UNIVERSITY OF EXETER

UKRI Gateway to Research · FY 2026 · 2026-12

For over half a century, influential arguments have suggested that the demands of social life drive cognitive evolution. However, if cognition allows individuals to learn who best to associate with, individuals’ mental processes may shape societies in return. This feedback has far-reaching consequences: it can determine when cooperation arises, how information and disease spread, and how populations respond to environmental change. Yet, surprisingly, we do not understand when and how learning shapes social networks, or how this affects social and cognitive evolution. Our work will break new ground by revealing how learning and social structure co-evolve. Current understanding of this crucial issue is limited by two critical gaps: a lack of formal theory that generates testable predictions and major barriers to testing predictions under natural conditions. We will tackle both by developing new evolutionary models and testing them through innovative field experiments. Using individual-based evolutionary simulations we will determine when natural selection favours learning in social decision-making. Our models will predict how early-life conditions shape whether animals benefit from learning about potential mates and non-mating partners (who we loosely term “friends”), the trade-offs between learning about these different types of partners, and how these decisions shape social networks throughout life and over evolutionary time. Testing these predictions in the wild is extremely challenging, but our long-term study of hundreds of microchipped wild jackdaws – highly social birds of the large-brained crow family – makes it possible. We have pioneered automated experiments using microchip-detecting feeders that reward or block access depending on whom a bird associates with, letting us experimentally control the value of social partners and track how jackdaws learn to keep good partners and drop unreliable ones. By integrating these state-of-the-art experiments with call playbacks and long-term tracking of individual life-histories, we will reveal how learning shapes social choices and how these choices affect fitness and group structure. We will tackle three key questions, combining theory and empirical work to generate robust, broadly applicable insights: How does learning influence partner choice under different environmental conditions? By focusing on early-life conditions – the crucial period for socialisation – we will determine when selection favours learning to build social connections and the consequences of these choices across lifespans and generations. Why learn to make friends? The benefits of forming non-reproductive partnerships remain poorly understood. We will determine when it pays to invest in many weak friendships versus a few strong ones across different ecological contexts (foraging and anti-predator behaviour). How do trade-offs shape the co-evolution of learning and social structure? Because learning takes time, investing in learning about mates will trade off with learning about friends. We will uncover the fitness impacts of this trade-off and its role in shaping the evolution of learning abilities and diverse social systems. This project will transform our understanding of the interplay between individual decisions and social dynamics – a central problem in evolutionary biology, ecology, psychology and anthropology – with applied relevance for assessing whether animal societies can respond plastically to environmental change, a key conservation goal. By providing open access to our theoretical tools and long-term data, we will stimulate future research. We will also offer training and paid internships for early-career researchers, and deliver innovative outreach to inspire and engage diverse audiences and under-represented communities, helping train the next generation of scientists.

UKRI Gateway to Research · FY 2026 · 2026-10

Terrestrial ecosystems mitigate climate change by absorbing carbon dioxide (CO2) and currently offset about one third of annual human induced CO2 emissions. Central to developing effective climate policy is knowing the remaining carbon budget – the amount of CO2 humanity can still emit before reaching dangerous warming levels such as 2°C globally (above pre-industrial), one of the warming targets of the Paris Agreement. The remaining carbon budget is estimated using global models, making it critically important to accurately represent carbon sinks in such models and to have reliable data to evaluate their performance. This is now urgent, as we could reach global warming of 1.5°C as early as 2028. Terrestrial carbon sinks result from a small imbalance between two large opposing fluxes: uptake of carbon from the atmosphere through photosynthesis and carbon release via respiration from plants and soils. This project focuses on respiration, a critical but highly understudied component -that remains one of the most uncertain processes- of the terrestrial carbon cycle. This uncertainty limits our ability to accurately predict the current and future land carbon sink and thus the remaining carbon budget. Quantification and modelling of respiration at all scales - from ecosystem to global - remains a challenge. During the day plants both photosynthesise and respire, making it difficult to measure these processes in isolation. Conundrum: Current observational-based methods estimate daytime plant respiration by measuring respiration at night when photosynthesis doesn't happen and then apply simple temperature-based formulas. Modelling approaches also use simple relationships that only depend on temperature to represent nocturnal respiratory processes. However, data from our team shows respiration is not influenced by temperature alone. Under constant temperature, plant respiration declines on average by 25% during the night and shows significant diurnal variation during daytime (Figure-1). The Challenge Our findings are in contrast with most current carbon cycle research assumptions of constant respiration under constant temperature. Our research demonstrates that when respiration models include photosynthetic products as fuel for respiration, the observations under constant temperature can be explained. Aims and objectives The project (Figure-1) aims to solve this massive conundrum in carbon cycle research by using the new understanding from the team to transform modelling of respiration within the following key methodologies currently used in this field:  i) a well-established and highly used ecosystem level observational network, basis of our current understanding of ecosystem level carbon fluxes and foundational data to evaluate models, ii) global models and iii) machine learning products that use observational ecosystem level network data to upscale to the globe to produce global carbon fluxes for evaluation of global models. Impact The project will deliver new estimates of remaining carbon budgets – information of critical importance for climate policy. By addressing this knowledge gap, the project will advance current understanding of the global land carbon sink, strengthen world-leading research and ultimately support society by providing robust scientific advice to inform climate policy. The project is particularly timely given the growing urgency of accurately quantifying remaining carbon budgets so we can meet international policy goals to limit global warming below 2°C.

UKRI Gateway to Research · FY 2026 · 2026-09

The key challenge addressed by this project is to deliver new datasets and modelling approaches needed to quantify climate change impacts on flood hazards that affect vulnerable floodplain populations in dynamic foreland rivers (DFRs) downstream of the Himalayan mountain front. This is timely because: (1) In regions such as Uttar Pradesh and Bihar, India (downstream of the Himalayas), regular floods already affect >35 million people. Projected population growth, rising flood peaks and river sediment loads will amplify future flood impacts in these regions significantly; (2) Existing approaches to predicting flood hazards in such dynamic rivers have critical flaws which mean they fail to provide reliable projections needed to inform flood adaption planning in response to climate change. This project aims to address the three key flaws in existing approaches to predicting flood hazards in such rivers: First, existing predictions focus on flood inundation and neglect major hazards that accompany flooding. These include extreme rates of riverbank erosion (up to 1 km per year) and river avulsions (abrupt movement of rivers to new floodplain locations). These hazards can destroy whole settlements during single floods. Second, existing predictions of flooding use models that assume river-floodplain landscapes do not evolve. These models represent water movement, but not erosion and deposition processes that drive changes in river and floodplain topography. This approach is wholly inadequate in dynamic rivers where geomorphic processes drive complete reworking of the active floodway over decades. Models that neglect these processes are effectively predicting flooding in a river-floodplain landscape that will not exist in future. Third, because existing flood predictions ignore processes controlling the downstream movement of sediment, they cannot account for how future changes in water and sediment delivery from Himalayan mountain basins will propagate downstream. This is important because climate change impacts on hazards in these environments will exhibit marked spatial variations downstream of the mountain front driven by this propagation, that are currently overlooked. This project will develop new approaches to predicting spatiotemporal patterns of hydrogeomorphic hazards in mountain-front rivers (hazards associated with bank erosion, avulsion and flooding in dynamic river-floodplain landscapes). Our objectives are to: (i) exploit advances in remote sensing and field data acquisition to quantify hydrogeomorphic hazards in dynamic rivers downstream of the Himalayan mountain front in Uttar Pradesh and Bihar; (ii) use these datasets to rigorously test models that represent the processes of river and floodplain evolution that control these hazards; (iii) apply these models to predict how hazards may evolve under future climate change, and map temporally-evolving hazard extent for a range of future climate change scenarios; and (iv) integrate this knowledge with socio-economic datasets and social surveys of floodplain populations to understand and quantify their vulnerability and evolving future exposure to hazards. Throughout the project we will work closely with government agencies (Departments of Irrigation and Water Resources, and State Disaster Management Authorities), NGOs and local floodplain communities, to share knowledge, experiences and perceptions, understand and address their priorities, and co-design approaches to deliver benefits that meet their needs. These will include new tools for predicting bank erosion and river susceptibility to avulsion, and hazard and population exposure projections that support climate change and flood adaption planning. The project will generate new knowledge and methods with applications in dynamic river settings across the wider Himalayas, Andes and Central Asia.

UKRI Gateway to Research · FY 2026 · 2026-08

Antimicrobial resistance (AMR) is a growing global threat to human, animal, and environmental health. In 2019, AMR was directly responsible for over 1.2 million deaths and contributed to more than 4 million additional deaths. While the prevalence of AMR in humans and farmed animals is relatively well-understood, the mechanisms driving patterns of antimicrobial resistance in wildlife and the environment remain poorly characterized. This shortfall in our understanding hinders efforts to trace the spread of AMR and identify effective intervention strategies. To combat AMR and mitigate its impact on wildlife and human health, it is crucial to understand the factors driving resistance at the individual level. Understanding how individual variation in AMR prevalence and transmission occurs, rather than treating entire species or populations as uniform groups, can help identify key host traits correlated with resistance and pinpoint when and where the likelihood of AMR transmission is highest. Migratory birds are particularly important in this context because they traverse long distances and may act as conduits for spreading AMR across different ecological and host networks. Despite their potential role in AMR transmission, little is known about how migratory birds contribute to the spread of resistant pathogens or how AMR impacts their health. To address these gaps in our knowledge, this study will use a model migratory bird, the Light-bellied Brent goose (Branta bernicla hrota; LBBG) to link AMR dynamics to individual behaviour, movement, microbial ecology, and interactions with the environment (where animals can pick up AMR). This first element of the grant will use the LBBG system to provide vital estimates of how variation among individuals in key traits like movement and social behaviour can drive variation in the prevalence and transmission of resistance genes. We urgently need to identify the spatial and temporal scales at which transmission of AMR by wildlife is highest. Building on these insights, the second part of the grant will investigate transmission dynamics of AMR among multiple bird species, including LBBG, sharing a common environment. Specifically, we want to know how important the environment is for acting as a bridge permitting transmission between different species that may not always come into direct contact with one another. Such estimates remain rare in the literature, but are crucial for so-called 'One Health' approaches to studies of AMR. This research will provide new insights into the ecological dynamics of AMR in wildlife, improving our understanding of how resistant pathogens spread in nature and helping to identify strategies to manage and mitigate the risks posed by AMR in wildlife populations. If we can understand the importance of wildlife and the environment as conduits through which AMR is spread, it will also  shed light on when and where risk of onward transmission to humans and farmed animals is highest. It's also vital that we try and understand the impact of carrying AMR on wildlife health, which to date we know little about. Ultimately, this work will advance the field of wild disease ecology and contribute to broader efforts to control the spread of AMR, with potential benefits for both wildlife and human health.

UKRI Gateway to Research · FY 2026 · 2026-06

This project will quantify the national-scale impact of beaver reintroduction on hydrological extremes and carbon cycling now and under future climate scenarios. Rivers and wetlands have become heavily degraded. Amid changing climate and catchment (mis)management we face increasing hydrological extremes (flooding and drought), strongly linked to terrestrial carbon loss. A positive countertrend is the growing appreciation of Nature based Solutions (NbS) which use natural processes to address social challenges effectively and adaptively, simultaneously proving human well-being and biodiversity benefits. As ecosystem engineers, creating ponds and wetlands, beavers epitomise NbS, building resilience to flooding and drought, whilst simultaneously adapting their ecosystems to changing conditions and potentially mitigating climate change by increasing storage. Absent from our landscapes until recent reintroductions, the ability to gather critical scientific understanding within Europe has been limited. Despite growing evidence highlighting biodiversity benefits, a rigorous assessment of their impact on hydrological extremes and carbon dynamics is absent. As beavers return to densely populated, intensively managed landscapes, we urgently need to establish the potential impacts at both catchment and national scales. Beaver ponds reduce flood peak discharge and increase water storage. However, their collective flow attenuation capacity is unknown and if this will be overwhelmed by the more extreme flows predicted into the future. By optimising nested, multi-site, empirical hydrological monitoring to parameterise landscape-scale models, this project will simulate and quantify the impact of beavers on hydrology during periods of flooding and drought at catchment scales both now and under predicted future hydrological extremes, testing hypotheses including: beaver ponds reduce downstream flood peaks during storm events; sustain baseflows during droughts and maintain flow attenuation across event size. Beaver wetland creation fundamentally alters carbon cycling; however the effects are poorly understood due to complex, contra-directional processes. Previous studies have focused on one or two carbon pathways with no measurements across temperate Europe. This project will fill this knowledge gap with co-located monitoring of sedimentary, aqueous and gaseous pathways at high-temporal and spatial resolutions. We will establish how beaver wetland creation impacts carbon cycling, testing hypotheses including: beaver ponds increase carbon storage; increase methane emissions and reduce dissolved organic carbon fluxes downstream thus improving water quality. A critical unknown is what the collective effect will be as populations spread, do beavers represent a meaningful NbS at the national scale? Combining existing beaver dam capacity models with new empirical understanding of the ecohydrological structure and function of beaver wetlands in high-resolution geospatial models, we will quantify the potential for hydrological and carbon NbS delivery at fine scales across a national extent under different climate change and beaver occupancy scenarios. Using Britain as an example we hypothesise greater beaver occupancy will result in more significant impacts even under climate change. Responding to a stated need from Government agencies and project partners for robust evidence on the impacts of beaver reintroduction, this project will develop modelling tools which enable policy relevant understanding whilst containing high-resolution, catchment-scale detail for on-the-ground implementation. Providing a framework to support future research across Europe and North America, as beavers return to these anthropogenic landscapes. Co-created with project partners, this project prioritises knowledge dissemination to ensure real world impact by developing and disseminating an evidence-based decision-making toolkit to guide beaver reintroduction. Aiming to optimise hydrological and carbon cycle change and minimise both conflict and negative impacts.

UKRI Gateway to Research · FY 2026 · 2026-05

The fate of soil organic carbon (SOC) stocks in Amazonia following deforestation represents a major uncertainty in the global carbon cycle and climate projections. As the world’s largest tropical forest, Amazonia plays a key role in regulating global climate. Its soils store ~60-90 GtC in the top metre alone1, making it one of the largest tropical terrestrial carbon reservoirs. However, widespread degradation and deforestation, primarily for agriculture, are turning the Amazon into a net carbon source2. This transformation of ‘forest to field’ is not only associated with the loss of trees but also substantial losses of SOC, with estimates ranging from ~20-50%3. Despite SOC’s critical role in the global carbon cycle, the processes controlling its loss, transformation, and potential recovery after deforestation remain poorly understood, especially in the tropics, where soils differ markedly from temperate regions. Specifically, there is an urgent need to understand how much carbon is retained or enters the soil after deforestation, in what form (e.g., particulate, mineral-associated, or stable pyrogenic carbon from burning), and how these pools respond over time to different land management practices and a changing climate3. Understanding these dynamics is essential for designing land management strategies that promote SOC retention and contribute to climate change mitigation, although its effectiveness may vary depending on soil type, climatic zone, and land use. Thus, determining the controls on soil carbon storage and emissions in post-deforestation Amazonian soils is essential for developing strategies to enhance C storage via land management to limit runaway climate emissions from soils. However, previous progress has been constrained by the scale and complexity of Amazonian ecosystems, a historical focus on aboveground carbon, and the lack of integrated, long-term studies across key environmental gradients. Current Earth System Models struggle to predict SOC loss because they lack a mechanistic framework that accounts for the complex interplay between diverse soil properties, altered climate regimes, and the distinct transformations during land-use change. This project will resolve these critical knowledge gaps by using the Amazon’s Arc of Deforestation as a natural laboratory to quantify the fundamental controls on SOC dynamics. Specifically, we will: Quantify early changes in SOC following deforestation and fire, including the formation of stable pyrogenic carbon4. Identify the long-term drivers of post-deforestation SOC dynamics, accounting for soil mineralogy, dominant land use (e.g. annual crops, pastures, silvopastoral systems), and environmental gradients. Assess the long-term consequences of these changes for regional SOC cycling and storage under future climate scenarios. To achieve these aims, we will combine field sampling across a chronosequence of post-forest fields spanning key soil physicochemical and climate gradients spanning the Amazon ‘Arc of Deforestation’, with high-resolution environmental monitoring and isotopic and radiocarbon analysis. These data will inform improved soil carbon models to guide optimal future management strategies. This interdisciplinary approach—leveraging a team of soil scientists, ecologists, and climate modellers to develop a unique Amazon-wide dataset —will allow us to determine how post-deforestation SOC stocks respond to agricultural land-use, fire, management practices, and climate change and identify strategies that maximise soil carbon sequestration in post-forest Amazonian landscapes (Figure 1a). This project will provide urgently needed insights on the fate and vulnerability of soil carbon after deforestation to inform climate mitigation strategies by identifying high-risk regions and land-use practices in one of the world’s most carbon-rich and threatened ecosystems.

UKRI Gateway to Research · FY 2026 · 2026-04

This project examines how the criminal justice system responds when children are harmed or killed in the context of domestic abuse, focusing on the ‘failure-to-protect’ offence under Section 5 of the Domestic Violence, Crime and Victims Act 2004. It aims to develop a theoretically grounded framework for understanding how key actors in the criminal justice process interpret maternal responsibility for male-perpetrated violence against children, drawing on doctrinal analysis as well as insights from feminist legal theory and cultural theory. Originally introduced to enable prosecutions where it was unclear which adult caused a child’s death, concerns have been raised that this offence has been used disproportionately to prosecute mothers, particularly those experiencing domestic abuse. The legal basis for liability – whether a mother was, or ought to have been, aware of the risk, whether the act was foreseeable, and whether she failed to take “reasonable steps” to prevent it – is complex and open to interpretation. Key questions arise about how factors that may influence what a mother can ‘reasonably’ do, such as coercive control and systemic disadvantage, are understood by prosecutors, judges, juries, and other professionals. Despite its potentially profound consequences for families, the offence has received limited scrutiny in legal scholarship, domestic abuse advocacy, and professional practice across criminal justice, family law, and child protection. There is also limited understanding of how intersecting inequalities – such as poverty, racism, disability, or mental illness – shape mothers’ experiences under this offence. This project investigates how maternal responsibility is constructed – that is, interpreted, expressed, and applied – in Section 5 cases, focusing on why and how mothers are held culpable for male-perpetrated domestic violence. It analyses prosecutions, criminal justice outcomes, and professional narratives in legal judgments and statutory reports to explore how maternal culpability is framed in this context. The project combines analysis of prosecution and conviction patterns with in-depth examination of legal judgments and professional reports to identify recurring themes and the stories they tell about mothers, responsibility, and blame. It also involves participatory workshops with survivors and practitioners, leading to the co-creation of a short film. These workshops will enable participants to engage with and respond to the findings, co-producing stories that may reveal or challenge assumptions about systemic constraints, coercive control, and structural disadvantage. The film will act as both a research tool and a creative output, translating insights into a form designed to reach and resonate with professional and public audiences. By centring experiences of coercive control, systemic failings, and intersecting inequalities, the research seeks to challenge and reframe prevailing professional and public understandings of how maternal responsibility is understood in the context of domestic abuse. Findings will inform awareness of the need for feminist, context-sensitive interpretations of ‘reasonable steps’ under the law and create the conditions for potential law and policy reform, with the film acting as a key means of amplifying these insights and broadening their impact, alongside academic dissemination. The project aims to: Investigate how maternal culpability is constructed in Section 5 ‘failure-to-protect’ cases. Examine whether, and if so how, systemic constraints – such as coercive control, institutional failings, and intersecting disadvantages – are overlooked in these constructions. Generate new, theoretically grounded understandings to challenge conventional professional and public narratives about maternal culpability, with impact achieved through both academic and creative outputs.

UKRI Gateway to Research · FY 2026 · 2026-03

Severe mental illness (SMI) research and funding is lacking. The UKRI Mental Health Platform is working to change this by supporting projects that aim to better understand and treat these conditions. We know that changes in a person’s genes can play a big role in SMI and may influence symptoms. The main aim of my project is to find new genetic changes linked to SMI. This will help us find specific genetic changes that underlie SMI, giving us new clues about how these disorders develop and helping to create better treatments in the future. To do this, I will combine new DNA and RNA sequencing data, both of which I will generate from individuals with SMI. I will predict the downstream effect of genetic data on the body in terms of SMI and its symptoms. During my fellowship, my objectives are: Find reliable genetic changes associated with SMI by combining my current data from the human brain and new DNA data collected from blood of individuals with SMI. Choose a subset of individuals with SMI, based on their genetic information and symptoms, and use advanced RNA sequencing methods to study how their gene activity is affected by genetic variants. Use advanced RNA sequencing techniques on single blood cell types (rather than the whole blood) to get a deeper look at gene activity in individual cells. The main result of this project will be a list of known and newly discovered genetic changes found in parts of the genome that have potential downstream effects on SMI. This information could help patients, and their families understand the possible genetic causes of their SMI. It could also be used to help diagnose future patients using DNA sequencing.

UKRI Gateway to Research · FY 2026 · 2026-03

Bacteriophage - viruses that infect bacteria - are the most abundant life-forms on Earth, and are thought to be important in controlling microbial communities and - through this control - key ecosystem functions such as carbon and nutrient cycling and preventing bacterial disease. However, the evidence of the role phage plays in microbial communities remains mixed, is mainly correlational, varies between environments, and is almost non-existent in soil. The overarching aim of this project is to better understand the ecological conditions under which phage exert control on microbial communities. This is essential to understanding how microbial communities - and their associated functions - will respond to environmental change. I predict that phage impact on microbial communities will be strongest under conditions that maximise encounter rates between susceptible bacteria and phage. For example, during algal blooms and cholera epidemics - textbook examples of phage control - phage infections cause sudden reductions in the density of susceptible hosts and increase the diversity of the bacterial community. In contrast, the increased bacterial and phage diversity and spatial structure of soil microbial communities likely result in reduced encounter rates, which may mean phages have a lower impact in soils. Furthermore, microbial communities may be less impacted by phages if all bacterial taxa can be affected by phages simultaneously. To complicate things further, soil conditions drastically change through time and space, thereby likely altering encounter rates and the impact of phages on soil communities. For example, we predict that phage impose stronger control in warmer and wetter soils where encounter rates are typically higher. Temperature and soil moisture are also two key factors that are likely to become more extreme and variable with climate change both globally and in the UK. To properly investigate the causal impact of phage, I will dis-assemble and then reassemble natural bacterial compost communities with, and crucially without, host-specific phages. I will measure whether increasing phage diversity reduces the overall impact of phage by comparing the composition and functioning of microbial communities grown in the absence and presence of single or multiple phages. Next, we will determine how temperature and soil moisture change phage-mediated impacts. Sequencing will uncover how the bacteria and phage have adapted to their environment and each other through the course of the experiment. Finally, I will combine my data with models of bacteria-phage dynamics to examine how general my results are, and compare these with identified patterns of phage impact on bacterial abundances in published datasets of natural microbial communities. By concentrating on ways in which conditions alter encounter rates, our work will be applicable across a wide range of environments. This work is crucial to understanding when and where phage control bacterial communities, whether this control is likely to be impacted by climate change, and the importance of phage in climate predictions. Furthermore, it will provide key information for the conditions under which phage application may be appropriate for microbiome engineering.

UKRI Gateway to Research · FY 2026 · 2026-03

Context: New technologies have recently made it possible to explore how differences across millions of people's DNA (called "variants") can affect the production of proteins and contribute to disease. DNA provides our cells with instructions for making proteins, and variants can alter the type or amount of protein produced, potentially causing disease. Although many variants have no effect, some can increase the risk of common diseases, whilst others can cause very rare diseases. Tens of thousands of variants have already been linked with thousands of different diseases. However, we still don't know why most variants predispose to common disease, and more than half of rare diseases remain undiagnosed. Challenge: Only around 1% of our DNA codes for genes that provide instructions for making proteins. Our understanding of why genetic variants cause disease is mostly limited to this 1%, but most variants linked to diseases occur in the other 99%. Here, we will focus on a specific part of DNA, called "untranslated regions," which do not provide instructions for making proteins but sit at both ends of protein-coding genes. These regions play a key role in controlling how much protein is made from each gene. Because variants in these regions could directly affect protein levels, their impact is easier to measure than variants in other parts of DNA. However, the effect of variants in these untranslated regions has been largely unexplored, as sequencing DNA in large numbers of people was previously too expensive. This project will use large recently-generated datasets to find new links between disease and variants in the untranslated regions of genes. Aims and Objectives: We will use genetic and medical data on >1 million people to understand how differences in people's DNA can affect the production of proteins and contribute to disease. We have already found that certain variants in untranslated regions can alter protein levels and lead to disease. Now, we want to expand our research to look at the effect of all genetic variants across untranslated regions. We will: Develop a new tool to better predict the effects of genetic variants in untranslated regions (for example, whether they are likely to change how much protein is made, and by how much). Test our tool using data on levels of proteins circulating in blood (using data from a large number of individuals who are part of UK Biobank). Use our tool to see if variants in untranslated regions are linked to hundreds of common diseases (for example, diabetes or heart disease). Apply our tool to find new diagnoses in untranslated regions for patients with rare diseases (for example, developmental disorders). Share our tool to enable other researchers to investigate untranslated regions. Applications and Benefits: New links between genetic variants and disease could provide diagnoses for families affected by rare diseases and help identify new drug targets that treat diseases by adjusting protein levels. By making our tool publicly available for other researchers to use, our work will provide new insights into the important role that untranslated regions play in health and disease. Our research is important for understanding how diseases work, improving diagnosis, and designing new treatments.

UKRI Gateway to Research · FY 2026 · 2026-03

Phytoplankton connect light to life in the ocean. They regulate cycling of key elements and compounds, particularly carbon, in the ocean, supplying energy to the marine ecosystem and influencing atmospheric CO2 concentrations. Understanding how phytoplankton are responding to climate change is critical to predicting future changes in the Earth’s carbon cycle and for managing fisheries. In recent years, our capacity to monitor phytoplankton globally has advanced significantly. With 27 years of continuous global data acquisition, satellite remote sensing of ocean colour has become instrumental in examining climate impacts on surface phytoplankton. New ocean colour climate data records now offer more accurate estimates of long-term changes in phytoplankton abundance by incorporating information on the phytoplankton type present in the water. Additionally, the increased use of ocean robotics and innovative tools designed to study subsurface environments allow us to investigate phytoplankton communities at depth—beyond the reach of satellites—and understand how they, too, may be responding to climate change. In this project, my team will leverage these advancements to quantify how global pools and fluxes of organic carbon in the ocean, driven by phytoplankton, are reacting to climate change. By combining new ocean colour climate data records with in-situ data compilations and new understanding of subsurface phytoplankton, we will create climate data records of phytoplankton carbon and primary production throughout the sunlit zone of the ocean. These climate data records will be used with ecosystem models to study the effects of climate change on vertical changes in phytoplankton physiology, biomass and primary production. Our aim is to use these tools and datasets to deepen our understanding of changes in the ocean’s biological carbon pump and to study shifts in the flow of carbon from phytoplankton into the marine ecosystem. The data produced through this project will serve as a benchmark, enhancing climate models that forecast future changes in the marine carbon cycle and fish stocks.

UKRI Gateway to Research · FY 2026 · 2026-03

Context Our bodies have remarkable defence mechanisms to protect our tissues from immune attack.  Every tissue and organ harbours unique and specialised stem/stromal cells to help keep our vital organs functioning. These naturally reparative stromal cells sense “danger signals” within their native environment and respond by producing anti-inflammatory and immunomodulatory therapeutics. Clinically, stromal cells (termed Mesenchymal Stromal Cells (MSCs)) are isolated from tissues such as bone marrow and fat so that they can be used to treat a wide range of inflammatory and autoimmune conditions including type 1 diabetes (T1D). MSCs preserve the function of insulin producing islet beta-cells in the pancreas of individuals with recently diagnosed T1D following their infusion into the blood stream. Emerging reports have also begun to establish the therapeutic potential of distinct pancreatic stromal cell populations including Pancreatic-MSCs and Pancreatic Stellate Cells (PSCs), to act as “islet helper cells”, similar to the more established functions of MSCs derived from extra-pancreatic tissues (including bone marrow and fat). Challenge the project addresses We know little about the role of endogenous/native PSCs in maintaining pancreatic islet survival in response to immune attack during T1D development. Understanding whether pancreatic stromal cells can survive during T1D progression is important because it will help us to understand the pancreatic stromal cell related changes that we can target therapeutically to help delay or prevent the development of T1D. Our project will further inform how distinct pancreatic stromal cell populations (PSCs and pancreatic-MSCs) may be used to support the long-term survival of transplanted islets/stem cell-derived islets (SC-islets) to treat individuals with already established T1D.   Aims and objectives By virtue of our access to rare T1D and control donor pancreas tissue, we will investigate pancreatic stromal cell populations in samples from individuals with recent-onset T1D where islet immune attack is still ongoing. We will use advanced imaging studies to determine T1D-related alterations in PSC number, location and islet-protective characteristics. We will investigate whether PSCs produce therapeutic factors that help to prevent harmful immune cell infiltration and destruction of insulin producing islet beta-cells during T1D development. In parallel, we will use “ex vivo” (outside of the body) experiments that model/mimic T1D pathogenesis/development and islet transplantation using defined pro-inflammatory stressors (cytokines). We aim to determine how pancreatic stromal cells (that have been isolated from the pancreas and grown in the laboratory) support the survival of isolated islets. We will establish how pancreatic stromal cells alter their DNA/gene expression to define the therapeutic factors through which PSCs/pancreatic-MSCs help in T1D. Potential applications and benefits Pancreatic stromal cells are a by-product of the clinical islet isolation/transplantation procedure. They represent a feasible source of “islet helper cells” with real potential to prevent the unwanted loss of islets/SC-islets after transplantation. For individuals with established T1D, islet or SC-islet transplantation offers the perfect treatment for continuous, real-time, insulin delivery avoiding short-term risks of low blood glucose and longer-term risks of high blood glucose. Using pancreatic stromal cells in transplantation may benefit individual islet graft recipients and allow the treatment of many more people with T1D. Reducing inflammation and preventing the loss of beta-cells with pancreatic “islet-helper cells” also has potential to improve quality of life for many people who would otherwise develop T1D.

UKRI Gateway to Research · FY 2026 · 2026-03

African ecosystems represent the vibrant heart of the continent’s wellbeing: as thriving habitat for the abundant, unique wildlife, as a basis for humanity’s survival and growth (e.g. clean water, agriculture, resilience), and as a key economic factor (e.g. clean energy provision, food, critical materials, tourism). Adapting to and combatting the ecological crises already battering Africa is crucial for its future, in which protecting and restoring terrestrial ecosystems will assume an inevitable role. One pertinent problem in sub-Saharan Africa is to improve agricultural yields for growing nutritious demand whilst restoring ecosystems on limited arable, already-degraded land. Increasingly encroached spaces, stressed by climate extremes and anthropogenic expansion, also proliferate human-wildlife conflicts that threaten shared multi-species livelihoods, balanced biodiversity, local productivity, as well as the economically important sector of sustainable wildlife tourism. Understanding complex ecosystems can only advance through data-driven evidence of their state, evolution, and sustainable interventions, and thereby inform decision-making. Scaling up data acquisition across large, complex landscapes is the key bottleneck. Our new paradigm--to bring physics into the ecosystem instead of ecosystems into labs or computers--aims at tackling this data-poverty crisis at scale. Ecosystem monitoring is extremely difficult: any comprehensive understanding of interactions between diverse agents, and how they change across spatial and temporal scales, across regions and over time, requires scalable, non-invasive, information-dense, well-understood data, ideally in real-time. To meet some of the most urgent and demanding challenges unfolding across Africa and elsewhere, this is the only viable path forward. We suggest conducting in-field physics applied to two key challenges in Africa: food provision and wildlife conflict, both intrinsically embedded in the climate crisis, while offering scalable climate solutions, improving community resilience and local stakeholder empowerment. This project will develop and deploy a rigorous physics-based ecosystem monitoring framework that integrates non-invasive geophysical data acquisition, sensor technology, and community co-design to address two intersecting challenges: Monitoring and restoring soil health by creating tomographic imaging of the evolving 3D soil, and mitigating crop-raiding elephant conflict by an early-warning system for farmers. We will design a modular, open-hardware physics-informed sensor kit (~£20-30 /unit), to be locally assembled at minimal cost and effort, for detecting seismic and environmental signals relevant to soil structure, moisture, weather and wildlife movement. This will be facilitated by symbiotic expertise between Kenyan and UK research, academic, non-profit institutions which already forged deep partnerships, each bringing into the project an integral role leading essential subprojects, ensuring equity and reciprocity. By the end of the project, we will have: Two physics-based monitoring sites operating in Kenya; open-source designs for wide-spread adaptation; a new generation of trained local physicists, environmental scientists, and farmers; demonstrated proof that physics research can drive solutions to imminent real-world problems. The combined effort on scaling up sensing while skilling up farmers, students, and scientists will break new grounds for large-scale ecosystem monitoring across Africa, not only to support local communities and scientists in their mitigation and adaption to the climate and ecological crises, but to empower them to lead innovations with bespoke solutions that may propel Africa to the fore of tackling these crises, and lead the way for other world regions that will face similar problems in the future. This unites rigorous scientific innovation with ethical, participatory implementation — a model for how intersectional physics collaborations can work for people and the planet.

UKRI Gateway to Research · FY 2026 · 2026-03

The Tudor Domesday opens up a neglected, nationwide survey of property and wealth in sixteenth-century England – Henry VIII’s first step after declaring his supremacy over the Church – to extend our ground-level knowledge and understanding of the development of landscapes, livelihoods and social organisation in every region of the kingdom over the course of their formative centuries. An audit of all sources of income claimed by Church institutions carried out in 1535, this ‘Valor ecclesiasticus’ [VE] was intended to capture for 50 historic counties of England and Wales comprehensive details of the infrastructure and income of 8000 parish churches, 650 monasteries, 22 cathedrals and countless chantries, colleges, hospitals and schools together with the people earning their living with them or from them. It describes agricultural land, woodland and waterways and working buildings from market stalls and mills to open-cast coal mines. It identifies the men, women and children who between them led, laboured for or benefited from these enterprises; and focuses the objects and outcomes of their efforts, recording livestock and crops and calculating yields and prices. Even local environmental conditions and weather patterns are noted in passing. VE was the most ambitious account of the realm to be compiled since Domesday Book. It surpasses it in the impression it provides of the natural and built environment and of the roles, responsibilities and needs of local society. Yet for two hundred years the data have been locked away in a printed transcript, badly-edited, which retains the densely abbreviated entries of the original manuscripts. It failed to address anomalies and omissions in the entries and overlooked related drafts and copies held outside of the Public Records. Consequently, the first generation of modern historians approached the data purely as an appendix to their assessment of the significance of the Tudor Reformation; subsequently scholars have held it at arm’s length. The insights the data offer into the physical, material and social development of diverse environments are still to be tapped. Advances in understanding of the neighbouring regions of Ireland, Scotland and northern Europe, and the re-emergence in the public domain of missing manuscript witnesses, set the continuing neglect of VE data in sharp relief. An interdisciplinary team experienced with comparable national datasets will re-assess the state of the record, explain its process and evaluate its importance as guide to the arc of regional developments up to 1535. They will establish a digital transcript supported by summary analysis graphically presented, enabling self-directed investigation for the widest range of users. In parallel, trial programmes for school teachers and UK archives sector professionals will test the use of the survey data as entry-points for exploring the environmental and social history of regional localities; community history groups will explore how they might encourage and enhance the discovery of heritage sites and landscapes both directly and through Local Studies research; webinars and a workshop will raise awareness of these little-known data on national land ownership, infrastructure and income with policymakers in a range of UK government departments.

UKRI Gateway to Research · FY 2026 · 2026-03

Charge transfer plays an essential role in fundamental chemical and biological processes such as photocatalysis and photosynthesis. This mechanism is also increasingly important in modern electric and optoelectronic devices that consist of semiconducting heterostructures, where the movement of charges across the interfaces between the constituent layers determines their overall effectiveness. Despite its significance, charge transfer remains largely unexploited in magnetic systems due to the challenge of finding materials that blend semiconducting and magnetic properties. Recently, the discovery of semiconducting van der Waals (vdW) materials that are magnetic down to single atomic layers has enabled the effective integration of semiconducting and magnetic properties along with reduced dimensionality. This project aims to investigate the lesser-known antiferromagnetic order, characterized by spins that align opposite to their neighbours, contrasting with traditional magnetic materials that depend on ferromagnets where neighbouring electron spins align parallel to establish ferromagnetic order. Antiferromagnetic alignment offers considerable advantages for memory technology, enabling magnetic bits to be packed more densely and operate at speeds typically a thousand times faster than those of ferromagnets. Additionally, the immunity of antiferromagnets to moderate external magnetic fields enhances memory application stability, although their detection challenges conventional methods. The proposed research is designed to demonstrate that charge transfer in antiferromagnetic vdW heterostructures facilitates ultrafast manipulation of magnetic order. Employing short laser pulses, time-resolved experiments will probe dynamic processes on femtosecond and picosecond scales. The focus will be on the effects of charge transfer across various vdW heterostructure combinations to enhance understanding of the interactions between key physical properties—electronic, optical, and magnetic. Specifically, the research will focus on the interaction between excitons (quasi-particles of bound electrons and holes), photons, and spins, aiming to incorporate quantum effects for ultrafast and energy-efficient electronic devices. Efforts will be concentrated on visualizing and manipulating antiferromagnetic spins in both space and time, striving to achieve rapid transitions between ferromagnetic and antiferromagnetic states, and exploring how these transitions affect excitonic properties. The envisioned ultrafast control of magnetic order through interfacial charge transfer holds significant promise for data storage and quantum technologies. By exploring the fundamental dynamic properties of the spin degree of freedom within a semiconducting environment, we can enhance the integration of magnetic compounds. Such advancements are crucial for achieving nonvolatility, faster data processing, reduced power consumption, and higher integration densities in future devices.        

UKRI Gateway to Research · FY 2026 · 2026-03

This proposal is for transitional operations support for the HARPS3 spectrograph at the 2.5m Isaac Newton Telescope on La Palma.  HARPS3 is a high-resolution, ultra-stable, visible echelle spectrograph designed for the precise radial velocity measurements required to discover Earth-mass planets in Earth-like orbits around Sun-like stars.

UKRI Gateway to Research · FY 2026 · 2026-02

A major source of emerging infectious diseases are viruses moving into new host species. Such ‘host shifts’ or ‘jumps’ are well-documented in the case of human pathogens such as HIV, Ebola-virus, and SARS-CoV-2. To understand the emergence of new viruses, we need to identify factors that predict which viruses infect which host species. However, we have much to learn about how the environment, evolutionary relatedness, and recent species history determine which species share viruses. Here we will use a ‘snapshot’ of the UK moths (Lepidoptera) and their viruses to tease apart the relative importance of the different factors that shape the virus community. Thanks to systematic sampling by the National Moth Recording Scheme and the Rothamsted Insect Survey, the British moths are arguably the most closely studied and best characterised group of invertebrates in the world. We will combine this unique dataset on moth ecology with the genomic sequencing of viruses from more than 200 species of moth. Our first goal is to understand what viruses infect UK moths, how they are related to each other and to other viruses, and how many host species they infect. We will test how often these viruses have jumped between hosts, and whether they preferentially jump between closely related hosts, or hosts in the same environment. Our second goal is to understand how host ecology and environment determine which hosts are infected by which viruses. For example, we will test whether more abundant host species have a greater number and diversity of viruses, and whether species with overlapping environments share more viruses. We will also test whether more generalist species, larger species, or species in certain environmental conditions are infected by a more diverse range of viruses. Our third goal is to examine the effect of host and virus evolutionary relatedness, and how these factors interact to predict virus sharing. For example, we will test whether closely related host species have similar viruses, and whether closely related viruses infect similar sets of hosts. Finally, we will examine whether species that have recently arrived in the UK and/or those with expanding ranges, have fewer viruses or viruses that are more likely to infect a broad range of hosts. This work will help to determine the relative importance of ecology and the environment, evolution, or species history in determining the distribution and abundance of viruses across host species, and will provide fundamental insights to help conceptualise a framework for understanding future disease emergence. While a focus on high-profile pathogens that infect humans is clearly essential from a public health perspective, such focus limits our ability to test the fundamental rules that underly pathogen emergence. Moreover, invertebrates are keystone species in many food webs and so are fundamental to life on earth, but at the same time act as pests and vector pathogens. Therefore, this work will also have important outcomes for both our fundamental understanding of disease biology, and also applied insect-science, biocontrol and applied virology.

UKRI Gateway to Research · FY 2026 · 2026-02

Context Current technologies for studying plant biochemistry, including metabolomics based on mass spectrometry (MS) or nuclear magnetic resonance (NMR), provide valuable molecular insights but lack the spatial resolution needed to understand how biomolecules are distributed within cells. MS imaging can provide spatial information across tissues and cells but not with the resolution of organelles within cells. This project proposes a novel imaging approach that bridges the gap between traditional microscopy and so called omic technologies. By combining high-resolution imaging with advanced biochemical analysis and machine learning, our technology will create new opportunities for functional analysis of plants at the subcellular scale.   The Challenge the Project Addresses Light microscopy non-destructively interrogates subcellular structures, but the challenge is to decode the complex biochemistry hidden within optical signals, without the use of labels or dyes, to yield the level of molecular specificity provided by MS and NMR. Our project will address this challenge through a combination of cutting-edge optical physics, to enhance the molecular (i.e Raman) signatures imparted on light when it interacts with matter, and artificial intelligence to extract meaningful biochemical information from these complex signatures.   Aims and Objectives Our aim is to create a transformative plant microscopy technology based on cutting-edge nonlinear optical techniques, four-wave-mixing and broadband Coherent anti-Stokes Raman Scattering, to acquire chemical fingerprints in plants at the subcellular scale. We will integrate this with machine-learning (a field of artificial intelligence) to develop computer models, trained using data from metabolic mutants of Arabidopsis thaliana, to map the fingerprints against biomolecular composition. This new chemical fingerprint imaging technology will shed new light on the cellular level biochemistry governing plant life, plant response to disease and environmental stresses. Our ultimate objective is the widespread adoption of the technology by the plant biology community. This will initially take place through specialised user access facilities and in the longer term, via translation into commercial microscopy products.   Potential Applications and Benefits This innovative technology holds tremendous potential across plant biology, offering a unique capability to study biomolecular composition on a spatial scale unavailable with current analytical methods. The novel chemical imaging capability will provide unprecedented insights into key cellular processes, such as photosynthesis, as well as plant responses to biotic and abiotic stresses. It will also provide a new medium-throughput chemical phenotyping approach which will be trialled by outreach to potential users in the later stages of the project. In the longer term the technique will be transferable to organisms other than plants.   Relevance to the BBSRC long-term research and innovation priorities The project sits within the research area Tools and Technology Underpinning Biological Research. The technology developed would support BBSRC’s research and innovation objective priorities by advancing frontiers of bioscience discovery in both Understanding the Rules of Life and Transformative Technologies. Moreover, it would provide scientists with a transformative capability to tackle the strategic challenge in Sustainable Agriculture and Food.  

UKRI Gateway to Research · FY 2026 · 2026-02

Transposons are mobile selfish genetic elements that occur in the genomes of organisms across the tree of life. Once largely dismissed as ‘junk DNA’, there is growing recognition of their widespread evolutionary influence. This propensity emerges from the varied gene content of transposons and their frequent incorporation of host regulatory sequences, enhanced by their repetitiveness, replicative potential, modularity and mobility. It is now apparent that co-option of transposon sequences has provided key contributions to the evolution of diverse host traits, including pregnancy, memory, and immunity. Correspondingly, a major emerging question is, to what extent are transposons fundamental contributors to host evolution, and thus the diversity and complexity of life on Earth? To address this, it is necessary to move beyond consideration of individual cases of transposon co-option, towards systematic, genome-wide screens of transposon-host gene interactions. A topic of urgent applied relevance where transposon co-option is increasingly implicated, is resistance evolution. The evolution of resistance to treatment in parasites, pathogens, and pests is a major societal challenge, with vast implications for health, agriculture, and environment. The ongoing genomics revolution offers powerful new avenues for addressing this high-priority challenge, towards managing resistance and developing innovative solutions. For example, by elucidating the mechanistic processes underlying resistance evolution. Consequently, we propose a rigorous investigation into the role of transposons as under-appreciated facilitators of resistance evolution in eukaryotic pests, focusing on the major international agricultural pest, the fall armyworm moth (FAW, Spodoptera frugiperda). FAW is extremely generalist, causing significant damage to a huge variety of major crop plants, including staples such as maize, rice, wheat, and potatoes. FAW is also highly invasive and has spread around the world from an origin in South America, endangering livelihoods and food security, particularly among vulnerable smallholders across the developing world. These problems are compounded by rapid evolution of resistance to pesticides and transgenic plants in FAW. Working closely with industry, we propose three work packages to interrogate major outstanding questions on the influence of transposons in facilitating resistance evolution. Firstly, employing detailed comparative genomic analyses, we will assess transposon enrichment at FAW detoxification genes, the processes underlying observed patterns, and crucially, their functional relevance. We will also consider whether interactions among transposons and host detoxification genes contribute to the extreme host range of FAW and closely related species, which is a key facilitator of pestiferousness. Secondly, we will leverage the power of recently developed massively parallel reporter assays, to provide an exciting cutting-edge investigation into FAW gene regulatory landscapes, and the extent that transposons underlie regulatory evolution at detoxification genes, including increased expression. Thirdly, we will conduct a large-scale test of the influence of host physiological stress on transposon activity, a major outstanding hypothesis of general evolutionary relevance, with key resistance significance if chemical stress directly increases genetic variation in target organisms. Collectively, our proposal offers a novel and timely examination of a topic of fundamental evolutionary interest, coupled with high applied relevance for addressing major societal need, which may open new avenues for managing and combating resistance evolution. Thus, it is directly relevant to central priorities in both BBSRC’s high-level objectives ‘Rules of Life’ and ‘Sustainable Agriculture’. Meanwhile, our integral link with industry, and focus on a major pest of great consequence for global food security, aligns with UKRI-wide priorities to facilitate a secure and resilient world.

UKRI Gateway to Research · FY 2026 · 2026-01

Ribosomes are the cellular protein-producing factories in all known life forms. They are central metabolic hubs and tightly regulated in response to physiological or environmental conditions. Protein biosynthesis is energy-expensive, consuming up to 40% of a cell's adenosine triphosphate (ATP). To survive shortages of ATP (e.g. caused by environmental or nutrient stress) cells can enter an energy-saving mode called dormancy, where most ribosomes are shifted into a “hibernating” state. Dormancy is typical for plant seeds or fungal spores that must endure drought or winter and underlies various infectious diseases and cancer. Dormancy is integral to life cycles of parasites that alternate between metabolically active phases inside hosts and dormant phases in the environment. A striking example is found in microsporidia—eukaryotic parasites capable of infecting a broad range of animals, including humans. Microsporidia exist as dormant spores in the environment, such as in contaminated water, and infect new hosts upon ingestion. During infection, microsporidia deploy a specialised invasion organelle, the polar tube (PT), to enter host cells. Fuelled by the host cell’s resources, the parasite then activates its metabolism, proliferates, and forms new dormant spores that ultimately kill the host cell and propagate the infection (Fig.1). Dormancy enables microsporidia to remain viable in the environment for weeks, poised to infect their next host. In humans, microsporidia are a health threat to immunocompromised individuals—including those with AIDS, transplant recipients, and malnourished children—causing chronic diarrhoea, wasting, and in severe cases, organ failure or brain infections leading to seizures. In agriculture, microsporidia devastate farmed animals such as fish and honeybees, endangering food security and agricultural economies. Despite their clinical and ecological importance, fundamental molecular questions about the microsporidian life cycle are poorly understood. For instance, how do microsporidia suppress most ribosomes to conserve energy during dormancy while keeping a subset active for survival? Equally mysterious is how ribosomes reactivate to power the parasite's protein metabolism during host invasion. This frontier biosciences proposal will quantify ribosomal activity and deconstruct the structural and mechanistic principles of ribosomal regulation across the microsporidian life cycle by harnessing the power of cutting-edge bioimaging and omics approaches. Our Objectives are to: O1: Study the structural basis of ribosome hibernation within dormant spores to determine the key factors that suppress most ribosomes O2: Map the dormant spore’s baseline ribosomal activity to decipher the minimum protein biosynthesis regime that keeps the spores alive O3: Investigate ribosome activation during host cell invasion to shed light on its triggers O4: Image the intracellular life cycle of microsporidia across scales to determine when protein biosynthesis is at its maximum and how ribosomes are switched off again when new spores are formed. To achieve these objectives, we will leverage an interdisciplinary and cutting-edge bioimaging and omics approach to advance knowledge of ribosome biology, cellular dormancy, and parasitic infection. This proposal unites a unique team of experts in microsporidian biology (Daum & Williams), structural biology (Daum & Isupov), omics (Williams), and bioimaging (Hacker & McLaren). The project will establish cutting-edge, multimodal pipelines, foster new skills, and train the next generation of researchers. Our proposal is poised to generate world-leading research that will contribute textbook-defining knowledge to the fields of microbiology, cell biology, and ribosome biology. Finally, our work will inspire innovations to combat parasitic infections, benefiting health care and food security.      

UKRI Gateway to Research · FY 2026 · 2026-01

Animal societies, including those of humans, are inherently dynamic, with individuals continually forming new relationships as old ones fade. However, how and why individuals update their social interactions remains poorly understood. Avoiding disease and gaining access to information have been suggested as key factors driving social dynamics. Work to date has focused almost exclusively on disease, finding that individuals modify their social interactions to reduce their risk of infection. Currently however, we lack a basic understanding of how and why individuals adjust their social relationships for information access. This research project will address this knowledge gap by using half a century of social and ecological data on the Southern Resident killer whales (SRKWs). The SRKWs are one of the best study systems available to determine how information access drives social dynamics – they have no natural predators, and one key ecological factor determines their survival and reproduction - the abundance of their primary prey, Chinook salmon. Salmon abundance is highly variable within and between years and we have shown that old individuals act as repositories for ecological knowledge of where and when to find salmon. During the summer, SRKWs are “resident” in a small inland/marginal sea off the Northwest Pacific Coast of North America, where they feed on migrating salmon. The tractability of this study system has provided one of the most complete and detailed datasets on a marine mammal anywhere in the world. Using 50 years of data on SRKW behaviour and salmon abundance, we will determine how accurately SRKWs time their arrival in the coastal waters with annual peaks in salmon abundance and how this depends on their own experience/knowledge and the experience/knowledge of others in their social group. We will quantify how individuals rewire their social interactions when salmon abundance changes, predicting that younger individuals will actively prefer to associate with old/experienced individuals in years of low salmon. Moreover, we will examine how the death of a knowledgeable social partner drives information-induced social dynamics, predicting that individuals who lose a knowledgeable partner will actively form new (or strengthen existing) associations with knowledgeable individuals. Finally, we will examine how information-induced social rewiring scales up to influence the population's social structure. For example, we predict that a decline in the proportion of old knowledgeable individuals in the population will be associated with the social collapse of the population, as individuals link to the few remaining knowledgeable individuals. Our understanding of mammalian social systems is heavily skewed towards terrestrial mammals. The maturation of long-term individual-based studies in the marine environment, such as the SRKW database, which spans half a century, opens a new frontier for research on animal societies. Our research will provide a new fundamental understanding of information-driven social dynamics, which has the potential to help explain widespread social dynamics seen across species, and as such, our research findings will be of broad interdisciplinary interest. Our research findings will guide the future conservation and management of the critically endangered SRKW population by providing new insight into the consequences of social behaviour for survival and reproductive success. Globally, animal populations are living under increasing anthropogenic pressures and our work will shine new light on the consequences of these effects for social dynamics, survival and reproduction, which has the potential to inform conservation strategies across a wide range of species.  

UKRI Gateway to Research · FY 2026 · 2026-01

Osteoporosis is a bone-wasting disease that makes bones thinner, weaker and more likely to break. Breaking bones in the hip and spine is painful, life-changing and costly to the NHS (currently £5.5 billion/yr), with cases expected to double by 2050 largely due to a growing ageing population. It is possible to avoid or delay getting osteoporosis, but other than general advice on nutrition or exercise, there is no support to help people strengthen their bones during everyday living across the lifespan. As osteoporosis affects one in two women over the age of 50 compared to one in five men, women are disproportionately impacted by the disease. In addition to being more common in women, osteoporosis and its consequences also affect people with lower incomes or less education more often, due to factors like poor nutrition, limited access to healthcare and lower awareness of bone health. When made aware of both their elevated risk and our research demonstrating that even modest bone-strengthening, impact activity can yield measurable benefits, women, and particularly those leading up to and after the menopause (40-60 years), express a strong demand for accessible interventions to improve their bone health before irreversible decline occurs.   Short, sharp bursts of bone strengthening impact activity cannot be inferred from common metrics such as steps, distance, heart rate or calories. As no existing app or wearable accurately captures this specific activity, we identified a critical gap for a digital health tool that helps both men and women incorporate bone-strengthening impacts into their everyday lives. To address this gap, we developed a novel bone-specific activity-tracking algorithm that uses data from smartphones or wearable devices to detect and encourage users to monitor and increase bone-strengthening impact activity for themselves. Similar to the goal-oriented habit of tracking daily steps on pre-installed apps, common even among phone users who don’t actively engage in structured exercise, our algorithm is designed to support the formation of a simple, low-burden, goal-oriented habit focused on tracking small but important amounts of bone-specific impact activity accumulated throughout daily life. We initially incorporated this algorithm into an early-stage alpha-prototype app and tested its function with a small subset of users (n=25). We have now embedded this algorithm in a user-friendly beta-prototype app, which provides a platform for further proof-of-concept and value testing with a larger sample of end-users in a real-world setting.   We now must assess how large groups of users, who differ in sex, age and deprivation, engage with the app and its potential to deliver sustained improvements to bone-strengthening activity habits. This will be achieved through a single work package where the usability of the app will be tracked in 410 users (men and women, aged 40-50 and 51-60, from areas with lower and higher levels of deprivation) over a 3-month period. The resulting data will determine how interested different user groups are in being recruited to a study like this, whether users engage meaningfully with the app (rate of user uptake and engagement; feasibility), the number of days users meet target impact scores and how these scores vary over time (rates of impact-target adherence). This evidence will rapidly de-risk further development by assessing the app’s viability for large-scale implementation, providing a clear go/no-go decision point.

UKRI Gateway to Research · FY 2026 · 2026-01

Due to rapid population growth and climate change, global food demand is expected to increase by over 60%, necessitating transformative advancements in crop production and improvement. The pace and magnitude of the change required to ensure food security is beyond present day technological capability of crop improvement programmes that combine genetics and molecular tools. Incorporating epigenetics into the breeding toolbox is the key to meet our future food demands as it expands the potential of crops to adapt to changing environments and enables us to rationally manipulate traits without changing DNA sequences.   Although significant progress has been made in model species such as Arabidopsis in elucidating epigenetics mechanisms in environmental responses, development, disease resistance, stress adaptation, and cellular memory - mechanisms paramount for the adaptation of all plants including high yield crops to changing environments - these have not been sufficiently exploited for crop improvement. The main barrier is the complexity of major crops, particularly polyploid species such as wheat, whose complex genomes hinder seamless application of epigenetic principles for crop improvement.   Establishing the fundamental mechanisms of epigenetic control of polygenic agronomic traits such as yield, stress resistance, and climate adaptability and optimisation of tools to manipulate these could offer unparalleled opportunities and add to the potential of modern breeding technologies including genome editing.   To address these challenges, we propose the development of a collaborative research network – The UK Plant Epigenetic Network (UK-PEN) that brings together experts in plant epigenetics and physiology, crop genomics and epigenetics, and crop breeding. Through building such a robust group of complementary expertise, from both academia and industry, this community aims to draw in knowledge, expertise and resources to accelerate the application of epigenetic insights to crop improvement. The complex nature of crop genomes requires a multidisciplinary approach, where experts from various fields share their expertise to identify and fill knowledge gaps and develop new strategies.   Central to this effort is the exchange of ideas, with the goal of identifying key research areas where epigenetics can make the greatest impact on crop performance. We will organise focussed actions to foster communication and knowledge-sharing among researchers, and the crop breeding industry. By consolidating existing research and identifying bottlenecks in our current understanding, the community will work to extend the knowledge of epigenetics principles to a broad range of crop species to allow integration of epigenetics into breeding programs. UK-PEN pump-priming projects will provide proof-of-concept and work towards developing novel methodologies and resources to build on. A curated repository of epigenetic knowledge will be developed to ensure that the wider community has access to up-to-date information and tools. A dedicated event on data analysis will ensure that the community develops and shares analysis capabilities.   The UK-PEN initiative seeks to deliver structured and transformational change in the field of plant epigenetics, with the ultimate goal of improving crop resilience and sustainability. As a community, we can develop novel approaches for developing climate resilient crops by combining the power of epigenetics and modern molecular tools. This collaborative effort will not only advance scientific understanding but also provide actionable strategies to enhance food security and sustainable crop production for future generations.

UKRI Gateway to Research · FY 2026 · 2026-01

This UK-US collaboration between the University of Exeter and the University of North Carolina investigates how Wikipedia shapes—and is shaped by—the rise of generative AI and large language models (LLMs). Wikipedia increasingly provides essential training data for AI systems that influence public knowledge, yet these models in turn are used back on Wikipedia, potentially reinforcing existing power dynamics or inaccuracies. Through original empirical research, this project will analyse how editorial practices, characteristics, and decision-making are integrated into AI interventions, examining the implications for trust, representation, and the integrity of the digital commons. Contextually, Wikipedia occupies a unique position at the heart of global knowledge production, frequently serving as the first port of call for online information seekers. Its articles often form the basis for the automated information summaries users encounter every day on major search engines and AI-generated tools, shaping the understanding and beliefs of millions globally. Concurrently, AI-generated content is increasingly being integrated into Wikipedia itself, either directly through automation or indirectly through human editors utilising AI-assisted tools. The challenge this project addresses lies in understanding how this recursive relationship between Wikipedia and AI models affects the quality and reliability of public knowledge. Specifically, it focuses on the central concept of “notability”—the criteria editors use to decide what information is worth including or excluding from Wikipedia—and examines how these criteria might shift when AI tools enter editorial workflows. This dynamic poses significant ethical, societal, and epistemological questions, especially concerning whose voices and perspectives are amplified or diminished, and what biases may emerge, in an increasingly AI-driven information landscape. The project's primary objectives are fourfold: To empirically investigate how Wikipedia's data is utilised by generative AI systems and assess how this reuse influences public-facing AI-generated information.  To explore how AI tools integrated into Wikipedia's editorial process might reinforce or reshape editorial priorities and standards of notability.  To provide practical guidance for policy makers, industry stakeholders, and the Wikipedia community on managing pathways / guardrails for responsible integration of AI tools, ensuring Wikipedia remains a reliable and sustainable source of public knowledge.  To create a public-facing educational video for youth audiences to help them develop search literacy.   In pursuing these objectives, the project adopts a humanities-driven, interdisciplinary approach, drawing from digital humanities, sociology, and computational communications. Key activities include analysing large-scale datasets documenting AI-Wikipedia interactions, conducting ethnographic observation and interviews with Wikipedia editors, and hosting a unique public-facing “Edit-AI-thon” event. This event will happen alongside a larger conference, to facilitate simultaneous scholarly insight, community engagement, and real-world observation of editors’ interactions with AI-driven content creation tools. Based on our data, our team will produce multiple academic papers/presentations, an educational video for youth, and a policy brief of recommendations for platform governance and regulation, aiding stakeholders—including policymakers, technology companies, cultural institutions, and Wikimedia affiliates—in making informed decisions about the intersection of AI and public knowledge. Core Team PL = Dr Patrick Gildersleve, University of Exeter PcL (I) = Dr Francesca Tripodi, University of North Carolina PcL = Dr Brett Zehner, University of Exeter Research associate = TBC, University of Exeter Research associate = TBC, University of North Carolina

UKRI Gateway to Research · FY 2026 · 2026-01

Context The proposed research will address counter-narratives through understanding the everyday ethical and spiritual bases of challenges to health (e.g. COVID-19), climate change, and urban planning (e.g. 15 minute cities) policies. To do this I shall use a mixed methods approach that will advance the ESRC priority to understand politics and governance in the UK. Bringing together critical approaches in anthropology and religious studies, I frame everyday conspiracy theories as counter-narratives and investigate the ethical and spiritual reasoning underlying seemingly irrational claims. In doing so, counter-narratives will be approached as both political and spiritual, as opposed to existing research that largely separates these domains. The growth of far-right discourse in wellness and spiritual communities has been met with surprise because of the assumed left-wing politics of these communities and their worldviews. This approach allows for an examination of how counter-narratives often challenge generalizations as either ‘right’ or ‘left’ wing and in the process undermine social cohesion. Challenge Counter-narratives about health, climate, and urban planning proliferate online and in person. Understanding the ethical and spiritual reasoning behind counter-narratives is necessary to learn how social polarization is formed, erodes trust in governance, and disrupts interpersonal relationships. Public health, climate adaptation, and urban planning policies will be less effective if people interpret experts in bad faith and reject the premises of scientific principles. Governance depends on some level of trust in medical, scientific, and political authorities to be effective, indicating the substantial challenge of counter-narratives that erode trust. Spirituality and politics overlap in poorly understood ways in wellness and new age spirituality making this a significant yet understudied context for counter-narratives. Objectives The objective is to study how counter-narratives drive political polarization in wellness and spiritual communities and undermine social cohesion. To address these challenges, the proposed research aims to: [1] advance the fields of anthropology and computational sociology through theorizing counter-narratives in British offline and online life using a mixed methods approach integrating ethnographic and computational text analysis. To do this, I will undertake participant observation ethnography and interviews in the town of Glastonbury, UK, and computational text analysis of online content to investigate how counter-narratives are spread online and offline. [2] Focusing on the social context over the specific content of counter-narratives, this project aims to extend anthropological analyses of social communication with work in religious studies on meta-empirical beliefs to theoretically reframe conspiracy theories as counter-narratives that broach social and epistemological gaps between experts and lay publics. [3] Impact policy on counter-narratives at both local and central government levels. Potential Applications The potential beneficiaries of this research are [1] academic researchers who study polarization and radicalization in the fields of politics, health, climate, and social science. [2] The local community through empowering them to reflect on polarization. Ongoing community consultation events will create a feedback loop between project, study community, and project partners to learn from and help communities reduce polarization and increase social cohesion. [3] Central government and policymakers who are concerned with the effects of eroding social trust on policy implementation such as in vaccine uptake, climate adaption, and traffic management. [4] Community organizations concerned with far-right infiltration and the effect this has on social cohesion and interpersonal relationships. Through these applications this research will advance the UKRI strategic theme to build a secure and resilient world.