A high-resolution record of early rift development and tectonic, sedimentary and environmental conditions in an active rift basin: IODP MSP drilling in the Corinth Rift, Greece (Expedition 381) - Lisa C. McNeill; Donna J. Shillington; Jeanine Ash; Gareth D.O. Carter; Richard E.Ll. Collier; Aleksandra Cvetkoska; Paula Diz; Mai-Linh Doan; Jeremy D. Everest; Natacha Fabregas; Eugenia Fatourou; Mary Ford; et al. (Marine Geology, 2026)

Corrigendum to “Lizards in the wind: The impact of wind on the thermoregulation of the common wall lizard” [J. Therm. Biol. 121 (2024) 103855] - Sierra Spears; Ciara Pettit; Sophie Berkowitz; Simone Collier; Cece Colwell; Ethan H. Livingston; Wyatt McQueen; Princeton L. Vaughn; Brooke L. Bodensteiner; Vianey Leos-Barajas; Eric J. Gangloff (Journal of Thermal Biology, 2024)

Estimating angler effort and catch from a winter recreational fishery using a novel Bayesian methodology to integrate multiple sources of creel survey data - Caroline M. Tucker; Simone Collier; Geoffrey Legault; George E. Morgan; Derrick K. de Kerckhove (Fisheries Research, 2024)

Lizards in the wind: The impact of wind on the thermoregulation of the common wall lizard - Sierra Spears; Ciara Pettit; Sophie Berkowitz; Simone Collier; Cece Colwell; Ethan H. Livingston; Wyatt McQueen; Princeton L. Vaughn; Brooke L. Bodensteiner; Vianey Leos-Barajas; Eric J. Gangloff (Journal of Thermal Biology, 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.

Neuroparacoccidioidomycosis (NPCM): Magnetic Resonance Imaging (MRI) Findings - Fabiano Reis; Priscila Pimentel Collier; Thiago Ferreira Souza; Guilherme Pinheiro Lopes; Eduardo Bronzatto; Nivaldo Adolfo Silva Junior; Ricardo Mendes Pereira; Simone Appenzeller (Mycopathologia, 2013)

Global assessment of experimental climate warming on tundra vegetation: heterogeneity over space and time - Sarah C. Elmendorf; Gregory H. R. Henry; Robert D. Hollister; Robert G. Björk; Anne D. Bjorkman; Terry V. Callaghan; Laura Siegwart Collier; Elisabeth J. Cooper; Johannes H. C. Cornelissen; Thomas A. Day; Anna Maria Fosaa; William A. Gould; et al. (Ecology Letters, 2012)
Ecology Letters (2011) Abstract Understanding the sensitivity of tundra vegetation to climate warming is critical to forecasting future biodiversity and vegetation feedbacks to climate. In situ warming experiments accelerate climate change on a small scale to forecast responses of local plant communities. Limitations of this approach include the apparent site‐specificity of results and uncertainty about the power of short‐term studies to anticipate longer term change. We address these issues with a synthesis of 61 experimental warming studies, of up to 20 years duration, in tundra sites worldwide. The response of plant groups to warming often differed with ambient summer temperature, soil moisture and experimental duration. Shrubs increased with warming only where ambient temperature was high, whereas graminoids increased primarily in the coldest study sites. Linear increases in effect size over time were frequently observed. There was little indication of saturating or accelerating effects, as would be predicted if negative or positive vegetation feedbacks were common. These results indicate that tundra vegetation exhibits strong regional variation in response to warming, and that in vulnerable regions, cumulative effects of long‐term warming on tundra vegetation – and associated ecosystem consequences – have the potential to be much greater than we have observed to date.