A self-supervised representation learning method for detecting and classifying fishing behaviour from AIS data in the St. Anns Bank MPA - Nicolas Beaulieu; Bryce MacInnis; Catherine Evans; Alysa Czenze; Melina Mehlmann; Maggie Sutherland; Christopher Whidden; Levi Morrison (Frontiers in Marine Science, 2026)
Marine Protected Areas (MPA) increasingly rely on automatic identification system (AIS) data to monitor fishing activity. Enforcement remains difficult because AIS is self-reported, labels of fishing behaviour are scarce, and traffic patterns differ strongly between regions. This study develops a hierarchical machine learning framework that estimates the probability of fishing from AIS position time series using only latitude and longitude. First, a self-supervised temporal encoder is trained on millions of unlabeled AIS messages to learn motion embeddings that summarize 75-minute vessel trajectories. Supervised classifiers are then trained on these embeddings to predict fishing vessel type, active fishing behaviour, and fishing gear type. Finally, a label-shift calibration step combines these outputs with operational assumptions about local vessel composition, fishing activity levels, and gear usage. This step adapts the globally trained models to the specific conditions of the St. Anns Bank MPA to produce locally calibrated fishing probabilities. On held-out data, the vessel-type and behaviour classifiers achieve areas under the receiver operating characteristic curve of 0.91 and 0.94, and average precision scores of 0.86 and 0.88, respectively, while the gear classifier obtained moderate overall performance, performing best for common gears. When applied to two years of AIS data from St. Anns Bank, the framework successfully highlights a sparse set of trajectories, allowing for more focused inspection. These results show that self-supervised motion embeddings, combined with probabilistic fusion and operational calibration, offer a label-efficient and adaptable approach to AIS-based monitoring in marine protected areas.

Adapting the COASTGUARD shoreline detection workflow to macrotidal estuaries: a case study in the Musquash Estuary Marine Protected Area - Peike Cong; Catherine Evans; Bryce MacInnis; Alysa Czenze; Melina Mehlmann; Maggie Sutherland; Christopher Whidden; Levi Morrison (Frontiers in Marine Science, 2026)
Tidal range, diverse land-cover conditions, and complex intertidal topography make accurately monitoring estuarine shoreline change difficult. This study extends the COASTGUARD workflow from traditional open coastline applications to complex, macrotidal estuarine environments, demonstrated through a case study in the Musquash Marine Protected Area. The revised pipeline introduces three key contributions: habitat-aware classification tailored to estuarine settings, a buffer-area strategy for tidal flat shorelines, and tidal correction based on DEM-derived slope estimation. High-resolution SuperDove imagery was used for habitat classification using a three-layer MLP with 91.94% accuracy validated against existing habitat maps. Slopes were derived through calculations of shoreline position using a 1 m LiDAR derived DEM. Water level was calculated through applying the Piecewise Cubic Hermite Interpolation on a seven-day moving window. Images captured during high tide had a 150 m buffer applied to the reference shoreline , reducing misclassification from offshore noise . These contributions to the COASTGUARD framework enhance shoreline tracking in a macrotidal environment of beaches, salt marshes, and tidal flats in close proximity. This introduces an accurate long term and event-based monitoring strategy for environments hosting across different tidal zones, advancing applied scientific research and management applications.

Pedigree-based genome-wide imputation using a low-density amplicon panel for the highly polymorphic Pacific oyster Crassostrea (Magallana) gigas - Ben J.G. Sutherland; Konstantin Divilov; Neil F. Thompson; Thomas A. Delomas; Spencer L. Lunda; Christopher J. Langdon; Timothy J. Green (Aquaculture, 2026)

Increases in regional brain volume across two native South American male populations - Nikhil N. Chaudhari; Phoebe E. Imms; Nahian F. Chowdhury; Margaret Gatz; Benjamin C. Trumble; Wendy J. Mack; E. Meng Law; M. Linda Sutherland; James D. Sutherland; Christopher J. Rowan; L. Samuel Wann; Adel H. Allam; et al. (GeroScience, 2024)
Industrialized environments, despite benefits such as higher levels of formal education and lower rates of infections, can also have pernicious impacts upon brain atrophy. Partly for this reason, comparing age-related brain volume trajectories between industrialized and non-industrialized populations can help to suggest lifestyle correlates of brain health. The Tsimane, indigenous to the Bolivian Amazon, derive their subsistence from foraging and horticulture and are physically active. The Moseten, a mixed-ethnicity farming population, are physically active but less than the Tsimane. Within both populations ( N = 1024; age range = 46–83), we calculated regional brain volumes from computed tomography and compared their cross-sectional trends with age to those of UK Biobank (UKBB) participants ( N = 19,973; same age range). Surprisingly among Tsimane and Moseten (T/M) males, some parietal and occipital structures mediating visuospatial abilities exhibit small but significant increases in regional volume with age. UKBB males exhibit a steeper negative trend of regional volume with age in frontal and temporal structures compared to T/M males. However, T/M females exhibit significantly steeper rates of brain volume decrease with age compared to UKBB females, particularly for some cerebro-cortical structures (e.g., left subparietal cortex). Across the three populations, observed trends exhibit no interhemispheric asymmetry. In conclusion, the age-related rate of regional brain volume change may differ by lifestyle and sex. The lack of brain volume reduction with age is not known to exist in other human population, highlighting the putative role of lifestyle in constraining regional brain atrophy and promoting elements of non-industrialized lifestyle like higher physical activity.

The Ontology of Biological Attributes (OBA)—computational traits for the life sciences - Ray Stefancsik; James P. Balhoff; Meghan A. Balk; Robyn L. Ball; Susan M. Bello; Anita R. Caron; Elissa J. Chesler; Vinicius de Souza; Sarah Gehrke; Melissa Haendel; Laura W. Harris; Nomi L. Harris; et al. (Mammalian Genome, 2023)
Existing phenotype ontologies were originally developed to represent phenotypes that manifest as a character state in relation to a wild-type or other reference. However, these do not include the phenotypic trait or attribute categories required for the annotation of genome-wide association studies (GWAS), Quantitative Trait Loci (QTL) mappings or any population-focussed measurable trait data. The integration of trait and biological attribute information with an ever increasing body of chemical, environmental and biological data greatly facilitates computational analyses and it is also highly relevant to biomedical and clinical applications. The Ontology of Biological Attributes (OBA) is a formalised, species-independent collection of interoperable phenotypic trait categories that is intended to fulfil a data integration role. OBA is a standardised representational framework for observable attributes that are characteristics of biological entities, organisms, or parts of organisms. OBA has a modular design which provides several benefits for users and data integrators, including an automated and meaningful classification of trait terms computed on the basis of logical inferences drawn from domain-specific ontologies for cells, anatomical and other relevant entities. The logical axioms in OBA also provide a previously missing bridge that can computationally link Mendelian phenotypes with GWAS and quantitative traits. The term components in OBA provide semantic links and enable knowledge and data integration across specialised research community boundaries, thereby breaking silos.

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)

Productivity and municipal wastewater nutrient bioremediation performance of new filamentous green macroalgal cultivars - Rebecca J. Lawton; Christopher R. K. Glasson; Phillip M. Novis; Judy E. Sutherland; Marie E. Magnusson (Journal of Applied Phycology, 2021)

Abiotic stress and biotic factors mediate range dynamics on opposing edges - Alexej P. K. Sirén; Christopher S. Sutherland; Christopher A. Bernier; Kimberly J. Royar; Jillian R. Kilborn; Catherine B. Callahan; Rachel M. Cliché; Leighlan S. Prout; Toni Lyn Morelli (Journal of Biogeography, 2021)
Aim In the face of global change, understanding causes of range limits are one of the most pressing needs in biogeography and ecology. A prevailing hypothesis is that abiotic stress forms cold (upper latitude/altitude) limits, whereas biotic interactions create warm (lower) limits. A new framework – Interactive Range‐Limit Theory (iRLT) – asserts that positive biotic factors such as food availability can ameliorate abiotic stress along cold edges, whereas abiotic stress can have a positive effect and mediate biotic interactions (e.g., competition) along warm limits. Location Northeastern United States Taxon Carnivora Methods We evaluated two hypotheses of iRLT using occupancy and structural equation modeling (SEM) frameworks based on data collected over a 6‐year period (2014–2019) of six carnivore species across a broad latitudinal (42.8–45.3°N) and altitudinal (3–1451 m) gradient. Results We found that snow directly limits populations, but prey or habitat availability can influence range dynamics along cold edges. For example, bobcats ( Lynx rufus ) and coyotes ( Canis latrans ) were limited by deep snow and long winters, but the availability of prey had a strong positive effect. Conversely, snow had a strong positive effect on the warm limits of Canada lynx ( Lynx canadensis ), countering the negative effect of competition with the phylogenetically similar bobcat and with coyotes, highlighting how climate mediates competition between species. Main conclusions We used an integrated dataset that included competitors and prey species collected at the same spatial and temporal scale. As such, this design, along with a causal modeling framework (SEM), allowed us to evaluate community‐wide hypotheses at macroecological scales and identify coarse‐scale drivers of species' range limits. Our study supports iRLT and underscores the need to consider direct and indirect mechanisms for studying range dynamics and species' responses to global change.

Recent advances toward the sustainable management of invasive Xylosandrus ambrosia beetles - Antonio Gugliuzzo; Peter H. W. Biedermann; Daniel Carrillo; Louela A. Castrillo; James P. Egonyu; Diego Gallego; Khalid Haddi; Jiri Hulcr; Hervé Jactel; Hisashi Kajimura; Naoto Kamata; Nicolas Meurisse; et al. (Journal of Pest Science, 2021)
We provide an overview of both traditional and innovative control tools for management of three Xylosandrus ambrosia beetles (Coleoptera: Curculionidae: Scolytinae), invasive species with a history of damage in forests, nurseries, orchards and urban areas. Xylosandrus compactus , X. crassiusculus and X. germanus are native to Asia, and currently established in several countries around the globe. Adult females bore galleries into the plant xylem inoculating mutualistic ambrosia fungi that serve as food source for the developing progeny. Tunneling activity results in chewed wood extrusion from entry holes, sap outflow, foliage wilting followed by canopy dieback, and branch and trunk necrosis. Maintaining plant health by reducing physiological stress is the first recommendation for long-term control. Baited traps, ethanol-treated bolts, trap logs and trap trees of selected species can be used to monitor Xylosandrus species. Conventional pest control methods are mostly ineffective against Xylosandrus beetles because of the pests’ broad host range and rapid spread. Due to challenges with conventional control, more innovative control approaches are being tested, such as the optimization of the push–pull strategy based on specific attractant and repellent combinations, or the use of insecticide-treated netting. Biological control based on the release of entomopathogenic and mycoparasitic fungi, as well as the use of antagonistic bacteria, has yielded promising results. However, these technologies still require validation in real field conditions. Overall, we suggest that management efforts should primarily focus on reducing plant stress and potentially be combined with a multi-faceted approach for controlling Xylosandrus damage.

SNAPSHOT USA 2019: a coordinated national camera trap survey of the United States - Michael V. Cove; Roland Kays; Helen Bontrager; Claire Bresnan; Monica Lasky; Taylor Frerichs; Renee Klann; Thomas E. Lee; Seth C. Crockett; Anthony P. Crupi; Katherine C. B. Weiss; Helen Rowe; et al. (Ecology, 2021)
With the accelerating pace of global change, it is imperative that we obtain rapid inventories of the status and distribution of wildlife for ecological inferences and conservation planning. To address this challenge, we launched the SNAPSHOT USA project, a collaborative survey of terrestrial wildlife populations using camera traps across the United States. For our first annual survey, we compiled data across all 50 states during a 14‐week period (17 August–24 November of 2019). We sampled wildlife at 1,509 camera trap sites from 110 camera trap arrays covering 12 different ecoregions across four development zones. This effort resulted in 166,036 unique detections of 83 species of mammals and 17 species of birds. All images were processed through the Smithsonian’s eMammal camera trap data repository and included an expert review phase to ensure taxonomic accuracy of data, resulting in each picture being reviewed at least twice. The results represent a timely and standardized camera trap survey of the United States. All of the 2019 survey data are made available herein. We are currently repeating surveys in fall 2020, opening up the opportunity to other institutions and cooperators to expand coverage of all the urban–wild gradients and ecophysiographic regions of the country. Future data will be available as the database is updated at eMammal.si.edu/snapshot‐usa, as will future data paper submissions. These data will be useful for local and macroecological research including the examination of community assembly, effects of environmental and anthropogenic landscape variables, effects of fragmentation and extinction debt dynamics, as well as species‐specific population dynamics and conservation action plans. There are no copyright restrictions; please cite this paper when using the data for publication.

First record of Bonnemaisonia hamifera (Bonnemaisoniales, Rhodophyta) in the South Pacific, from the South Island of New Zealand - David J. Garbary; Roberta D’Archino; Brendan Flack; Christopher D. Hepburn; Wendy A. Nelson; Daniel Pritchard; Judy. E. Sutherland (New Zealand Journal of Marine and Freshwater Research, 2020)
The tetrasporophytic ‘ Trailliella ’ stage of the red algal genus Bonnemaisonia is reported for the first time from the Southern Hemisphere. Here we describe a bloom of the tetrasporophyte of B. hamifera from the mouth of the Waikouaiti River, Karitāne, South Island, where it occurred as thousands of free‐floating tufts up to 1 cm wide in shallow water, accumulated in windrows on sand banks and beaches, and in the water column at depths of 10–12 m on the adjacent open coast. Gametophytic stages have not yet been found in New Zealand. The material collected to date is strictly vegetative, and reproduction occurs via fragmentation. The identity of the New Zealand samples as B. hamifera was confirmed by both morphology and rbc L sequencing. The abundance and floating dispersal of B. hamifera suggests that it is invasive and will become widely distributed in New Zealand.

Effectiveness of Panama as an intercontinental land bridge for large mammals - Ninon F. V. Meyer; Ricardo Moreno; Christopher Sutherland; J. Antonio de la Torre; Helen J. Esser; Christopher A. Jordan; Melva Olmos; Josué Ortega; Rafael Reyna‐Hurtado; Samuel Valdes; Patrick A. Jansen (Conservation Biology, 2020)
Habitat fragmentation is a primary driver of wildlife loss, and establishment of biological corridors is a common strategy to mitigate this problem. A flagship example is the Mesoamerican Biological Corridor (MBC), which aims to connect protected forest areas between Mexico and Panama to allow dispersal and gene flow of forest organisms. Because forests across Central America have continued to degrade, the functioning of the MBC has been questioned, but reliable estimates of species occurrence were unavailable. Large mammals are suitable indicators of forest functioning, so we assessed their conservation status across the Isthmus of Panama, the narrowest section of the MBC. We used large‐scale camera‐trap surveys and hierarchical multispecies occupancy models in a Bayesian framework to estimate the occupancy of 9 medium to large mammals and developed an occupancy‐weighted connectivity metric to evaluate species‐specific functional connectivity. White‐lipped peccary ( Tayassu pecari ), jaguar ( Panthera onca ), giant anteater ( Myrmecophaga tridactyla ), white‐tailed deer ( Odocoileus virginianus ), and tapir ( Tapirus bairdii ) had low expected occupancy along the MBC in Panama. Puma ( Puma concolor ), red brocket deer ( Mazama temama ), ocelot ( Leopardus pardalis ), and collared peccary ( Pecari tajacu ), which are more adaptable, had higher occupancy, even in areas with low forest cover near infrastructure. However, the majority of species were subject to ≥1 gap that was larger than their known dispersal distances, suggesting poor connectivity along the MBC in Panama. Based on our results, forests in Darien, Donoso–Santa Fe, and La Amistad International Park are critical for survival of large terrestrial mammals in Panama and 2 areas need restoration.

Extracellular superoxide production by key microbes in the global ocean - Kevin M. Sutherland; Allison Coe; Rebecca J. Gast; Sydney Plummer; Christopher P. Suffridge; Julia M. Diaz; Jeff S. Bowman; Scott D. Wankel; Colleen M. Hansel (Limnology and Oceanography, 2019)
Bacteria and eukaryotes produce the reactive oxygen species superoxide both within and outside the cell. Although superoxide is typically associated with the detrimental and sometimes fatal effects of oxidative stress, it has also been shown to be involved in a range of essential biochemical processes, including cell signaling, growth, differentiation, and defense. Light‐independent extracellular superoxide production has been shown to be widespread among many marine heterotrophs and phytoplankton, but the extent to which this trait is relevant to marine microbial physiology and ecology throughout the global ocean is unknown. Here, we investigate the dark extracellular superoxide production of five groups of organisms that are geographically widespread and represent some of the most abundant organisms in the global ocean. These include Prochlorococcus , Synechococcus , Pelagibacter , Phaeocystis , and Geminigera . Cell‐normalized net extracellular superoxide production rates ranged seven orders of magnitude, from undetectable to 14,830 amol cell −1 h −1 , with the cyanobacterium Prochlorococcus being the lowest producer and the cryptophyte Geminigera being the most prolific producer. Extracellular superoxide production exhibited a strong inverse relationship with cell number, pointing to a potential role in cell signaling. We demonstrate that rapid, cell‐number–dependent changes in the net superoxide production rate by Synechococcus and Pelagibacter arose primarily from changes in gross production of extracellular superoxide, not decay. These results expand the relevance of dark extracellular superoxide production to key marine microbes of the global ocean, suggesting that superoxide production in marine waters is regulated by a diverse suite of marine organisms in both dark and sunlit waters.

Reserve design to optimize functional connectivity and animal density - Amrita Gupta; Bistra Dilkina; Dana J. Morin; Angela K. Fuller; J. Andrew Royle; Christopher Sutherland; Carla P. Gomes (Conservation Biology, 2019)
Ecological distance‐based spatial capture–recapture models (SCR) are a promising approach for simultaneously estimating animal density and connectivity, both of which affect spatial population processes and ultimately species persistence. We explored how SCR models can be integrated into reserve‐design frameworks that explicitly acknowledge both the spatial distribution of individuals and their space use resulting from landscape structure. We formulated the design of wildlife reserves as a budget‐constrained optimization problem and conducted a simulation to explore 3 different SCR‐informed optimization objectives that prioritized different conservation goals by maximizing the number of protected individuals, reserve connectivity, and density‐weighted connectivity. We also studied the effect on our 3 objectives of enforcing that the space‐use requirements of individuals be met by the reserve for individuals to be considered conserved (referred to as home‐range constraints). Maximizing local population density resulted in fragmented reserves that would likely not aid long‐term population persistence, and maximizing the connectivity objective yielded reserves that protected the fewest individuals. However, maximizing density‐weighted connectivity or preemptively imposing home‐range constraints on reserve design yielded reserves of largely spatially compact sets of parcels covering high‐density areas in the landscape with high functional connectivity between them. Our results quantify the extent to which reserve design is constrained by individual home‐range requirements and highlight that accounting for individual space use in the objective and constraints can help in the design of reserves that balance abundance and connectivity in a biologically relevant manner.

Initiating Climate Adaptation in a Western Larch Forest - Justin S Crotteau; Elaine Kennedy Sutherland; Theresa B Jain; David K Wright; Melissa M Jenkins; Christopher R Keyes; Linda M Nagel (Forest Science, 2019)

Characterisation of the NRF2 transcriptional network and its response to chemical insult in primary human hepatocytes: implications for prediction of drug-induced liver injury - Ian M. Copple; Wouter den Hollander; Giulia Callegaro; Fiona E. Mutter; James L. Maggs; Amy L. Schofield; Lucille Rainbow; Yongxiang Fang; Jeffrey J. Sutherland; Ewa C. Ellis; Magnus Ingelman-Sundberg; Stephen W. Fenwick; et al. (Archives of Toxicology, 2019)

Future Challenges in Southern Ocean Ecology Research - José C. Xavier; Angelika Brandt; Yan Ropert-Coudert; Renuka Badhe; Julian Gutt; Charlotte Havermans; Christopher Jones; Erli S. Costa; Karin Lochte; Irene R. Schloss; Mahlon C. Kennicutt; William J. Sutherland (Frontiers in Marine Science, 2016)

The role of regional climate projections in managing complex socio-ecological systems - Joseph David Daron; Kate Sutherland; Christopher Jack; Bruce C. Hewitson (Regional Environmental Change, 2015)

Preclinical strategies to define predictive biomarkers for therapeutically relevant cancer subtypes - Marina Pajic; Christopher J. Scarlett; David K. Chang; Robert L. Sutherland; Andrew V. Biankin (Human Genetics, 2011)

A novel locus for Meckel-Gruber syndrome, MKS3 , maps to chromosome 8q24 - Neil Morgan; Paul Gissen; Saghira Sharif; Laura Baumber; Joan Sutherland; Deirdre Kelly; Kingi Aminu; Christopher Bennett; Geoffrey Woods; Robert Mueller; Richard Trembath; Eamonn Maher; et al. (Human Genetics, 2002)