It’s possible that I shall make an ass of myself. But in that case one can always get out of it with a little dialectic. I have, of course, so worded my proposition as to be right either way (K.Marx, Letter to F.Engels on the Indian Mutiny)
Wednesday, June 18, 2025
To what extent are tree species in Mexico and Central America threatened by extinction?
More than 4,000 tree species are found only in Mexico and Central America, orMesoamerica. Research published in Plants, People, Planet reveals that nearly half of these tree species are threatened by extinction. As part of the Global Tree Assessment, an initiative to assess the conservation status of the world's tree species, a group of investigators compiled International Union for the Conservation of Nature’s Red List assessments for each species, collating information about species' range, habitat, threats, and conservation actions.
They found that 46% of trees in Mesoamerica are at risk of extinction and that agriculture and logging are the major drivers of decline. Also, most of the threatened tree species do not have targeted conservation actions that might help protect them from extinction.
“With this collaborative effort to assess the conservation status of tree species in Mesoamerica, we can now prioritize conservation actions for the region's most threatened tree species. Now it is possible to pinpoint on a country level which species are most at risk, what threatens them, and what conservation actions are already in place,” said corresponding author Emily Beech, of Botanic Gardens Conservation International, in the UK. “We hope this will inspire further conservation work to prevent tree extinctions.”
Additional Information NOTE: The information contained in this release is protected by copyright. Please include journal attribution in all coverage. For more information or to obtain a PDF of any study, please contact: Sara Henning-Stout, newsroom@wiley.com.
About the Journal Plants, People, Planet publishes innovative research at the interface between plants, society, and the planet. Owned by the New Phytologist Foundation, we aim to publish studies that generate societal impact and address global issues with plant-focused solutions.
About Wiley Wiley is one of the world’s largest publishers and a trusted leader in research and learning. Our industry-leading content, services, platforms, and knowledge networks are tailored to meet the evolving needs of our customers and partners, including researchers, students, instructors, professionals, institutions, and corporations. We empower knowledge-seekers to transform today’s biggest obstacles into tomorrow’s brightest opportunities. For more than two centuries, Wiley has been delivering on its timeless mission to unlock human potential. Visit us at Wiley.com. Follow us on Facebook, X, LinkedIn and Instagram.
In a study published in Weather, researchers estimated the current chances and characteristics of extreme hot episodes in the UK, and how they have changed over the last 6 decades.
The team found that temperatures several degrees above those recorded during the UK’s heatwave in July 2022 are plausible in today’s climate, with a simulated maximum of over 45°C (113°F). The likelihood of 40°C (104°F) is now over 20 times more likely than it was in the 1960s. Moreover, the chance of 40°C will likely continue to rise as the climate warms. The investigators estimate that there is approximately a 50% chance of again exceeding 40°C in the next 12 years.
Through multiple storylines of how temperatures could evolve through the summer season, they also found that prolonged heatwaves of over a month above 28°C (82°F) are possible in southeast England today. These storylines are valuable for modeling and stress testing.
“Our findings highlight the need to prepare and plan for the impacts of rising temperatures now, so we can better protect public health, infrastructure, and the environment from the growing threat of extreme heat,” said corresponding author Gillian Kay, PhD, of the Met Office Hadley Centre.
Additional Information NOTE: The information contained in this release is protected by copyright. Please include journal attribution in all coverage. For more information or to obtain a PDF of any study, please contact: Sara Henning-Stout, newsroom@wiley.com.
About the Journal Weather publishes articles written for a broad audience, including those having a professional and a general interest in the weather, as well as those working in related fields such as climate science, oceanography, hydrometeorology and other related atmospheric and environmental sciences. Articles covering recent weather and climate events are particularly welcome.
About Wiley Wiley is one of the world’s largest publishers and a trusted leader in research and learning. Our industry-leading content, services, platforms, and knowledge networks are tailored to meet the evolving needs of our customers and partners, including researchers, students, instructors, professionals, institutions, and corporations. We empower knowledge-seekers to transform today’s biggest obstacles into tomorrow’s brightest opportunities. For more than two centuries, Wiley has been delivering on its timeless mission to unlock human potential. Visit us at Wiley.com. Follow us on Facebook, X, LinkedIn and Instagram.
Using a toy gun converted into a laser pointer, a test subject in Chalmers' acoustics lab tries to locate warning sounds from electric cars. One of the most common signal types turned out to be very difficult for humans to locate.
As electric cars become more common, vulnerable road users are encountering more and more warning signals from them. Now, new research from Chalmers University of Technology in Sweden, shows that one of the most common signal types is very difficult for humans to locate, especially when multiple similar vehicles are in motion simultaneously.
In a recently published study, researchers from Chalmers investigated how well people can locate three common types of warning (or AVAS -Acoustic Vehicle Alerting System) signals from hybrid and electric vehicles moving at low speeds. The researchers’ tests showed that all the signal types were harder to locate than the sound of an internal combustion engine. For one of the signals, the majority of test subjects were unable to distinguish the direction of the sound or determine whether they were hearing one, two or more vehicles simultaneously.
“The requirements placed on car manufacturers relate to detection, or detectability, not about locating sound direction or the number of vehicles involved. But if you imagine, say, a supermarket carpark, it’s not inconceivable that several similar car models with the same AVAS signal will be moving at the same time and in different directions,” says Leon Müller, a doctoral student at the Department of Architecture and Civil Engineering at Chalmers.
Today’s electric and hybrid vehicles meet the requirements set for acoustic warning systems according to international standards. In Europe, plus China and Japan, for example, vehicles travelling at a speed below 20 kph must emit a warning signal consisting of tones or noise, to allow pedestrians, cyclists and other non-car users to detect them. In the United States, warning signals are required from vehicles travelling at speeds of up to 30 kph.
“The way the requirements are worded allows car manufacturers to design their own signature sounds. These warning signals are often tested without the complication of background noise. But in a real traffic environment there are usually many different types of sound,” says Wolfgang Kropp, professor of acoustics at the Department of Architecture and Civil Engineering at Chalmers.
Trying multiple different signals
The experiments involved some 52 test subjects and were conducted in Chalmers’ acoustics laboratory in soundproofed, anechoic chambers. The aim of the tests was to emulate real conditions in, say, larger carparks. The subject was placed at the centre of the room and surrounded by 24 loudspeakers placed in a ring at chest height. Three types of simulated vehicle sounds were played on the loudspeakers, corresponding to the signals from one, two or more electric and hybrid vehicles, plus an internal combustion engine. One of the signals consisted of two tones, one had multiple tones and one was just noise. The test subjects heard a vehicle warning signal at about 7.5 meters away, mixed with pre-recorded background noise from a quiet city carpark. When they heard the signal, the subjects had to mark the direction it was coming from as quickly as possible. The signal comprising two tones coming from three vehicles simultaneously was the most difficult and none of the test subjects managed to locate all the two-tone signals within the ten-second time limit.
New signal types needed
The test subjects were easily able to locate the sound corresponding to an internal combustion engine. Leon Müller says this sound consists of short pulses comprising all frequencies; something that is easier for the ear to perceive than a fixed tone at a single frequency. The fact that people can more easily perceive this type of sound may also be because of its familiarity.
“Naturally, as acousticians, we welcome the fact that electric cars are significantly quieter than internal combustion engines but it’s important to find a balance,” says Müller.
Existing research has focused mainly on detectability and what is usually referred to as “detection distance”. No previous studies have investigated what happens when two or three cars emit the same type of signal. The researchers see a major need for further knowledge of how people react in traffic situations involving electric vehicles.
“From a traffic safety point of view, it would be desirable to find a signal that’s as effective as possible in terms of detection and localisation but which doesn’t affect people negatively; something our previous research has shown to be true of traffic noise,” says Kropp.
In a follow-up study, the researchers have begun investigating how AVAS signals are perceived and what effect they may have on non-road users.
The authors are Leon Müller, Jens Forssén and Wolfgang Kropp, all working at the Division of Engineering Acoustics, Department of Architecture and Civil Engineering at Chalmers University of Technology in Sweden.
Caption: Using a toy gun converted into a laser pointer, a test subject in Chalmers' acoustics lab tries to locate warning sounds from electric cars. One of the most common signal types turned out to be very difficult for humans to locate. Credit: Chalmers/Unsplash
Since the mid-1800s, human activities have rapidly facilitated the spread of rice yellow mottle virus (RYMV), a pathogen that infects rice, far and wide across Africa, according to a new study led by Eugénie Hébrard, at the Institut de Recherche pour le Développement (IRD, France), published June 17, 2025 in the open-access journal PLOS Pathogens.
RYMV is a pathogen that infects rice and a few related grass species, and that poses a major threat to rice production in Africa. In the new study, researchers investigated how human history has shaped the spread of RYMV, looking at how distinct strains of RYMV evolved in different locations and times.
The research team compared the gene sequences that code for a viral protein or the full-length viral genomes, fromup to 335 virus samples collected across more than 770,000 square miles in East Africa between 1966 and 2020. Based on variations and similarities in the gene sequences, the researchers found evidence that RYMV emerged in the middle of the 1800s in the Eastern Arc Mountains, a biodiversity hotspot, located in what is now Tanzania, where people grew rice slash-and-burn agriculture. Several spillovers of RYMV from wild grasses into cultivated rice were identified, with the virus rapidly spreading to the nearby rice growing areas, including Kilombero valley and the Morogoro region in southern Tanzania.
The study also suggested that humans transported RYMV long distances in infected rice plant matter at multiple points in history. The virus spread along the caravan routes from the Indian Ocean Coast to Lake Victoria in the second half of the 1800s, from East Africa to West Africa at the end of the 1800s, from Lake Victoria to the north of Ethiopia in the second half of the 1900s, and then on to Madagascar at the end of 1970s. Unexpectedly, it moved from the Kilombero Valley to the southern end of Lake Malawi toward the end of the First World War, likely due to rice being a staple food for troops.
Altogether, these findings suggest that transporting contaminated rice seeds was a major factor in spreading RYMV across long distances, not only within East Africa, but also in bringing it from East Africa to West Africa and Madagascar. The researchers conclude that, due to human activities, RYMV can spread as efficiently as some highly mobile zoonotic viruses that humans have contracted from animals. The study also sheds light on the risk of transmitting RYMV and other plant viruses from Africa to other continents.
The authors add, “This paper highlights the role of human history in the transmission of plant pathogens and underscores the risks of intercontinental transmission. The paradoxical role of seeds in the spread of a major pest of rice - which is not seed transmitted, but seed associated – is explained in the light of rice biology and agronomy. This study is a major achievement of a long-term, multilateral and interdisciplinary partnership.”
Citation: Ndikumana I, Onaga G, Pinel-Galzi A, Rocu P, Hubert J, Wéré HK, et al. (2025) Grains, trade and war in the multimodal transmission of Rice yellow mottle virus: An historical and phylogeographical retrospective. PLoS Pathog 21(6): e1013168. https://doi.org/10.1371/journal.ppat.1013168
Movie caption: Spatio-temporal dispersion of rice yellow mottle virus throughout East Africa visualized by Evolaps. https://www.evolaps.org/
Author Countries: Belgium, Cote d’Ivoire, France, Kenya, Rwanda, Singapore, Tanzania, United States
Funding: This work was partly supported by the French National Research Agency as an “Investissements d’avenir” program (ANR-10-LABX-001-01 Labex Agro) coordinated by Agropolis Foundation (project no. 1504-004 E-SPACE to IN, EPG, NP, DF, EH) and by a bilateral project between Kenya and France (PHC PAMOJA no 36128PK to HKW, AA, MNW, EH) cofunded by National Commission for Science, Technology and Innovation (NACOSTI) and Ministère de l’Europe et des Affaires Etrangères (MEAE). PR’s internship at the University of Montpellier was founded by the I-SITE MUSE through the Key Initiative “Data and Life Sciences”. SD acknowledges support from the Fonds National de la Recherche Scientifique (F.R.S.-FNRS, Belgium; grant n°F.4515.22), from the Research Foundation - Flanders (Fonds voor Wetenschappelijk Onderzoek - Vlaanderen, FWO, Belgium; grant n°G098321N), from the European Union Horizon 2020 projects MOOD (grant agreement n°874850) and LEAPS (grant agreement n°101094685). GO acknowledges support from the Plant Health Initiative (PHI) funded by the CGIAR Trust Fund. The funders had no role in the study design, data collection and interpretation, or the decision to submit the work for publication.
Aurelie Poncet, left, and Mario Soto conducted a study showing how a sensor and AI/Machine Learning can be used to assist weed scientists in rating herbicide effectiveness on plants. Poncet is an assistant professor of precision agriculture in the crop, soil and environmental sciences department for the Division of Agriculture and the Dale Bumpers College of Agricultural, Food and Life Sciences. Mario Soto is a master's student in the department.
Credit: U of A System Division of Agriculture photo
FAYETTEVILLE, Ark. — By combining artificial intelligence and sensors that can see beyond visible light, Arkansas researchers have developed a system that exceeds human discernment when it comes to measuring herbicide-induced stress in plants.
Scientists with the Arkansas Agricultural Experiment Station, the research arm of the University of Arkansas System Division of Agriculture, recently published a study in Smart Agricultural Technology providing proof-of-concept that hyperspectral sensors like a spectroradiometer can help in quantifying herbicide effectiveness, a critical element of weed management that helps curb herbicide resistance.
While normal cameras use three visible light bands — red, green and blue — to create images in the spectral range of 380 to 750 nanometers, hyperspectral sensing captures bands ranging from 250 nanometers to 2,500 nanometers and thermal infrared.
The researchers used this technology to evaluate how common lambsquarters responded to glyphosate. They also turned up empirical evidence that photosynthesis in the plant actually increased when exposed to a sub-lethal dose of the herbicide. Common lambsquarters — Chenopodium album L. — is a weed in agricultural and garden settings.
“Plant response to herbicide application is measured using visual ratings, but accuracy varies with the quality of training and years of practice of the rater,” said principal investigator of the study Aurelie Poncet, assistant professor of precision agriculture in the crop, soil and environmental sciences department for the Division of Agriculture and the Dale Bumpers College of Agricultural, Food and Life Sciences. “We thought, if we could have a sensor that automates some of this decision, we might be able to implement it into applications down the road.”
Weed scientists are trained to rate herbicide efficacy within a 10 percent margin of error, plus or minus 5 percent. The researchers were able to use machine learning models on data collected with a spectroradiometer to reach a margin of error of 12.1 percent. Their goal is to get below 10 percent.
The researchers used a random forest machine learning algorithm to analyze thousands of vegetation index data points collected in the experiment. The algorithm combines the output of multiple decision trees to reach a single result.
“Our success using random forest to describe common lambsquarters response to glyphosate application opens the possibility of moving beyond the development of vegetation indices, another approach gaining traction in the published literature,” said Mario Soto, lead author of the study and a crop, soil and environmental sciences master’s student in Bumpers College.
Next steps
Once refined, hyperspectral sensing could be used to measure specific weed response to herbicide application and overcome limitations of a human’s visual assessment. Further development of the method and validation may also be used to create a platform for high-throughput categorization of weed response to herbicides and screening for herbicide resistance, the study’s authors noted.
While training can overcome lack of experience for evaluators, mental and physical fatigue from long workdays evaluating treatments in harsh environmental conditions can affect judgement for even the most experienced evaluator, said Nilda Roma-Burgos, professor of weed physiology and molecular biology for the experiment station and Bumpers College.
“This method, in principle, could remove the human factor in herbicide efficacy evaluations and will be an invaluable research tool for weed science,” said Burgos, a co-author of the study. “Meanwhile, much work still awaits to validate the method across key weed species, herbicide modes of action, time after herbicide application and environmental conditions.”
Co-authors of the study included Kristofor Brye, University Professor of applied soil physics and pedology; Wesley France, program associate, and Juan C. Velasquez, weed science graduate research assistant, of the crop, soil and environmental sciences department.
Cengiz Koparan, assistant professor of precision agriculture technology with the agricultural education, communication and technology department and the biological and agricultural engineering department, and Amanda Ashworth, research soil scientist with the U.S. Department of Agriculture’s Agricultural Research Service, were also co-authors.
The hyperspectral imaging study was supported in part by the National Science Foundation’s NSF-SBIR Phase II Award No. 2304528 and the USDA’s National Institute of Food and Agriculture, Hatch projects ARK0–2734 and ARK0–2852.
The University of Arkansas System Division of Agriculture’s mission is to strengthen agriculture, communities, and families by connecting trusted research to the adoption of best practices. Through the Agricultural Experiment Station and the Cooperative Extension Service, the Division of Agriculture conducts research and extension work within the nation’s historic land grant education system.
The Division of Agriculture is one of 20 entities within the University of Arkansas System. It has offices in all 75 counties in Arkansas and faculty on three system campuses.
Pursuant to 7 CFR § 15.3, the University of Arkansas System Division of Agriculture offers all its Extension and Research programs and services (including employment) without regard to race, color, sex, national origin, religion, age, disability, marital or veteran status, genetic information, sexual preference, pregnancy or any other legally protected status, and is an equal opportunity institution.
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Mario Soto, left, a master's student in the crop, soil and environmental sciences department, and Aurelie Poncet, assistant professor of precision agriculture in the crop, soil and environmental sciences department for the Division of Agriculture and the Dale Bumpers College of Agricultural, Food and Life Sciences, demonstrate a piece of equipment used in a study to measure herbicide effectiveness on plants.
