Integrated Reanalysis of Global Riverine Fish eDNA Datasets Shows Robustness and Congruence of Biodiversity Conclusions - Yan Zhang; Heng Zhang; Hiroshi Akashi; Camille P. Albouy; Kara J. Andres; José Barquín; Jeanine Brantschen; Richard E. Connon; Joseph M. Craine; Deirdre Gleeson; Alejandra Goldenberg‐Vilar; Alexia M. González‐Ferreras; et al. (Molecular Ecology, 2026)
The analysis of environmental DNA (eDNA) has revolutionized biodiversity assessments in aquatic ecosystems, enabling non‐invasive monitoring of fish communities across diverse regions. However, the global comparability of these eDNA datasets remains ambiguous due to heterogeneous sampling protocols and bioinformatic workflows across studies, making it difficult to assess how robust and comparable the biodiversity patterns inferred from these datasets actually are. Here, we conducted a meta‐analysis of 58 riverine fish eDNA metabarcoding studies, covering 1818 sampling sites worldwide, to evaluate the robustness of eDNA‐derived biodiversity patterns. We found that species richness estimates and metrics of community structure derived under a common bioinformatic workflow were overall consistent with those of original analyses, despite the relatively high variability in bioinformatic analyses in the respective original studies. Contrastingly, congruence of species identity varied more extensively across datasets, mostly reflecting different completeness and regional relevance of reference databases. Restricting taxonomic assignment to basin‐specific species pools improved species identification accuracy, while datasets lacking publicly accessible or well‐curated reference data were more prone to mismatches. Year of sampling had a positive effect on taxonomic congruence, such that more recent studies showed increased robustness, also reflecting improved reference database coverage and enhanced species‐level identification over time and overall method congruence in more recent years. Overall, the suitability and potential of eDNA for global biodiversity monitoring is corroborating overall robust biodiversity estimates, irrespective of the bioinformatic approaches. Our study underlines the effectiveness and need for further harmonization of bioinformatic workflows and strengthened region‐specific reference databases for improved taxonomic resolution and comparability across studies.

Pilot Trial of Nutri, a Digital Intervention for Personalized Dietary Management of Diabetes in Safety-Net Primary Care - Marissa Burgermaster; Madalyn Rosenthal; Brandon S. Altillo; Mariana Rendon Flores; Eesha Nayak; Dagny N. Larson; James Custer; Lola Okunade; William M. Tierney; Steven Andrews; Grant Daniels; Paul J. Rathouz (Journal of Nutrition Education and Behavior, 2025)

BioTIME 2.0: Expanding and Improving a Database of Biodiversity Time Series - Maria Dornelas; Laura H. Antão; Amanda E. Bates; Viviana Brambilla; Jonathan M. Chase; Cher F. Y. Chow; Ada Fontrodona‐Eslava; Anne E. Magurran; Inês S. Martins; Faye Moyes; Alban Sagouis; Samuel Adu‐Acheampong; et al. (Global Ecology and Biogeography, 2025)
Motivation Here, we make available a second version of the BioTIME database, which compiles records of abundance estimates for species in sample events of ecological assemblages through time. The updated version expands version 1.0 of the database by doubling the number of studies and includes substantial additional curation to the taxonomic accuracy of the records, as well as the metadata. Moreover, we now provide an R package (BioTIMEr) to facilitate use of the database. Main Types of Variables Included The database is composed of one main data table containing the abundance records and 11 metadata tables. The data are organised in a hierarchy of scales where 11,989,233 records are nested in 1,603,067 sample events, from 553,253 sampling locations, which are nested in 708 studies. A study is defined as a sampling methodology applied to an assemblage for a minimum of 2 years. Spatial Location and Grain Sampling locations in BioTIME are distributed across the planet, including marine, terrestrial and freshwater realms. Spatial grain size and extent vary across studies depending on sampling methodology. We recommend gridding of sampling locations into areas of consistent size. Time Period and Grain The earliest time series in BioTIME start in 1874, and the most recent records are from 2023. Temporal grain and duration vary across studies. We recommend doing sample‐level rarefaction to ensure consistent sampling effort through time before calculating any diversity metric. Major Taxa and Level of Measurement The database includes any eukaryotic taxa, with a combined total of 56,400 taxa. Software Format csv and. SQL.

Corrigendum to “Troubled waters in the land down under: Pervasive threats and high extinction risks demand urgent conservation actions to protect Australia's native freshwater fishes” [Biol. Conserv. 300 (2024), 110843] - Mark Lintermans; Maiko Lutz; Nick S. Whiterod; Bernd Gruber; Michael P. Hammer; Mark J. Kennard; David L. Morgan; Tarmo A. Raadik; Peter Unmack; Steven Brooks; Brendan C. Ebner; Dean Gilligan; et al. (Biological Conservation, 2025)

Troubled waters in the land down under: Pervasive threats and high extinction risks demand urgent conservation actions to protect Australia's native freshwater fishes - Mark Lintermans; Maiko Lutz; Nick S. Whiterod; Bernd Gruber; Michael P. Hammer; Mark J. Kennard; David L. Morgan; Tarmo A. Raadik; Peter Unmack; Steven Brooks; Brendan C. Ebner; Dean Gilligan; et al. (Biological Conservation, 2024)

Correction: Major histocompatibility complex class I molecule expression by pancreatic cancer cells is regulated by activation and inhibition of the epidermal growth factor receptor - Shelby M. Knoche; Alaina C. Larson; Gabrielle L. Brumfield; Steven Cate; William H. Hildebrand; Joyce C. Solheim (Immunologic Research, 2024)

Major histocompatibility complex class I molecule expression by pancreatic cancer cells is regulated by activation and inhibition of the epidermal growth factor receptor - Shelby M. Knoche; Alaina C. Larson; Gabrielle L. Brumfield; Steven Cate; William H. Hildebrand; Joyce C. Solheim (Immunologic Research, 2022)

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.

Uranium Adsorption on Three Nanohydroxyapatites Under Various Biogeochemical Conditions - Precious Cooper; Jing Nie; Steven L. Larson; John H. Ballard; Heather M. Knotek-Smith; Ahmet Celik; Shaloam Dasari; Xianchun Zhu; Fengxiang X. Han (Water, Air, & Soil Pollution, 2021)

Microbially Induced Carbonate Precipitation Techniques for the Remediation of Heavy Metal and Trace Element–Polluted Soils and Water - Xue Chen; Dan Zhang; Steven L. Larson; John H. Ballard; Heather M. Knotek-Smith; Jing Nie; Nan Hu; Dexin Ding; Fengxiang X. Han (Water, Air, & Soil Pollution, 2021)

Shallow lake management enhanced habitat and attracted waterbirds during fall migration - Danelle M. Larson; Steven D. Cordts; Nicole Hansel-Welch (Hydrobiologia, 2020)

Influence of occupation history and habitat on Washington sea otter diet - Jessica R. Hale; Kristin L. Laidre; M. Tim Tinker; Ronald J. Jameson; Steven J. Jeffries; Shawn E. Larson; James L. Bodkin (Marine Mammal Science, 2019)
Habitat characteristics are primary determinants of nearshore marine communities. However, biological drivers like predation can also be important for community composition. Sea otters ( Enhydra lutris ssp.) are a salient example of a keystone species exerting top‐down control on ecosystem community structure. The translocation and subsequent population growth and range expansion of the northern sea otter ( Enhydra lutris kenyoni ) in Washington State over the last five decades has created a spatio‐temporal gradient in sea otter occupation time and density, and acts as a natural experiment to quantify how sea otter population status and habitat type influence sea otter diet. We collected focal observations of sea otters foraging at sites across the gradient in varying habitat types between 2010 and 2017. We quantified sea otter diet composition and diversity, and long‐term rates of energy gain across the gradient. We found that sea otter diet diversity was positively correlated with cumulative sea otter density, while rate of energy gain was negatively correlated with cumulative density. Additionally, we found that habitat type explained 1.77 times more variance in sea otter diet composition than sea otter cumulative density. Long‐term diet studies can provide a broader picture of sea otter population status in Washington State.

Development of a quantitative PCR method for screening ichthyoplankton samples for bigheaded carps - Andrea K. Fritts; Brent C. Knights; James H. Larson; Jon J. Amberg; Christopher M. Merkes; Tariq Tajjioui; Steven E. Butler; Matthew J. Diana; David H. Wahl; Michael J. Weber; John D. Waters (Biological Invasions, 2019)

Age-related changes in the corpus callosum in early-onset bipolar disorder assessed using volumetric and cross-sectional measurements - Melissa Lopez-Larson; Janis L. Breeze; David N. Kennedy; Steven M. Hodge; Lena Tang; Constance Moore; Anthony J. Giuliano; Nikos Makris; Verne S. Caviness; Jean A. Frazier (Brain Imaging and Behavior, 2010)

Grid soil sampling adoption and abandonment in cotton production - Jonathan C. Walton; Roland K. Roberts; Dayton M. Lambert; James A. Larson; Burton C. English; Sherry L. Larkin; Steven W. Martin; Michele C. Marra; Kenneth W. Paxton; Jeanne M. Reeves (Precision Agriculture, 2010)

Species delimitation tests of endemic Lepidium papilliferum and identification of other possible evolutionarily significant units in the Lepidium montanum complex (Brassicaceae) of western North America - Steven R. Larson; C. M. Culumber; R. N. Schweigert; N. J. Chatterton (Conservation Genetics, 2010)

Factors affecting farmer adoption of remotely sensed imagery for precision management in cotton production - James A. Larson; Roland K. Roberts; Burton C. English; Sherry L. Larkin; Michele C. Marra; Steven W. Martin; Kenneth W. Paxton; Jeanne M. Reeves (Precision Agriculture, 2008)

Extraction of the magnetohydrodynamic blood flow potential from the surface electrocardiogram in magnetic resonance imaging - Grace M. Nijm; Steven Swiryn; Andrew C. Larson; Alan V. Sahakian (Medical & Biological Engineering & Computing, 2008)

Molecular targeting of the lymphovascular system for imaging and therapy - Heiko Schöder; Edwin C. Glass; Alain P. Pecking; Jay K. Harness; Anne M. Wallace; Peter Hirnle; Jean L. Alberini; Didier Vilain; Steven M. Larson; Carl K. Hoh; David R. Vera (Cancer and Metastasis Reviews, 2006)

Enhancing the Uptake of Chemotherapeutic Drugs into Tumors using an “Artificial Lymphatic System” - Gene R. DiResta; Jongbin Lee; John H. Healey; Steven M. Larson; Ehud Arbit (Annals of Biomedical Engineering, 2000)

“Artificial Lymphatic System”: A New Approach to Reduce Interstitial Hypertension and Increase Blood Flow, pH and pO 2 in Solid Tumors - Gene R. DiResta; Jongbin Lee; John H. Healey; Andrey Levchenko; Steven M. Larson; Ehud Arbit (Annals of Biomedical Engineering, 2000)

The human FE65 gene: genomic structure and an intronic biallelic polymorphism associated with sporadic dementia of the Alzheimer type - Q. Hu; Walter A. Kukull; Steven L. Bressler; Matthew D. Gray; Judith A. Cam; Eric B. Larson; George M. Martin; Samir S. Deeb (Human Genetics, 1998)