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.

Collaborative evaluation of in silico predictions for high throughput toxicokinetics - John F. Wambaugh; Nisha S. Sipes; Gilberto Padilla Mercado; Jon A. Arnot; Linda Bertato; Trevor N. Brown; Nicola Chirico; Christopher Cook; Daniel E. Dawson; Sarah E. Davidson-Fritz; Stephen S. Ferguson; Michael-Rock Goldsmith; et al. (Toxicology in Vitro, 2026)

Network of networks: Time series clustering of AmeriFlux sites - David E Reed; Housen Chu; Brad G. Peter; Jiquan Chen; Michael Abraha; Brian Amiro; Ray G. Anderson; M. Altaf Arain; Paulo Arruda; Greg A. Barron-Gafford; Carl Bernacchi; Daniel P. Beverly; et al. (Agricultural and Forest Meteorology, 2025)

Mineralogy, mineral chemistry, and genesis of Cu-Ni-As-rich ores at Lisheen, Ireland - Max Frenzel; Markus Röhner; Nigel J. Cook; Sarah Gilbert; Cristiana L. Ciobanu; John F. Güven (Mineralium Deposita, 2025)
The Irish Orefield is characterised by the presence of both Zn-Pb- and Cu-Ni-As-rich deposits, prospects, and orebodies in similar structural and stratigraphic positions. However, the genetic relationships between these mineralisation types are still debated. In this article, we present new mineralogical, paragenetic, and mineral-chemical observations from the Cu-Ni-As-rich ores at the classic Lisheen deposit, County Tipperary. These observations indicate the intimate association and cogenetic nature of these ores with the more abundant Zn-Pb-rich mineralisation. Specifically, both mineralisation types appear to have formed at the same time, under similar physicochemical conditions, and from the same ore fluids. In addition, both types of mineralisation contain elevated Ge contents. The cogenetic nature of the two mineralisation types, the relative absence of Cu-Ni-As-rich ores from most of the larger Irish-type Zn-Pb deposits compared to expectations derived from probable ore fluid compositions, and finally, the known geological characteristics of larger Cu-Ni-As-rich ore bodies, like Gortdrum, indicate that significant Cu-Ni-As-rich mineralisation could be present at lower stratigraphic levels across the Irish Orefield. Areas with extensive known Zn-Pb mineralisation are expected to be particularly prospective for such ores, which may occur at stratigraphic levels as deep as the Old Red Sandstone. This may have additional implications beyond Ireland, and could point to the potential for undiscovered Cu-rich ores in low-temperature carbonate-hosted Zn-Pb districts elsewhere.

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.

Genetic analyses of gynecological disease identify genetic relationships between uterine fibroids and endometrial cancer, and a novel endometrial cancer genetic risk region at the WNT4 1p36.12 locus - Pik Fang Kho; Sally Mortlock; Frederic Amant; Daniela Annibali; Katie Ashton; John Attia; Paul L. Auer; Matthias W. Beckmann; Amanda Black; Louise Brinton; Daniel D. Buchanan; Stephen J. Chanock; et al. (Human Genetics, 2021)

Conjoint use of hydraulic head and groundwater age data to detect hydrogeologic barriers - Sarah K. Marshall; Peter G. Cook; Leonard F. Konikow; Craig T. Simmons; Shawan Dogramaci (Hydrogeology Journal, 2020)

Population Pharmacokinetic Modeling in the Presence of Missing Time-Dependent Covariates: Impact of Body Weight on Pharmacokinetics of Paracetamol in Neonates - Wojciech Krzyzanski; Sarah F. Cook; Melanie Wilbaux; Catherine M. T. Sherwin; Karel Allegaert; An Vermeulen; John N. van den Anker (The AAPS Journal, 2019)

Disease Progression Modeling: Key Concepts and Recent Developments - Sarah F. Cook; Robert R. Bies (Current Pharmacology Reports, 2016)