SNAPSHOT USA 2024: Year 6 of the Coordinated National Camera Trap Survey of the United States - Brigit Rooney; Roland Kays; Michael V. Cove; Alex Jensen; Daniel J. Herrera; Camilla Price; Phuong‐Thao Nguyen‐Nu; Katrina Adamczyk; Peter D. Alexander; David Allen; Jesse M. Alston; Diego F. Alvarado‐Serrano; et al. (Global Ecology and Biogeography, 2026)
Motivation SNAPSHOT USA is an annual, multi‐contributor camera trap survey of mammals across the United States. The growing SNAPSHOT USA dataset is intended for tracking the spatial and temporal responses of mammal populations to changes in land use, land cover and climate. These data will be useful for exploring the drivers of spatial and temporal changes in relative abundance and distribution, as well as the impacts of species interactions on daily activity patterns. Main Types of Variables Contained SNAPSHOT USA 2024 contains 377,427 records of camera trap image sequence data and 3127 records of camera trap deployment metadata. Spatial Location and Grain Data were collected across the United States of America in 49 states, 12 ecoregions and many ecosystems. Time Period and Grain Data were collected between 1 August and 19 December in 2024. Major Taxa and Level of Measurement The dataset includes a wide range of taxa but is primarily focused on medium to large mammals. Software Format SNAPSHOT USA 2024 comprises two .csv files. The original data can be found within the SNAPSHOT USA 2024 project on the Wildlife Insights platform.

Mind the gap - The need to integrate novel plankton methods alongside ongoing long-term monitoring - Matthew M. Holland; Luis Felipe Artigas; Angus Atkinson; Mike Best; Eileen Bresnan; Michelle Devlin; Dafne Eerkes-Medrano; Marie Johansen; David G. Johns; Margarita Machairopoulou; Sophie Pitois; James Scott; et al. (Ocean & Coastal Management, 2025)

SNAPSHOT USA 2019–2023: The First Five Years of Data From a Coordinated Camera Trap Survey of the United States - Brigit Rooney; Roland Kays; Michael V. Cove; Alex Jensen; Benjamin R. Goldstein; Christopher Pate; Paula Castiblanco; Maggie E. Abell; Jessie Adley; Briana Agenbroad; Adam A. Ahlers; Peter D. Alexander; et al. (Global Ecology and Biogeography, 2025)
Motivation SNAPSHOT USA is an annual, multicontributor camera trap survey of mammals across the United States. The growing SNAPSHOT USA dataset is intended for tracking the spatial and temporal responses of mammal populations to changes in land use, land cover and climate. These data will be useful for exploring the drivers of spatial and temporal changes in relative abundance and distribution, as well as the impacts of species interactions on daily activity patterns. Main Types of Variables Contained SNAPSHOT USA 2019–2023 contains 987,979 records of camera trap image sequence data and 9694 records of camera trap deployment metadata. Spatial Location and Grain Data were collected across the United States of America in all 50 states, 12 ecoregions and many ecosystems. Time Period and Grain Data were collected between 1st August and 29th December each year from 2019 to 2023. Major Taxa and Level of Measurement The dataset includes a wide range of taxa but is primarily focused on medium to large mammals. Software Format SNAPSHOT USA 2019–2023 comprises two .csv files. The original data can be found within the SNAPSHOT USA Initiative in the Wildlife Insights platform.

The challenge of assessing the effects of drifting fish aggregating devices on the behaviour and biology of tropical tuna - Amaël Dupaix; Frédéric Ménard; John D. Filmalter; Yannick Baidai; Nathalie Bodin; Manuela Capello; Emmanuel Chassot; Hervé Demarcq; Jean‐Louis Deneubourg; Alain Fonteneau; Fabien Forget; Francesca Forrestal; et al. (Fish and Fisheries, 2024)
Fishers have intensively used drifting fish aggregating devices (DFADs) over the last three decades to facilitate their catch of tropical tunas. DFADs increase purse‐seine efficiency, potentially increasing tuna fishing mortality. They could also have impacts on tuna natural mortality and reproductive potential, and assessing the consequences of their presence at sea on tuna populations is a challenge. The use of DFADs results in a major increase in the number of floating objects, which are spatially heterogeneous at sea. To date, no converging scientific results exist regarding the effects of DFADs on the large‐scale movements and behaviour of tuna, mainly due to the difficulty of disentangling the respective roles of DFADs and environmental factors. Some biological indices show that tuna condition is lower when associated to a floating object than in a free‐swimming school. However, it is not clear whether this is the cause or the consequence of the association nor if it has long‐term effects on individuals' fitness. Further scientific progress requires (i) the collection of time series of indicators to monitor habitat change, individual behaviour, individual fitness, and population dynamics and (ii) experimental studies to identify the underlying behavioural and biological processes involved in associative behaviour. The extent of the modification of the surface habitat by the massive deployment of DFADs and the current uncertainty of the possible long‐term consequences on the individual fitness and dynamics of tuna populations argue for the need for increased awareness of this issue by Regional Fisheries Management Organisations regulating tuna fishing.

Corrigendum to “Priorities to inform research on marine plastic pollution in Southeast Asia” [Sci. Total Environ. volume 841 (2022) Article 156704] - Lucy C.M. Omeyer; Emily M. Duncan; Kornrawee Aiemsomboon; Nicola Beaumont; Sujaree Bureekul; Bin Cao; Luis R. Carrasco; Suchana Chavanich; James R. Clark; Muhammad R. Cordova; Fay Couceiro; Simon M. Cragg; et al. (Science of The Total Environment, 2023)

Prediction of disability-free survival in healthy older people - Johannes Tobias Neumann; Le T. P. Thao; Anne M. Murray; Emily Callander; Prudence R. Carr; Mark R. Nelson; Rory Wolfe; Robyn L. Woods; Christopher M. Reid; Raj C. Shah; Anne B. Newman; Jeff D. Williamson; et al. (GeroScience, 2022)
Prolonging survival in good health is a fundamental societal goal. However, the leading determinants of disability-free survival in healthy older people have not been well established. Data from ASPREE, a bi-national placebo-controlled trial of aspirin with 4.7 years median follow-up, was analysed. At enrolment, participants were healthy and without prior cardiovascular events, dementia or persistent physical disability. Disability-free survival outcome was defined as absence of dementia, persistent disability or death. Selection of potential predictors from amongst 25 biomedical, psychosocial and lifestyle variables including recognized geriatric risk factors, utilizing a machine-learning approach. Separate models were developed for men and women. The selected predictors were evaluated in a multivariable Cox proportional hazards model and validated internally by bootstrapping. We included 19,114 Australian and US participants aged ≥65 years (median 74 years, IQR 71.6–77.7). Common predictors of a worse prognosis in both sexes included higher age, lower Modified Mini-Mental State Examination score, lower gait speed, lower grip strength and abnormal (low or elevated) body mass index. Additional risk factors for men included current smoking, and abnormal eGFR. In women, diabetes and depression were additional predictors. The biased-corrected areas under the receiver operating characteristic curves for the final prognostic models at 5 years were 0.72 for men and 0.75 for women. Final models showed good calibration between the observed and predicted risks. We developed a prediction model in which age, cognitive function and gait speed were the strongest predictors of disability-free survival in healthy older people. Trial registration Clinicaltrials.gov (NCT01038583)

Common, low-frequency, rare, and ultra-rare coding variants contribute to COVID-19 severity - Chiara Fallerini; Nicola Picchiotti; Margherita Baldassarri; Kristina Zguro; Sergio Daga; Francesca Fava; Elisa Benetti; Sara Amitrano; Mirella Bruttini; Maria Palmieri; Susanna Croci; Mirjam Lista; et al. (Human Genetics, 2022)
The combined impact of common and rare exonic variants in COVID-19 host genetics is currently insufficiently understood. Here, common and rare variants from whole-exome sequencing data of about 4000 SARS-CoV-2-positive individuals were used to define an interpretable machine-learning model for predicting COVID-19 severity. First, variants were converted into separate sets of Boolean features, depending on the absence or the presence of variants in each gene. An ensemble of LASSO logistic regression models was used to identify the most informative Boolean features with respect to the genetic bases of severity. The Boolean features selected by these logistic models were combined into an Integrated PolyGenic Score that offers a synthetic and interpretable index for describing the contribution of host genetics in COVID-19 severity, as demonstrated through testing in several independent cohorts. Selected features belong to ultra-rare, rare, low-frequency, and common variants, including those in linkage disequilibrium with known GWAS loci. Noteworthily, around one quarter of the selected genes are sex-specific. Pathway analysis of the selected genes associated with COVID-19 severity reflected the multi-organ nature of the disease. The proposed model might provide useful information for developing diagnostics and therapeutics, while also being able to guide bedside disease management.

The influence of groundwater abstraction on interpreting climate controls and extreme recharge events from well hydrographs in semi-arid South Africa - James P. R. Sorensen; Jeff Davies; Girma Y. Ebrahim; John Lindle; Ben P. Marchant; Matthew J. Ascott; John P. Bloomfield; Mark O. Cuthbert; Martin Holland; K. H. Jensen; M. Shamsudduha; Karen G. Villholth; et al. (Hydrogeology Journal, 2021)
There is a scarcity of long-term groundwater hydrographs from sub-Saharan Africa to investigate groundwater sustainability, processes and controls. This paper presents an analysis of 21 hydrographs from semi-arid South Africa. Hydrographs from 1980 to 2000 were converted to standardised groundwater level indices and rationalised into four types (C1–C4) using hierarchical cluster analysis. Mean hydrographs for each type were cross-correlated with standardised precipitation and streamflow indices. Relationships with the El Niño–Southern Oscillation (ENSO) were also investigated. The four hydrograph types show a transition of autocorrelation over increasing timescales and increasingly subdued responses to rainfall. Type C1 strongly relates to rainfall, responding in most years, whereas C4 notably responds to only a single extreme event in 2000 and has limited relationship with rainfall. Types C2, C3 and C4 have stronger statistical relationships with standardised streamflow than standardised rainfall. C3 and C4 changes are significantly ( p < 0.05) correlated to the mean wet season ENSO anomaly, indicating a tendency for substantial or minimal recharge to occur during extreme negative and positive ENSO years, respectively. The range of different hydrograph types, sometimes within only a few kilometres of each other, appears to be a result of abstraction interference and cannot be confidently attributed to variations in climate or hydrogeological setting. It is possible that high groundwater abstraction near C3/C4 sites masks frequent small-scale recharge events observed at C1/C2 sites, resulting in extreme events associated with negative ENSO years being more visible in the time series.

Correction to: Bacterial etiology of community-acquired pneumonia in immunocompetent hospitalized patients and appropriateness of empirical treatment recommendations: an international point-prevalence study - Manuela Carugati; S. Aliberti; G. Sotgiu; F. Blasi; A. Gori; R. Menendez; M. Encheva; M. Gallego; P. Leuschner; S. Ruiz-Buitrago; S. Battaglia; R. Fantini; et al. (European Journal of Clinical Microbiology & Infectious Diseases, 2021)

A Roadmap for Policy-Relevant Sea-Level Rise Research in the United Arab Emirates - Hannah Melville-Rea; Clare Eayrs; Nasser Anwahi; John A. Burt; Denise Holland; Fatin Samara; Francesco Paparella; Ahmed Hassan Al Murshidi; Maryam Rashed Al-Shehhi; David M. Holland (Frontiers in Marine Science, 2021)
The United Arab Emirates (UAE) has a long-term policy horizon, the financial capital, and a vision for a sustainable knowledge-based economy. These characteristics uniquely situate it as a potential leader for sea-level rise research. Climate science is already growing, and at the center of the UAE's pivot toward climate research is a burgeoning concern for sea-level rise. Over 85% of the UAE's population and more than 90% of the nation's infrastructure is within a few meters of present-day sea-level. With its low-lying and shallow-sloping geography (about 35 cm per km), this high-value coastline, including the rapidly expanding cities of Dubai and Abu Dhabi, is particularly vulnerable to sea-level rise. Meanwhile, limited regional research and data scarcity create deep uncertainty for sea-level projections. We set out a potential roadmap for the UAE to capitalize on its strengths to create usable and relevant sea-level projections for the region. With a newly established Climate Change Research Network, the UAE government is beginning to draw together universities and research centers for “furthering effective data collection and management, and advancing policy-relevant research on climate impacts and adaptation 1 .” By consolidating ideas from the science community within the UAE, we identify promoters and barriers to data gathering, information sharing, science-policy communication, and funding access. Our paper proposes pathways forward for the UAE to integrate sea-level science with coastal development and form best practices that can be scaled across climate science and throughout the region.

Bacterial etiology of community-acquired pneumonia in immunocompetent hospitalized patients and appropriateness of empirical treatment recommendations: an international point-prevalence study - Manuela Carugati; S. Aliberti; G. Sotgiu; F. Blasi; A. Gori; R. Menendez; M. Encheva; M. Gallego; P. Leuschner; S. Ruiz-Buitrago; S. Battaglia; R. Fantini; et al. (European Journal of Clinical Microbiology & Infectious Diseases, 2020)

The best wildflowers for wild bees - Rachel N. Nichols; Dave Goulson; John M. Holland (Journal of Insect Conservation, 2019)
Governmental agri-environment schemes (AES) aim to improve pollinator abundance and diversity on farmland by sowing wildflower seed mixes. These often contain high proportions of Fabaceae, particularly Trifolium (clovers), which are attractive to some bumblebee species, but not to most of the ~ 240 solitary bee species in the UK. Here we identify wildflowers that are attractive to a greater range of wild bee species. Forty-five wildflower species being farmed for commercial seed production on a single farm were surveyed for native bees. Bee walks were conducted through discrete wildflower areas from April until August in 2018. The results indicate that including a range of Apiaceae, Asteraceae, and Geraniaceae in seed mixes would cater for a wide diversity of bee species. A total of 14 wildflower species across nine families attracted 37 out of the 40 bee species recorded on the farm, and accounted for 99.7% of all visitations. Only two of these 14 species are included in current AES pollinator mixes. Unexpectedly, few visits were made by bumblebees to Trifolium spp. (0.5%), despite their being considered an important food source for bumblebees, while Anthyllis vulneraria and Geranium pratense were highly attractive. For solitary bees, Crepis capillaris , Sinapsis arvensis , Convolvulus arvensis and Chaerophyllum temulum were amongst the best performing species, none of which are usually included in sown flower mixes. We suggest that the standard ‘pollinator’ mixes used in AES might be updated to include some of these wildflower species, and trialled as seed mixes on farmland.

Sensitivity of Antarctic sea ice to the Southern Annular Mode in coupled climate models - Marika M. Holland; Laura Landrum; Yavor Kostov; John Marshall (Climate Dynamics, 2017)

Fast and slow responses of Southern Ocean sea surface temperature to SAM in coupled climate models - Yavor Kostov; John Marshall; Ute Hausmann; Kyle C. Armour; David Ferreira; Marika M. Holland (Climate Dynamics, 2017)

Targeted agri‐environment schemes significantly improve the population size of common farmland bumblebee species - Thomas J. Wood; John M. Holland; William O. H. Hughes; Dave Goulson (Molecular Ecology, 2015)
Changes in agricultural practice across Europe and North America have been associated with range contractions and local extinction of bumblebees ( Bombus spp.). A number of agri‐environment schemes have been implemented to halt and reverse these declines, predominantly revolving around the provision of additional forage plants. Although it has been demonstrated that these schemes can attract substantial numbers of foraging bumblebees, it remains unclear to what extent they actually increase bumblebee populations. We used standardized transect walks and molecular techniques to compare the size of bumblebee populations between Higher Level Stewardship ( HLS ) farms implementing pollinator‐friendly schemes and Entry Level Stewardship ( ELS ) control farms. Bumblebee abundance on the transect walks was significantly higher on HLS farms than ELS farms. Molecular analysis suggested maximum foraging ranges of 566 m for Bombus hortorum , 714 m for B. lapidarius , 363 m for B. pascuorum and 799 m for B. terrestris . Substantial differences in maximum foraging range were found within bumblebee species between farm types. Accounting for foraging range differences, B. hortorum (47 vs 13 nests/km 2 ) and B. lapidarius (45 vs 22 nests/km 2 ) were found to nest at significantly greater densities on HLS farms than ELS farms. There were no significant differences between farm type for B. terrestris (88 vs 38 nests/km 2 ) and B. pascuorum (32 vs 39 nests/km 2 ). Across all bumblebee species, HLS management had a significantly positive effect on bumblebee nest density. These results show that targeted agri‐environment schemes that increase the availability of suitable forage can significantly increase the size of wild bumblebee populations.

The spatial distribution of canopy-resident and ground-resident cereal aphids (Sitobion avenae and Metopolophium dirhodum) in winter wheat - Linton Winder; Colin J. Alexander; Chris Woolley; Joe N. Perry; John M. Holland (Arthropod-Plant Interactions, 2013)

CETP polymorphisms associate with brain structure, atrophy rate, and Alzheimer’s disease risk in an APOE-dependent manner - Elizabeth A. Murphy; John Cooper Roddey; Linda K. McEvoy; Dominic Holland; D. J. Hagler; Anders M. Dale; James B. Brewer (Brain Imaging and Behavior, 2012)

Coping with climate variability and climate change in La Ceiba, Honduras - Joel B. Smith; Kenneth M. Strzepek; Julio Cardini; Mario Castaneda; Julie Holland; Carlos Quiroz; Tom M. L. Wigley; Jose Herrero; Peter Hearne; John Furlow (Climatic Change, 2011)

Monoclonal antibodies reveal changes in predator efficiency with prey spatial pattern - GEORGIANNE J. K. GRIFFITHS; COLIN J. ALEXANDER; JOHN M. HOLLAND; PETER J. KENNEDY; JOE N. PERRY; WILLIAM O. C. SYMONDSON; LINTON WINDER (Molecular Ecology, 2008)
Spatially explicit predator–prey interactions can alter the predatory potential of natural enemies augmented through conservation biological control. To test hypotheses regarding such interactions and predatory efficiency, we used a combination of molecular techniques and mark–release–recapture to study the foraging behaviour of a generalist carabid predator, Poecilus cupreus , in response to spatial patterns of its cereal aphid prey ( Metapolophium dirhodum and Sitobion avenae ). Beetle and aphid numbers were measured across two grids of sampling locations, within which aphid spatial pattern had been manipulated to generate patchy and more homogenous distributions. Aphid consumption was measured by enzyme‐linked immunosorbent assays (ELISA) of beetle gut contents, using an aphid‐specific monoclonal antibody. Movement and distribution patterns suggest that P. cupreus does not aggregate at, nor instigate prey‐taxis within, aphid patches. However, more than two‐thirds of the 2169 P. cupreus tested by ELISA had consumed aphids and the proportion of beetles containing aphid proteins was positively related to aphid density. Against expectation, the proportion of predators feeding on aphids was greatest where prey were homogenously distributed, and this was attributed to the loss of partial refuges for prey in aphid patches. The functional value of this type of uniform foraging strategy is ideally suited to early colonization of the crop habitat, when aphid numbers are low, before populations build up and form strong spatial patterns.

Complement - Dimitrios Mastellos; Dimitrios Morikis; Stuart N. Isaacs; M. Claire Holland; Cristoph W. Strey; John D. Lambris (Immunologic Research, 2003)

Evaluation in barley lines of a simple pollen method for breeding for drought tolerance in wheat - James M. Morgan; John F. Holland; Barbara J. Read (Cereal Research Communications, 2002)

The Value of Uncropped Field Margins For Foraging Bumblebees - Andrea R. Kells; John M. Holland; Dave Goulson (Journal of Insect Conservation, 2001)

Modelling the dynamic spatio‐temporal response of predators to transient prey patches in the field - Linton Winder; Colin J. Alexander; John M. Holland; Chris Woolley; Joe N. Perry (Ecology Letters, 2001)
The spatio‐temporal dynamics of two aphid species ( Metopolophium dirhodum and Sitobion avenae ) and a generalist predator ( Pterostichus melanarius ) were observed in a field‐scale study using a grid of 256 sampling locations with a 12‐m spacing. Using Spatial Analysis by Distance Indices we demonstrate that populations show ephemeral spatial pattern at the field scale. We observed a positive, lagged beetle response to this aphid pattern; conversely, the aphids displayed a negative, lagged response to beetle spatial pattern. Examination of the local structure of the spatio‐temporal dynamics revealed a strong response by the beetle population to aphid patches. The temporal structure of spatial associations between the species shows a strong correspondence with those from a conceptual model of predator–prey spatial interaction. The spatially coupled dynamics were sufficiently strong for the predator to have a negative effect on the intrinsic rate of increase of their prey.