Isotope metrics refine herbivory among three nominally herbivorous reef fishes of socio-ecological importance - Joshua Pi; Stephane Martinez; Dana T. Cook; Milo Tasopulu; John Rulmal; Michelle J. Paddack; Nicole L. Crane; Giacomo Bernardi; Jonathan D. Cybulski; Kelton W. McMahon (Coral Reefs, 2026)
Herbivorous coral reef fishes are often assigned to different functional groups based on feeding mode and presumed ecosystem processes, such as algal removal ( i.e. , functional herbivory). However, these functional assignments do not necessarily identify assimilated resources nor predict nutritional pathways supporting fish biomass. We used stable carbon and nitrogen isotopes of amino acids to refine our understanding of herbivory among three nominally herbivorous fishes: Chlorurus spilurus , Ctenochaetus striatus , and Naso lituratus . Amino acid carbon isotope fingerprinting indicated much higher and more variable algal carbon contribution for N. lituratus (52.0% [22.0–84.1]) than C. spilurus (5.4% [0.9–17.8]) or C. striatus (4.8% [0.8–15.6]), which were corroborated by low trophic transfer values of N. lituratus ( Δδ 15 N Glu-Lys = 6.0 ± 0.9‰), high source δ 15 N Lys values (4.7 ± 1.0‰), and low microbial reworking ΣV values (0.9 ± 0.2). Conversely, higher Δδ 15 N Glu-Lys values of C. spilurus (7.9 ± 0.9‰) and C. striatus (9.0 ± 1.1‰) coupled with low δ 15 N Lys values (3.6 ± 1.0‰; 3.6 ± 1.1‰, respectively) and higher ΣV values (1.4 ± 0.2; 1.3 ± 0.2, respectively) indicated increased reliance on heterotrophically recycled production ( e.g. , bacteria, detritus, sponge tissue, mucus). Taken together, these data indicate N. lituratus as the most algivorous among our study species, while its broad source credible intervals may reflect epibiont assimilation, algal source variability, or intraspecific dietary variation. By linking carbon source assimilation and trophic transfer at the molecular level, we show that functionally “herbivorous” fishes can occupy distinct nutritional niches and that nutritional and functional definitions of herbivory may not always align.

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.

The Toxicology Investigators Consortium 2024 Annual Report - Kim Aldy; Shao Li; Mari Costantini; Alyssa Falise; Rachel Culbreth; Paul M. Wax; Jeffery Brent; Michael Abesamis; Faiz Ahmed; Salman Ahsan; Peter Akpunonu; Adam Algren; et al. (Journal of Medical Toxicology, 2026)

Correcting the heartwood-sapwood transition in blue intensity measurements with change point detection methods - Hung T.T. Nguyen; Rory Abernethy; Rob Wilson; Daniel L. Druckenbrod; Kathryn J. Allen; Brendan M. Buckley; Edward R. Cook; Rosanne D’Arrigo; Jonathan G. Palmer (Dendrochronologia, 2025)

Informatics for toxicokinetics - Gilberto Padilla Mercado; Christopher Cook; Norman Adkins; Lucas Albrecht; Grace Cary; Brenda Edwards; Derik E. Haggard; Nancy M. Hanley; Michael F. Hughes; Anna Jarnagin; Tirumala D. Kodavanti; Evgenia Korol-Bexell; et al. (Journal of Pharmacokinetics and Pharmacodynamics, 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.

Reframing wildlife disease management problems with decision analysis - Margaret C. McEachran; Johanna A. Harvey; Riley O. Mummah; Molly C. Bletz; Claire S. Teitelbaum; Elias Rosenblatt; F. Javiera Rudolph; Fernando Arce; Shenglai Yin; Diann J. Prosser; Brittany A. Mosher; Jennifer M. Mullinax; et al. (Conservation Biology, 2024)
Contemporary wildlife disease management is complex because managers need to respond to a wide range of stakeholders, multiple uncertainties, and difficult trade‐offs that characterize the interconnected challenges of today. Despite general acknowledgment of these complexities, managing wildlife disease tends to be framed as a scientific problem, in which the major challenge is lack of knowledge. The complex and multifactorial process of decision‐making is collapsed into a scientific endeavor to reduce uncertainty. As a result, contemporary decision‐making may be oversimplified, rely on simple heuristics, and fail to account for the broader legal, social, and economic context in which the decisions are made. Concurrently, scientific research on wildlife disease may be distant from this decision context, resulting in information that may not be directly relevant to the pertinent management questions. We propose reframing wildlife disease management challenges as decision problems and addressing them with decision analytical tools to divide the complex problems into more cognitively manageable elements. In particular, structured decision‐making has the potential to improve the quality, rigor, and transparency of decisions about wildlife disease in a variety of systems. Examples of management of severe acute respiratory syndrome coronavirus 2, white‐nose syndrome, avian influenza, and chytridiomycosis illustrate the most common impediments to decision‐making, including competing objectives, risks, prediction uncertainty, and limited resources.

Epidemiology, Clinical Features, and Management of Texas Coral Snake (Micrurus tener) Envenomations Reported to the North American Snakebite Registry - Spencer Greene; Anne-Michelle Ruha; Sharan Campleman; Jeffrey Brent; Paul Wax; Kim Aldy; Peter Akpunonu; Vikhyat S. Bebarta; Gillian A. Beauchamp; Michael C. Beuhler; Mary Billington; William Boroughf; et al. (Journal of Medical Toxicology, 2021)

A fluvially derived flood deposit dating to the Kamikaze typhoons near Nagasaki, Japan - Caroline Ladlow; Jonathan D. Woodruff; Timothy L. Cook; Hannah Baranes; Kinuyo Kanamaru (Natural Hazards, 2019)

Factors affecting distribution and abundance of jellyfish medusae in a temperate estuary: a multi-decadal study - Jason Baumsteiger; Teejay A. O’Rear; Jonathan D. Cook; Amber D. Manfree; Peter B. Moyle (Biological Invasions, 2018)

Sedimentological records of the C.E. 1707 Hōei Nankai Trough tsunami in the Bungo Channel, southwestern Japan - Hannah E. Baranes; Jonathan D. Woodruff; Davin J. Wallace; Kinuyo Kanamaru; Timothy L. Cook (Natural Hazards, 2016)

Assessing the genetic architecture of epithelial ovarian cancer histological subtypes - Gabriel Cuellar-Partida; Yi Lu; Suzanne C. Dixon; Peter A. Fasching; Alexander Hein; Stefanie Burghaus; Matthias W. Beckmann; Diether Lambrechts; Els Van Nieuwenhuysen; Ignace Vergote; Adriaan Vanderstichele; Jennifer Anne Doherty; et al. (Human Genetics, 2016)

Genome-wide association study of subtype-specific epithelial ovarian cancer risk alleles using pooled DNA - Madalene A. Earp; Linda E. Kelemen; Anthony M. Magliocco; Kenneth D. Swenerton; Georgia Chenevix-Trench; Yi Lu; Alexander Hein; Arif B. Ekici; Matthias W. Beckmann; Peter A. Fasching; Diether Lambrechts; Evelyn Despierre; et al. (Human Genetics, 2014)

Sensitivity of Spring Phenology to Warming Across Temporal and Spatial Climate Gradients in Two Independent Databases - Benjamin I. Cook; Elizabeth M. Wolkovich; T. Jonathan Davies; Toby R. Ault; Julio L. Betancourt; Jenica M. Allen; Kjell Bolmgren; Elsa E. Cleland; Theresa M. Crimmins; Nathan J. B. Kraft; Lesley T. Lancaster; Susan J. Mazer; et al. (Ecosystems, 2012)

A novel approach of homozygous haplotype sharing identifies candidate genes in autism spectrum disorder - Jillian P. Casey; Tiago Magalhaes; Judith M. Conroy; Regina Regan; Naisha Shah; Richard Anney; Denis C. Shields; Brett S. Abrahams; Joana Almeida; Elena Bacchelli; Anthony J. Bailey; Gillian Baird; et al. (Human Genetics, 2012)

Haplotype structure in Ashkenazi Jewish BRCA1 and BRCA2 mutation carriers - Kate M. Im; Tomas Kirchhoff; Xianshu Wang; Todd Green; Clement Y. Chow; Joseph Vijai; Joshua Korn; Mia M. Gaudet; Zachary Fredericksen; V. Shane Pankratz; Candace Guiducci; Andrew Crenshaw; et al. (Human Genetics, 2011)

Using Light-Use and Production Efficiency Models to Predict Photosynthesis and Net Carbon Exchange During Forest Canopy Disturbance - Bruce D. Cook; Paul V. Bolstad; Jonathan G. Martin; Faith Ann Heinsch; Kenneth J. Davis; Weiguo Wang; Ankur R. Desai; Ron M. Teclaw (Ecosystems, 2008)

The effect of polymorphism at the serotonin transporter gene on decision-making, memory and executive function in ecstasy users and controls - Jonathan P. Roiser; Robert D. Rogers; Lynnette J. Cook; Barbara J. Sahakian (Psychopharmacology, 2006)