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In a groundbreaking advancement for artificial intelligence in healthcare, researchers at Mass General Brigham have unveiled BRIDGE, a comprehensive multilingual benchmark designed to critically assess how effectively large language models (LLMs) comprehend and interpret clinical patient-care text. Unlike existing AI evaluation metrics that rely primarily on structured and standardized medical exam questions, BRIDGE is engineered to engage with the multifaceted and complex language found in real-world clinical communications, including electronic health records (EHRs), case reports, and patient-doctor consultations, across nine different languages. This innovation represents a transformative step toward making AI tools more reliable and contextually aware in actual healthcare settings.
The existing paradigm in medical AI evaluation has predominantly centered on licensing exam questions composed in a controlled, formalized medical lexicon. These assessments, while rigorous, often fall short of reflecting the nuanced, variable, and sometimes ambiguous language used in actual clinical environments. The BRIDGE benchmark circumvents this limitation by employing authentic clinical texts, which capture the complexities and heterogeneity inherent to patient care dialogues, medical documentation, and clinical decision-making processes. This shift brings essential granularity and relevance to model performance metrics, providing clinicians and developers with more actionable insights.
The creators of BRIDGE demonstrated the stark contrast in performance between conventional exam-based evaluations and real-world clinical comprehension. For instance, the highest-performing LLM evaluated scored impressively on standard medical exams, achieving up to 92%. However, when subjected to BRIDGE’s rigorous clinical text test, the same model’s proficiency plummeted to only 44.8%. This significant disparity exposes considerable gaps in the AI’s ability to grasp the subtle clinical context, implicit meanings, and domain-specific language patterns prevalent in healthcare communications.
To validate the robustness and breadth of BRIDGE, the research team conducted a systematic performance evaluation of 95 distinct LLMs sourced from 59 different clinical AI initiatives. These models were subjected to a comprehensive battery of real-world clinical tasks encompassing the entire patient care continuum, ranging across 14 medical specialties. The tasks included patient triage, extraction of critical information from records, diagnostic reasoning, prognostic forecasting, and administrative functions such as billing code assignment. This extensive benchmarking provides a panoramic view of LLM capabilities and limitations in diverse clinical scenarios.
One of the more innovative features of BRIDGE is its public and continuously updated leaderboard hosted on the Hugging Face platform. This dynamic leaderboard catalogs the performance metrics of over 100 LLMs, enabling stakeholders including clinicians, health administrators, and AI developers to track comparative model efficacy in near real-time. The leaderboard thus fosters transparency and spurs iterative improvements by highlighting strengths and vulnerabilities within specific clinical tasks or language domains.
Another salient discovery made possible by BRIDGE is the identification of variability in AI performance across different medical specialties. Given that the benchmark corpus includes nine languages, the tool also illuminates disparities in model effectiveness when dealing with non-English clinical texts. This multilingual adaptability is particularly crucial as healthcare becomes more globally interconnected, underscoring the urgent need to develop culturally and linguistically sensitive AI applications that avoid exacerbating health inequities.
The scientific rigor of BRIDGE is underscored by its deep collaboration among experts spanning pharmacoepidemiology, pharmacoeconomics, clinical medicine, and computational modeling. The team includes senior authors such as Jie Yang, PhD, and Joshua Lin, MD, along with co-first authors Jiageng Wu and Bowen Gu, whose collective expertise was critical in ensuring the benchmark’s relevance and accuracy. Such interdisciplinary engagement is vital for bridging the gap between AI innovation and clinical applicability.
BRIDGE’s architecture and methodology leverage advanced computational simulation and modeling techniques, facilitating nuanced task designs that mimic real clinical workflows. This approach allows the benchmark to capture the dynamic and context-rich nature of clinical text interactions, incorporating elements like colloquial doctor-patient exchanges, complex diagnostic narratives, and procedural documentation. Consequently, BRIDGE functions as a high-fidelity proxy for real healthcare communication scenarios, offering a much-needed calibration tool for medical LLMs.
Funding generously provided by the Patient-Centered Outcomes Research Institute, the National Institutes of Health, and institutional scholarships reflects the strategic priority placed on refining AI’s role in healthcare delivery. Moreover, the rigorous conflict of interest disclosures and adherence to institutional compliance underscore the study’s commitment to transparency and ethical research standards. These factors enhance the credibility of BRIDGE as a benchmark tool destined to influence clinical AI development profoundly.
Importantly, BRIDGE is more than a passive evaluation tool—it is a catalyst for elevated AI design tailored to the clinical domain. By exposing the blind spots and differential performance across specialties and languages, it empowers AI developers to iterate more purposefully, embedding clinical nuance and real-world complexity into model training. This iterative feedback loop has the potential to accelerate the maturation of AI models from theoretical capabilities to practical clinical decision-support systems.
The release of BRIDGE is poised to address one of the persistent challenges in clinical AI—trust. Reliable understanding of patient-care language is paramount to fostering clinician confidence in AI-assisted diagnoses, prognoses, and patient management recommendations. The benchmark’s capacity to expose and rectify shortcomings before clinical deployment mitigates risks of errors caused by misinterpretation of nuanced clinical text, thereby safeguarding patient safety and improving care outcomes.
In closing, BRIDGE exemplifies a paradigm shift that acknowledges the inherent complexities of clinical language and seeks to elevate the fidelity of AI’s interpretative functions accordingly. As healthcare continues its digital transformation, integrating intelligent systems into everyday practice demands benchmarks as sophisticated and reflective as the environments they serve. BRIDGE sets a new gold standard in this endeavor, bridging the divide between cutting-edge AI performance and meaningful clinical utility.
Subject of Research: People
Article Title: BRIDGE: benchmarking large language models for understanding real-world clinical practice texts
News Publication Date: 17-Jun-2026
Web References:
References: Wu, J. et al. “BRIDGE: Benchmarking Large Language Models for Understanding Real-world Clinical Practice Text” Nature Biomedical Engineering DOI: 10.1038/s41551-026-01719-2
Keywords: Artificial intelligence, machine learning, clinical medicine, large language models, electronic health records, multilingual AI, clinical text comprehension, medical AI benchmarking, healthcare AI, patient care AI
Researchers have uncovered a massive breach of Fortinet firewalls that has given Russian-speaking attackers near-unrestricted access to some of the world’s largest and most powerful organizations, including Oracle, Chevron, Lenovo, Federal Express, a NATO defense contractor, and Fortinet itself.
Nearly 74,000 Fortinet devices from more than 21,000 IP addresses in 194 countries have been compromised and their plaintext credentials exposed online, Bob Diachenko, a security researcher and head of SecurityDiscovery.com, said online and in an interview. He said he found the data after gaining access to the attackers’ command-and-control server and other infrastructure. The exposed data also included the industry, revenue, and employee count for each compromised organization.
Independent researcher Kevin Beaumont reported that “almost all” of the compromised devices remained online as of Wednesday morning. He went on to say that he has confirmed with multiple organizations found in the attackers’ logs that the credentials are real and current. In many cases, once the threat actors compromised the devices, they went on to access affected organizations’ centralized authentication systems, such as Radius servers and Microsoft Active Directory. The number of compromised devices comprises roughly half of all Internet-facing Fortinet firewalls, based on polling from Shodan.
© Getty Images
Each year, nearly 800,000 Americans survive a stroke, embarking on a challenging journey toward recovery marked by relearning foundational motor skills such as walking. The aftermath of a stroke often results in muscle weakness, impaired coordination, and compromised leg control, making even the simplest of movements daunting. Traditional rehabilitation protocols heavily depend on intensive, therapist-led sessions where patients progressively regain mobility, independence, and confidence. However, the physical demands on therapists and the limitations of conventional methods necessitate innovative approaches that can enhance therapy effectiveness while mitigating therapist fatigue.
A groundbreaking study led by researchers from Shirley Ryan AbilityLab and Northwestern University introduces a novel paradigm that integrates lower-limb exoskeletons to enhance therapist-patient interaction during functional gait training. Published in the prestigious journal Science Robotics, the study unveils a transformative approach termed Therapist-Exoskeleton-Patient Interaction (TEPI). This system connects a therapist and a stroke survivor physically via complementary lower-limb exoskeletons, linked through virtual spring-damper elements at the hips and knees. This design facilitates real-time bidirectional physical interaction, where the therapist’s movements dynamically guide and respond to the patient’s gait by modulating forces through the exoskeleton interface.
Conventional physical therapy for gait rehabilitation involves therapists providing hands-on corrective assistance to patients, focusing typically on isolated aspects of walking mechanics due to their ability to assist only a limited number of joints or movements simultaneously. Complex, whole-body retraining often demands multiple therapists, posing logistical and physical constraints. While robotic rehabilitation devices can increase therapy intensity by enabling prolonged walking practice, most systems operate on preprogrammed, fixed movement trajectories that lack the flexibility to adapt instantaneously to patient performance or allow meaningful therapist input. This gap limits personalized care and the nuanced adaptability essential in neurorehabilitation.
TEPI fundamentally redefines this intervention landscape by leveraging the dexterous control capabilities of therapists in conjunction with robotic consistency and scalability. Through the exoskeleton-mediated connection, therapists can impose finely tuned guidance, resistance, or assistance, tailored in real time to the patient’s biomechanical status and response patterns. This synergy allows the therapy to encompass intricate whole-body dynamics within a single therapeutic session, eliminating the need for multiple practitioners in many cases. Moreover, the system’s responsiveness facilitates continuous adjustment throughout the gait cycle, enhancing motor learning through immediate feedback.
During the pilot evaluation involving eight stroke survivors, TEPI was contrasted with conventional therapist-guided treadmill walking sessions. Quantitative motion analysis revealed that TEPI training elicited significantly greater joint range of motion, augmented step length, and increased step height compared to standard therapy. Electromyographic assessments indicated comparable muscle activation patterns between the two modalities, affirming that TEPI does not compromise neuromuscular engagement while augmenting kinematic outcomes. Subjective evaluations reflected high patient motivation and enjoyment, underscoring the system’s potential to enhance adherence and therapeutic enthusiasm.
The TEPI framework also addresses a critical occupational health issue: therapist fatigue and injury risk associated with manual gait rehabilitation. By externalizing some physical effort to the exoskeleton-mediated interaction, therapists can guide patient movements more sustainably and ergonomically. This innovative method not only preserves the expertise of hands-on care but also reduces the biomechanical strain on providers, potentially extending the longevity and well-being of rehabilitation professionals.
From an engineering perspective, the system employs a sophisticated control architecture that harmonizes the exoskeleton’s stiffness and damping properties with the therapist’s voluntary movements. The virtual spring-damper coupling dynamically modulates mechanical impedance at key lower-limb joints, enabling a naturalistic yet controlled interaction paradigm. This technical advancement permits the system to act almost like an intelligent mechanical extension of the therapist’s own legs, enabling seamless transfer of movement intent and corrective forces.
Looking ahead, the researchers plan to expand the TEPI model beyond treadmill walking to include overground ambulation, stair navigation, and sit-to-stand transitions—functional tasks that more holistically represent daily living activities. The capacity to apply this approach across varied locomotor challenges promises to broaden its clinical applicability and deepen its therapeutic impact. Furthermore, scaling the technology into more accessible and user-friendly configurations could facilitate home-based rehabilitation, supporting remote care delivery and extending therapeutic supervision beyond clinical settings.
Such remote rehabilitation capability aligns with emerging trends in teletherapy and digital health, addressing barriers to access and continuity of care, especially for patients in underserved regions or with mobility limitations. By integrating sensor networks, adaptive control algorithms, and connectivity protocols, future iterations of TEPI could enable therapists to remotely guide patients through personalized gait training regimens with real-time haptic feedback and data monitoring.
This pioneering work symbolizes a major step forward in merging human expertise and robotic technology to optimize post-stroke rehabilitation. By synergizing the adaptability and intuitive understanding of therapists with the precision and endurance of robotic exoskeletons, TEPI opens a new frontier for restoring functional mobility—ultimately enhancing quality of life for millions of stroke survivors.
The collaborative research team behind this innovative study includes José L. Pons, PhD, scientific chair at Shirley Ryan AbilityLab and professor at Northwestern University; postdoctoral researchers Lorenzo Vianello, PhD, and Matthew R. Short, PhD; and co-first author Emek Barış Küçüktabak, PhD. Their collective expertise spans neurorehabilitation, robotics, and biomechanical engineering, driving the development of this cutting-edge, translational technology.
As the field advances, the TEPI approach may serve as a blueprint for next-generation rehabilitation robotics, where human-robot collaboration is optimized to support recovery from complex neurological impairments. The blend of immersive therapist control, real-time adaptability, and patient-centered design embodied by TEPI heralds a new era in rehabilitation science—one poised to transform care standards and patient outcomes.
Subject of Research: People
Article Title: Therapist-exoskeleton-patient interaction for gait therapy
News Publication Date: 17-Jun-2026
Web References: DOI link
Image Credits: Shirley Ryan AbilityLab
Keywords: Health care, Diseases and disorders, Biomedical engineering
Rivers serve as the lifeblood of our planet, weaving through landscapes and ecosystems while sustaining human civilizations. Despite their critical importance, many rivers remain under-studied, often due to the difficulties presented by their accessibility and variability. Small streams can be intermittent and unpredictable, sometimes disappearing for months or even years. This presents a formidable challenge for hydrologists and environmental scientists tasked with understanding these dynamic systems and their impact on water resources. Now, cutting-edge satellite remote sensing technology is revolutionizing how researchers monitor and analyze river health and water quality on a global scale.
Professor Dongmei Feng of the University of Cincinnati is at the forefront of this emerging discipline. Specializing in hydrological modeling and remote sensing, Feng recognizes that satellite data offers an unprecedented opportunity to observe rivers wherever they flow, even those in remote or inaccessible regions. Through spectral analysis of satellite imagery, scientists can detect changes in water quality and identify key pollutants, nutrients, and biological stressors that are difficult to measure through traditional fieldwork alone. This technology enables continuous and comprehensive monitoring, which is essential in managing freshwater resources sustainably.
The article recently published in Nature Water by Feng and her international collaborators underscores the importance of a holistic yet detailed approach to river science. By combining systematic review techniques with satellite-based observations, the researchers advocate studying rivers both individually and collectively. Each river exhibits a unique combination of climatic conditions, geographical features, and human impacts, which influence its health and quality. Understanding these nuances at multiple scales is crucial for predicting the rivers’ response to environmental pressures and human activities.
Rivers are not isolated entities; they are integral to planetary processes, acting as conduits connecting terrestrial landscapes with oceans and the atmosphere. The sediment and nutrients transported from rivers to estuaries serve as essential nourishment for diverse marine ecosystems. Estuaries themselves act as critical breeding grounds and nurseries for countless marine species, making the health of upstream river systems vital to ocean biodiversity. Satellite remote sensing provides a powerful lens through which to monitor these interactions in near real-time with astonishing spatial coverage.
One of the most pressing global environmental concerns linked to river systems is nutrient pollution, which frequently leads to harmful algal blooms. These blooms, fueled by excess nitrogen and phosphorus from fertilizer runoff and sewage discharge, pose severe risks to public health and aquatic ecosystems. Professor Feng’s ongoing research, supported by a substantial grant from the National Science Foundation, aims to unravel nutrient dynamics over the past five decades across multiple rivers worldwide. This extensive historical analysis is anticipated to improve early warning systems, allowing water managers to preemptively respond to developing algal blooms before they reach toxic levels.
The biogeochemical cycles underlying these nutrient movements involve complex feedback mechanisms. Algal blooms block sunlight from penetrating the water column, suffocating submerged vegetation that supports aquatic life. Upon decomposition of the dead algae, oxygen levels in the water plummet, creating ‘dead zones’ where fish and other organisms cannot survive. This process, known as eutrophication, exemplifies how human-induced nutrient loading can trigger cascading ecological failures. Understanding and modeling this cycle is critical for devising targeted mitigation strategies.
Satellite technology, combined with sophisticated computer modeling, is revolutionizing the ability to track water quality parameters such as turbidity, chlorophyll concentration, and dissolved organic matter with unprecedented precision. Dr. Xiao Yang from Southern Methodist University highlights how spectral signatures obtained from satellites can differentiate among various pollutants and ecological indicators. This technological advancement enables continuous global surveillance and geographically detailed water quality assessments that were not feasible before.
The applications of these remote sensing tools extend beyond academic research; they have real-world implications for managing urban infrastructure and protecting public health. Cities that rely heavily on river water for drinking need accurate and timely data to prevent toxic algal contaminants from entering treatment plants. Given that around 90% of the world’s population lives within six miles of a river, technological breakthroughs in monitoring river systems have direct societal benefits, including safeguarding drinking water, supporting recreational activities, and preserving biodiversity.
Moreover, this satellite-enabled river science promises to illuminate previously hidden aspects of hydrological variability and change. By tracking fluctuations in river flow and quality across diverse climatic zones, researchers hope to better understand how climate change will impact freshwater availability and ecosystem services. The integration of historical datasets with contemporary remote sensing observations offers a pathway to predictive models that inform adaptation and conservation efforts worldwide.
The multidisciplinary collaboration evident in Feng’s study incorporates expertise from hydrology, environmental engineering, satellite physics, and data science. Such integrative research approaches are becoming increasingly necessary to tackle complex environmental challenges that span geographic and disciplinary boundaries. The comprehensive global perspective championed in this research paves the way for a new era of river science, where policy decisions and resource management are underpinned by data-driven insights and continuous observation.
As research progresses, the challenge will be to translate these tremendous amounts of data into actionable knowledge. This entails developing user-friendly platforms for water managers and policymakers to interpret satellite-derived information effectively. Ensuring accessibility while maintaining scientific rigor requires ongoing innovation in data analytics and communication. Nonetheless, the promise of these technological tools to safeguard freshwater resources against pollution and ecological degradation has galvanized the scientific community and stakeholders alike.
In conclusion, the integration of satellite remote sensing into river science marks a transformative advancement in understanding and managing one of Earth’s most essential natural resources. Pioneered by experts such as Professor Dongmei Feng, this approach enables scientists to overcome traditional barriers to studying rivers, track nutrient pollution trends, and predict ecological threats such as toxic algal blooms. As the global population continues to grow and climate change accelerates, technologies that provide real-time, global-scale insights into river ecosystems are indispensable for sustainable water management and environmental protection.
Subject of Research: Hydrology, water quality control, and nutrient dynamics in rivers using satellite remote sensing technology.
Article Title: Remote sensing and the new global river science
News Publication Date: 17-Jun-2026
Web References: DOI: 10.1038/s44221-026-00665-2
Image Credits: Andrew Higley
Keywords: Hydrology, Water quality control, Sewage treatment, Water delivery, Environmental engineering, Natural resources management, Pollution control
According to Keir Starmer, a teenager doesn’t have the judgement to scroll through Instagram without state supervision, but does have the judgement to pick the next government. We are governed by idiots, says Clive Pinder.
The post Too Young for TikTok, Old Enough to Vote? appeared first on The Daily Sceptic.
Corvids, including ravens and crows, have earned a reputation for being some of the smartest birds on Earth. They can recognize human faces, use tools, solve multistep puzzles and even hold funerals.
In recent years, scientists have added another surprising skill to the list: a grasp of numbers. Research suggests that corvids can distinguish between different quantities and, in some cases, even perform statistical analysis.
These discoveries have raised a provocative question: How deep do the roots of mathematical thinking go? While modern humans are the only known species to develop formal mathematics, studies of crows, monkeys and other animals suggest that the cognitive building blocks of math may have evolved hundreds of millions of years before people began doing calculations.
Few researchers have done more to uncover these abilities than Andreas Nieder, a professor of animal physiology and the director of the Institute of Neurobiology at the University of Tübingen in Germany. By examining the neural activity of both monkeys and crows, Nieder has found evidence that very different animal brains can process numerical information in surprisingly similar ways. Live Science spoke with Nieder about how these findings may reveal that the origins of mathematics are far older than our species.
Kenna Hughes-Castleberry: How did you get into researching crows and primates?
Andreas Nieder: After studying the auditory and visual systems for several years as a student, I realized that I wanted to focus on the neuronal foundations of intelligence and cognitive control functions. How does the brain give rise to abstract concepts, working memory, or the ability to follow complex rules deliberately? Of course, to study intelligence, you need intelligence specialists. I therefore began working with primates — more specifically, rhesus monkeys, arguably among the most intelligent mammals. They are closely related to humans, possess relatively similar brains, and share many cognitive abilities with us.
However, as a trained biologist, I was always interested in a broader evolutionary question: Are sophisticated cognitive abilities unique to mammals, or can they emerge in very different brains? Crows provided an ideal comparative species. Birds diverged from mammals more than 360 million years ago — roughly six times longer ago than the extinction of the dinosaurs. Yet despite this immense evolutionary distance, corvids display remarkably flexible behavior; in many ways, they are the feathered primates of the air.
Some are reliable, highly motivated workers that perform consistently day after day. Others are sensitive divas who seem to require special treatment before they are willing to cooperate.
Andreas Nieder
KHC: Are crows difficult to study? Are they fun? Do they have personalities?
AN: Both primates and crows are demanding to study. Because they are highly intelligent, they require special housing and care. Since we investigate cognitive abilities under tightly controlled experimental conditions, they also require extensive behavioral training by skilled personnel. And, of course, the regulations governing research with these species are particularly strict.
At the same time, they are fascinating research subjects. Individual monkeys and crows differ noticeably in temperament and behavior. Some are curious and adventurous, others are cautious and reserved, and some learn new tasks much faster than others.
Their qualities can be quite striking. Some are reliable, highly motivated workers that perform consistently day after day. Others are sensitive divas who seem to require special treatment before they are willing to cooperate. Researchers generally avoid anthropomorphizing, but there is little doubt that individual animals exhibit stable behavioral traits that we would reasonably describe as distinct characters.
KHC: You've found that crows understand the concept of zero. How do we know this?
AN: We trained crows to recognize different numbers — sets containing one, two, three, four objects, and so forth. We then included trials in which no items appeared at all. The remarkable finding was that the birds treated an empty set as a quantity and as part of the numerical continuum. They behaved as though the empty set belonged before "one." Their error patterns were particularly revealing: They confused zero more often with one than with larger numbers, exactly as one would expect if zero were mentally represented as a numerical quantity next to one. In addition, recordings from neurons in the crow brain showed cells that responded selectively to empty sets. This suggests that zero is not merely a behavioral trick but is represented neurally as a meaningful numerical category.
KHC: To play devil's advocate, is the ability to recognize the difference between something and the lack of something really that surprising? Is it akin to the human concept of zero?
AN: That's an important question. Simply recognizing that nothing is present or absent is not surprising. Many animals can distinguish between the presence and absence of objects. The key issue is whether they treat "nothing" as a quantity that can be compared to other quantities.
Our experiments suggest that crows do more than detect absence. They position empty sets within an ordered numerical sequence, at the low end of the number line, and show distance effects similar to those observed with other numbers. For example, they find it easier to distinguish zero from two than zero from one.
That said, we should not claim that crows possess the full human mathematical concept of zero. Humans use symbolic zero in arithmetic, algebra, calculus and formal mathematics. What we have demonstrated is a foundational precursor: a nonsymbolic numerical representation of zero. This may represent an evolutionary building block from which more sophisticated human concepts eventually developed.
KHC: You've also found that crows can perform statistical analysis. Tell me more about these findings and what you showed.
AN: We trained carrion crows [Corvus corone] to associate a series of arbitrary visual signs, colored geometric images displayed on a touch screen, with different reward probabilities. One sign might yield a food reward 90% of the time, another 70%, another 50%, and so on down to 10%. Importantly, the signs themselves carried no inherent meaning; the birds had to learn these probabilities through experience.
Once the birds had learned these sign-probability associations, we presented them with pairs of signs and asked them to choose one. To maximize their rewards, they should select the sign associated with the higher reward probability. The crows did exactly that. Even when confronted with many novel pairings, they reliably chose the statistically more favorable option.
This does not mean that crows perform formal statistics in the human sense. They are not calculating percentages or solving probability equations. However, the results show that they can extract probabilistic regularities from experience, store this information in memory, and use it flexibly to make reward-maximizing decisions under uncertainty. These are fundamental ingredients of statistical reasoning and are highly valuable in natural environments, where animals constantly have to make decisions based on incomplete information.
KHC: Have researchers tried similar tests on babies or young humans, and if so, how do we stack up?
AN: Yes. Developmental psychologists have conducted many related studies with infants and young children. Even before learning language, infants show sensitivity to quantities, numerical differences and simple probabilistic information. By around 4 years of age, children also display an intuitive understanding of empty sets.
What is striking is that the behavioral signatures observed in crows resemble those seen in preverbal human infants and nonhuman primates. Of course, human children eventually develop symbolic mathematics through language, education and culture, which takes them far beyond the abilities observed in animals.
KHC: Can these findings tell us anything about how the human understanding of math evolved?
AN: They suggest that some foundations of mathematics may predate humans by a very long evolutionary timescale. Humans did not invent numerical intuition from scratch. Rather, we appear to have inherited ancient cognitive systems that allow brains to estimate quantities, compare numbers, and represent concepts such as zero approximately.
The fact that crows and primates — two distantly related groups — show similar numerical abilities suggests that these capacities may emerge whenever evolution favors flexible intelligence. Human mathematics likely built upon these ancient cognitive foundations and then expanded dramatically through language, symbols and culture.
What is striking is that the behavioral signatures observed in crows resemble those seen in preverbal human infants and nonhuman primates.
Andreas Nieder
KHC: What's something a general audience might be surprised to learn about crows?
Many people are surprised to learn that crows are songbirds. Most people associate songbirds with melodic singers such as nightingales or blackbirds, not with the harsh cawing of a crow. Yet crows do learn a significant part of their vocal repertoire and are even known as apt imitators, even of human speech sounds — the internet is full of funny videos in which crows imitate human speech.
What makes this particularly interesting is that their vocalizations are not merely reflexive calls. In our experiments, we found that crows can exert volitional control over their vocal behavior. They can learn to produce vocalizations in response to arbitrary cues and withhold them when required, demonstrating a level of cognitive control over vocal output that is considered an important prerequisite for complex communication and, ultimately, language.
More recently, we showed that crows can even use their vocalizations to count. In a recent study published in [the journal] Science, we trained crows to produce a specific number of calls — between one and four — in response to visual or auditory cues. Remarkably, they not only generated the correct number of vocalizations but also appeared to prepare the intended number before they started calling. This suggests that they can represent numerical information and use it to guide a self-generated sequence of vocal actions.
Taken together, these findings show that crow vocalizations are far more sophisticated than most people assume. Their characteristic "caw" is not just a simple call — it can be brought under deliberate cognitive control and even used to express numerical information. For a bird, that is a remarkably advanced ability.
This interview has been edited for length and clarity.
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In recent years, forests have emerged as pivotal players in global climate mitigation efforts, representing one of the most promising nature-based climate solutions available today. These ecosystems sequester approximately 31% of anthropogenic carbon dioxide emissions annually, providing a critical buffer against the accelerating pace of climate change. However, the reliability of forest carbon credit systems—mechanisms designed to monetize and incentivize carbon sequestration efforts—has come under intense scrutiny. A groundbreaking study published in the journal Biological Diversity unveils deep-rooted methodological flaws that cast profound doubt on the environmental integrity of current carbon credit frameworks, signaling a crisis of confidence across global carbon markets.
The rigorous analysis, spearheaded by environmental scientists from Yangtze University and Beijing Normal University, meticulously dissects the complex architecture of forest carbon credit systems and identifies four principal structural weaknesses that collectively undermine their trustworthiness. Foremost among these is the use of subjective assessments of additionality, a core concept requiring that credited emissions reductions would not have occurred in the absence of the project. Present carbon credit models predominantly rely on static historical baselines to calculate additionality, yet only an alarming 6% of REDD+ credits—credits allocated under the United Nations’ Reducing Emissions from Deforestation and Forest Degradation program—provide robust empirical evidence to substantiate genuine additional carbon mitigation.
Beyond the critical challenge of additionality, the permanence of carbon sequestration—signifying the long-term retention of carbon stock in forest biomass—is grossly overestimated by current standards. This overestimation is particularly precarious in light of escalating ecological disturbances linked to climate change including wildfires, prolonged droughts, pestilence outbreaks, and inadvertent carbon leakage where forest degradation shifts to unmonitored regions. The failure to appropriately incorporate these growing risks into permanence calculations means that many credited projects likely exaggerate their true contribution to climate mitigation, presenting an illusory picture of impact.
The study further reveals that leakage accounting—the assessment and adjustment for project-driven emissions displacement—is critically underdeveloped. Prevailing methodologies apply a modest average leakage deduction of only 7%, a figure that starkly contrasts with empirical findings suggesting leakage rates ranging from 10% to a staggering 70%. Such systemic under-accounting inflates the perceived net climate benefits of these forest projects, enabling an artificially optimistic valuation of carbon credits within international markets and undermining carbon trading integrity.
Compounding these shortcomings are the conspicuous omissions of biophysical impacts such as albedo and evapotranspiration effects in carbon accounting. Forest ecosystems substantially influence Earth’s energy balance through their reflectance properties and water cycling functions. Neglecting these elements obscures the true net climate impact, as alterations in surface albedo can significantly offset the cooling benefits gained from carbon sequestration, thereby diluting the overall effectiveness of forest-based interventions in climate regulation.
The collective failure to address these intertwined issues has deep ramifications not only for the credibility of carbon markets but also for biodiversity conservation and community well-being, which are often marginalized in project implementation. Insufficient local community involvement and opaque benefit-sharing arrangements risk alienating indigenous stakeholders, raising social equity concerns, and jeopardizing the sustainability and durability of mitigation efforts.
In response to these multifaceted challenges, the research team advocates for a transformative overhaul of forest carbon credit systems through a data-driven, science-based, and integrative accounting framework. Central to this reform is the replacement of static baselines with dynamic monitoring systems that leverage high-frequency remote sensing technologies alongside advanced machine learning algorithms. This approach enables objective, continuous, and quantitative assessments of additionality, dramatically enhancing transparency and scientific rigor in credit issuance.
Addressing permanence requires the establishment of a comprehensive three-tier risk management architecture comprised of prevention, buffering, and insurance mechanisms. This tiered system proactively mitigates disturbances by integrating biodiversity conservation as a mandatory compliance criterion rather than considering it a supplemental benefit, thus embedding ecosystem resilience at the heart of carbon project governance.
Transparency and standardization are equally emphasized through the call for stringent Monitoring, Reporting, and Verification (MRV) protocols. The use of cutting-edge technologies such as Light Detection and Ranging (LiDAR) and environmental DNA (eDNA) is prescribed to ensure precise biomass and biodiversity assessments. Additionally, mandatory disclosure of datasets and verification methodologies aims to foster independent third-party audits, enhancing accountability and stakeholder confidence in carbon accounting practices.
Sociopolitical dimensions are also addressed, with the framework highlighting the critical necessity of formalized community governance structures and the institutionalization of Free, Prior, and Informed Consent (FPIC) procedures. These mandates ensure that forest-dependent communities retain decision-making power and equitable access to the socioeconomic benefits derived from carbon sequestration projects, thereby reinforcing local stewardship and long-term project viability.
While the introduction of these rigorous standards is expected to contract the overall volume of carbon credits issued—reflecting a more conservative and realistic accounting of mitigation gains—the resultant credits will embody higher integrity and trustworthiness. This qualitative transformation is paramount for forest carbon credits to evolve from contested commodities susceptible to skepticism into robust and reliable assets underpinning credible global climate governance.
The implications of this research are profound. By embedding scientific rigor and standardized risk management, forest carbon credits can realize their full potential as durable climate mitigation tools while simultaneously safeguarding biodiversity and respecting community rights. This paradigm shift promises to restore confidence among stakeholders, catalyze more effective climate finance mechanisms, and advance global efforts to stabilize the Earth’s climate system.
Ultimately, this work underscores a crucial message: nature-based climate solutions like forests must be governed by scientifically sound and socially just frameworks. Only through such commitment to transparency, accuracy, and inclusivity can these natural assets deliver genuine and lasting contributions to the fight against climate change.
Subject of Research: Not applicable
Article Title: Restoring Trust: Rebuilding the Forest Carbon Credit System Through Scientific Rigor
News Publication Date: June 17, 2026
Web References: http://dx.doi.org/10.1002/bod2.70026
References: Chen, Xiaoqian, and Shaokun Li. 2026. “Restoring Trust: Rebuilding the Forest Carbon Credit System Through Scientific Rigor,” Biological Diversity: 1–5.
Image Credits: Xiaoqian Chen, and Shaokun Li
Keywords: Environmental sciences, Carbon emissions, Biodiversity conservation, Climate change mitigation, Risk management, Deforestation, Community ecology, Albedo, Resource policy, Environmental economics, Sustainable development, Land use, Climate change adaptation, Forestry, Carbon, Environmental policy, Environmental impact assessments, Environmental management, Remote sensing, Forest ecosystems
In the relentless quest to uncover signs of life beyond Earth, scientists have turned their gaze towards the mysterious realms of ocean worlds—icy moons like Enceladus, Europa, and Titan. These celestial bodies harbor vast, hidden oceans beneath their frozen crusts, creating environments that could potentially support life. Yet, the challenge remains daunting: distinguishing genuine biological signatures from complex abiotic processes that could mimic these signals. A groundbreaking study recently published in Nature Astronomy proposes a sophisticated quantitative framework designed to rigorously evaluate these abiotic baselines on ocean worlds, shedding new light on how future life detection missions might navigate this delicate terrain.
Ocean worlds have captivated astrobiologists not merely because they contain liquid water, a fundamental criterion for habitability, but also because they offer diverse chemical environments where life as we know it might exist. However, confirming the presence of life requires more than spotting chemicals commonly associated with biology; it demands a nuanced understanding of how non-biological processes could generate similar signals, muddying the interpretative waters. The novel framework developed by Higgins, Chen, Warr, and colleagues provides an unprecedented approach to dissect this ambiguity, employing Enceladus as a primary example to demonstrate its utility.
At the heart of the study lies the challenge of interpreting isotopic measurements, particularly of methane (CH₄) and carbon dioxide (CO₂), molecules widely regarded as potential biosignatures due to their roles in Earth’s carbon cycle. The study scrutinizes the isotopic ratios of these molecules, expressed as δ¹³C values, which reflect the ratio of carbon-13 to carbon-12 isotopes. Traditionally, biological processes tend to prefer lighter isotopes, leading to distinctive fractionation patterns. However, the researchers highlight that uncertainties inherent in abiotic chemistry within Enceladus’ ocean and vent systems can produce isotopic signatures overlapping with those produced by biological activity, thereby defying straightforward interpretation.
The implication is profound: future missions that might measure δ¹³C in carbon-bearing molecules emanating from Enceladus’ plumes could misinterpret data, either falsely declaring a biosignature or overlooking subtle hints of life concealed beneath abiotic noise. The framework thus urges caution against over-reliance on isotopic biosignatures without a comprehensive assessment of the abiotic baseline. This is a pivotal insight that recalibrates how missions might prioritize scientific instruments and analytical strategies aboard orbiters or landers.
Complementing isotopic analysis, the study explores amino acid chirality as an alternative biosignature. Chirality, the “handedness” of molecules, is a hallmark of terrestrial biology, as living organisms almost exclusively synthesize left-handed amino acids. Nevertheless, the researchers caution that abiotic synthesis of amino acids on ocean worlds, influenced by factors such as radiation, mineral surfaces, and catalytic processes, could yield racemic mixtures or even chiral excesses unrelated to life. This ambiguity necessitates robust characterization of abiotic organic chemistry before interpreting chirality as a definitive biosignature in extraterrestrial contexts.
Another layer of complexity arises from the physical and geological attributes of the ocean worlds themselves. The study emphasizes that factors like internal temperature gradients, rheology (the deformation behavior of the icy shell and underlying materials), and lithology (rock types beneath the ocean) significantly influence abiotic chemical pathways. Understanding these properties with finer precision could narrow the range of isotopic and chemical signatures attributable to non-biological processes, thereby enhancing the confidence in detecting life.
Central to reducing the abiotic baseline uncertainty is the challenge of constraining the internal temperatures of ocean worlds. The framework points out that if internal temperatures can be pinpointed within a range of about 10 to 100 degrees Celsius, models of abiotic chemistry become markedly more predictive. Doing so would help delineate which molecular signals likely stem from hydrothermal activity and mineral interactions rather than biogenic outputs. This underscores the vital role of geophysical observations, such as gravity mapping, heat flux measurements, and ice shell thickness determinations, in complementing chemical analyses.
Transport timescales within the ocean and the overlying ice shell also feature as critical parameters. The timeframe over which molecules or small organic compounds travel from the ocean floor to the surface can alter their chemical and isotopic signatures dramatically. For instance, longer transport times may lead to isotopic exchanges or degradation processes that obscure the original biosignature signal. Hence, understanding ocean circulation patterns and ice shell permeability is integral to accurately interpreting any detected anomaly.
Expanding beyond Enceladus, the framework’s holistic approach is applicable to other ocean worlds such as Europa and Titan, each with their distinct environments and chemical contexts. On Europa, for example, the ocean’s interaction with a silicate seafloor and potential radiolysis-driven chemistry creates a different abiotic baseline compared to Enceladus. Titan’s complex organic-rich atmosphere and potential subsurface oceans add further layers of chemical diversity. The framework enables tailoring of life detection strategies and biosignature interpretations to these distinct habitats.
The study’s methodology can also inform future mission design, influencing instrument selection, sampling strategies, and data interpretation pipelines. By anticipating where abiotic ambiguity is most pronounced, mission planners can prioritize measurements that either better constrain abiotic baselines or provide multiple independent biosignature lines of evidence. This may include coupling isotopic data with mineralogical, geophysical, and molecular chirality information to build a more integrated and less ambiguous picture of habitability.
Furthermore, the framework embodies a precautionary principle against false positives and false negatives. Past and ongoing searches for life beyond Earth have grappled with ambiguous signals, from Viking’s methyl chloride controversy on Mars to debates over methane on the Red Planet. The ocean worlds’ complex chemistry and challenging environments elevate this problem, making a rigorous, quantitative approach like that offered by Higgins et al. indispensable in the life detection toolkit.
Importantly, this work illustrates the multidisciplinarity essential in astrobiology. Geochemistry, planetary science, biology, and physics converge to piece together the puzzle of extraterrestrial biosignatures. The framework’s integrated perspective exemplifies the collaborative spirit needed to interpret subtle clues from distant worlds and avoid the pitfalls of isolated or oversimplified analyses.
Looking ahead, technological advancements in both remote sensing and in situ exploration promise to enhance constraints on ocean world environments, thereby sharpening the framework’s applicability. For instance, sophisticated flyby missions or landers equipped with mass spectrometers, isotopic analyzers, and chiral detection capabilities may provide richer datasets. Simultaneously, laboratory simulations and terrestrial analog studies will refine models of abiotic chemistry and kinetics under relevant conditions.
The impact of this research extends beyond ocean worlds to the broader quest for life in the cosmos. The principles of robustly addressing abiotic baselines and embracing interdisciplinary data fusion can guide biosignature evaluation on exoplanets and other planetary bodies where life’s chemical fingerprints, if present, might be similarly elusive or confounded by non-biological processes.
In conclusion, the study spearheaded by Higgins and colleagues fundamentally reshapes our approach to biosignature interpretation on ocean worlds. By proposing a quantitative, comprehensive framework that weighs biosignature potential against carefully characterized abiotic backgrounds, it sets a new standard for rigor in the search for extraterrestrial life. As humanity’s exploration of the Solar System’s ocean realms advances, this framework will be pivotal in ensuring that claims of discovering life are grounded in unambiguous, scientifically defensible evidence.
Subject of Research: Evaluation of biosignature potential versus abiotic baselines on ocean worlds in the Solar System.
Article Title: A framework for evaluating biosignature potential against the abiotic baseline on ocean worlds.
Article References:
Higgins, P.M., Chen, W., Warr, O. et al. A framework for evaluating biosignature potential against the abiotic baseline on ocean worlds. Nat Astron (2026). https://doi.org/10.1038/s41550-026-02893-8
As Earth’s climate system evolves with unprecedented rapidity, forests — vital guardians of global ecological balance — are undergoing complex transformations that extend far beyond the mere sequestration of carbon. Emerging research has begun to unravel the subtle yet profound ways in which climate change reshapes the biophysical interactions between forested landscapes and their surrounding environments, particularly regarding land surface temperature dynamics. A recent groundbreaking study delves deep into these dynamics, revealing starkly contrasting trends that underscore the dualistic nature of forests as climate regulators amidst rising atmospheric dryness. This nuanced revelation challenges long-held assumptions about the uniform benefits of forest cooling and opens new frontiers for understanding ecosystem-climate feedbacks in the Anthropocene.
Forests have long been recognized as crucial climate buffers, primarily through their capacity for carbon storage and evapotranspiration-driven cooling effects. The new research pivots attention to a complementary biophysical mechanism: the difference in growing-season land surface temperature (LST) between forested areas and adjacent open lands, designated as ∆LSTgs. By systematically quantifying ∆LSTgs globally across a span of more than two decades (2001–2023), the researchers uncovered contrasting temporal patterns that vary profoundly with geography and changing atmospheric conditions. Notably, these patterns defy a simplistic narrative of consistent forest cooling, instead revealing a dynamic response heavily modulated by atmospheric humidity levels.
Central to these divergent forest temperature dynamics is the rising vapor pressure deficit (VPD), a measure of atmospheric dryness that quantifies the difference between the amount of moisture in the air and its saturation point. The study identifies VPD as the predominant driver behind the observed variations in ∆LSTgs, exerting a stronger influence than other conventional climatic factors such as temperature, precipitation, or solar radiation. This finding shines light on the critical role that atmospheric moisture stress plays in forest surface energy exchanges, fundamentally altering the cooling potential traditionally attributed to forests under wetter conditions.
However, the forest response to this intensifying atmospheric dryness is far from uniform across global biomes. The research highlights a pivotal interaction between VPD fluctuations and plant hydraulic traits, particularly stomatal regulation strategies embodied by anisohydricity, a measure of plants’ ability to regulate water loss through stomata under drought stress. Forests exhibiting high anisohydricity maintain more open stomata even under dry conditions, enabling continued transpiration and evaporative cooling but at increased risk of hydraulic failure. In contrast, isohydric forests tightly conserve water by closing stomata earlier, reducing cooling at the leaf surface.
Intriguingly, this stomatal regulatory behavior correlates with latitude, delineating distinct forest cooling trajectories. Tropical forests near the equator tend to display more isohydric characteristics. Here, rising VPD often surpasses the hydraulic safety threshold of these ecosystems, leading to stomatal closure and a consequent weakening of forest cooling effects. This trend portends a diminished capacity of tropical forests to mitigate local heating as atmospheric dryness intensifies, potentially accelerating heat stress on these already vulnerable ecosystems.
Conversely, high-latitude forests manifest a more anisohydric strategy, maintaining open stomata under increasing VPD levels that nonetheless remain within their hydraulic safety margins. As a result, these boreal and temperate forests continue to sustain transpiration-driven cooling, which paradoxically intensifies with rising VPD. This phenomenon enhances the biophysical benefits of northern forests, amplifying their role as regional climate coolants and underscoring the heterogeneous nature of forest climate feedbacks across latitudes.
This nuanced physiological interplay yields profound implications regarding future forest-climate interactions under global warming. It underscores that elevated atmospheric dryness will not only influence ecosystem carbon dynamics but also significantly alter the biophysical feedback mechanisms by which forests regulate surface temperatures. As VPD continues to climb worldwide, the traditional ecological services of forests, particularly their cooling benefits, may become compromised in many parts of the globe, particularly within tropical zones critical for biodiversity and global climate regulation.
Moreover, the study’s integrative approach—which combines satellite observations of surface temperature with detailed climatological measurements and physiological trait data—provides a comprehensive framework to understand how climatic stressors mediate forest cooling effects. By leveraging large-scale data spanning two decades, the researchers offer robust evidence that forest cooling is not static but dynamically contingent on complex interactions among atmospheric moisture, plant hydraulics, and geographic distribution, emphasizing the need for ecosystem-specific climate mitigation strategies.
The findings challenge the prevailing optimism about forests’ capacity to offset warming through biophysical means alone. In vulnerable tropical regions, the erosion of cooling benefits linked to stomatal closure under heightened VPD may exacerbate heat stress, increase fire risk, and undermine forest resilience. This could trigger feedback loops accelerating tropical forest degradation and amplifying global warming, raising alarm over the future of these essential carbon sinks.
Conversely, the sustained or even enhanced cooling in high-latitude forests might partially offset regional warming trends, but the balance of such compensatory effects at the global scale remains uncertain. These complexities highlight an urgent need to integrate physiological and biophysical forest attributes into predictive climate models, allowing for more accurate assessments of forest contributions to local and global temperature regulation.
Crucially, the research points to the hydraulic safety margin as a vital threshold parameter dictating the tipping points at which forests transition from cooling to warming agents. This insight offers potential pathways for management interventions aimed at bolstering forest hydraulic resilience, such as selective species planting or conservation strategies tailored to optimize ecosystem-level responses to rising VPD.
In a broader context, the study underscores that atmospheric dryness—often overshadowed by temperature-centric perspectives on climate change—constitutes a formidable and multifaceted challenge for forest ecosystems worldwide. Rising VPD alters not only physiological processes at the leaf level but also cascades through landscape-scale energy budgets, with cascading impacts on regional climate patterns, hydrology, and ecosystem services.
As the global community contemplates reforestation and afforestation policies as climate mitigation tools, these findings call for a recalibrated understanding that accounts for the limits imposed by plant hydraulic behavior and atmospheric moisture constraints. The simplistic paradigm of “more trees equal cooler climate” must evolve into a sophisticated appreciation of when, where, and how forest ecosystems can be expected to maintain their biophysical cooling contributions in a drying and warming world.
Ultimately, this pioneering research adds a critical dimension to our grasp of climate-vegetation feedbacks, illuminating the complex, sometimes counterintuitive outcomes of drying atmospheres on forested landscapes. By highlighting the paramount role of VPD and stomatal regulation across global latitudinal gradients, it informs the scientific community, policymakers, and conservationists alike about the nuanced realities shaping the future of Earth’s green lungs and their vital climate services.
Understanding these relationships better will be indispensable to crafting adaptable and resilient conservation strategies capable of sustaining the biophysical cooling functions of forests. The study’s revelations lay groundwork for future research probing genetic, species-specific, and ecosystem-level hydraulic traits, as well as remote sensing advancements to monitor forest physiological stress and energy exchanges in real time under changing climates.
As atmospheric dryness intensifies in the coming decades, the fate of forests as biophysical climate modulators will hinge on the delicate balance between environmental stressors and intrinsic plant water regulation mechanisms. This research presents an urgent clarion call to incorporate these intricate biophysical and physiological insights into forest management and climate policy frameworks, lest the cooling benefits of the planet’s forests risk becoming relics of a less-dry past.
Subject of Research:
Forest biophysical effects on land surface temperature under changing atmospheric dryness and climate conditions.
Article Title:
Globally constrained forest biophysical cooling benefits under rising atmospheric dryness.
Article References:
Zhang, C., Su, Y., Liao, Z. et al. Globally constrained forest biophysical cooling benefits under rising atmospheric dryness. Nat. Clim. Chang. (2026). https://doi.org/10.1038/s41558-026-02677-y
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