 meters to the east of the fault and was 120 kilometers away from the earthquake’s hypocenter.

The resulting video is astonishing. A fault in motion as never seen before — shaking followed by a visible northward slide of the land on the western side of the fault.

“I saw this on YouTube an hour or two after it was uploaded, and it sent chills down my spine straight away,” Kearse recalled. “It shows something that I think every earthquake scientist has been desperate to see, and it was just right there, so very exciting.”

Watching it over and over again, he noticed something else.

“Instead of things moving straight across the video screen, they moved along a curved path that has a convexity downwards, which instantly started bells ringing in my head,” Kearse said, “because some of my previous research has been specifically on curvature of fault slip, but from the geological record.”

Kearse had studied curved slickenlines associated with other earthquakes, such as the 2016 magnitude 7.8 Kaikoura earthquake in New Zealand, and their implications for understanding how faults rupture.

With the Myanmar video, “we set about to quantify the movement a bit more carefully, to extract objective quantitative information from the video rather than just pointing at it to say, look, it’s curved,” he said.

The researchers decided to track the movement of objects in the video by pixel cross correlation, frame by frame. The analysis helped them measure the rate and direction of fault motion during the earthquake.

They conclude that the fault slipped 2.5 meters for roughly 1.3 seconds, at a peak velocity of about 3.2 meters per second. This shows that the earthquake was pulse-like, which is a major discovery and confirms previous inferences made from seismic waveforms of other earthquakes. In addition, most of the fault motion is strike-slip, with a brief dip-slip component. [For a quick review of fault types, visit this USGS FAQ.]

The slip curves rapidly at first, as it accelerates to top velocity, then remains linear as the slip slows down, the researchers found.

The pattern fits with what earthquake scientists had previously proposed about slip curvature, that it might occur in part because stresses on the fault near the ground surface are relatively low. “The dynamic stresses of the earthquake as it’s approaching and begins to rupture the fault near the ground surface are able to induce an obliquity to the fault movement,” said Kearse.

“These transient stresses push the fault off its intended course initially, and then it catches itself and does what it’s supposed to do, after that.”

The researchers previously concluded that the type of slip curvature—whether it curves in one direction, or in the other—is dependent on the direction that the rupture travels, and is consistent with the north to south rupture of the Myanmar earthquake. This means that slickenlines can record the dynamics of past earthquakes, which can be useful for understanding future seismic risks.

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Journal

The Seismic Record

DOI

10.1785/0320250024 

Method of Research

Observational study

Subject of Research

Not applicable

Article Title

Curved Fault Slip Captured by CCTV Video During the 2025 7.7 Myanmar Earthquake

Article Publication Date

18-Jul-2025