Standard NH3-SCR and N2O formation kinetics over Cu-CHA monolith catalysts: transient and steady-state redox models - Nicola Usberti; Ramona Resmini; Andrea Gjetja; Maria Elena Azzoni; Isabella Nova; Enrico Tronconi; Roberta Villamaina; Maria Pia Ruggeri; Djamela Bounechada; Andrew P.E. York; Jillian Collier (Chemical Engineering Journal, 2026)

The Coastal Ocean Environment Summer School In Nigeria and Ghana: The Value of Long-Term, Sustained Capacity Sharing - Brian Arbic; Johnson Adjetey; Andrews Agyekumhene; Mosunmola Akinwunmi; Lailah Akita; Lois Anderson; Joseph Ansong; Kwasi Appeaning Addo; Eunice Asamoah; Olawale Awe; Christian Buckingham; Janae’ Collier; et al. (Oceanography, 2025)
The Coastal Ocean Environment Summer School In Nigeria and Ghana (COESSING; https://coessing.org) has been run for one week every year since 2015. The school, an endorsed project of the United Nations Decade of Ocean Science for Sustainable Development (2021–2030), has provided a platform for approximately 1,000 scientists from Africa, the United States, and Europe to exchange scientific knowledge, to network, to learn, and to collaborate. Our interdisciplinary, multicultural, and multi-institutional approach offers a model for knowledge exchange across the globe and across different educational levels.

Building and Sharing Ocean Sciences Capacity Through Project-Based Learning - Ebenezer Nyadjro; Anthi Oikonomou; Abdulwakil Saba; Edem Mahu; Georgios Vagenas; Joseph Ansong; Paige Martin; Andrews Agyekumhene; Eunice Asamoah; Richmond Kennedy Quarcoo; Janae’ Collier; Lailah Akita (Oceanography, 2025)
The challenges facing the ocean and its resources have become increasingly complex and transboundary, requiring coordinated efforts for effective management and sustainable use. However, this coordination is currently hindered by the uneven distribution of capacity and equipment, particularly in developing regions. This article discusses project-based learning (PBL) as a pathway to transferring and sharing capacity in global ocean sciences. It highlights a successful PBL program, as well as challenges encountered and lessons learned. Addressing these obstacles is crucial for ensuring equity in solving issues that impact the ocean.

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.

In-situ observations of resident space objects with the CHEOPS space telescope - Nicolas Billot; Stephan Hellmich; Willy Benz; Andrea Fortier; David Ehrenreich; Christopher Broeg; Alexis Heitzmann; Anja Bekkelien; Alexis Brandeker; Yann Alibert; Roi Alonso; Tamas Bárczy; et al. (Journal of Space Safety Engineering, 2024)

Global maps of soil temperature - Jonas J. Lembrechts; Johan van den Hoogen; Juha Aalto; Michael B. Ashcroft; Pieter De Frenne; Julia Kemppinen; Martin Kopecký; Miska Luoto; Ilya M. D. Maclean; Thomas W. Crowther; Joseph J. Bailey; Stef Haesen; et al. (Global Change Biology, 2022)
Research in global change ecology relies heavily on global climatic grids derived from estimates of air temperature in open areas at around 2 m above the ground. These climatic grids do not reflect conditions below vegetation canopies and near the ground surface, where critical ecosystem functions occur and most terrestrial species reside. Here, we provide global maps of soil temperature and bioclimatic variables at a 1‐km 2 resolution for 0–5 and 5–15 cm soil depth. These maps were created by calculating the difference (i.e. offset) between in situ soil temperature measurements, based on time series from over 1200 1‐km 2 pixels (summarized from 8519 unique temperature sensors) across all the world's major terrestrial biomes, and coarse‐grained air temperature estimates from ERA5‐Land (an atmospheric reanalysis by the European Centre for Medium‐Range Weather Forecasts). We show that mean annual soil temperature differs markedly from the corresponding gridded air temperature, by up to 10°C (mean = 3.0 ± 2.1°C), with substantial variation across biomes and seasons. Over the year, soils in cold and/or dry biomes are substantially warmer (+3.6 ± 2.3°C) than gridded air temperature, whereas soils in warm and humid environments are on average slightly cooler (−0.7 ± 2.3°C). The observed substantial and biome‐specific offsets emphasize that the projected impacts of climate and climate change on near‐surface biodiversity and ecosystem functioning are inaccurately assessed when air rather than soil temperature is used, especially in cold environments. The global soil‐related bioclimatic variables provided here are an important step forward for any application in ecology and related disciplines. Nevertheless, we highlight the need to fill remaining geographic gaps by collecting more in situ measurements of microclimate conditions to further enhance the spatiotemporal resolution of global soil temperature products for ecological applications.

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.

Plant–Environment Interactions in the Low Arctic Torngat Mountains of Labrador - Emma Davis; Andrew Trant; Luise Hermanutz; Robert G. Way; Antoni G. Lewkowicz; Laura Siegwart Collier; Alain Cuerrier; Darroch Whitaker (Ecosystems, 2021)
The eastern Canadian Subarctic and Arctic are experiencing significant environmental change with widespread implications for the people, plants, and animals living there. In this study, we integrate 10 years of research at the Nakvak Brook watershed in Torngat Mountains National Park of Canada, northern Labrador, to assess the sensitivity of ecological and geomorphological systems to regional climate warming. A time series of the Normalized Difference Vegetation Index indicates that the area has undergone a significant greening trend over the past four decades. Analyses of shrub cross sections suggest that greening has been caused by a combination of rapid establishment and growth that began in the late 1990’s and coincided with warmer growing season temperatures. Recent (2010–2015) vegetation change has been subtle and heavily moderated by soil moisture status. Plant canopy height is greater in wet areas and has an insulating effect on ground surface temperatures during the winter, a consequence of snow trapping by shrub canopies. Observations of subsurface conditions indicate that the study site is best characterized as having discontinuous near-surface permafrost. The importance of subsurface conditions for above-ground vegetation depends on the geomorphological context, with plants in wet areas underlain by fine materials being the most likely to be growth-limited by permafrost, thus being potential hot-spots for future change. With the expectation of sustained climate change, loss of adjacent sea ice, and proximity to the forest-tundra ecotone, it is likely that the Torngat Mountains will continue to be an area of rapid environmental change in the coming decades.

Predisposing factors for the development of diabetic ketoacidosis with lower than anticipated glucose levels in type 2 diabetes patients on SGLT2-inhibitors: a review - Adeboye Olakunle Bamgboye; Isaac Oluwadamilare Oni; Andrew Collier (European Journal of Clinical Pharmacology, 2021)

Impact of free-living pattern of sedentary behaviour on intra-day glucose regulation in type 2 diabetes - Aye C. Paing; Kathryn A. McMillan; Alison F. Kirk; Andrew Collier; Allan Hewitt; Sebastien F. M. Chastin (European Journal of Applied Physiology, 2020)
Purpose To investigate how the pattern of sedentary behaviour affects intra-day glucose regulation in type 2 diabetes. Methods This intensive longitudinal study was conducted in 37 participants with type 2 diabetes (age, 62.8 ± 10.5 years). Glucose and sedentary behaviour/physical activity were assessed with a continuous glucose monitoring (Abbott FreeStyle Libre) and an activity monitor (activPAL3) for 14 days. Multiple regression models with generalised estimating equations (GEEs) approach were used to assess the associations of sedentary time and breaks in sedentary time with pre-breakfast glucose, pre-lunch glucose, pre-dinner glucose, post-breakfast glucose, post-lunch glucose, post-dinner glucose, bedtime glucose, the dawn phenomenon, time in target glucose range (TIR, glucose 3.9–10 mmol/L) and time above target glucose range (TAR, glucose > 10 mmol/L). Results Sedentary time was associated with higher pre-breakfast glucose ( p = 0.001), pre-dinner glucose ( p < 0.001), post-lunch glucose ( p = 0.005), post-dinner glucose ( p = 0.013) and the dawn phenomenon ( p < 0.001). Breaks in sedentary time were associated with lower pre-breakfast glucose ( p = 0.023), pre-dinner glucose ( p = 0.023), post-breakfast glucose ( p < 0.001) and the dawn phenomenon ( p = 0.004). The association between sedentary time and less TIR ( p = 0.022) and the association between breaks in sedentary time and more TIR ( p = 0.001) were also observed. Conclusions Reducing sedentary time and promoting breaks in sedentary time could be clinically relevant to improve intra-day glucose regulation in type 2 diabetes.

Management of candidaemia with reference to the European confederation of medical mycology quality indicators - Sophia Nemer; Toufeeq Imtiaz; Mohan Varikkara; Andrew Collier; Abhijit M. Bal (Infectious Diseases, 2019)

Tundra Trait Team: A database of plant traits spanning the tundra biome - Anne D. Bjorkman; Isla H. Myers‐Smith; Sarah C. Elmendorf; Signe Normand; Haydn J. D. Thomas; Juha M. Alatalo; Heather Alexander; Alba Anadon‐Rosell; Sandra Angers‐Blondin; Yang Bai; Gaurav Baruah; Mariska te Beest; et al. (Global Ecology and Biogeography, 2018)
Motivation The Tundra Trait Team (TTT) database includes field‐based measurements of key traits related to plant form and function at multiple sites across the tundra biome. This dataset can be used to address theoretical questions about plant strategy and trade‐offs, trait–environment relationships and environmental filtering, and trait variation across spatial scales, to validate satellite data, and to inform Earth system model parameters. Main types of variable contained The database contains 91,970 measurements of 18 plant traits. The most frequently measured traits (> 1,000 observations each) include plant height, leaf area, specific leaf area, leaf fresh and dry mass, leaf dry matter content, leaf nitrogen, carbon and phosphorus content, leaf C:N and N:P, seed mass, and stem specific density. Spatial location and grain Measurements were collected in tundra habitats in both the Northern and Southern Hemispheres, including Arctic sites in Alaska, Canada, Greenland, Fennoscandia and Siberia, alpine sites in the European Alps, Colorado Rockies, Caucasus, Ural Mountains, Pyrenees, Australian Alps, and Central Otago Mountains (New Zealand), and sub‐Antarctic Marion Island. More than 99% of observations are georeferenced. Time period and grain All data were collected between 1964 and 2018. A small number of sites have repeated trait measurements at two or more time periods. Major taxa and level of measurement Trait measurements were made on 978 terrestrial vascular plant species growing in tundra habitats. Most observations are on individuals (86%), while the remainder represent plot or site means or maximums per species. Software format csv file and GitHub repository with data cleaning scripts in R; contribution to TRY plant trait database ( www.try-db.org ) to be included in the next version release.

BioTIME: A database of biodiversity time series for the Anthropocene - Maria Dornelas; Laura H. Antão; Faye Moyes; Amanda E. Bates; Anne E. Magurran; Dušan Adam; Asem A. Akhmetzhanova; Ward Appeltans; José Manuel Arcos; Haley Arnold; Narayanan Ayyappan; Gal Badihi; et al. (Global Ecology and Biogeography, 2018)
Motivation The BioTIME database contains raw data on species identities and abundances in ecological assemblages through time. These data enable users to calculate temporal trends in biodiversity within and amongst assemblages using a broad range of metrics. BioTIME is being developed as a community‐led open‐source database of biodiversity time series. Our goal is to accelerate and facilitate quantitative analysis of temporal patterns of biodiversity in the Anthropocene. Main types of variables included The database contains 8,777,413 species abundance records, from assemblages consistently sampled for a minimum of 2 years, which need not necessarily be consecutive. In addition, the database contains metadata relating to sampling methodology and contextual information about each record. Spatial location and grain BioTIME is a global database of 547,161 unique sampling locations spanning the marine, freshwater and terrestrial realms. Grain size varies across datasets from 0.0000000158 km 2 (158 cm 2 ) to 100 km 2 (1,000,000,000,000 cm 2 ). Time period and grain BioTIME records span from 1874 to 2016. The minimal temporal grain across all datasets in BioTIME is a year. Major taxa and level of measurement BioTIME includes data from 44,440 species across the plant and animal kingdoms, ranging from plants, plankton and terrestrial invertebrates to small and large vertebrates. Software format .csv and .SQL.

International guidelines: the need to standardize the management of candidaemia - Laura Jack; Abhijit M. Bal; Sam Harte; Andrew Collier (Infectious Diseases, 2016)