Roy Sanderson

Enhanced Rock Weathering (ERW) involves the application of crushed silicate-rich minerals to agricultural soils as a promising Carbon Dioxide Removal (CDR) strategy, with potential benefits for soil health and crop productivity. Effective Monitoring, Reporting, and Verification (MRV) techniques are essential for carbon credit validation and scalability of ERW. Current MRV methods, such as in-field soil porewater extraction, represent a potential barrier for scaling-up ERW because the accuracy, sensitivity, and consistency of this technique is limited by soil moisture availability. Here we test a new technique for quantifying ERW called the SATuration Centrifugation (SAT-C) technique, which could prove to be a more accurate, sensitive, and consistent means of quantifying ERW. This novel method combines soil core saturation using deionized water and centrifugation to extract porewater from a defined soil volume, independent of initial moisture conditions. Comparative analyses show strong concordance between SAT-C and conventional rhizon sampling for key elemental concentrations. Furthermore, bicarbonate concentrations inferred from charge balance correlate with measured alkalinity across distinct soil types from two grassland ERW trials. SAT-C provides a robust, consistent tool for soil porewater extraction in ERW MRV, improving sampling accuracy regardless of soil moisture and thereby supporting more reliable carbon accounting and verification frameworks.

Background: There is a significant hidden burden of infectious intestinal disease (IID) in the UK community, which has increased over time. In the late 2000s, the Second Study of Infectious Intestinal Disease (IID2 study) estimated 17 million IID cases annually in the United Kingdom. However, only a small proportion of cases present to health care, and even those are often not tested for causative organisms. Objective: The Third Study of Infectious Intestinal Disease (IID3 study) aims to determine the IID burden in the UK community, estimate the underreporting level in routine practice and the general population, and recalibrate UK national surveillance based on the new incidence rates. Methods: We will follow methods of previous studies, along with modern pathogen detection methods and digital platforms for recruitment and follow-up. Participants will be recruited to three population-based prospective cohorts: cohort 1 (the general population), cohort 2 (patients with IID presenting to general practices [GPs]), and cohort 3 (enumeration study of IID cases presenting to GPs). Microbiological analysis of stool samples in cohorts 1 and 2 will include testing for a wide range of causative organisms using molecular assays, including pathogen targets not routinely sought by National Health Service (NHS) laboratories. Additional characterization of pathogens will be conducted at national reference laboratories. The incidence rates of IID and organisms detected in cohorts 1-3 will be compared to national surveillance systems, both laboratory and syndromic. Descriptive statistics and analysis will allow comparison of IID rates within each cohort, estimate the overall burden of disease caused by different pathogens, and compare findings to earlier IID studies. Results: A favorable ethical opinion was obtained from the UK Health Research Authority on August 4, 2022. A pilot phase to test the sampling process was conducted from January to August 2023. Participant recruitment commenced on September 1, 2023, for cohort 2 and on March 16, 2024, for cohort 1; recruitment ceased on August 31, 2025. Data collection is complete, and data analysis is to begin. The study is expected to end in September 2026. Conclusions: Since the first and second IID studies, changes have occurred within national surveillance systems, the NHS structure, and public recommendations about when to consult a GP and where to seek health care advice, which may have altered the extent of IID reporting and the perceived burden in the community, creating greater uncertainty about the representativeness of IID rates. The IID3 study results will provide insight into trends in disease incidence over time and help quantify inequalities in IID in the UK community. Revised estimates can inform policy related to prevention, including food standards and disease management. Furthermore, advances in molecular diagnostics will significantly enhance pathogen detection, increasing our understanding of the causes of IID. International Registered Report Identifier (IRRID): DERR1-10.2196/88759

BACKGROUND There is a significant hidden burden of infectious intestinal disease (IID) in the UK community, which has increased over time. In the late 2000s, the Second Study of Infectious Intestinal Disease (IID2 study) estimated 17 million IID cases annually in the United Kingdom. However, only a small proportion of cases present to health care, and even those are often not tested for causative organisms. OBJECTIVE The Third Study of Infectious Intestinal Disease (IID3 study) aims to determine the IID burden in the UK community, estimate the underreporting level in routine practice and the general population, and recalibrate UK national surveillance based on the new incidence rates. METHODS We will follow methods of previous studies, along with modern pathogen detection methods and digital platforms for recruitment and follow-up. Participants will be recruited to three population-based prospective cohorts: cohort 1 (the general population), cohort 2 (patients with IID presenting to general practices [GPs]), and cohort 3 (enumeration study of IID cases presenting to GPs). Microbiological analysis of stool samples in cohorts 1 and 2 will include testing for a wide range of causative organisms using molecular assays, including pathogen targets not routinely sought by National Health Service (NHS) laboratories. Additional characterization of pathogens will be conducted at national reference laboratories. The incidence rates of IID and organisms detected in cohorts 1-3 will be compared to national surveillance systems, both laboratory and syndromic. Descriptive statistics and analysis will allow comparison of IID rates within each cohort, estimate the overall burden of disease caused by different pathogens, and compare findings to earlier IID studies. RESULTS A favorable ethical opinion was obtained from the UK Health Research Authority on August 4, 2022. A pilot phase to test the sampling process was conducted from January to August 2023. Participant recruitment commenced on September 1, 2023, for cohort 2 and on March 16, 2024, for cohort 1; recruitment ceased on August 31, 2025. Data collection is complete, and data analysis is to begin. The study is expected to end in September 2026. CONCLUSIONS Since the first and second IID studies, changes have occurred within national surveillance systems, the NHS structure, and public recommendations about when to consult a GP and where to seek health care advice, which may have altered the extent of IID reporting and the perceived burden in the community, creating greater uncertainty about the representativeness of IID rates. The IID3 study results will provide insight into trends in disease incidence over time and help quantify inequalities in IID in the UK community. Revised estimates can inform policy related to prevention, including food standards and disease management. Furthermore, advances in molecular diagnostics will significantly enhance pathogen detection, increasing our understanding of the causes of IID. INTERNATIONAL REGISTERED REPORT DERR1-10.2196/88759

Mycoforestry, a farming system that produces edible fungi crops in forest plantations through controlled mycorrhizal symbiosis, has the potential to enhance biodiversity in forestry plantations and mitigate some of the negative impacts associated with modern agriculture, such as soil erosion, habitat degradation, and carbon emissions. Mycoforestry systems typically exploit a range of native fungi that can be inoculated into planting stock of commercial tree species, with biodiversity benefits delivered through expanded habitat provision for the fungi and a range of other organisms through alterations to stand structure. One mycoforestry system showing strong potential for commercial viability involves the cultivation of Lactarius deliciosus (L.:Fr.) S.F. Gray in Pinaceae plantations. This review aims to evaluate the benefits of mycoforestry systems with a focus on Lactarius deliciosus (L.:Fr.) as a case study. It will review the state of the art and discuss technical developments necessary for the successful large-scale application of mycoforestry systems.

Objectives: Fluoride exposure in children is commonly estimated using questionnaires or urinary biomarkers. However, no study has yet compared these methods for classifying participants into five intake categories ranging from low to high. This study aimed to estimate the extent of agreement and classification consistency between questionnaire‐ and urinary‐based methods for assessing total daily fluoride intake (TDFI) in children aged 4–7 years. Methods: A total of 104 healthy children across three countries (UK, Brazil, Chile) receiving one of three fluoridation modalities (non‐fluoridated‐water, fluoridated‐water, or fluoridated‐milk) provided a 24‐h urine sample and completed validated dietary and oral hygiene questionnaires. TDFI was estimated from dietary sources and toothpaste ingestion, adjusted for body weight. Urinary fluoride concentration was measured and 24 h‐UFE determined by multiplying urine volume by fluoride concentration. TDFI was predicted from 24 h‐UFE using the WHO's recommended method. Method agreement was assessed using paired t‐tests and Bland–Altman analysis to evaluate continuous fluoride intake estimates. Cohen's kappa was used to assess agreement between categorical intake classifications, while descriptive statistics reported the percentage of children in each intake group. Results: The questionnaire method estimated a higher mean TDFI (0.072 mg/kgbw/day) than the urine‐based method (0.058 mg/kgbw/day, p = 0.01). Bland–Altman analysis showed good agreement for lower mean TDFI values (< 0.10 mg/kgbw/day) but increasing variability at higher fluoride intake levels. The questionnaire classified a larger proportion of children as high exposure (≥ 0.1 mg/kgbw/day) than the urine method (19.2% vs. 11.5%), with the greatest discrepancy observed in the fluoridated milk group (46.2% vs. 7.7%). Despite these classifications, Cohen's kappa revealed minimal agreement between methods (κ = 0.034, p = 0.508), suggesting that classification concordance was likely due to chance. Conclusion: This first study comparing questionnaire and urinary methods for assessing TDFI in children found significant discrepancies and minimal agreement, especially in higher exposure groups, highlighting the risk of misclassification and the need for research into combined assessment approaches.

Background : SARS-CoV-2 emerged in the UK in January 2020. The UK government introduced control measures including national ‘lockdowns’ and local ‘tiers’ in England to control virus transmission. As the outbreak continued, new variants were detected through two national monitoring programmes that conducted genomic sequencing. This study aimed to determine the effects of weather, demographic features, and national and local COVID-19 restrictions on positive PCR tests at a sub-regional scale. Methods : We examined the spatial and temporal patterns of COVID-19 in the Teesside sub-region of the UK, from January to December 2020, capturing the first two waves of the epidemic. We used a combination of disease mapping and mixed-effect modelling to analyse the total positive tests, and those of the eight most common virus lineages, in response to potential infection risk factors: socio-economic deprivation, population size, temperature, rainfall, government interventions, and a government restaurant subsidy (“Eat Out to Help Out”). Results : Total positive tests of SARS-CoV-2 were decreased by temperature and the first national lockdown (the only one to include school closures), while deprivation, population, the second national lockdown, and the local tiered interventions were associated with increased cases. The restaurant subsidy and rainfall had no apparent effect. The relationships between positive tests and covariates varied greatly between lineages, likely due to the strong heterogeneity in their spatial and temporal distributions. Cases during the second wave appeared to be higher in areas that recorded fewer first-wave cases, however, an additional model showed the number of first-wave cases was not predictive of second-wave cases. Discussion : National and local government interventions appeared to be ineffective at the sub-regional level if they did not include school closures. Examination of viral lineages at the sub-regional scale was less useful in terms of investigating covariate associations but may be more useful for tracking spread within communities. Our study highlights the importance of understanding the effects of government interventions in local and regional contexts, and the importance of applying local restrictions appropriately within such settings.

Research on impacts of subsistence hunting on habitat use and species communities of forest wildlife is limited. Subsistence hunting of mammals in one of the world's most biodiverse region, Manu National Park, Peru, is considered sustainable, but this is based on sparse evidence. We analyzed change in species relative abundance and functional composition of mammal communities, including non‐hunted species along a hunting pressure gradient. We used camera trap data and tested for confounding effects of environmental and disturbance gradients (distances to rivers, lakes, settlements, and trails; NDVI at survey point). We found that sites with no hunting or at further distances from settlements harbor relatively more species with a larger body mass, long generation lengths, and small litters (primarily carnivores: 36% at non‐hunted site vs. 13%–29% at hunted sites), indicating selective impacts of hunting pressure on mammal communities. However, all carnivore species still occurred at all sites. Species with a smaller body mass, short generation lengths, and large litters were more prevalent at the hunted sites (mostly rodents: 23%–31% at hunted sites vs. 20% at non‐hunted site). Surprisingly, large herbivores appeared unaffected by hunting despite being one of the most hunted mammals in Manu (25% at non‐hunted site vs. 23%–27% at hunted sites). Our findings suggest that current hunting pressure is largely sustainable with only local depletion of a few sensitive species. Habitat is more important for some species than hunting pressure (e.g., distance to lake), further emphasizing the importance of local forest management.

Summary: Global biodiversity is at a heightened risk of extinction and we are losing species faster than at any other time. It is important to understand the threats that drive a species towards extinction in order to address those drivers. In this paper, we assess our knowledge of the threats faced by 24 Himalayan Galliformes species by undertaking a review of the threats reported in the published literature and the supporting evidence that the threat is having an impact on the species’ populations. Only 24 papers were deemed suitable to be included in the study. We found that biological resource use and agriculture and aquaculture are the predominant threats to the Galliformes in the Greater Himalaya but the evidence available in the studies is quite poor as only one paper quantified the impact on species. This study shows that major gaps exist in our understanding of threats to species, and it is imperative to fill those gaps if we want to prevent species from going extinct.

Species distribution models (SDMs) have been widely used to create maps of expected species incidence, often using citizen science (CS) occurrence data as inputs. Environmental policy is informed by knowledge of community distributions, but there have been fewer attempts to utilise the potential of community distribution models (CDMs) to predict these. Many countries have vegetation community classification systems which include phytosociological information on individual species. Within Great Britain, the National Vegetation Classification (NVC) is the primary standard for vegetation communities, and while maps have been produced at regional scales, cost‐effective techniques are required for national scales. Published NVC occurrence records of 22 upland NVC communities in England and Wales were used as observed occurrences (presence‐only data). Predictors for the CDMs were enhanced vegetation index (EVI), elevation, slope, aspect, temperature and rainfall. Five modelling methods were investigated: generalised linear models (GLMs), support vector machines (SVMs), random forests (RFs), maximum entropy (MaxEnt) and maximum likelihood (MaxLike). Model quality was assessed via bootstrapping via area under the curve (AUC), true skill statistic (TSS) and Kappa index. There were only small differences in the accuracy of the models (median TSS model accuracy 0.742; range 0.280 to 0.873) with RF models the best overall CDM method. Across all NVC communities, summer and winter maximum temperatures and annual rainfall were the most important predictor variables. NVCs with spatially disjunct distributions in both lowlands and uplands, or that responded to localised management or environmental conditions, were poorly predicted. Synthesis and applications. Vegetation communities can be reliably predicted at large spatial scales using CDMs from extant datasets. Management practitioners can use community‐level predictions to design targeted field surveys for individual species typically associated with specific communities. Most existing CS survey schemes focus on species rather than communities. Hence future development of new CS schemes similar to the National Plant Monitoring Scheme (NPMS), that aligns with the NVC, will enable CS data to generate up‐to‐date maps of both communities and species.