The research builds on a monitoring programme initiated by the UK Technical Advisory Group under the European Union Water Framework Directive, which sought a reliable, non-invasive alternative to electrofishing and netting for assessing lake fish communities. Earlier pilot work, including a landmark study of Windermere, England’s largest lake, had established that twenty water samples collected at equidistant points around a lake’s perimeter were sufficient to detect the vast majority of fish species and to produce ecologically meaningful estimates of relative abundance. What remained unclear was how much of that effort was truly necessary, and whether cutting the number of samples would distort estimates of species richness or community composition.

To answer those questions, the team assembled an unusually comprehensive dataset: 2,134 water samples collected between January 2015 and March 2019 from 101 lakes spanning the full range of British lake types, from Scoat Tarn at just 4.3 hectares to Loch Lomond at nearly 5,159 hectares, and from shallow, nutrient-rich lowland waters to deep, acidic upland tarns. Most sampling took place in winter, between November and March, when British lakes are typically well mixed and free of thermal stratification. Each two-litre sample was a composite of five subsamples drawn along a 100-metre transect, filtered within 24 hours, and processed using a vertebrate-specific 12S ribosomal RNA marker that amplifies a short fragment of fish DNA.

After bioinformatic cleaning, which removed low-frequency reads below a 0.1 percent noise threshold and excluded taxa that the marker could not reliably resolve to species level, the final dataset contained 1,792 successfully sequenced shoreline samples and recorded 40 fish taxa across the lakes. Individual lakes yielded between 2 and 18 species, with an average of just under 8. The researchers then applied three complementary analytical approaches: rarefaction-based species accumulation curves, statistical estimation of sample coverage, and extensive resampling of the data to simulate reduced sampling effort.

The results were striking. Sample coverage analysis showed that 93 of the 101 lakes achieved at least 95 percent coverage of their fish species with only ten samples, and 96 lakes reached that threshold with eleven. The mean sampling threshold across all lakes was just 5.37 samples. Resampling analysis, which generated hundreds of unique random combinations of samples for each of 82 lakes with fifteen or more samples, confirmed the pattern: at a sample size of ten, fewer than two species went undetected on average in 95 percent of lakes. Community composition estimates were similarly robust, with Bray-Curtis dissimilarity between reduced subsets and the full lake dataset falling below an arbitrary threshold of 0.1 in 95 percent of lakes at fifteen samples.

Perhaps the most surprising finding concerned lake size. Intuitively, one might expect that a vast lake like Loch Lomond would demand far more sampling than a small tarn, because DNA shed by fish in the middle of a large water body may never reach the shore. Yet the analysis found no correlation between lake surface area and the number of samples needed to achieve reliable detection. Instead, the strongest predictor of sampling effort was species richness itself: lakes harbouring more fish species required more samples to capture them all. This means that monitoring programmes can use prior knowledge of a lake’s expected diversity, rather than its size, to plan an efficient survey.

The study also validated a major simplification in field logistics. In the 20 lakes where both shoreline and offshore transects had been sampled, species richness showed no significant difference between the two approaches, and the proportion of total species detected was nearly identical, averaging 87 percent for shoreline samples and 85 percent for offshore ones. Only one species, the invasive topmouth gudgeon Pseudorasbora parva, was unique to offshore samples, while six species were recorded only from shoreline transects. Although ordination analysis revealed small differences in community composition between transect types in some lakes, these were minor compared with differences among lakes. The practical implication is substantial: monitoring teams can skip boats and specialised deep-water sampling equipment entirely during winter, collecting all samples on foot from accessible shoreline points.

The researchers attribute the success of winter shoreline sampling to the physics of temperate lakes in the cold season. With thermal stratification absent, wind and convective mixing circulate water, and the DNA it carries, throughout the lake, transporting genetic material from deeper habitats toward the shore. Cold temperatures also slow the degradation of extracellular DNA, prolonging the window in which it can be detected. This picture is consistent with earlier work showing that in stratified summer conditions, eDNA distribution becomes far more localised, and shoreline sampling can miss deepwater species entirely. The authors are careful to note that their recommendations apply specifically to polymictic conditions in autumn and winter, and may not transfer to summer surveys or to lakes in warmer climates.

There is an important caveat for conservation applications. While halving the sampling effort had little effect on estimates of overall richness and community structure, rare species were disproportionately likely to be missed in reduced datasets. For programmes targeting endangered natives or early-stage invasive species, where a single detection can trigger management action, the authors recommend retaining a minimum of twenty samples per lake. Detection probability in eDNA surveys also depends on factors beyond sample number, including PCR replication, primer choice, extraction protocol and sequencing depth, so laboratories using different workflows may need to recalibrate these thresholds for their own pipelines.

The broader significance of the study lies in its framework rather than any single number. By combining species accumulation curves, coverage estimation and both random and spatially informed resampling, the authors provide a template that other monitoring programmes can apply to their own systems and objectives. Halving the number of samples per lake translates directly into fewer person-hours in the field and lower filtration and molecular processing costs, potentially allowing the same budget to cover twice as many lakes. For a method whose promise is landscape-scale biodiversity monitoring, that kind of cost optimisation may prove as important as the molecular innovations that made eDNA metabarcoding possible in the first place.

Subject of Research: Optimising environmental DNA sampling effort for lake fish biodiversity monitoring

Article Title: Optimising species detection probability and sampling effort in lake fish eDNA surveys

Article References: Sellers, G. S., Jerde, C. L., Harper, L. R., Benucci, M., Di Muri, C., Li, J., Peirson, G., Walsh, K., Hatton-Ellis, T., Duncan, W., Duguid, A., Ottewell, D., Willby, N., Law, A., Bean, C. W., Winfield, I. J., Read, D. S., Handley, L. L., & Hänfling, B. (2024). Optimising species detection probability and sampling effort in lake fish eDNA surveys. Metabarcoding and Metagenomics, 8, Article e104655. https://doi.org/10.3897/mbmg.8.104655

Image Credits: AI Generated

DOI: 10.3897/mbmg.8.104655

Keywords: environmental DNA, eDNA metabarcoding, lake fish, biodiversity monitoring, sampling effort, species richness, Water Framework Directive, shoreline sampling, rarefaction, community composition, Great Britain, conservation

The research team, led by Sarah E. Jackson of University College London’s Department of Behavioural Science and Health, analysed monthly, nationally representative survey data collected across England, Wales and Scotland. Alcohol consumption was measured using the AUDIT-C, the consumption subset of the Alcohol Use Disorders Identification Test, a validated screening instrument widely used in epidemiological research. The AUDIT-C scores respondents on three questions covering drinking frequency, typical quantity, and frequency of heavy episodic drinking, yielding a total score from 0 to 12. In this study, a score of 5 or above was defined as risky drinking, a threshold that captures patterns of consumption associated with elevated long-term health risks including cancer, liver disease and cardiovascular damage. A score of 11 or above was classified as possible dependent drinking, indicating a pattern consistent with alcohol dependence, characterised by loss of control over intake and continued drinking despite harm.

The headline prevalence figures for 2024/25 are sobering in their scale. The study found that 31.8 percent of adults reported risky drinking, with a 95 percent confidence interval of 31.5 to 32.1 percent, while 1.49 percent reported possible dependent drinking, with a confidence interval of 1.42 to 1.57 percent. Because the Alcohol Toolkit Study samples adults aged 18 and over in a manner designed to reflect the national population, these percentages can be converted into population estimates with reasonable confidence: approximately 16.2 million risky drinkers and 814,000 possible dependent drinkers in Great Britain. Put another way, for every person whose drinking pattern suggests possible dependence, roughly twenty more are drinking at levels that quietly elevate their risk of future disease. The sheer size of the risky-drinking group is what makes the finding a population-level concern rather than a niche clinical one.

Perhaps the most valuable contribution of the analysis lies in its disaggregation, revealing that harmful drinking is far from evenly spread. Risky drinkers as a group were slightly younger than the adult population overall, with a mean age of 46.0 years compared with 48.6 years, and were markedly more likely to be men, at 61.9 percent versus 48.5 percent of the general adult population. This male skew is consistent with long-standing patterns in alcohol epidemiology, but the study shows the imbalance becomes dramatically steeper at the severe end of the spectrum. Among those drinking at levels indicative of possible dependence, 77.2 percent were men. The mean age of this group was 49.1 years, suggesting that dependence in this population is concentrated in middle age, a life stage when the cumulative physiological toll of heavy drinking begins to manifest as measurable organ damage.

Socioeconomic patterning emerged as another critical dimension of the findings. Possible dependent drinkers were disproportionately drawn from less advantaged occupational social grades, with 26.7 percent belonging to these categories compared with 23.3 percent of all adults. This overrepresentation, while numerically modest at the group level, compounds existing health inequalities because disadvantaged communities already bear a disproportionate burden of alcohol-attributable mortality and morbidity. The study also found that fewer possible dependent drinkers lived with children, at 20.7 percent compared with 28.3 percent of the general adult population. The authors note this may reflect the social disruption that accompanies severe alcohol problems, including relationship breakdown and family separation, though the cross-sectional nature of the survey data means the direction of any such association cannot be established from this study alone.

Geography matters too, and the regional contrasts revealed by the analysis are among its most striking elements. Risky drinking was modestly more prevalent in northern England than elsewhere, but the gradient sharpened considerably for possible dependent drinking. In Yorkshire and Humber, 2.35 percent of adults reported drinking at levels indicative of possible dependence, a figure more than two and a half times the 0.91 percent recorded in London. This north-south divide echoes broader patterns in British health statistics, where life expectancy, chronic disease prevalence and alcohol-specific deaths all worsen along a gradient running from the affluent southeast toward deindustrialised northern regions. The concentration of dependent drinking in specific regions suggests that interventions may need to be geographically targeted rather than uniformly applied, channelling resources toward the communities where the severe end of the drinking spectrum is most heavily represented.

The timing of the study gives it particular significance. Alcohol-specific mortality in Great Britain has risen since 2020, a trend widely linked to disruptions during the COVID-19 pandemic, when lockdowns, bereavement, economic insecurity and social isolation altered drinking habits in ways that appear to have persisted for some people. By anchoring its measurement window in October 2020, the Alcohol Toolkit Study captures the population in the immediate aftermath of the first pandemic wave and follows it through five full years of change. The study’s monthly cadence is a methodological strength: rather than relying on occasional snapshots, it smooths out seasonal fluctuations in drinking, such as the well-documented December peaks, and provides a stable rolling estimate of population behaviour. With 135,295 respondents, the sample size also gives the confidence intervals enough precision to distinguish between regions and demographic groups with statistical confidence.

The measurement approach deserves attention from readers weighing the findings. The AUDIT-C is a brief self-report instrument, and self-reported consumption is known to understate true intake, since people systematically underestimate both how much they drink and how often. This means the prevalence figures, already alarming, are likely conservative. The threshold of 11 for possible dependence is a screening cut-off, not a clinical diagnosis; a formal diagnosis of alcohol dependence requires a fuller assessment covering withdrawal symptoms, craving and functional impairment. The authors are careful in their language, describing the 1.49 percent figure as possible dependent drinking rather than confirmed dependence. Even so, screening instruments of this kind are designed to cast a wide net for clinical follow-up, and when applied to a population of tens of millions, the numbers of people flagged become a genuine public health signal rather than statistical noise.

The study was supported by Cancer Research UK and the Economic and Social Research Council, and its authors declare no financial links with the alcohol industry apart from a disclosed unrelated project on alcohol-free drinks funded by Alcohol Change UK, a charity of which less than 0.6 percent of 2024/25 funds came from a non-alcoholic drinks producer. The researchers conclude that the combination of high overall prevalence, roughly one in three adults drinking at risky levels, and pronounced sociodemographic and geographic inequalities underscores an urgent need for effective population-level interventions. Such measures, in the broader public health literature, include pricing policies such as minimum unit pricing, restrictions on alcohol marketing and availability, and improved access to treatment and brief interventions in primary care. What this study adds is the evidence base for targeting: knowing that dependent drinking clusters among middle-aged men, disadvantaged social grades, households without children, and specific northern regions allows policymakers to direct screening and treatment resources with far greater precision than a one-size-fits-all national campaign would permit.

For a nation whose drinking culture is woven into social life, the message of this research is difficult to dismiss. Sixteen million people drinking at risky levels is not a fringe phenomenon but a mainstream pattern, one that guarantees a steady downstream flow of liver disease, cancers, injuries and premature deaths unless the trajectory changes. The study’s five-year window demonstrates that these patterns have proven durable since the pandemic rather than transient. As alcohol-specific mortality continues to climb, the data argue that the window for prevention is not in the clinic, where dependence is already entrenched, but in the population at large, where a modest shift in the drinking distribution of 16 million people would avert far more harm than treating the 814,000 at the severe end alone. The numbers are now on the table; the question is what Britain chooses to do with them.

Subject of Research: Prevalence and sociodemographic and geographic patterns of risky and dependent alcohol drinking among adults in Great Britain from 2020 to 2025.

Article Title: Prevalence and patterns of risky and dependent drinking in Great Britain, 2020–2025

Article References: Jackson, S. E., Cox, S., Buss, V., Hamilton, T., Brown, J., & Oldham, M. (2026). Prevalence and patterns of risky and dependent drinking in Great Britain, 2020–2025. BMC Medicine. https://doi.org/10.1186/s12916-026-05210-2

Image Credits: AI Generated

DOI: 10.1186/s12916-026-05210-2

Keywords: alcohol consumption, risky drinking, alcohol dependence, AUDIT-C, Great Britain, public health, health inequalities, Alcohol Toolkit Study, alcohol-specific mortality, regional disparities, epidemiology, BMC Medicine

The study, led by David Wembridge of the People’s Trust for Endangered Species together with statisticians from the British Trust for Ornithology and the Game and Wildlife Conservation Trust, brings together records collected between 1981 and 2024. Because hedgehogs are nocturnal, widely dispersed and often present at low densities, no single survey can capture the national trajectory of the species. Instead, the researchers combined five independent sources: the BTO’s Garden BirdWatch, PTES’ Living with Mammals, the Breeding Bird Survey run by BTO, JNCC and RSPB, PTES’ Mammals on Roads, and the National Gamebag Census maintained by the Game and Wildlife Conservation Trust. Each scheme uses different methods, covers different periods and samples different habitats, which makes agreement between them all the more persuasive.

The most alarming signal comes from the National Gamebag Census, which records animals accidentally killed in tunnel traps set by gamekeepers for species such as stoats and brown rats. In the first five years of the dataset, from 1981 to 1985, an average of 19.3 per cent of participating estates reported hedgehogs each year. By 2019 to 2023, that figure had collapsed to just 2.7 per cent, with the number of contributing sites in England falling from 124 per year to seven. After statistical smoothing, the national index showed a decline of 70.7 per cent between 1981 and 2023, with England faring worst at 80.4 per cent and Scotland at 64.9 per cent. Crucially, the rate of decline has accelerated: the mean annual rate over the last ten years of the series was 6.81 per cent, more than double the long-term average.

The spatial story is equally troubling. When the researchers mapped standardised counts across 10 by 10 kilometre grid squares, hedgehogs in the 1980s appeared widespread and comparatively abundant across much of Great Britain. By the 2010s, high-density areas had contracted to a narrow band covering south-east Scotland, north Wales and eastern England. Zones with no hedgehog records expanded eastward from the west coast, and the animals are no longer reported from most of western and northern Scotland, apart from some Hebridean islands, nor from parts of the West Midlands, northern England and the southern regions. The researchers argue that this pattern is unlikely to be an artefact of changing reporting behaviour, since a shift in attitudes among gamekeepers would not produce a decline that begins in the south-west and spreads east; the data instead point to genuine population loss.

Two further rural datasets corroborate the trend. The Breeding Bird Survey, in which volunteers walk randomly selected 1-kilometre transects each spring, recorded an 80.4 per cent decline in hedgehog occurrence between 2002 and 2023. Mammals on Roads, which logged casualties reported by volunteers on summer journeys, showed a 54.4 per cent drop in encounter rates between 2002 and 2013. The authors took care to control for journey length and recording method, both of which influenced casualty counts, yet the underlying decline persisted. Together with the Gamebag Census, these three independent schemes, using three different methodologies, tell a consistent story of steep rural decline.

Against this backdrop, the urban data come as a surprise. Garden BirdWatch, drawing on more than 5,000 gardens, showed an initial dip in the proportion of sites recording hedgehogs, but the index rose above its 2009 baseline by 2017, ending the series 24 per cent higher. Living with Mammals, which surveys green spaces within 200 metres of buildings, showed a plateau after 2012 and an overall occurrence change of minus 23.9 per cent between 2004 and 2024, though with wide uncertainty. More tellingly, average maximum counts at sites where hedgehogs were actually seen increased in both surveys, by 6.7 per cent in Garden BirdWatch and 20 per cent in Living with Mammals. In other words, where hedgehogs persist in towns, they appear to be doing reasonably well.

Why would a species thrive in cities while collapsing in the countryside? The authors point to several plausible mechanisms. Urban gardens offer a mosaic of habitat features, supplementary food and connectivity through garden boundaries, and hedgehogs are known to select such environments even within intensively farmed landscapes. Densities of badgers, an intraguild predator that can dominate hedgehogs, are generally lower in built-up areas than in rural ones, and badger populations have grown substantially since the 1980s. In the wider countryside, agricultural intensification has reduced habitat diversity and the abundance of the invertebrate prey on which hedgehogs depend, while road mortality compounds pressures at local scales. The study’s analysis of Living with Mammals sites found significant changes in garden characteristics over two decades, including increases in ponds, bird feeders and, remarkably, a 40.7 per cent rise in the proportion of sites with hedgehog nest boxes, suggesting that wildlife-friendly gardening may be actively supporting urban populations.

The authors are candid about the limitations of their evidence. None of the five schemes was designed specifically to monitor hedgehogs, and detection of a nocturnal species during daytime surveys is inherently low; the Breeding Bird Survey’s estimated detection rate was just 8.6 per cent. Changes in participant effort, trap design, legislation protecting non-target species and the growing use of trail cameras could all influence the indices. Yet the researchers found no evidence that trapping effort in the Gamebag Census declined, with capture rates for stoats and weasels remaining similar between the early 1980s and recent years, which suggests the hedgehog decline is real and specific. They also note that self-selection bias in garden surveys means participants are likely to be wildlife enthusiasts whose sites may not represent gardens in general.

The broader significance extends beyond one charismatic species. Hedgehogs are generalists, and the decline of a widespread, adaptable mammal may signal wider ecological degradation of the British landscape, echoing the well-documented collapses of farmland birds and butterflies across Europe. Because common species contribute disproportionately to ecosystem functioning, their loss can matter more than the extinction of rare ones. The hedgehog was recently reassessed as Vulnerable in Great Britain and Near Threatened globally, and the new figures will feed into ongoing conservation planning, including a national hedgehog conservation strategy coordinated by the IUCN’s Conservation Planning Specialist Group.

The study’s authors call for a standardised, hedgehog-specific monitoring programme to fill knowledge gaps, verify regional patterns and produce robust density estimates across habitats. A pilot project using camera-trap arrays within a citizen science framework is already under way and may address some of the detection problems that have hampered volunteer surveys to date. In the meantime, the findings carry a clear message for the public: the gardens, parks and allotments of Britain’s towns may now be among the last strongholds of one of its most cherished mammals, and the choices made in those green spaces, from hedgehog highways in fences to ponds and supplementary feeding, could shape the species’ future more than any rural intervention currently on offer.

Subject of Research: National-scale population trends and conservation status of the West European hedgehog in Great Britain

Article Title: West European Hedgehog (Erinaceus europaeus) Decline in Great Britain: Evidence From Multiple National‐Scale Surveys

Article References: Wembridge, D. E., Langton, S. D., Pringle, H., Aebischer, N. J., Ewald, J. A., Noble, D. G., & Petrovan, S. O. (2026). West European Hedgehog ( Erinaceus europaeus ) Decline in Great Britain: Evidence From Multiple National‐Scale Surveys. Ecology and Evolution, 16(10), Article e74321. https://doi.org/10.1002/ece3.74321

Image Credits: AI Generated

DOI: 10.1002/ece3.74321

Keywords: hedgehog, Erinaceus europaeus, population decline, citizen science, Great Britain, agricultural intensification, urban ecology, badger predation, National Gamebag Census, monitoring schemes, conservation, road mortality

The challenge the researchers faced is a familiar one in the extra-tropics: seasonal weather forecasting is hard. Britain’s variable maritime climate has long limited the usefulness of seasonal hydrological forecasts, and even the best global models achieve only weak correlations with observed seasonal rainfall over the UK. The earlier version of the national forecasting scheme, driven by the Met Office’s GloSea5 seasonal prediction system, had a further handicap. Although the underlying climate model ran at roughly 50 kilometre resolution, only the UK-average rainfall anomaly was supplied operationally. To feed a hydrological model working at 1 kilometre, that single national number was spread uniformly across the country, wiping out the dramatic regional contrasts that define British weather, from the drenched hills of western Scotland to the drier east of England.

The new approach, known as Historic Weather Analogues (HWA), takes a different route. Rather than using raw rainfall output from the climate model directly, the team exploits the fact that large-scale atmospheric circulation patterns, such as the North Atlantic Oscillation (NAO), are predicted considerably better than local rainfall itself. The method begins with an ensemble of roughly 40 mean sea level pressure forecasts from the current GloSea6 system, covering the North Atlantic and Europe. For each ensemble member, the researchers search the observational record for historical years whose pressure patterns most closely match the forecast, ranking candidates by root mean squared difference and selecting the best ten. The observed rainfall from those analogue years, drawn from the 1 kilometre HadUK-Grid dataset and adjusted with a linear climate-change correction, then becomes the rainfall forecast.

There is a subtle statistical twist for winter forecasts. Climate scientists have identified a so-called signal-to-noise paradox, in which the ensemble mean of a seasonal forecast system correlates well with observations even though its variance is too small. To correct for this, the team amplifies the NAO signal in the GloSea6 pressure ensembles for forecasts spanning November through April, restricting the pool of analogue years to those with a monthly-mean NAO index within 4 hectopascals of the adjusted forecast. This conditioning step is one reason the system performs best in winter, when the NAO’s grip on British rainfall is strongest, particularly across the north and west of the country.

These rainfall forecasts then feed a two-stage hydrological pipeline. First, the Grid-to-Grid (G2G) hydrological model is run over the preceding months using observed rainfall and evaporation, producing detailed estimates of the water held in surface and subsurface stores at the moment the forecast begins. These hydrological initial conditions capture the memory of the landscape, how wet the soils are, how full the aquifers lie. Second, a monthly-resolution Water Balance Model combines those initial stores with the forecast rainfall, evaporation and storage-dependent outflows to project river flows one to three months ahead. Runoff from every upstream grid cell is accumulated along the river network, and the resulting flows are expressed as anomalies relative to long-term conditions and sorted into seven classes, from exceptionally low to exceptionally high, mirroring the Environment Agency’s Water Situation Reports.

To test the system, the team generated hindcasts, re-forecasts of past conditions, covering 1993 to 2017, the international standard verification period for seasonal prediction systems participating in the Copernicus Climate Change Service. They scored the forecasts with three complementary metrics: the Pearson correlation, which measures how well the ensemble mean tracks the observed signal; the Continuous Ranked Probability Skill Score, which rewards forecasts whose full probability distributions beat simply assuming climatology; and the Relative Operating Characteristic, which tests the ability to detect above-normal and below-normal flow events. The verdict is nuanced but encouraging. The rainfall forecasts themselves are only marginally skilful on average, with spatially averaged winter correlations of about 0.18 at 1 kilometre resolution, and they are actively misleading in summer, when the underlying GloSea6 model struggles to predict summer pressure patterns.

The river flow forecasts, however, tell a much stronger story. Seasonal flow predictions achieve spatially averaged correlations of 0.48 in winter, with 90 percent of river pixels exceeding 0.2, and remain useful in spring (0.38) and autumn (0.36), collapsing only in summer (0.08). Much of this skill does not come from the rainfall forecasts at all, but from the hydrological initial conditions. Rivers in many catchments have long hydrological memory, and knowing how much water is already stored in the ground can carry a forecast a long way. The most striking example is the chalk of southern England, where deep aquifers dominate river behaviour; there, even summer forecasts reach correlations of 0.4 to 0.7, and the classified forecasts consistently pick the right flow category.

Perhaps the most elegant result is a national-scale decomposition of where the skill comes from. By running the model with rainfall forecasts paired with climatological initial conditions, and separately with historical rainfall sequences paired with modelled initial conditions, the researchers mapped the complementary contributions of meteorology and memory. In responsive catchments of the northwest, where flows track recent rainfall and the NAO, the analogue rainfall forecasts supply most of the skill. In the south and east, where slow-draining aquifers dominate, the initial conditions carry the forecast. In western Scotland, neither source alone suffices, but combining them yields significant skill. This pattern, previously demonstrated only for a handful of gauged catchments, now extends across the entire 1 kilometre river network, and it tells forecast developers precisely where better rainfall predictions or better hydrological modelling would pay the greatest dividends.

Compared with the previous GloSea5-based scheme, the new system better predicts the likelihood of high- and low-flow events in three of the four seasons, with December monthly forecasts flipping from negative to positive skill and spring skill scores more than doubling. The authors are candid about limitations: the hindcast sample is small, excludes the most extreme events, and predates recent climatic shifts, though operational comparisons suggest performance has not changed materially. Future work will enlarge the atmospheric ensemble as supercomputing capacity grows, explore replacing the simple monthly water balance with the full process-based G2G model, and statistically blend the multiple forecasting methods behind the Hydrological Outlook. For now, high-resolution monthly and seasonal forecasts are already being released through the Hydrological Outlook Portal, giving water managers, flood responders and reservoir operators across Britain a genuine three-month head start.

Subject of Research: Seasonal hydrological forecasting of river flows in Great Britain using historical weather analogue rainfall forecasts and national-scale hydrological modelling

Article Title: Improved seasonal hydrological forecasting for Great Britain

Article References: Rhodes-Smith, M. D., Bell, V. A., Stringer, N., Baron, H., Davies, H., & Knight, J. (2026). Improved seasonal hydrological forecasting for Great Britain. Hydrology and Earth System Sciences, 30(19), 6189-6206. https://doi.org/10.5194/hess-30-6189-2026

Image Credits: AI Generated

DOI: 10.5194/hess-30-6189-2026

Keywords: seasonal forecasting, hydrology, river flows, Great Britain, historical weather analogues, North Atlantic Oscillation, GloSea6, flood prediction, drought, hydrological model, UK Hydrological Outlook, water resources

The research, published in the Journal of Environmental Studies and Sciences by a team led by Emma Hankinson of Oxford Brookes University alongside experienced consultant ecologists, evaluated 38 commercial reptile survey reports produced between 2009 and 2024. The reports covered three of Britain’s lesser-protected native reptiles: the common lizard (Zootoca vivipara), the slow worm (Anguis fragilis) and the grass snake (Natrix helvetica). All had been drafted to inform planning applications under the Town and Country Planning Act 1990, and all were publicly available online under the Environmental Information Regulations 2004.

To measure quality, the team built a novel nine-category scoring rubric drawn from both statutory guidance and the wider best-practice literature, including the Herpetofauna Workers Manual, Froglife advice sheets and peer-reviewed survey protocols. Categories ranged from habitat suitability assessments and preliminary data searches to weather conditions, survey seasonality, the number of presence or absence surveys, population size class estimates, use of artificial cover objects and transects, surveyor experience and recommended monitoring. Each report was rated on a four-point ordinal scale per category, yielding a total score between 9 and 36. A second independent rater scored every report, and agreement was strikingly high, with a pooled weighted Cohen’s kappa of 0.98 and an intraclass correlation of 0.99 on total scores, confirming the rubric could be applied consistently.

The headline finding is a stark split between legal compliance and scientific best practice. Reports scored significantly higher on categories anchored in statutory guidance, with a mean item score of 3.09, than on non-statutory best-practice categories, which averaged just 1.95, a difference confirmed by a Wilcoxon signed-rank test at p < 0.001. In other words, consultants reliably tick the boxes the law requires but routinely skip the techniques that would make their surveys genuinely robust. The weakest categories of all were population size class estimates and recommended monitoring, each averaging a dismal 1.13 out of 4. Although every report confirming reptile presence provided some population estimate, more than three quarters based it solely on the initial presence or absence surveys without any additional effort. Even more striking, 85.71 percent of reports mentioned no post-construction monitoring whatsoever, meaning the effectiveness of mitigation is almost never verified.

This pattern has deep roots. Britain’s current reptile survey methodologies rest on guidance more than two decades old, and earlier attempts to modernise it faltered; Natural England updated its reptile guidance in 2011 only to withdraw it within the same year over concerns about the survey effort it demanded. More recent documents tend to reference older guidance circularly rather than incorporating newer, evidence-based methods. Because reptiles are small, cryptic and highly seasonal, survey design matters enormously, and research consistently shows that greater effort and varied techniques dramatically improve detection. Yet the statutory floor remains low, particularly for the four widespread species, whose habitats enjoy no formal legal protection at all.

Perhaps the most consequential finding concerns reports that conclude reptiles are absent. Confirming absence reliably requires far more survey effort across a wider seasonal window than confirming presence, yet absence reports scored significantly lower on precisely the two categories most tied to that evidentiary standard: survey month and season (p = 0.002) and the number of presence or absence surveys undertaken (p = 0.022). Nearly 41 percent of absence reports conducted all their surveys in sub-optimal months, and almost 18 percent undertook no surveys at all, simply declaring the habitat unsuitable. Grass snakes, for example, linger for weeks around egg-laying sites in June and July; if those months go unsampled or the sites fall outside the survey area, the species can be missed entirely. A false absence conclusion is legally corrosive, because it removes any statutory obligation to mitigate harm, whereas a correctly identified presence triggers protection.

There are faint signs of progress. Total rubric scores rose significantly across the 2009 to 2024 period, with a Spearman correlation of 0.378, despite no change in statutory guidance, suggesting that evolving professional norms, sector-wide guidance from bodies such as CIEEM and increased scrutiny of environmental compliance are nudging standards upward. Report quality was also positively associated with the severity of development impact reported, though intriguingly, rubric score showed no relationship at all with the mitigation strategies recommended. The dominant mitigation was translocation of reptiles to non-adjacent habitat they had not previously occupied, an approach with a troubling evidence base: one study recorded only a 1.6 percent recapture rate of translocated reptiles during subsequent monitoring, and other work has documented displaced lizards in poor body condition with elevated parasite loads.

The authors argue that statutory guidance alone is insufficient to guarantee reliable survey outcomes, and they point to an alternative delivery model already proving itself for amphibians. The NatureSpace district licensing scheme for great crested newts replaces site-by-site consultant surveys with a single centrally funded body that creates and manages compensatory habitat strategically, in advance of development, backed by 25-year monitoring agreements. Published results from 2021 to 2025 show 90 percent of mature compensation sites already occupied by target and other species. With the Planning and Infrastructure Act 2025 establishing Environmental Delivery Plans and a Nature Restoration Fund along similar lines, reptiles could be strong candidates for such a strategic approach, though the authors caution that any extension would need robust monitoring safeguards, since some conservation organisations fear these schemes may weaken project-level scrutiny.

The study has honest limitations. Reports were found via a single search engine, likely favouring consultancies with stronger online visibility; one report per consultancy means results are unweighted by output volume; and the rubric, while internally reliable, was devised by the authors and has not been externally validated, with its quality thresholds remaining partly subjective. The modest sample of 38 reports also limits statistical power for subgroup comparisons. Crucially, the analysis could only assess what consultants self-reported, with no independent means of verifying the underlying data.

Even so, the picture that emerges is sobering for a country now ranked among the most nature-depleted on Earth. Reptiles are exceptionally sensitive to disturbance: they cannot recolonise across long distances, cannot wait out adverse conditions, and are acutely vulnerable to small climatic shifts. Britain’s reptiles were first recognised as declining in the 1970s and 1980s, and recent assessments suggest nearly a third of the nation’s amphibian and reptile species face extinction risk. If the reports that decide their fate meet only the legal minimum, and the legal minimum is anchored to outdated, quasi-quantitative methods, then countless small failures may be compounding into a landscape-scale problem. The authors’ prescription is clear: revise statutory guidance to embed monitoring, habitat suitability assessment and adequate survey effort, and seriously consider whether centrally delivered, long-term compensated conservation, already working for newts, should now extend to the snakes and lizards slipping through the current system’s cracks.

Subject of Research: Quality and statutory compliance of commercial reptile survey reports informing development planning in Great Britain

Article Title: Falling short: inconsistent statutory compliance and widespread best-practice neglect in commercial reptile survey reports across Great Britain

Article References: Hankinson, E., Bartlett, K., Goldsmith, J., Sharma-Vicary, K., & Nijman, V. (2026). Falling short: inconsistent statutory compliance and widespread best-practice neglect in commercial reptile survey reports across Great Britain. Journal of Environmental Studies and Sciences. https://doi.org/10.1007/s13412-026-01148-2

Image Credits: AI Generated

DOI: 10.1007/s13412-026-01148-2

Keywords: reptile conservation, ecological consultancy, survey methodology, statutory guidance, mitigation translocation, great crested newts, biodiversity net gain, planning policy, herpetofauna, Great Britain, wildlife protection, monitoring

The study, published in the journal Parasites & Vectors, exploits a regulatory quirk that most surveillance systems can only dream of. Unlike passive reporting schemes, which depend on farmers choosing to notify disease, the Imizol notification requirement captures treatment events systematically, because compliance is mandated whenever the drug is used. Between 2016 and 2024, these notifications provided a proxy dataset for clinically recognised bovine babesiosis at a resolution fine enough to map disease presence onto a grid of two-kilometre squares covering Great Britain. The disease itself is caused by protozoan parasites of the genus Babesia, transmitted by ticks, with the sheep tick Ixodes ricinus serving as the principal vector in the British Isles. Infected cattle can develop fever, anaemia, red urine and, in severe cases, death, making early detection and treatment critical for herd health and farm economics.

To transform the notification records into a predictive map, the team turned to machine learning, specifically boosted regression trees, a method that excels at capturing complex, nonlinear relationships between environmental variables and disease occurrence. The predictor variables fell into four broad categories. Seasonal climate metrics characterised temperature and moisture conditions across the year. Vegetation greenness, derived from satellite observations, served as a proxy for habitat quality and tick-friendly landscapes. Livestock densities captured the availability of hosts on which ticks could feed. Finally, the researchers included predicted habitat suitability for three species of deer, red, roe and fallow, which act as key reproductive hosts for adult Ixodes ricinus ticks and are known to shape tick population dynamics across British landscapes.

The modelling strategy was deliberately rigorous. Models were trained on notification data from southwest England, a recognised hotspot for the disease, using records from 2016 to 2022. They were then temporally validated against data from the same region for 2023 and 2024, testing whether the models could anticipate disease patterns in years they had never seen. Crucially, the models were also evaluated externally against independent notification data from outside the training region, a demanding test of whether the relationships learned in one part of Britain could transfer to environments elsewhere on the island.

The results were striking. In internal cross-validation, the models achieved a mean area under the receiver operating characteristic curve, or AUC, of 0.81, with a mean correlation of 0.55, indicating strong discrimination between areas with and without notified cases. Temporal validation yielded a continuous Boyce Index of 0.81, confirming that the models reliably ranked habitat suitability in unseen years. External validation outside southwest England produced a Boyce Index of 0.58, suggesting moderate transferability, a respectable figure for a disease model extrapolated beyond its training domain. For a condition that has historically lacked any systematic national mapping, these performance metrics represent a substantial advance in the epidemiology of bovine babesiosis.

Perhaps the most revealing findings concerned which variables actually drove the predicted patterns. Climatic predictors accounted for the greatest relative influence by a wide margin, with autumn cooling alone contributing a mean relative influence of 37.3 percent and atmospheric moisture adding a further 8.5 percent. This dominance of autumnal temperature decline aligns closely with the ecology of Ixodes ricinus, whose activity depends on specific thermal and humidity windows. Ticks in Britain typically show peaks of questing activity in spring and autumn, and the timing and intensity of autumn cooling appears to constrain how long ticks remain active late in the season, shaping the window during which cattle can be exposed to infected bites.

Among the non-climatic predictors, habitat suitability for roe deer and sheep density emerged as the most influential factors, each contributing moderate explanatory power, while vegetation greenness exerted a smaller effect. The prominence of roe deer is ecologically coherent: deer of this species are widespread across woodland and fragmented rural landscapes in Britain and serve as efficient hosts for adult ticks, amplifying tick populations in areas where they thrive. Sheep density, meanwhile, may reflect both the presence of additional hosts and the movement of livestock between farms, which can transport ticks and, in some contexts, the parasites themselves. Notably, the proportional land-cover variables that are staples of many landscape epidemiology studies showed consistently low individual influence, suggesting that the composition of habitat types matters less for this disease than the climatic and host-related conditions that govern tick survival and abundance.

Beyond its ecological insights, the study carries immediate practical value for British agriculture. The risk maps generated by the models can help anticipate areas of elevated babesiosis risk and guide disease surveillance at regional scales. Of particular interest are the locations where environmental conditions appear suitable for disease occurrence but treated cases have not yet been reported. Such mismatches between predicted suitability and observed notifications may indicate genuine gaps in surveillance, under-recognition of disease by veterinarians, or areas where the disease is emerging as conditions change. Identifying these frontier zones allows veterinary authorities and farmers to target awareness campaigns, diagnostic efforts and tick control measures before outbreaks become established.

The research also demonstrates a methodological lesson with implications far beyond a single disease. Mandatory veterinary medicines notification data, the authors show, can serve as a credible proxy for disease occurrence at national scale, opening a surveillance channel that exists independently of voluntary reporting. Many countries maintain compulsory reporting requirements for the use of specific veterinary drugs, and the British experience suggests these records can be mined for spatial epidemiology at little additional cost. As climate change alters the seasonal rhythms of temperature and moisture across Europe, the activity patterns of Ixodes ricinus and the diseases it carries are expected to shift, making robust, repeatable mapping systems increasingly valuable.

For British cattle farmers, the message is that the geography of babesiosis risk is now legible in unprecedented detail, and that the levers shaping that geography are largely environmental: the coolness of autumn, the dampness of the air, the abundance of roe deer in the surrounding woods and the density of sheep grazing nearby fields. The work, funded through a University of Liverpool PhD studentship in partnership with the Animal and Plant Health Agency and supported by the BBSRC-DEFRA OPTICK project, exemplifies how collaboration between academic modellers and government surveillance units can convert routine regulatory data into actionable ecological intelligence. As warming winters and shifting rainfall patterns continue to redraw the map of tick-borne disease across the British Isles, studies of this kind provide the baseline against which future change will be measured, and the tools with which farmers and veterinarians can stay one step ahead of a parasite that thrives in the margins of the season.

Subject of Research: Spatial modelling of bovine babesiosis risk in Great Britain using mandatory imidocarb treatment notifications and machine learning

Article Title: Climate, host and landscape determinants of bovine babesiosis in Great Britain: analysis of Imidocarb treatment notifications, 2016–2024

Article References: Shanks, S., Duncan, J., Johnson, N., Millins, C., Hassall, R., & Purse, B. V. (2026). Climate, host and landscape determinants of bovine babesiosis in Great Britain: analysis of Imidocarb treatment notifications, 2016–2024. Parasites &amp; Vectors. https://doi.org/10.1186/s13071-026-07665-x

Image Credits: AI Generated

DOI: 10.1186/s13071-026-07665-x

Keywords: bovine babesiosis, Ixodes ricinus, tick-borne disease, imidocarb dipropionate, machine learning, boosted regression trees, climate determinants, roe deer, sheep density, Great Britain, veterinary surveillance, risk mapping