University of Stirling

Inadequate waste management and poor sanitation practices in Low- and Middle-Income Countries (LMICs) leads to waste accumulation in urban and peri-urban residential areas. This increases human exposure to hazardous waste, including plastics, which can harbour pathogenic bacteria. Although lab-based studies demonstrate how plastic pollution can increase the persistence and dissemination of dangerous pathogens, empirical data on pathogen association with plastic in real-world settings are limited. We conducted a year-long spatiotemporal sampling survey in a densely populated informal settlement in Malawi, quantifying enteric bacterial pathogens including ESBL-producing E. coli, Klebsiella pneumoniae, Salmonella spp., Shigella spp., and Vibrio cholerae. Culture-based screening and molecular approaches were used to quantify the presence of each pathogen, together with the distribution and frequency of resistance to antibiotics. Our data indicate that these pathogens commonly associate with urban waste materials. Elevated levels of these pathogens precede typical infection outbreaks, suggesting that urban waste piles may be an important source of community transmission. Notably, many pathogens displayed increased levels of AMR, including against several ‘last resort’ antibiotics. These findings highlight urban waste piles as potential hotspots for the dissemination of infectious diseases and AMR and underscores the need for urgent waste management interventions to mitigate public health risks.

Ever since the first large language models (LLMs) have become available, both academics and practitioners have used them to aid software engineering tasks. However, little research as yet has been done in combining search-based software engineering (SBSE) and LLMs. In this paper, we evaluate the use of LLMs as mutation operators for genetic improvement (GI), an SBSE approach, to improve the GI search process. In a preliminary work, we explored the feasibility of combining the Gin Java GI toolkit with OpenAI LLMs in order to generate an edit for the JCodec tool. Here we extend this investigation involving three LLMs and three types of prompt, and five real-world software projects. We sample the edits at random, as well as using local search. We also conducted a qualitative analysis to understand why LLM-generated code edits break as part of our evaluation. Our results show that, compared with conventional statement GI edits, LLMs produce fewer unique edits, but these compile and pass tests more often, with the OpenAI model finding test-passing edits 77% of the time. The OpenAI and Mistral LLMs are roughly equal in finding the best run-time improvements. Simpler prompts are more successful than those providing more context and examples. The qualitative analysis reveals a wide variety of areas where LLMs typically fail to produce valid edits commonly including inconsistent formatting, generating non-Java syntax, or refusing to provide a solution.

Riverbank erosion is a naturally occurring process that influences riparian zone habitats. However, anthropogenic activities are increasing rates of riverbank erosion. Climate change and hydrological and physical modifications drive riparian zone perturbations. Whilst native riparian vegetation can reduce riverbank erosion, the proliferation of non‐native riparian plant species has been linked to riverbank instability, with marked changes in fluvial erosional regimes attributed to invasion by species such as Impatiens glandulifera (Himalayan Balsam) or Tamarix (Tamarisk) into riparian zones. Yet, the role of non‐native plant species in modulating riverbank erosion remains unclear, in part due to the lack of investigations that quantify geomorphic change. We systematically assessed the relevant ecological and geomorphological literature to determine current understanding and to offer recommendations for future research on non‐native plant—riverbank erosion. Included articles focused on a limited number of non‐native plant species across a restricted range of habitats types, with dependency on topographic change and generally short study duration obscuring potential causal links or feedback cycles. It is critical in the face of parallel rapid proliferation of riparian non‐native plant species and climate change effects, that we improve mechanistic understanding of their role in riverbank erosion.

Trees affect organic matter decomposition through allocation of recently fixed carbon belowground, but the magnitude and direction of this effect may depend on substrate type and decomposition stage. Here, we followed mass loss, chemical composition and fungal colonisation of leaf and root litters incubated in mountain birch forests over 4 years, in plots where belowground carbon allocation was severed by tree girdling or in control plots. Initially, girdling stimulated leaf and root litter mass loss by 12% and 22%, respectively, suggesting competitive release of saprotrophic decomposition when tree‐mediated competition by ectomycorrhizal fungi was eliminated (Gadgil effect). After 4 years, girdling instead hampered mass loss of root litter by 30%, suggesting late‐stage priming of decomposition in the presence of trees, in parallel with increased growth of shrubs and associated fungi following tree elimination. Hence, different mechanisms driving early‐ and late‐stage litter decomposition should be considered in climate‐feedback evaluations of plant–soil interactions.

Aim The long‐term survival of many mammal populations relies on how effectively we mitigate the threat from unsustainable hunting. Yet, hunting activities are often cryptic, especially in unprotected forests. Here, we investigate whether hunting signs can help understand the spatiotemporal dynamics of hunting activities in an unprotected African rainforest and examine how landscape characteristics predict various indicators of hunting. Location Ebo forest, Cameroon, Central Africa. Methods We recorded hunting signs (e.g., shotgun cartridges, wire snares, direct sightings) systematically on 23 parallel recce lines across the Ebo forest from 2008 to 2023. We assigned hunting data and spatial covariates (e.g., elevation, distance to village) to 1 × 1 km grid cells and applied generalised linear mixed models to predict the effects of these covariates on hunting. Results We found that hunting was commonplace across the entire Ebo forest. The best‐fitting models for each hunting sign differed considerably. Shotgun cartridges and all hunting signs combined increased significantly from 2016 to 2023 and varied non‐linearly along the village‐distance gradient. We found a progressive inversion of hunting trends along the anthropogenic gradient; between 2016 and 2018, wire snares declined with the distance to road but from 2021, they increased along the road‐distance gradient. Wire snares showed a similar pattern along the river‐distance gradient. Our results also revealed differences between shotgun hunting and snaring along the altitudinal gradient; the effect of elevation was positive on shotgun cartridges and negative on wire snares. Hunting signs and trails decreased significantly with increasing terrain ruggedness. Main Conclusions Using long‐term monitoring data, we show how hunting patterns change dynamically with respect to human and landscape‐related features. We also demonstrate complex hunting patterns along the gradient of human influence, therefore questioning the use of proxies such as the distance to human settlements and even topography to account for hunting pressure. Overall, we show that hunting sign data can reveal the spatiotemporal patterns of hunting, crucial in evaluating the effectiveness of conservation interventions and guiding the prioritisation of limited conservation resources.

Tree-planting is increasingly presented as a cost-effective strategy to maximise ecosystem carbon (C) storage and thus mitigate climate change. Its success largely depends on the associated response of soil C stocks, where most terrestrial C is stored. Yet, we lack a precise understanding of how soil C stocks develop following tree planting, and particularly how it affects the form in which soil C is stored and its associated stability and resistance to climate change. Here, we present changes in C and nitrogen (N) stored as mineral-associated organic matter (OM), occluded particulate OM, free particulate OM and dissolved OM, from four regional chronosequences of Scots pine (Pinus sylvestris L.) forests planted on former grasslands across Scotland. We found that c. 58-68 years after the plantation, bulk soil C and N stocks in the organic layer and the top 20 cm of mineral soil decreased by half relative to unforested grasslands-a decrease roughly equivalent to a third of the simultaneous C gain in the tree biomass. This pattern was driven predominantly by a decrease in the amount of C and N stored as mineral-associated OM, an OM fraction considered as relatively long-lived. Our findings demonstrate the need to estimate C storage in response to tree planting based both on soil C stocks and tree biomass, as the use of the latter alone may significantly overestimate net C benefits of tree planting on permanent grasslands.

Many US policy process theories have been applied as much in Europe as in the US. We assess this journey in three ways. First, we use published reviews of the field to identify the high quantity of applications and their concentration in Western European liberal democracies. Second, we identify the absence of a typical European country experience and our expectation of finding variability across European countries when applying US theories. Third, we survey policy scholars in Europe on how and why they apply US theories to European contexts. Our survey establishes what theories they applied, why, and to what effect. It takes forward a new research agenda on the international application of mainstream policy theories.

A limited qualitative literature explores children's lived experiences of violence; boys’ relationships with perpetrator fathers remain largely unexplored. Drawing on interviews with 31 boys, this paper explores the accounts of their relationships with their perpetrator fathers, focusing particularly on the implications of boys’ understanding of these relationships for their sense of burgeoning masculinity. Three themes are considered: in (a) relational ambiguity; (b) performing masculinities, managing violence; and (c) envisioning alternative futures and re-visioning the past. Our findings highlight the importance of interventions for boys that facilitate the expression of their often complex and ambivalent feelings and fears about their father's violence, and what it means for them and their future.

Enabled by the rapid rise in data collected by technologies, Digital Biomarkers (DBx) have emerged as a novel mechanism for assessment, diagnosis, and monitoring. However, the exponential growth and ability to generate new data has also raised questions about ways of ensuring the authenticity and accuracy of digital data. A recent study highlights how Large Language Models (LLMs) generating human-like content amplify these risks, and propose watermarking as a scalable solution to ensure data integrity. This article examines the potential of digital watermarking to help safeguard the reliability and provenance of DBx data, whilst also addressing broader challenges in health systems.

Background Traumatic brain injury (TBI) is associated with an increased risk of major depressive disorder (MDD) and post-traumatic stress disorder (PTSD). We aimed to identify predictors and develop models for the prediction of depression and PTSD symptoms at 6 months post-TBI. Methods We analysed data from the Collaborative European NeuroTrauma Effectiveness Research in Traumatic Brain Injury study. We used linear regression to model the relationship between predictors and depression (Patient Health Questionnaire-9) and PTSD symptoms (PTSD Checklist for Diagnostic and Statistical Manual for Mental Health Disorders Fifth Edition). Predictors were selected based on Akaike’s Information Criterion. Additionally, we fitted logistic models for the endpoints ‘probable MDD’ and ‘probable PTSD’. We also examined the incremental prognostic value of 2–3 weeks of symptoms. Results We included 2163 adults (76% Glasgow Coma Scale=13–15). Depending on the scoring criteria, 7–18% screened positive for probable MDD and about 10% for probable PTSD. For both outcomes, the selected models included psychiatric history, employment status, sex, injury cause, alcohol intoxication and total injury severity; and for depression symptoms also preinjury health and education. The performance of the models was modest (proportion of explained variance=R ² 8% and 7% for depression and PTSD, respectively). Symptoms assessed at 2–3 weeks had a large incremental prognostic value (delta R ² =0.25, 95% CI 0.24 to 0.26 for depression symptoms; delta R ² =0.30, 95% CI 0.29 to 0.31 for PTSD). Conclusion Preinjury characteristics, such as psychiatric history and unemployment, and injury characteristics, such as violent injury cause, can increase the risk of mental health problems after TBI. The identification of patients at risk should be guided by early screening of mental health.

In this paper, two researchers with backgrounds in ethnography describe and reflect on their experiences from a qualitative, transnational study called 'Back to the Future: Archiving in Residential Children's Homes (ARCH) in Scotland and Germany. Important goals of the study are the investigation and development of digital community archives for young people, care workers and care leavers from residential homes in order to support their memories of shared everyday life. Methodologically, the study is based on ideas of participatory research in combination with ethnographic elements, although there were some changes in the implementation compared to the original plan. These changes were made on the basis of conditions found in the field and represented attempts to achieve the goals of the study despite some unexpected situations and developments. This resulted in moments of tension, which we reflect on self-critically in this article. Using the example of our research, we highlight some of the opportunities and challenges of qualitative study designs that seek to understand and change realities in the context of social work.