Studies shed new light on how biodiversity influences plant decay

Two independent studies exploring how biodiversity impacts plant decay in forests worldwide could help predict the potential effect of species loss on ecosystems

ELIFE

IMAGE: SCIENTISTS HAVE PROVIDED NEW INSIGHTS ON THE RELATIONSHIP BETWEEN PLANT DIVERSITY IN FORESTS AND THE DIVERSITY OF ORGANISMS INVOLVED IN THEIR DECAY, SUCH AS BACTERIA AND FUNGI. view more 

CREDIT: LÉA BEAUMELLE (CC BY 4.0)

Scientists have provided new insights on the relationship between plant diversity in forests and the diversity of organisms involved in their decay, such as bacteria and fungi.

Plant litter decomposition is a major ecosystem function, linking plant biomass to carbon stocks in the soil and atmosphere, and releasing nutrients including nitrogen and phosphorus that influence soil biodiversity. Two new independent studies, published today in eLife, report how plant biodiversity impacts decomposition processes and could help predict how the loss of species might affect forest ecosystems.

For the first study, researchers based in China and France analysed the relationship between the diversity of plant litter and decomposition across 65 field studies in forests around the world. Their results show that plant decomposition is faster when litter is composed of more than one species. This was particularly clear in forests with mild temperatures, but were more variable in other forest environments.

"We also found that plant diversity accelerated the release of nitrogen, but not phosphorus, potentially indicating a shift in ecosystem nutrient limitation caused by a change in biodiversity," explains joint first author Liang Kou, Associate Professor at the Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, China. "This discovery was again clear for temperate forests, but still needs confirmation for boreal, Mediterranean, subtropical and tropical forests that are currently limited on data."

"Our results suggest that biodiversity loss will modify carbon and nutrient cycling in forest ecosystems," adds joint senior author Huimin Wang, Professor at the Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences. "The potential impact of changes in litter diversity on carbon and nutrient cycling warrants particular attention in future studies, which would ideally integrate responses from decomposers for a better understanding of changes in carbon and nutrient cycling and the mechanisms driving them."

The second study in eLife, from researchers based in Germany and Belgium, similarly highlights the important links between plant litter and decomposer diversity, but it also shows how these links can be influenced by human activity.

"Industrial and agricultural activities can have detrimental effects on decomposer organisms," says first author Léa Beaumelle, a postdoctoral researcher at the German Centre for Integrative Biodiversity Research (iDiv) Halle-Jena-Leipzig, University of Leipzig, Germany. "They release chemical stressors such as metals and pesticides, as well as nutrients, into soil and water. Chemical stressors and added nutrients modify decomposer communities by affecting their diversity, abundance and metabolism."

Previous experiments conducted in simplified conditions have shown that biodiversity loss has detrimental effects on ecosystem processes. But how these results apply to real-world scenarios of change in biodiversity remains unclear. The researchers set out to discover if the responses of plant litter decomposition to chemical stressors and added nutrients can be explained by changes in decomposer diversity across ecosystems.

To do this, the team analysed the results of 69 independent studies that reported 660 observations of the effects of chemical stressors or nutrient enrichment on animal and microbial decomposers and on plant litter decomposition. They found that declines in the diversity and abundance of decomposers explained reductions in plant decay rates under the influence of chemical stressors, but not added nutrients. This suggests that human activities decrease decomposer biodiversity, which then leads to significant effects on ecosystem functions.

"These findings could inform the design of suitable strategies to maintain biodiversity and ecosystem functioning," concludes senior author Nico Eisenhauer, Head of Experimental Interaction Ecology at the German Centre for Integrative Biodiversity Research (iDiv) Halle-Jena-Leipzig, University of Leipzig. "But they also show that these strategies must take human activities into account and cannot rely solely on improving biodiversity alone."

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References

The papers 'Diversity-decomposition relationships in forests worldwide' and 'Biodiversity mediates the effects of stressors but not nutrients on litter decomposition' can be freely accessed online at https://doi.org/10.7554/eLife.55813 and https://doi.org/10.7554/eLife.55659, respectively. Contents, including text, figures and data, are free to reuse under a CC BY 4.0 license.

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About eLife

eLife is a non-profit organisation created by funders and led by researchers. Our mission is to accelerate discovery by operating a platform for research communication that encourages and recognises the most responsible behaviours. We work across three major areas: publishing, technology and research culture. We aim to publish work of the highest standards and importance in all areas of biology and medicine, including Ecology, while exploring creative new ways to improve how research is assessed and published. We also invest in open-source technology innovation to modernise the infrastructure for science publishing and improve online tools for sharing, using and interacting with new results. eLife receives financial support and strategic guidance from the Howard Hughes Medical Institute, the Knut and Alice Wallenberg Foundation, the Max Planck Society and Wellcome. Learn more at https://elifesciences.org/about.

To read the latest Ecology research published in eLife, visit https://elifesciences.org/subjects/ecology.

AI may offer a better way to ID drug-resistant superbugs

Machine learning algorithm uses high-temporal-resolution growth curves to identify pathogens with 98% accuracy and predict antibiotic resistance just as well as genetic-based methods

DUKE UNIVERSITY

 

IMAGE: A NEW METHOD FOR IDENTIFYING STRAINS OF BACTERIA AND GUESSING THEIR RESISTANCE TO ANTIBIOTICS USES AN AI MODEL TO ANALYZE THEIR GROWTH DYNAMICS IN CULTURE. view more 

CREDIT: DUKE UNIVERSITY

Biomedical engineers at Duke University have shown that different strains of the same bacterial pathogen can be distinguished by a machine learning analysis of their growth dynamics alone, which can then also accurately predict other traits such as resistance to antibiotics. The demonstration could point to methods for identifying diseases and predicting their behaviors that are faster, simpler, less expensive and more accurate than current standard techniques.

The results appear online on August 3 in the Proceedings of the National Academy of Sciences.

For most of the history of microbiology, bacteria identification has relied on growing cultures and analyzing the physical traits and behaviors of the resulting bacterial colony. It wasn't until recently that scientists could simply run a genetic test.

Genetic sequencing, however, isn't universally available and can often take a long time. And even with the ability to sequence entire genomes, it can be difficult to tie specific genetic variations to different behaviors in the real world.

For example, even though researchers know the genetic mutations that help shield/protect bacteria from beta-lactam antibiotics--the most commonly used antibiotic in the world--sometimes the DNA isn't the whole story. While a single resistant bacteria usually can't survive a dose of antibiotics on its own, large populations often can.

Lingchong You, professor of biomedical engineering at Duke, and his graduate student, Carolyn Zhang, wondered if a new twist on older methods might work better. Maybe they could amplify one specific physical characteristic and use it to not only identify the pathogen, but to make an educated guess about other traits such as antibiotic resistance.

"We thought that the slight variance in the genes between strains of bacteria might have a subtle effect on their metabolism," You said. "But because bacterial growth is exponential, that subtle effect could be amplified enough for us to take advantage of it. To me, that notion is somewhat intuitive, but I was surprised at how well it actually worked."

How quickly a bacterial culture grows in a laboratory depends on the richness of the media it is growing in and its chemical environment. But as the population grows, the culture consumes nutrients and produces chemical byproducts. Even if different strains start with the exact same environmental conditions, subtle differences in how they grow and influence their surroundings accumulate over time.

In the study, You and Zhang took more than 200 strains of bacterial pathogens, most of which were variations of E. coli, put them into identical growth environments, and carefully measured their population density as it increased. Because of their slight genetic differences, the cultures grew in fits and starts, each possessing a unique temporal fluctuation pattern. The researchers then fed the growth dynamics data into a machine learning program, which taught itself to identify and match the growth profiles to the different strains.

To their surprise, it worked really well.

"Using growth data from only one initial condition, the model was able to identify a particular strain with more than 92 percent accuracy," You said. "And when we used four different starting environments instead of one, that accuracy rose to about 98 percent."

Taking this idea one step further, You and Zhang then looked to see if they could use growth dynamic profiles to predict another phenotype--antibiotic resistance.

The researchers once again loaded a machine learning program with the growth dynamic profiles from all but one of the various strains, along with data about their resilience to four different antibiotics. They then tested to see if the resulting model could predict the final strain's antibiotic resistances from its growth profile. To bulk up their dataset, they repeated this process for all of the other strains.

The results showed that the growth dynamic profile alone could successfully predict a strain's resistance to antibiotics 60 to 75 percent of the time.

"This is actually on par or better than some of the current techniques in the literature, including many that use genetic sequencing data," said You. "And this was just a proof of principle. We believe that with higher-resolution data of the growth dynamics, we could do an even better job in the long term."

The researchers also looked to see if the strains exhibiting similar growth curves also had similar genetic profiles. As it turns out, the two are completely uncorrelated, demonstrating once again how difficult it can be to map cellular traits and behaviors to specific stretches of DNA.

Moving forward, You plans to optimize the growth curve procedure to reduce the time it takes to identify a strain from 2 to 3 days to perhaps 12 hours. He's also planning on using high-definition cameras to see if mapping how bacterial colonies grow in space in a Petri dish can help make the process even more accurate.

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This research was conducted in collaboration with groups of Deverick J. Anderson, Joshua T. Thaden and Vance G. Fowler from the Duke University School of Medicine, and Minfeng Xiao from BGI Genomics.

This research was partially supported by the National Institutes of Health (LY, R01GM098642, R01GM110494, 1A1125604), the Army Research Office (LY, W911NF-14-1-0490), the David and Lucile Packard Foundation, the Shenzhen Peacock Team Plan grant (MX, No. KQTD2015033117210153), the Centers for Disease Control and Prevention (DJA, U54CK000164), AHRQ (DJA, R01-HS23821), NIH (VGF, R01-AI068804), and the National Science Foundation's Graduate Research Fellowship (CZ, HRM).

"Temporal encoding of bacterial identity and traits in growth dynamics." Carolyn Zhang, Wenchen Song, Helena R. Ma, Xiao Peng, Deverick J. Anderson, Vance G. Fowler Jr, Joshua T. Thaden, Minfeng Xiao, and Lingchong You. PNAS, 2020. DOI: 10.1073/pnas.2008807117

Disclaimer: AAAS and EurekAlert! are not responsible for the accuracy of news releases

"Grown-ups don't always get it right, you know"

New research shows children don't expect adults to have all the answers, and want them to understand more about the role of media messages and approval in their lives.

UNIVERSITY OF PORTSMOUTH

 

New research shows children don't expect adults to have all the answers, and want them to understand more about the role of media messages and approval in their lives.

When 11 year old Oscar told his mum, Dr Emma Maynard that "grown-ups don't always get it right, you know" the statement struck a chord with the Senior Lecturer in Education at the University of Portsmouth.

Dr Maynard and colleagues Sarah Barton and Kayleigh Rivett asked Oscar and some friends to create a series of interview questions they could ask each other, about their views on adult knowledge and decision making - the first time this is thought to have been done for a peer reviewed research paper. Although there have been many projects where children have actively participated in research, the authors are not aware of other studies where children have taken the lead from the original idea, through to peer-reviewed publication.

The results have just appeared in the Journal of Qualitative Research in Psychology (July 2020), with the children listed as co-authors of the report. It finds that children think adults spend their time worrying that they should know the answers to everything, but the young people who took part in the research don't believe they should feel like this.

The young researchers also reported feeling a huge importance in adults recognising their achievements. The group as a whole was very frustrated by knowing a right answer, but not being able to show it. They cited occasions when teachers picked other students to answer a question, and didn't give them a chance to show they had a correct response. They related this to the constant messages they receive from media and school about striving for perfection in their self image, bodies, and learning expectations. Adult acknowledgement seems to reassure children they are on the right track to meet the very high expectations surrounding them.

The entire group argued that adults complain too much about the new generation's attitude to digital devices and their online activity. They urge adults to listen more to them about what it is like to have been immersed in new technology since birth, rather than impose parental views based on a childhood without it. Dr Maynard analysed these responses, and a feeling from the group that, despite a desire to do so, they felt unable to stop constantly using their phones because they would "feel left out".

Dr Maynard said: "The children presented the concept of phones and social media as being 'just there', so now they have to use them. We interpreted this as the adult generation having created the assessment pressures, and the presence of social media and mobile phone based communication. Children did not invent these things. This led us to think that in this context, criticisms of children and young people being attached to their phones is somewhat unfair."

The paper shows that children don't always think that adult knowledge is superior, demonstrated in these quotes from the interview process:

Ben: "adults... just need to realise they might have forgotten"

Jamie: "adults can't think they're just the best because they've already been through their childhood..."

Harry: "just because they're older and they've already been to school, it doesn't mean they've paid attention in school"

Eve: "...because they say that... they were once a child too but because we're different I think we should be allowed to have our own opinions sometimes"

The report is seen as an excellent and a useful example of 'allyship' - a process of building relationships based on trust, consistency, and accountability. Dr Maynard is now recommending the approach to others in her field, noting that it has delivered rich and insightful findings from children who conclude: "If this childhood is different to yours, then listen to ours".

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WALDEN EFFECT

In a warming world, New England's trees are storing more carbon

Unprecedented 25-year study traced forest carbon through air, trees, soil, and water

HARVARD UNIVERSITY

 

IMAGE: AN EDDY-FLUX TOWER MEASURES ATMOSPHERIC CARBON DIOXIDE ENTERING AND LEAVING A DECLINING HEMLOCK STAND AT HARVARD FOREST. view more 

CREDIT: PHOTO BY DAVID FOSTER

Climate change has increased the productivity of forests, according to a new study that synthesizes hundreds of thousands of carbon observations collected over the last quarter century at the Harvard Forest Long-Term Ecological Research site, one of the most intensively studied forests in the world.

The study, published today in Ecological Monographs, reveals that the rate at which carbon is captured from the atmosphere at Harvard Forest nearly doubled between 1992 and 2015. The scientists attribute much of the increase in storage capacity to the growth of 100-year-old oak trees, still vigorously rebounding from colonial-era land clearing, intensive timber harvest, and the 1938 Hurricane - and bolstered more recently by increasing temperatures and a longer growing season due to climate change. Trees have also been growing faster due to regional increases in precipitation and atmospheric carbon dioxide, while decreases in atmospheric pollutants such as ozone, sulfur, and nitrogen have reduced forest stress.

"It is remarkable that changes in climate and atmospheric chemistry within our own lifetimes have accelerated the rate at which forest are capturing carbon dioxide from the atmosphere," says Adrien Finzi, Professor of Biology at Boston University and a co-lead author of the study.

The volume of data brought together for the analysis - by two dozen scientists from 11 institutions - is unprecedented, as is the consistency of the results. Carbon measurements taken in air, soil, water, and trees are notoriously difficult to reconcile, in part because of the different timescales on which the processes operate. But when viewed together, a nearly complete carbon budget - one of the holy grails of ecology - emerges, documenting the flow of carbon through the forest in a complex, multi-decadal circuit.

"Our data show that the growth of trees is the engine that drives carbon storage in this forest ecosystem," says Audrey Barker Plotkin, Senior Ecologist at Harvard Forest and a co-lead author of the study. "Soils contain a lot of the forest's carbon - about half of the total - but that storage hasn't changed much in the past quarter-century."

The trees show no signs of slowing their growth, even as they come into their second century of life. But the scientists note that what we see today may not be the forest's future. "It's entirely possible that other forest development processes like tree age may dampen or reverse the pattern we've observed," says Finzi.

The study revealed other seeds of vulnerability resulting from climate change and human activity, such as the spread of invasive insects.

At Harvard Forest, hemlock-dominated forests were accumulating carbon at similar rates to hardwood forests until the arrival of the hemlock woolly adelgid, an invasive insect, in the early 2000s. In 2014, as more trees began to die, the hemlock forest switched from a carbon "sink," which stores carbon, to a carbon "source," which releases more carbon dioxide to the atmosphere than it captures.

The research team also points to extreme storms, suburbanization, and the recent relaxation of federal air and water quality standards as pressures that could reverse the gains forests have made.

"Witnessing in real time the rapid decline of our beloved hemlock forest makes the threat of future losses very real," says Barker Plotkin. "It's important to recognize the vital service forests are providing now, and to safeguard those into the future."

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Key brain region was 'recycled' as humans developed the ability to read

Part of the visual cortex dedicated to recognizing objects appears predisposed to identifying words and letters, a study finds

MASSACHUSETTS INSTITUTE OF TECHNOLOGY

 

CAMBRIDGE, MA -- Humans began to develop systems of reading and writing only within the past few thousand years. Our reading abilities set us apart from other animal species, but a few thousand years is much too short a timeframe for our brains to have evolved new areas specifically devoted to reading.

To account for the development of this skill, some scientists have hypothesized that parts of the brain that originally evolved for other purposes have been "recycled" for reading. As one example, they suggest that a part of the visual system that is specialized to perform object recognition has been repurposed for a key component of reading called orthographic processing -- the ability to recognize written letters and words.

A new study from MIT neuroscientists offers evidence for this hypothesis. The findings suggest that even in nonhuman primates, who do not know how to read, a part of the brain called the inferotemporal (IT) cortex is capable of performing tasks such as distinguishing words from nonsense words, or picking out specific letters from a word.

"This work has opened up a potential linkage between our rapidly developing understanding of the neural mechanisms of visual processing and an important primate behavior -- human reading," says James DiCarlo, the head of MIT's Department of Brain and Cognitive Sciences, an investigator in the McGovern Institute for Brain Research and the Center for Brains, Minds, and Machines, and the senior author of the study.

Rishi Rajalingham, an MIT postdoc,, is the lead author of the study, which appears today in Nature Communications. Other MIT authors are postdoc Kohitij Kar and technical associate Sachi Sanghavi. The research team also includes Stanislas Dehaene, a professor of experimental cognitive psychology at the Collège de France.

Word recognition

Reading is a complex process that requires recognizing words, assigning meaning to those words, and associating words with their corresponding sound. These functions are believed to be spread out over different parts of the human brain.

Functional magnetic resonance imaging (fMRI) studies have identified a region called the visual word form area (VWFA) that lights up when the brain processes a written word. This region is involved in the orthographic stage: It discriminates words from jumbled strings of letters or words from unknown alphabets. The VWFA is located in the IT cortex, a part of the visual cortex that is also responsible for identifying objects.

DiCarlo and Dehaene became interested in studying the neural mechanisms behind word recognition after cognitive psychologists in France reported that baboons could learn to discriminate words from nonwords, in a study that appeared in Science in 2012.

Using fMRI, Dehaene's lab has previously found that parts of the IT cortex that respond to objects and faces become highly specialized for recognizing written words once people learn to read.

"However, given the limitations of human imaging methods, it has been challenging to characterize these representations at the resolution of individual neurons, and to quantitatively test if and how these representations might be reused to support orthographic processing," Dehaene says. "These findings inspired us to ask if nonhuman primates could provide a unique opportunity to investigate the neuronal mechanisms underlying orthographic processing."

The researchers hypothesized that if parts of the primate brain are predisposed to process text, they might be able to find patterns reflecting that in the neural activity of nonhuman primates as they simply look at words.

To test that idea, the researchers recorded neural activity from about 500 neural sites across the IT cortex of macaques as they looked at about 2,000 strings of letters, some of which were English words and some of which were nonsensical strings of letters.

"The efficiency of this methodology is that you don't need to train animals to do anything," Rajalingham says. "What you do is just record these patterns of neural activity as you flash an image in front of the animal."

The researchers then fed that neural data into a simple computer model called a linear classifier. This model learns to combine the inputs from each of the 500 neural sites to predict whether the string of letters that provoked that activity pattern was a word or not. While the animal itself is not performing this task, the model acts as a "stand-in" that uses the neural data to generate a behavior, Rajalingham says.

Using that neural data, the model was able to generate accurate predictions for many orthographic tasks, including distinguishing words from nonwords and determining if a particular letter is present in a string of words. The model was about 70 percent accurate at distinguishing words from nonwords, which is very similar to the rate reported in the 2012 Science study with baboons. Furthermore, the patterns of errors made by model were similar to those made by the animals.

Neuronal recycling

The researchers also recorded neural activity from a different brain area that also feeds into IT cortex: V4, which is part of the visual cortex. When they fed V4 activity patterns into the linear classifier model, the model poorly predicted (compared to IT) the human or baboon performance on the orthographic processing tasks.

The findings suggest that the IT cortex is particularly well-suited to be repurposed for skills that are needed for reading, and they support the hypothesis that some of the mechanisms of reading are built upon highly evolved mechanisms for object recognition, the researchers say.

The researchers now plan to train animals to perform orthographic tasks and measure how their neural activity changes as they learn the tasks.

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The research was funded by the Simons Foundation and the U.S. Office of Naval Research.

What influences adolescents to share marijuana-related content on social media?

EDWARD R. MURROW COLLEGE OF COMMUNICATION

 

PULLMAN, Wash. - With social media use being as prevalent as ever, a new study from Washington State University's Edward R. Murrow College of Communication shows that adolescents may share marijuana-related content on social media in an effort to fit in with their peers.

Led by Murrow College Associate Professor Jessica Willoughby, this recently published study, "An Exploratory Study of Adolescents' Social Media Sharing of Marijuana-Related Content", examined the types of marijuana-related content that adolescents are posting on social media and what factors may influence adolescents' decisions to share marijuana-related content on social media.

The team of researchers surveyed 350 participants between the ages of 13-17 living in Washington state, where recreational marijuana use is legal for people 21 and older. The participants answered various questions related to their social media habits and whether they posted content relating to marijuana.

Previous research shows that young people may be exposed to a variety of marijuana-related content on social media, and this exposure may impact marijuana use. Other studies demonstrated youth and young adults' active engagement in displaying risky behaviors on social media, including marijuana use, which highlights a shared concern with the normalization of risky behaviors among young people.

"Nearly one-third of Washington adolescents we surveyed indicated that they shared marijuana-related content - primarily memes, pictures, and videos - on social media platforms such as Facebook, Snapchat, and Instagram," Willoughby said. "Even though many marijuana-related web sites require viewers to verify they are old enough to legally use the product, such verification processes are absent from social media."

"The adolescents we surveyed were also more likely to share marijuana-related social media content if they perceived their peers use marijuana and if they believed their parents would approve of them sharing such content," said Murrow College Associate Dean Stacey J.T. Hust, who is second author of the study. "In contrast, if they perceived that their parents were monitoring their behavior, in general, they were less likely to share marijuana-related content on social media.

"Essentially, adolescents who reported their parents were aware of where they were going and who they were spending time with, were less likely to share marijuana-related content," Willoughby said. "But, we didn't find an association between parents checking their adolescents' social media and the sharing of marijuana-related content."

The motives behind sharing marijuana-related content are still unclear, according to this study. As young people use social media for a variety of reasons, including to present themselves to others, it is important to gauge the risk-related messages youth display on social media and what may be associated with this sharing on social platforms.

"Overall, our findings suggest adolescents may post content that is inconsistent with their personal beliefs in a desire to conform to their peers," Hust said. This is of potential concern because young people tend to overestimate peer use and acceptance of substance use, and social media posting related to substance use may imply an intention to use substances or increase perceptions of their use.

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Scientists propose a novel method for controlling fusion reactions

DOE/PRINCETON PLASMA PHYSICS LABORATORY

 

IMAGE: PHYSICIST SUYING JIN. view more 

CREDIT: PHOTO COURTESY OF SUYING JINL

Scientists have found a novel way to prevent pesky magnetic bubbles in plasma from interfering with fusion reactions - delivering a potential way to improve the performance of fusion energy devices. And it comes from managing radio frequency (RF) waves to stabilize the magnetic bubbles, which can expand and create disruptions that can limit the performance of ITER, the international facility under construction in France to demonstrate the feasibility of fusion power.

Magnetic islands

Researchers at the U.S. Department of Energy's (DOE) Princeton Plasma Physics Laboratory (PPPL) have developed the new model for controlling these magnetic bubbles, or islands. The novel method modifies the standard technique of steadily depositing radio (RF) rays into the plasma to stabilize the islands -- a technique that proves inefficient when the width of an island is small compared with the characteristic size of the region over which the RF ray deposits its power.

This region denotes the "damping length," the area over which the RF power would typically be deposited in the absence of any nonlinear feedback. The effectiveness of the RF power can be greatly reduced when the size of the region is greater than the width of the island -- a condition called "low-damping" -- as much of the power then leaks from the island.

Tokamaks, doughnut-shaped fusion facilities that can experience such problems, are the most widely used devices by scientists around the world who seek to produce and control fusion reactions to provide a virtually inexhaustible supply of safe and clean power to generate electricity. Such reactions combine light elements in the form of plasma -- the state of matter composed of free electrons and atomic nuclei that makes up 99 percent of the visible universe -- to generate the massive amounts of energy that drives the sun and stars.

Overcoming the problem

The new model predicts that depositing the rays in pulses rather than steady state streams can overcome the leakage problem, said Suying Jin, a graduate student in the Princeton Program in Plasma Physics based at PPPL and lead author of a paper (link is external) that describes the method in Physics of Plasmas. "Pulsing also can achieve increased stabilization in high-damping cases for the same average power," she said.

For this process to work, "the pulsing must be done at a rate that is neither too fast nor too slow," she said. "This sweet spot should be consistent with the rate that heat dissipates from the island through diffusion."

The new model draws upon past work by Jin's co-authors and advisors Allan Reiman, a Distinguished Research Fellow at PPPL, and Professor Nat Fisch, director of the Program in Plasma Physics at Princeton University and associate director for academic affairs at PPPL. Their research provides the nonlinear framework for the study of RF power deposition to stabilize magnetic islands.

"The significance of Suying's work," Reiman said, "is that it expands considerably the tools that can be brought to bear on what is now recognized as perhaps the key problem confronting economical fusion using the tokamak approach. Tokamaks are plagued by these naturally arising and unstable islands, which lead to disastrous and sudden loss of the plasma."

Added Fisch: "Suying's work not only suggests new control methodologies; her identification of these newly predicted effects may force us to re-evaluate past experimental findings in which these effects might have played an unappreciated role. Her work now motivates specific experiments that could clarify the mechanisms at play and point to exactly how best to control these disastrous instabilities."

Original model

The original model of RF deposition showed that it raises the temperature and drives current in the center of an island to keep it from growing. Nonlinear feedback then kicks in between the power deposition and changes in the temperature of the island that allows for greatly improved stabilization. Governing these temperature changes is the diffusion of heat from the plasma at the edge of the island.

However, in high-damping regimes, where the damping length is smaller than the size of the island, this same nonlinear effect can create a problem called "shadowing" during steady state deposition that causes the RF ray to run out of power before it reaches the center of the island.

"We first looked into pulsed RF schemes to solve the shadowing problem," Jin said. "However, it turned out that in high-damping regimes nonlinear feedback actually causes pulsing to exacerbate shadowing, and the ray runs out of power even sooner. So we flipped the problem around and found that the nonlinear effect can then cause pulsing to reduce the power leaking out of the island in low-damping scenarios."

These predicted trends lend themselves naturally to experimental verification, Jin said. "Such experiments," she noted, "would aim to show that pulsing increases the temperature of an island until optimum plasma stabilization is reached."

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Funding for this research comes from the DOE Office of Science.

PPPL, on Princeton University's Forrestal Campus in Plainsboro, N.J., is devoted to creating new knowledge about the physics of plasmas -- ultra-hot, charged gases -- and to developing practical solutions for the creation of fusion energy. The Laboratory is managed by the University for the U.S. Department of Energy's Office of Science, which is the single largest supporter of basic research in the physical sciences in the United States and is working to address some of the most pressing challenges of our time. For more information, visit energy.gov/science (link is external).

FSU geologists publish new findings on carbonate melts in Earth's mantle

FLORIDA STATE UNIVERSITY

 

Geologists from Florida State University's Department of Earth, Ocean and Atmospheric Science have discovered how carbon-rich molten rock in the Earth's upper mantle might affect the movement of seismic waves.

The new research was coauthored by EOAS Associate Professor of Geology Mainak Mookherjee and postdoctoral researcher Suraj Bajgain. Findings from the study were published in the journal Proceedings of the National Academy of Sciences .

"This research is quite important since carbon is a crucial constituent for the habitability of the planet, and we are making strides to understand how solid earth may have played a role in storing and influencing the availability of carbon in the Earth's surface," Mookherjee said. "Our research gives us a better understanding of the elasticity, density and compressibility of these rocks and their role in Earth's carbon cycle."

Carbon, one of the primary building blocks for life, is widely distributed throughout the Earth's upper mantle and is mostly stored in forms of carbonate minerals as accessory minerals in mantle rocks. When carbonate-rich magma erupts on the surface, it is notable for its unique, mud-like appearance. These types of eruptions occur at specific locations around the world, such as at the Ol Doinyo Lengai volcano in Tanzania.

Experts believe that the presence of carbonates in rocks significantly lowers the temperature at which they melt. Carbonates that sink to the Earth's interior, via a process known as subduction, likely cause this low-degree melting of the Earth's upper mantle rocks, which plays an important role in the planet's deep carbon cycle.

"Earth's mantle has less free oxygen available at increasing depths," Mookherjee said. "As the mantle upwells through a process of mantle convection, the slowly moving rocks that were reduced, or had less oxygen, at a greater depth become progressively more oxidized at shallower depth. The carbon in the mantle is likely to be reduced deeper in the Earth and get oxidized as the mantle upwells."

This change in depth-dependent oxidation state is likely to cause melting of mantle rocks, a process called redox melting, which could produce carbon-rich molten rock, also known as melts. These melts are likely to affect the physical property of a rock, which can be detected using geophysical probes such as seismic waves, he said.

Prior to this study, geologists had poor knowledge of the elastic properties of these carbonate-induced partial melts, which made them difficult to directly detect.

One set of clues that geologists use to better understand their science are measurements of seismic waves as they move through the layers of the Earth. A type of seismic wave known as a compressional wave is faster than another type known as a shear wave, but at depths of around 180 to 330 kilometers into the Earth, the ratio of their speeds is even higher than is typical.

"This elevated ratio of compressional waves to the shear waves has been a puzzle, and using the findings from our study, we are able to explain this perplexing observation," Mookherjee said.

Minor quantities of carbon-rich melts, approximately 0.05 percent, might be dispersed pervasively through the Earth's deep upper mantle, and that may lead to the elevated ratio of compressional to shear sound velocity, researchers explained.

To conduct the study, researchers took high-pressure ultrasonic measurements and density measurements on cores of the carbonate mineral dolomite. These experiments were complemented by theoretical simulations to provide a new understanding of the fundamental physical properties of carbonate melts.

"We have been trying to understand the elastic and transport properties of aqueous fluids, silicate melt and metallic melt properties, to gain better insight into the mass of volatiles stored in the deep solid earth," Bajgain said.

These findings mean the partially molten rocks in the mantle could hold as much as 80 to 140 parts per million of carbon, which would be 20 to 36 million gigatons of carbon in the deep upper mantle region, making it a substantial carbon reservoir. In comparison, Earth's atmosphere contains just over 410 ppm of carbon, or around 870 gigatons.

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Researchers from Case Western Reserve University in Cleveland, Southern University of Science and Technology in Shenzhen, China, and the University of Chicago contributed to this study. They performed calculations at the High Performance Computing Cluster at Florida State and at supercomputing facilities provided by the National Science Foundation's Extreme Science and Engineering Discovery Environment.

The work was partly supported by the National Science Foundation and the National Natural Science Foundation of China.

Epidemic model shows how COVID-19 could spread through firefighting camps

Demonstrates potential risks, scenarios COVID-19 could pose for fire management

COLORADO STATE UNIVERSITY

 

IMAGE: LARIMER COUNTY AND WELLINGTON FIREFIGHTERS MOP UP A SPOT FIRE AREA ON THE ELK FIRE, OCT. 18, 2019. view more 

CREDIT: BILL COTTON/COLORADO STATE UNIVERSITY PHOTOGRAPHY

With wildfire season in full swing, a COVID-19 outbreak at a traditional large fire camp is a potential disaster. A transient, high-density workforce of firefighters and volunteers responds to blazes while staying in close quarters with limited hygiene - conditions that could facilitate the spread of a contagious respiratory disease.

To support fire agencies as they continue their mission-critical work, a team that includes Colorado State University experts has developed an epidemiological modeling exercise for the USDA Forest Service and other fire managers that demonstrates potential risks and various scenarios COVID-19 could pose for the fire management community. Their model is published in the journal Fire.

The report is co-authored by Jude Bayham, assistant professor in the CSU Department of Agricultural and Resource Economics; and Erin Belval, research scientist in the CSU Department of Forest and Rangeland Stewardship; with first author Matthew P. Thompson, Research Forester at the USDA Forest Service Rocky Mountain Research Station. Bayham and Belval worked with Thompson on the study under a longstanding joint venture agreement with the Forest Service on wildfire-related research, which primarily operates through a partnership with the Warner College of Natural Resources. Thompson serves as the team's liaison to the fire management community.

The researchers developed a simulation model of COVID-19 in the context of a wildfire incident in which the population of firefighters changes over time. The team then analyzed a range of scenarios with different infection transmission rates, percentages of arriving workers who are infected, and fatality rates.

They applied their model to real firefighter population data from three recent wildfires - Highline, Lolo Peak and Tank Hollow - to illustrate potential outbreak dynamics.

During the Highline fire in Idaho, for example, which at its peak had over 1,000 firefighters on site (See Figure 1.), a worst-case scenario would have seen close to 500 infections, and a best-case scenario of eight infections. (See Figure 7.) The researchers used a variety of infection fatality rates to estimate possible deaths due to COVID-19 on the fires, ranging from a low of 0.1% to an "extreme" of 2%, with a medium, or best-guess, of 0.3%. (See Table 1.)

Model is not a prediction

Like most modeling exercises, the report is not intended to predict real numbers; rather, it is a tool for comparing different scenarios and analyzing how various interventions could have small or large effects.

"There is a need in the modeling community to better communicate what we can and cannot learn from models," Bayham said. "The model itself is not meant to be predictive in the sense of number of cases or deaths, because there are so many things moving."

Bayham said the model does provide insight into the relative benefits of two risk-mitigation strategies: screening; and implementing social distancing measures at camps.

They found that aggressive screening as soon as firefighters arrive at camp could reduce the spread of infection, but those benefits diminish as a wildfire incident goes on longer. For longer campaigns lasting several months, aggressive social distancing measures, including increased use of remote briefings, dispersed sleeping camps, and operating under the "module as one" concept, would be more effective at reducing infections than screening. "Module as one" is a social distancing adaptation in which a crew operates mostly as normal but isolates from other, similarly isolating crews.

"It all comes down to exposure, which is a basic risk management concept," Thompson said. "Reducing the exposure of susceptible individuals to those who may be infectious is the idea behind screening and social distancing. Our results underscore the importance of deploying these risk mitigation measures and provide insights into how characteristics of a wildfire incident factor into the effectiveness of these mitigations."

Bayham added, "Both interventions are useful, and they both have an effect, but they each have times and places where they are even more effective,"

Such findings could help inform the wildland fire management community as it develops guidance for fire response strategies during the pandemic.

Thompson added, "I'm fortunate to have worked with Jude and Erin for several years now, and in my opinion their collective depth and breadth of expertise is uniquely well suited to address this complex issue. We're grateful for the support from the Joint Fire Science Program and more broadly the fire management community to continue this important work."

Extending the work

The team will continue their work with a $74,200 award from the Joint Fire Science Program by way of the USDA Forest Service Rocky Mountain Research Station joint venture agreement. They plan to extend their model and create an interactive dashboard for agencies to provide real-time modeling and risk assessment support as fire season continues.

They are also working on a model that would be better suited to analyze season-long implications of COVID-19 outbreaks, spread across multiple fires and geographic distances.

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THIS HAS BEEN THE DREAM SINCE FIRST DISCOVERED IN THE SEVENTIES 

How thoughts could one day control electronic prostheses, wirelessly

Today's brain implants already connect the nervous system to electronic devices to help people with spinal cord injuries regain some motor control. But they use ungainly wires.

STANFORD SCHOOL OF ENGINEERING

 

IMAGE: PHOTO OF A CURRENT NEURAL IMPLANT, THAT USES WIRES TO TRANSMIT INFORMATION AND RECEIVE POWER. NEW RESEARCH SUGGESTS HOW TO ONE DAY CUT THE WIRES. view more 

CREDIT: SERGEY STAVISKY

Stanford researchers have been working for years to advance a technology that could one day help people with paralysis regain use of their limbs, and enable amputees to use their thoughts to control prostheses and interact with computers.

The team has been focusing on improving a brain-computer interface, a device implanted beneath the skull on the surface of a patient's brain. This implant connects the human nervous system to an electronic device that might, for instance, help restore some motor control to a person with a spinal cord injury, or someone with a neurological condition like amyotrophic lateral sclerosis, also called Lou Gehrig's disease.

The current generation of these devices record enormous amounts of neural activity, then transmit these brain signals through wires to a computer. But when researchers have tried to create wireless brain-computer interfaces to do this, it took so much power to transmit the data that the devices would generate too much heat to be safe for the patient.

Now, a team led by electrical engineers and neuroscientists Krishna Shenoy, PhD, and Boris Murmann, PhD, and neurosurgeon and neuroscientist Jaimie Henderson, MD, have shown how it would be possible to create a wireless device, capable of gathering and transmitting accurate neural signals, but using a tenth of the power required by current wire-enabled systems. These wireless devices would look more natural than the wired models and give patients freer range of motion.

Graduate student Nir Even-Chen and postdoctoral fellow Dante Muratore, PhD, describe the team's approach in a Nature Biomedical Engineering paper.

The team's neuroscientists identified the specific neural signals needed to control a prosthetic device, such as a robotic arm or a computer cursor. The team's electrical engineers then designed the circuitry that would enable a future, wireless brain-computer interface to process and transmit these these carefully identified and isolated signals, using less power and thus making it safe to implant the device on the surface of the brain.

To test their idea, the researchers collected neuronal data from three nonhuman primates and one human participant in a (BrainGate) clinical trial.

As the subjects performed movement tasks, such as positioning a cursor on a computer screen, the researchers took measurements. The findings validated their hypothesis that a wireless interface could accurately control an individual's motion by recording a subset of action-specific brain signals, rather than acting like the wired device and collecting brain signals in bulk.

The next step will be to build an implant based on this new approach and proceed through a series of tests toward the ultimate goal.

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