Correction: Reducing herbicide leaching by split-dose applications in organomineral and mineral soils - Shane Scannell; Mark G. Healy; John McGinley; Paraic C. Ryan; Per-Erik Mellander; Liam Morrison; Jenny Harmon O’Driscoll; Alma Siggins (Environment, Development and Sustainability, 2026)

AI-driven seasonal streamflow prediction in Victoria: a focus on ENSO climate predictor - Sabrina Bani; Iqbal Hossain; Monzur Imteaz; Patrick Ryan Morrison (Stochastic Environmental Research and Risk Assessment, 2026)
Seasonal prediction of streamflow plays a crucial role in water allocation in southeastern Australia, where hydroclimatic variability is modulated by large-scale ocean-atmosphere interactions. Among them, the El Niño Southern Oscillation (ENSO) is recognised as a dominant driver, commonly represented by the Niño 3.4 index anomalies. This study examines the Niño 3.4 index to predict spring streamflow across Victoria. Two modelling strategies were employed. A conventional linear regression (LR) model as a baseline, compared with a nonlinear Artificial Intelligence neural network (AINN) framework based on a fully connected neural network (FCNN). The FCNN corresponds to a multilayer perceptron trained using the Levenberg–Marquardt algorithm. Antecedent Niño 3.4 values were used as predictors. Model performance was assessed using mean squared error (MSE), root mean squared error (RMSE), mean absolute error (MAE), and the Pearson correlation coefficient (R). The results demonstrate that the FCNN substantially improves predictive capability compared with the LR benchmark. The FCNN achieved R values between 0.70 and 0.96, whereas the LR model produced considerably weaker relationships, with R ranging from 0.01 to 0.45. The highest accuracy was obtained at the 3-month lag, where the FCNN produced a maximum correlation of 0.96 and a corresponding RMSE of 0.051. To further investigate temporal dependency, a Long Short-Term Memory (LSTM) network was also implemented. Although the LSTM captured certain temporal patterns and produced moderate correlations between 0.30 and 0.78, its performance was less consistent than FCNN with the limited dataset. These findings demonstrate that neural network models can effectively exploit climate-streamflow teleconnections for seasonal prediction.

Reducing herbicide leaching by split-dose applications in organomineral and mineral soils - Shane Scannell; Mark G. Healy; John McGinley; Paraic C. Ryan; Per-Erik Mellander; Liam Morrison; Jenny Harmon O’Driscoll; Alma Siggins (Environment, Development and Sustainability, 2026)

Experimental Challenge of Chinook Salmon ( Oncorhynchus tshawytscha ) With Tenacibaculum maritimum and Tenacibaculum dicentrarchi Fulfils Koch's Postulates - Karthiga Kumanan; Jeremy Carson; Ryan B. J. Hunter; Anne Rolton; Ulla von Ammon; Chaya Bandaranayake; Connie Angelucci; Richard N. Morrison; Seumas P. Walker; Jane E. Symonds; Kate S. Hutson (Journal of Fish Diseases, 2025)
The bacterial skin disease tenacibaculosis, caused by Tenacibaculum species, affects numerous economically important marine fish, including salmonids. This study reports the ability of three Tenacibaculum maritimum strains, belonging to different molecular O‐AGC types, and a single Tenacibaculum dicentrarchi strain to induce tenacibaculosis in farmed Chinook salmon ( Oncorhynchus tshawytscha , Walbaum 1792) in Aotearoa New Zealand. Naïve Chinook salmon were exposed to T. maritimum (2 × 10 8 cells/mL) and T. dicentrarchi (2 × 10 7 cells/mL) by immersion using natural seawater. Clinical signs of tenacibaculosis were apparent in all T. maritimum strains used in the challenged fish. Of these, 100% of the fish challenged with O‐AGC Type 2‐1 and Type 3‐2 strains became moribund, whereas only 60% of the O‐AGC Type 3‐0 challenged fish became moribund. Fish exposed to T. dicentrarchi showed more severe symptoms, exposing musculature in 51% of the challenged population, with 28% of fish becoming moribund. Gross pathological signs of fin rot, scale loss, skin ulcers and haemorrhagic skin spots were observed for both Tenacibaculum species and were consistent with those observed on farmed fish. Pure T. maritimum and T. dicentrarchi cultures were reisolated from epidermal damage of challenged fish. Tenacibaculum species was not isolated from the anterior kidney of affected fish, which indicates no systemic infection in Chinook salmon.

Quantifying the influence of climate change on pesticide risks in drinking water - J. Harmon O'Driscoll; M.G. Healy; A. Siggins; J. McGinley; E. O'Brien; J. Wang; P. Holloway; P.-E. Mellander; L. Morrison; S. Scannell; P.C. Ryan (Science of The Total Environment, 2025)

Environmental drivers of tropospheric bromine and mercury variability in coastal East Antarctica - Neil C. Page; Jenny A. Fisher; Stephen R. Wilson; Robyn Schofield; Robert G. Ryan; Sean Gribben; Andrew R. Klekociuk; Grant C. Edwards; Anthony Morrison (Atmospheric Environment, 2025)

Distribution of logjams in relation to lateral connectivity in the River Corridor - Ellen Wohl; Anna E. Marshall; Shayla Triantafillou; Mattea Mobley; Mickey Means-Brous; Ryan R. Morrison (Geomorphology, 2024)

Stochastic modelling of pesticide transport to drinking water sources via runoff and resulting human health risk assessment - J. Harmon O'Driscoll; J. McGinley; M.G. Healy; A. Siggins; P.-E. Mellander; L. Morrison; E. Gunnigle; P.C. Ryan (Science of The Total Environment, 2024)

Field assessment of coconut-based activated carbon systems for the treatment of herbicide contamination - John McGinley; Mark G. Healy; Shane Scannell; Paraic C. Ryan; Jenny Harmon O'Driscoll; Per-Erik Mellander; Liam Morrison; Alma Siggins (Chemosphere, 2024)

Serological and molecular typing of Tenacibaculum maritimum from New Zealand farmed salmon, Oncorhynchus tshawytscha - Karthiga Kumanan; Lizenn Delisle; Connie Angelucci; Ryan B.J. Hunter; Oleksandra Rudenko; Jeremy Carson; Richard N. Morrison; Andrew C. Barnes; Kate S. Hutson (Aquaculture, 2024)

Determining the response of riparian vegetation and river morphology to drought using Google Earth Engine and machine learning - Smriti Chaulagain; Mark C. Stone; Ryan R. Morrison; Liping Yang; Julie Coonrod; Noelani E. Villa (Journal of Arid Environments, 2023)

Current State and Opportunities with Long-acting Injectables: Industry Perspectives from the Innovation and Quality Consortium “Long-Acting Injectables” Working Group - Andrea Bauer; Philippe Berben; Sudhir S. Chakravarthi; Sayantan Chattorraj; Ashish Garg; Betty Gourdon; Tycho Heimbach; Ye Huang; Christopher Morrison; Deepak Mundhra; Ramesh Palaparthy; Pratik Saha; et al. (Pharmaceutical Research, 2023)

Discovery of pyrrolo[2,1-f][1,2,4]triazine-based inhibitors of adaptor protein 2-associated kinase 1 for the treatment of pain - Carolyn D. Dzierba; Bireshwar Dasgupta; George Karageorge; Walter Kostich; Brian Hamman; Jason Allen; Kim M. Esposito; Ramesh Padmanabha; James Grace; Kimberley Lentz; John Morrison; Daniel Morgan; et al. (Medicinal Chemistry Research, 2023)

Research priorities for the sustainability of coral-rich western Pacific seascapes - Graeme S. Cumming; Maja Adamska; Michele L. Barnes; Jon Barnett; David R. Bellwood; Joshua E. Cinner; Philippa J. Cohen; Jennifer M. Donelson; Katharina Fabricius; R. Quentin Grafton; Alana Grech; Georgina G. Gurney; et al. (Regional Environmental Change, 2023)
Nearly a billion people depend on tropical seascapes. The need to ensure sustainable use of these vital areas is recognised, as one of 17 policy commitments made by world leaders, in Sustainable Development Goal (SDG) 14 (‘Life below Water’) of the United Nations. SDG 14 seeks to secure marine sustainability by 2030. In a time of increasing social-ecological unpredictability and risk, scientists and policymakers working towards SDG 14 in the Asia–Pacific region need to know: (1) How are seascapes changing? (2) What can global society do about these changes? and (3) How can science and society together achieve sustainable seascape futures? Through a horizon scan, we identified nine emerging research priorities that clarify potential research contributions to marine sustainability in locations with high coral reef abundance. They include research on seascape geological and biological evolution and adaptation; elucidating drivers and mechanisms of change; understanding how seascape functions and services are produced, and how people depend on them; costs, benefits, and trade-offs to people in changing seascapes; improving seascape technologies and practices; learning to govern and manage seascapes for all; sustainable use, justice, and human well-being; bridging communities and epistemologies for innovative, equitable, and scale-crossing solutions; and informing resilient seascape futures through modelling and synthesis. Researchers can contribute to the sustainability of tropical seascapes by co-developing transdisciplinary understandings of people and ecosystems, emphasising the importance of equity and justice, and improving knowledge of key cross-scale and cross-level processes, feedbacks, and thresholds.

Evaluating neonicotinoid insecticide uptake by plants used as buffers and cover crops - Benjamin A. Morrison; Kang Xia; Ryan D. Stewart (Chemosphere, 2023)

Impact of historical legacy pesticides on achieving legislative goals in Europe - J. McGinley; M.G. Healy; P.C. Ryan; J. Harmon O'Driscoll; P.-E. Mellander; L. Morrison; A. Siggins (Science of The Total Environment, 2023)

Potential for redistribution of post‐moult habitat for Eudyptes penguins in the Southern Ocean under future climate conditions - Cara‐Paige Green; David B. Green; Norman Ratcliffe; David Thompson; Mary‐Anne Lea; Alastair M. M. Baylis; Alexander L. Bond; Charles‐André Bost; Sarah Crofts; Richard J. Cuthbert; Jacob González‐Solís; Kyle W. Morrison; et al. (Global Change Biology, 2023)
Anthropogenic climate change is resulting in spatial redistributions of many species. We assessed the potential effects of climate change on an abundant and widely distributed group of diving birds, Eudyptes penguins, which are the main avian consumers in the Southern Ocean in terms of biomass consumption. Despite their abundance, several of these species have undergone population declines over the past century, potentially due to changing oceanography and prey availability over the important winter months. We used light‐based geolocation tracking data for 485 individuals deployed between 2006 and 2020 across 10 of the major breeding locations for five taxa of Eudyptes penguins. We used boosted regression tree modelling to quantify post‐moult habitat preference for southern rockhopper ( E. chrysocome ), eastern rockhopper ( E. filholi ), northern rockhopper ( E. moseleyi ) and macaroni/royal ( E. chrysolophus and E. schlegeli ) penguins. We then modelled their redistribution under two climate change scenarios, representative concentration pathways RCP4.5 and RCP8.5 (for the end of the century, 2071–2100). As climate forcings differ regionally, we quantified redistribution in the Atlantic, Central Indian, East Indian, West Pacific and East Pacific regions. We found sea surface temperature and sea surface height to be the most important predictors of current habitat for these penguins; physical features that are changing rapidly in the Southern Ocean. Our results indicated that the less severe RCP4.5 would lead to less habitat loss than the more severe RCP8.5. The five taxa of penguin may experience a general poleward redistribution of their preferred habitat, but with contrasting effects in the (i) change in total area of preferred habitat under climate change (ii) according to geographic region and (iii) the species (macaroni/royal vs. rockhopper populations). Our results provide further understanding on the regional impacts and vulnerability of species to climate change.

Data-driven approaches for runoff prediction using distributed data - Heechan Han; Ryan R. Morrison (Stochastic Environmental Research and Risk Assessment, 2022)

Prediction of disability-free survival in healthy older people - Johannes Tobias Neumann; Le T. P. Thao; Anne M. Murray; Emily Callander; Prudence R. Carr; Mark R. Nelson; Rory Wolfe; Robyn L. Woods; Christopher M. Reid; Raj C. Shah; Anne B. Newman; Jeff D. Williamson; et al. (GeroScience, 2022)
Prolonging survival in good health is a fundamental societal goal. However, the leading determinants of disability-free survival in healthy older people have not been well established. Data from ASPREE, a bi-national placebo-controlled trial of aspirin with 4.7 years median follow-up, was analysed. At enrolment, participants were healthy and without prior cardiovascular events, dementia or persistent physical disability. Disability-free survival outcome was defined as absence of dementia, persistent disability or death. Selection of potential predictors from amongst 25 biomedical, psychosocial and lifestyle variables including recognized geriatric risk factors, utilizing a machine-learning approach. Separate models were developed for men and women. The selected predictors were evaluated in a multivariable Cox proportional hazards model and validated internally by bootstrapping. We included 19,114 Australian and US participants aged ≥65 years (median 74 years, IQR 71.6–77.7). Common predictors of a worse prognosis in both sexes included higher age, lower Modified Mini-Mental State Examination score, lower gait speed, lower grip strength and abnormal (low or elevated) body mass index. Additional risk factors for men included current smoking, and abnormal eGFR. In women, diabetes and depression were additional predictors. The biased-corrected areas under the receiver operating characteristic curves for the final prognostic models at 5 years were 0.72 for men and 0.75 for women. Final models showed good calibration between the observed and predicted risks. We developed a prediction model in which age, cognitive function and gait speed were the strongest predictors of disability-free survival in healthy older people. Trial registration Clinicaltrials.gov (NCT01038583)

Conventional versus drug-eluting embolic transarterial chemoembolization with doxorubicin: comparative drug delivery, pharmacokinetics, and treatment response in a rabbit VX2 tumor model - Ron C. Gaba; Ramzy C. Khabbaz; Ruth N. Muchiri; Joseph D. Morrison; Lobna Elkhadragy; William M. Totura; Jonathan P. Samuelson; Herbert E. Whiteley; Ryan L. Deaton; Peter L. Nguyen; Maria Sverdlov; Jeremy J. Johnson; et al. (Drug Delivery and Translational Research, 2022)

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.

Effects of temperature on sexual development in steelhead, Oncorhynchus mykiss - Kathleen S. Cole; David L. G. Noakes; Neil Thompson; Michael Blouin; Bruce Morrison; Ryan B. Couture; Joseph O’Neil; Carl B. Schreck (Environmental Biology of Fishes, 2021)

Leveraging linkage evidence to identify low-frequency and rare variants on 16p13 associated with blood pressure using TOPMed whole genome sequencing data - Karen Y. He; Xiaoyin Li; Tanika N. Kelly; Jingjing Liang; Brian E. Cade; Themistocles L. Assimes; Lewis C. Becker; Amber L. Beitelshees; Adam P. Bress; Yen-Pei Christy Chang; Yii-Der Ida Chen; Paul S. de Vries; et al. (Human Genetics, 2019)

Assessing the Hydrogeomorphic Effects of Environmental Flows using Hydrodynamic Modeling - Angela Gregory; Ryan R. Morrison; Mark Stone (Environmental Management, 2018)

Five ways to support interdisciplinary work before tenure - Melinda Harm Benson; Christopher D. Lippitt; Ryan Morrison; Barbara Cosens; Jan Boll; Brian C. Chaffin; Alexander K. Fremier; Robert Heinse; Derek Kauneckis; Timothy E. Link; Caroline E. Scruggs; Mark Stone; et al. (Journal of Environmental Studies and Sciences, 2016)

Abundance and distribution of major groups of diazotrophic cyanobacteria and their potential contribution to N 2 fixation in the tropical Atlantic Ocean - Nicole L. Goebel; Kendra A. Turk; Katherine M. Achilles; Ryan Paerl; Ian Hewson; Amanda E. Morrison; Joseph P. Montoya; Christopher A. Edwards; Jonathan P. Zehr (Environmental Microbiology, 2010)
Summary The abundances of six N 2 ‐fixing cyanobacterial phylotypes were profiled at 22 stations across the tropical Atlantic Ocean during June 2006, and used to model the contribution of the diazotrophs to N 2 fixation. Diazotroph abundances were measured by targeting the nifH gene of Trichodesmium , unicellular groups A, B, C (UCYN‐A, UCYN‐B and UCYN‐C), and diatom‐cyanobiont symbioses Hemiaulus–Richelia , Rhizosolenia–Richelia and Chaetoceros–Calothrix . West to east gradients in temperature, salinity and nutrients [NO 3 ‐ + NO 2 ‐ , PO 4 3− , Si(OH) 4 ] showed the influence of the Amazon River plume and its effect on the distributions of the diazotrophs. Trichodesmium accounted for more than 93% of all nifH genes detected, dominated the warmer waters of the western Atlantic, and was the only diazotroph detected at the equatorial upwelling station. UCYN‐A was the next most abundant (> 5% of all nifH genes) and dominated the cooler waters of the eastern Atlantic near the Cape Verde Islands. UCYN‐C was found at a single depth (200 m) of high salinity and low temperature and nutrients, whereas UCYN‐B cells were widespread but in very low abundance (6.1 × 10 1 ± 4.6 × 10 2 gene copies l −1 ). The diatom‐cyanobionts were observed primarily in the western Atlantic within or near the high Si(OH) 4 input of the Amazon River plume. Overall, highest diazotroph abundances were observed at the surface and declined with depth, except for some subsurface peaks in Trichodesmium , UCYN‐B and UCYN‐A. Modelled contributions of Trichodesmium , UCYN‐B and UCYN‐A to total N 2 fixation suggested that Trichodesmium had the largest input, except for the potential of UCYN‐A at the Cape Verde Islands.

A genetic test for recruitment enhancement in Chesapeake Bay oysters, Crassostrea virginica, after population supplementation with a disease tolerant strain - Matthew P. Hare; Standish K. Allen; Paulette Bloomer; Mark D. Camara; Ryan B. Carnegie; Jenna Murfree; Mark Luckenbach; Donald Meritt; Cheryl Morrison; Kennedy Paynter; Kimberly S. Reece; Colin G. Rose (Conservation Genetics, 2006)

Nest- and colony-mate recognition in polydomous colonies of meat ants (Iridomyrmex purpureus) - E. van Wilgenburg; D. Ryan; P. Morrison; P. J. Marriott; M. A. Elgar (The Science of Nature, 2006)