Spectral colour calibration improves flowering phenology detection in phenocam imagery in an evergreen woodland - Wesley Cooper; Jason Beringer; Caitlin E. Moore (Agricultural and Forest Meteorology, 2026)

An experimental approach to assess the combined effects of multiple stressors on a large vertebrate species - Enrico Pirotta; Catriona M. Harris; Lori H. Schwacke; Len Thomas; Jason B. Allen; Aaron A. Barleycorn; Marco Casoli; Jonathan Crossman; Laura Aichinger Dias; Laura Engleby; Erin LaBrecque; Jenny A. Litz; et al. (Conservation Biology, 2026)
The design of experiments to investigate the combined effects of multiple stressors requires exposing target organisms to multiple combinations of stressor doses. Concurrent manipulation of stressors is often infeasible with wildlife, but long‐lasting health effects allow individual health to be used as an integrator of prior stressor exposure. The population of bottlenose dolphins in Barataria Bay, Louisiana, experienced long‐lasting health effects after exposure to oil from the Deepwater Horizon spill. We investigated whether compromised health status affects dolphins’ ability to respond to other stressors, specifically vessel traffic, potentially leading to increased collision risk. We used this case study to develop a hypothesis‐driven experimental approach to assess the combined effects of multiple stressors in a large, long‐lived vertebrate species. We conducted controlled vessel approaches to test whether the health status of targeted dolphins affected their behavioral responses. Our results highlighted some effects of health, suggesting that oil spills may exacerbate the effects of other stressors in coastal populations. For example, lung disease was associated with a delayed dive response, which could affect the ability to vertically avoid vessels and lead to increased collision risk. However, health effects on response probability were overall smaller than anticipated, and other contextual variables (e.g., sex, age, calf presence, prior experience, and exposure context) contributed to response variability. Our work demonstrated the value of formalizing stressor interactions as multidimensional dose–response functions and showed the feasibility of an experimental, multiple‐stressor study in a wild system in which individual health status can be used as an integrator of prior stressor exposure. This approach has broad implications for other species that are difficult to handle experimentally. The quantification and management of the cumulative risk from multiple stressors on wildlife will require a combination of empirical and mechanistic approaches to inform long‐term, population consequences.

Interpretable deep learning reveals spatiotemporal MRI features of brain aging that align with neurodegeneration - Nikhil N. Chaudhari; Owen M. Vega; Phoebe Imms; Jaron M. Kawamura; Nahian F. Chowdhury; Tamara Jafar; Andrei Irimia; Michael Weiner; Paul Aisen; Ronald Petersen; Clifford R. Jack; William Jagust; et al. (GeroScience, 2026)
Cortical thinning and atrophy are hallmarks of brain aging that have been characterized using magnetic resonance imaging (MRI). Brain aging involves many neuroanatomic features whose effects on brain structure remain unexplored. To address this challenge, we trained interpretable deep neural networks (DNNs) to estimate brain age (BA) from T 1 -weighted ( T 1 w) MRI. By identifying MRI features unapparent to humans, DNNs can find aging-related structural alterations above and beyond cortical thickness and atrophy. Using a novel approach to DNN interpretability, we mapped brain aging progression in 25,539 cognitively normal UK Biobank adults aged 45–83 years. Cortical aging is found to involve anatomic features becoming prominent during the 50s within frontolateral, mesolimbic, cuneal, and occipitotemporal regions. From these foci, aging-related features propagate to adjacent areas at rates peaking in the 60s. Cortical thinning and atrophy do not trend closely with neurodegeneration, but important DNN-identifiable anatomic features have spatiotemporal dynamics that match those of amyloid or tau. Our results challenge the assumption that MRI cannot map anatomic features trending with neurodegeneration. Interpretable DNNs can empower MRI to quantify anatomic aging as a process of spatial feature expansion from focal regions into nearby structures in the sequence of neurodegenerative pathology. Traditional morphometrics explain only ∼1% of variance in DNN-identifiable features, which clarifies why the former are insensitive to anatomic changes involving neurodegeneration. Our results conceptualize brain aging in the context of spatial and temporal parallels between anatomic senescence and neuropathology. These findings may help to map cognitively normal adults’ neurodegenerative anatomy even without PET measurements. Graphical Abstract

Success of restoration strategies in preventing extirpation of 2 critically endangered coral species - Erinn M. Muller; Mark C. Ladd; Richard Karp; Phanor H. Montoya‐Maya; Ilsa B. Kuffner; Andrew C. Baker; Erich Bartels; Amanda Bourque; Abigail S. Clark; Nikkie Cox; Martine D'Alessandro; Ben Daughtry; et al. (Conservation Biology, 2026)
An unprecedented marine heatwave in 2023 caused widespread coral bleaching and mortality throughout the Caribbean. In the Florida Keys (USA), 2 foundation species, elkhorn coral ( Acropora palmata ) and staghorn coral ( Acropora cervicornis ), were severely affected. These species have been the primary focus of reef restoration in Florida for decades. Substantial losses of these species occurred in outplanted populations, in ocean‐based nurseries, and among remnant wild colonies, leading to uncertainty over their future in the Florida Keys, given recent observed trends in climate conditions. However, the past 2 decades of restoration activity created a community of experts, a network of ocean‐based and land‐based coral‐rearing infrastructure, and 2 independent land‐based coral gene banks that prevented regional extirpation and preserved much of the genetic richness of these critically endangered coral species. Without the past decades of effort and the emergency response associated with the 2023 bleaching event, Florida acroporids would largely have been lost. This outcome afforded by the restoration network in Florida demonstrates the value of proactively establishing resources prior to major disturbances. We identified several critical strategies that, in the context of existing climate change, are preventing the extirpation of coral species in Florida, including extending collaborative restoration efforts to solidify a network of trained experts; establishing trust‐focused relationships among management agencies and restoration groups; testing direct interventions to reduce light and temperature stress early during thermal anomalies; developing redundant ocean‐based and land‐based nurseries; and establishing living coral gene banks prior to major threats to prevent the extirpation of coral species.

Sex and APOE genotype specific brain regional vulnerability to Alzheimer's Disease - Qi Zeng; Minghui Wang; Erming Wang; Xianxiao Zhou; Peng Xu; Vahram Haroutunian; Dongming Cai; Bin Zhang; Michael Weiner; Paul Aisen; Ronald Petersen; Clifford R. Jack; et al. (GeroScience, 2026)
Alzheimer’s disease (AD) disproportionately affects women and carriers of the apolipoprotein E ε4 allele (APOE4), yet little is known about how sex and APOE interact to influence white matter (WM) integrity during disease progression. We integrated diffusion MRI and matched blood transcriptomic data to investigate these interactions and their underlying biological mechanisms. WM microstructure was quantified using diffusion tensor imaging (DTI) and neurite orientation dispersion and density imaging (NODDI), and regional vulnerability was assessed with a composite vulnerability score (CVS) derived from associations between diffusion features and AD severity across clinical traits in each of the four sex-APOE groups (female or male, with or without APOE4). Brain parcellation with the Eve atlas revealed regions consistently affected across sex-APOE groups (e.g., parahippocampal and superior temporal gyri) and regions specific to individual groups (e.g., the cingulum in females with APOE4 and the middle frontal gyrus in males without APOE4). Gene co-expression network analysis of the matched blood expression data identified gene subnetworks linked to group-specific regional vulnerability, including a muscle tissue morphogenesis module regulated by NEURL1B and HIST1H2BN associated with middle frontal gyrus vulnerability. These findings demonstrate that sex and APOE genotype jointly shape region-specific WM vulnerability and its molecular signatures in AD. Understanding these interactions provides novel mechanistic insights and may inform precision approaches to drug development, biomarker discovery, and clinical trial design for AD.

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)

Exploring Marine Mammal Cognition as a Conservation Tool - Gordon B. Bauer; Peter F. Cook; Heidi E. Harley; Jason Bruck; Mel Cosentino; Charles J. Deutsch; Nicola Erdsack; Wendi Fellner; Tabitha Gunnars; Heather Manitzas Hill; Sonia V. Kumar; Malin K. Lilley; et al. (Marine Mammal Science, 2026)
Cognition is an animal's real‐time adaptation system for responding to change. Rapid environmental change, often anthropogenic, is expanding the range and severity of challenges confronting wild animals. Effective conservation requires a multifaceted approach that includes animals' capacities. Large‐brained, long‐lived animals such as marine mammals often have extensive capability to adaptively modify their behavior due to their cognition, which comprises the mechanisms of information acquisition, processing, and flexible action. Consequently, current behavior need not be a final predictor of future behavior for these animals. This flexibility provides an underutilized and under examined point of leverage for humans interested in improving life outcomes for wild animals. In this team‐written, interdisciplinary paper, we argue that application of cognitive approaches may facilitate many conservation efforts directed toward marine mammals. Starting with a workshop on this topic at the 24th Biennial Conference on the Biology of Marine Mammals, scientists representing a wide range of disciplinary expertise addressed eight different conservation concerns for six marine mammal species and provided potential cognitive explanations of and interventions aimed at related behavior. Our treatment highlights the value of integrated laboratory and field research, and the importance of tight lines of communication between scientists and conservation managers.

Optimizing automated photo identification for population assessments - Philip T. Patton; Krishna Pacifici; Robin W. Baird; Erin M. Oleson; Jason B. Allen; Erin Ashe; Aline Athayde; Charla J. Basran; Elsa Cabrera; John Calambokidis; Júlio Cardoso; Emma L. Carroll; et al. (Conservation Biology, 2025)
Several legal acts mandate that management agencies regularly assess biological populations. For species with distinct markings, these assessments can be conducted noninvasively via capture‐recapture and photographic identification (photo‐ID), which involves processing considerable quantities of photographic data. To ease this burden, agencies increasingly rely on automated identification (ID) algorithms. Identification algorithms present agencies with an opportunity—reducing the cost of population assessments—and a challenge—propagating misidentifications into abundance estimates at a large scale. We explored several strategies for generating capture histories with an ID algorithm, evaluating trade‐offs between labor costs and estimation error in a hypothetical population assessment. To that end, we conducted a simulation study informed by 39 photo‐ID datasets representing 24 cetacean species. We fed the results into a custom optimization tool to discern the optimal strategy for each dataset. Our strategies included choosing between truly and partially automated photo‐ID and, in the case of the latter, choosing the number of suggested matches to inspect. True automation was optimal for datasets for which the algorithm identified individuals well. As identification performance declined, the optimization recommended that users inspect more suggested matches from the ID algorithm, particularly for small datasets. False negatives (i.e., individual was resighted but erroneously marked as a first capture) strongly predicted estimation error. A 2% increase in the false negative rate translated to a 5% increase in the relative bias in abundance estimates. Our framework can be used to estimate expected error of the abundance estimate, project labor effort, and find the optimal strategy for a dataset and algorithm. We recommend estimating a strategy's false negative rate before implementing the strategy in a population assessment. Our framework provides organizations with insights into the conservation benefits and consequences of automation as conservation enters a new era of artificial intelligence for population assessments.

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.

Predicting the progression of MCI and Alzheimer’s disease on structural brain integrity and other features with machine learning - Marthe Mieling; Mushfa Yousuf; Nico Bunzeck; Michael Weiner; Paul Aisen; Ronald Petersen; Clifford R. Jack; William Jagust; Susan Landau; Monica Rivera-Mindt; Leslie M. Shaw; Edward B. Lee; et al. (GeroScience, 2025)
Machine learning (ML) on structural MRI data shows high potential for classifying Alzheimer’s disease (AD) progression, but the specific contribution of brain regions, demographics, and proteinopathy remains unclear. Using Alzheimer’s Disease Neuroimaging Initiative (ADNI) data, we applied an extreme gradient-boosting algorithm and SHAP (SHapley Additive exPlanations) values to classify cognitively normal (CN) older adults, those with mild cognitive impairment (MCI) and AD dementia patients. Features included structural MRI, CSF status, demographics, and genetic data. Analyses comprised one cross-sectional multi-class classification (CN vs. MCI vs. AD dementia, n = 568) and two longitudinal binary-class classifications (CN-to-MCI converters vs. CN stable, n = 92; MCI-to-AD converters vs. MCI stable, n = 378). All classifications achieved 70–77% accuracy and 61–83% precision. Key features were CSF status, hippocampal volume, entorhinal thickness, and amygdala volume, with a clear dissociation: hippocampal properties contributed to the conversion to MCI, while the entorhinal cortex characterized the conversion to AD dementia. The findings highlight explainable, trajectory-specific insights into AD progression.

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)

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.

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)

Expanded Combined Loading Injury Criterion for the Human Lumbar Spine Under Dynamic Compression - Maria Ortiz-Paparoni; Joost Op ‘t Eynde; Christopher Eckersley; Concetta Morino; Mitchell Abrams; Derek Pang; Jason Kait; Frank Pintar; Narayan Yoganandan; Jason Moore; David Barnes; Kathryn Loftis; et al. (Annals of Biomedical Engineering, 2024)

The Toxicology Investigators Consortium 2023 Annual Report - Adrienne Hughes; Alexandra Amaducci; Sharan L. Campleman; Shao Li; Mari Costantini; Meghan B. Spyres; Hannah Spungen; Jessica Kent; Alyssa Falise; Rachel Culbreth; Paul M. Wax; Jeffery Brent; et al. (Journal of Medical Toxicology, 2024)

A warming western boundary current increases the prevalence of commercially disruptive parasites in broadbill swordfish - Jessica A. Bolin; Karen Evans; David S. Schoeman; Claire M. Spillman; Thomas S. Moore; Jason R. Hartog; Scott F. Cummins; Kylie L. Scales (Fisheries Oceanography, 2024)
Meat quality is of paramount importance in the fisheries and aquaculture industries, but the quality of seafood can be affected by environmental variability and change, creating uncertainties in the delivery of consistent, high‐end product. Reports from fishers operating in an Australian fishery catching broadbill swordfish ( Xiphias gladius ) suggest that anomalously warm waters are linked with myoliquefaction of muscle tissue. The condition affects the marketability of fish by turning the meat into a soft, mushy texture post‐mortem and is caused by infection by the myxozoan parasite Kudoa musculoliquefaciens . Here, we combine microscopy, molecular techniques and ecological modelling to explore potential environmental drivers of the prevalence and intensity of K. musculoliquefaciens in swordfish, as a first step in understanding how a warming ocean might exacerbate the risk of harvesting an infected swordfish and the resultant potential risk of myoliquefaction. We develop predictive dynamic risk surfaces on seasonal timescales, with results revealing both the likelihood of harvesting an infected swordfish and the intensity of parasite load increase during the Austral summer. The prevalence of the parasite further increases in the region dominated by the East Australian Current, when locally warm areas are atypically cool and when average monthly temperatures are more variable. These findings provide information useful in predicting the conditions under which the risk of harvesting infected swordfish might be intensified, enabling adaptation to climate change impacts and optimisation of decision‐making when fishing under risky conditions.

CamTrapAsia : A dataset of tropical forest vertebrate communities from 239 camera trapping studies - Calebe P. Mendes; Wido R. Albert; Zachary Amir; Marc Ancrenaz; Eric Ash; Badrul Azhar; Henry Bernard; Jedediah Brodie; Tom Bruce; Elliot Carr; Gopalasamy Reuben Clements; Glyn Davies; et al. (Ecology, 2024)
Information on tropical Asian vertebrates has traditionally been sparse, particularly when it comes to cryptic species inhabiting the dense forests of the region. Vertebrate populations are declining globally due to land‐use change and hunting, the latter frequently referred as “defaunation.” This is especially true in tropical Asia where there is extensive land‐use change and high human densities. Robust monitoring requires that large volumes of vertebrate population data be made available for use by the scientific and applied communities. Camera traps have emerged as an effective, non‐invasive, widespread, and common approach to surveying vertebrates in their natural habitats. However, camera‐derived datasets remain scattered across a wide array of sources, including published scientific literature, gray literature, and unpublished works, making it challenging for researchers to harness the full potential of cameras for ecology, conservation, and management. In response, we collated and standardized observations from 239 camera trap studies conducted in tropical Asia. There were 278,260 independent records of 371 distinct species, comprising 232 mammals, 132 birds, and seven reptiles. The total trapping effort accumulated in this data paper consisted of 876,606 trap nights, distributed among Indonesia, Singapore, Malaysia, Bhutan, Thailand, Myanmar, Cambodia, Laos, Vietnam, Nepal, and far eastern India. The relatively standardized deployment methods in the region provide a consistent, reliable, and rich count data set relative to other large‐scale pressence‐only data sets, such as the Global Biodiversity Information Facility (GBIF) or citizen science repositories (e.g., iNaturalist), and is thus most similar to eBird. To facilitate the use of these data, we also provide mammalian species trait information and 13 environmental covariates calculated at three spatial scales around the camera survey centroids (within 10‐, 20‐, and 30‐km buffers). We will update the dataset to include broader coverage of temperate Asia and add newer surveys and covariates as they become available. This dataset unlocks immense opportunities for single‐species ecological or conservation studies as well as applied ecology, community ecology, and macroecology investigations. The data are fully available to the public for utilization and research. Please cite this data paper when utilizing the data.

Deep diving by offshore bottlenose dolphins ( Tursiops spp.) - Andreas Fahlman; Reny B. Tyson Moore; Rae Stone; Jay Sweeney; Robyn Faulkner Trainor; Aaron A. Barleycorn; Katherine McHugh; Jason B. Allen; Randall S. Wells (Marine Mammal Science, 2023)
We used satellite‐linked tags to evaluate dive behavior in offshore bottlenose dolphins ( Tursiops spp.) near the island of Bermuda. The data provide evidence that bottlenose dolphins commonly perform both long (>272 s) and deep (>199 m) dives, with the deepest and longest dives being to 1,000 m and 826 s (13.8 min), respectively. The data show a relationship between dive duration and dive depth for dives longer than about 272 s. There was a diurnal pattern to dive behavior, with most dives deeper than 50 m being performed at night; deep diving began at sunset and varied throughout the night. We used the cumulative frequency of dive duration to estimate a behavioral aerobic dive limit (bADL) of around 560–666 s (9.3–11.1 min) in adult dolphins in this population. Dives exceeding the bADL spent significantly longer time in the upper‐most 50 m following a dive as compared with dives less than the bADL. We conclude that the offshore ecotype off Bermuda, unlike the shallow‐diving near‐shore bottlenose dolphin, is a deep‐diving ecotype, and may provide a useful animal model to study extreme diving behavior and adaptations.

Comprehensive voxel-wise, tract-based, and network lesion mapping reveals unique architectures of right and left visuospatial neglect - Margaret Jane Moore; Luke Hearne; Nele Demeyere; Jason B. Mattingley (Brain Structure and Function, 2023)
Visuospatial neglect is a common, post-stroke cognitive impairment which is widely considered to be a disconnection syndrome. However, the patterns of disconnectivity associated with visuospatial neglect remain unclear. Here, we had 480 acute stroke survivors [age = 72.8 (SD = 13.3), 44.3% female, 7.5 days post-stroke (SD = 11.3)] undertake routine clinical imaging and standardised visuospatial neglect testing. The data were used to conduct voxel-wise, tract-level, and network-level lesion-mapping analyses aimed at localising the neural correlates of left and right egocentric (body-centred) and allocentric (object-centred) visuospatial neglect. Only minimal anatomical homogeneity was present between the correlates of right and left egocentric neglect across all analysis types. This finding challenges previous work suggesting that right and left visuospatial neglect are anatomically homologous, and instead suggests that egocentric neglect may involve damage to a shared, but hemispherically asymmetric attention network. By contrast, egocentric and allocentric neglect was associated with disconnectivity in a distinct but overlapping set of network edges, with both deficits related to damage across the dorsal and ventral attention networks. Critically, this finding suggests that the distinction between egocentric and allocentric neglect is unlikely to reflect a simple dichotomy between dorsal versus ventral networks dysfunction, as is commonly asserted. Taken together, the current findings provide a fresh perspective on the neural circuitry involved in regulating visuospatial attention, and provide important clues to understanding the cognitive and perceptual processes involved in this common and debilitating neuropsychological syndrome.

OME-Zarr: a cloud-optimized bioimaging file format with international community support - Josh Moore; Daniela Basurto-Lozada; Sébastien Besson; John Bogovic; Jordão Bragantini; Eva M. Brown; Jean-Marie Burel; Xavier Casas Moreno; Gustavo de Medeiros; Erin E. Diel; David Gault; Satrajit S. Ghosh; et al. (Histochemistry and Cell Biology, 2023)
A growing community is constructing a next-generation file format (NGFF) for bioimaging to overcome problems of scalability and heterogeneity. Organized by the Open Microscopy Environment (OME), individuals and institutes across diverse modalities facing these problems have designed a format specification process (OME-NGFF) to address these needs. This paper brings together a wide range of those community members to describe the cloud-optimized format itself—OME-Zarr—along with tools and data resources available today to increase FAIR access and remove barriers in the scientific process. The current momentum offers an opportunity to unify a key component of the bioimaging domain—the file format that underlies so many personal, institutional, and global data management and analysis tasks.

Forecast‐ready models to support fisheries' adaptation to global variability and change - Kylie L. Scales; Thomas S. Moore; Bernadette Sloyan; Claire M. Spillman; J. Paige Eveson; Toby A. Patterson; Ashley J. Williams; Alistair J. Hobday; Jason R. Hartog (Fisheries Oceanography, 2023)
Ocean and climate drivers affect the distribution and abundance of marine life on a global scale. Marine ecological forecasting seeks to predict how living marine resources respond to physical variability and change, enabling proactive decision‐making to support climate adaptation. However, the skill of ecological forecasts is constrained by the skill of underlying models of both ocean state and species‐environment relationships. As a test of the skill of data‐driven forecasts for fisheries, we developed predictive models of catch‐per‐unit‐effort (CPUE) of tuna and billfish across the south‐west Pacific Ocean, using a 12‐year time series of catch data and a large ensemble climate reanalysis. Descriptors of water column structure, particularly temperature at depth and upper ocean heat content, emerged as useful predictors of CPUE across species. Enhancing forecast skill over sub‐seasonal to multi‐year timescales in any system is likely to require the inclusion of sub‐surface ocean data and explicit consideration of regional physical dynamics.

Living on the edge: thermal limitations of zebra mussels (Dreissena polymorpha) in Central Texas - Astrid N. Schwalb; David Swearingen; Josi J. Robertson; Jason L. Locklin; Josiah S. Moore; Monica McGarrity (Biological Invasions, 2023)

The rank abundance distribution of large-bodied vertebrates from Natural Trap Cave, Wyoming - Cory M. Redman; Jason R. Moore; David M. Lovelace; Julie A. Meachen (Quaternary International, 2023)

Correction: The Human Lumbar Spine During High-Rate Under Seat Loading: A Combined Metric Injury Criterion - Maria Ortiz-Paparoni; Joost Op’t Eynde; Jason Kait; Brian Bigler; Jay Shridharani; Allison Schmidt; Courtney Cox; Concetta Morino; Frank Pintar; Narayan Yoganandan; Jason Moore; JiangYue Zhang; et al. (Annals of Biomedical Engineering, 2023)

Linking changes in species composition and biomass in a globally distributed grassland experiment - Emma Ladouceur; Shane A. Blowes; Jonathan M. Chase; Adam T. Clark; Magda Garbowski; Juan Alberti; Carlos Alberto Arnillas; Jonathan D. Bakker; Isabel C. Barrio; Siddharth Bharath; Elizabeth T. Borer; Lars A. Brudvig; et al. (Ecology Letters, 2022)
Global change drivers, such as anthropogenic nutrient inputs, are increasing globally. Nutrient deposition simultaneously alters plant biodiversity, species composition and ecosystem processes like aboveground biomass production. These changes are underpinned by species extinction, colonisation and shifting relative abundance. Here, we use the Price equation to quantify and link the contributions of species that are lost, gained or that persist to change in aboveground biomass in 59 experimental grassland sites. Under ambient (control) conditions, compositional and biomass turnover was high, and losses (i.e. local extinctions) were balanced by gains (i.e. colonisation). Under fertilisation, the decline in species richness resulted from increased species loss and decreases in species gained. Biomass increase under fertilisation resulted mostly from species that persist and to a lesser extent from species gained. Drivers of ecological change can interact relatively independently with diversity, composition and ecosystem processes and functions such as aboveground biomass due to the individual contributions of species lost, gained or persisting.

SNAPSHOT USA 2020: A second coordinated national camera trap survey of the United States during the COVID ‐19 pandemic - Roland Kays; Michael V. Cove; Jose Diaz; Kimberly Todd; Claire Bresnan; Matt Snider; Thomas E. Lee; Jonathan G. Jasper; Brianna Douglas; Anthony P. Crupi; Katherine C. B. Weiss; Helen Rowe; et al. (Ecology, 2022)
Managing wildlife populations in the face of global change requires regular data on the abundance and distribution of wild animals, but acquiring these over appropriate spatial scales in a sustainable way has proven challenging. Here we present the data from Snapshot USA 2020, a second annual national mammal survey of the USA. This project involved 152 scientists setting camera traps in a standardized protocol at 1485 locations across 103 arrays in 43 states for a total of 52,710 trap‐nights of survey effort. Most (58) of these arrays were also sampled during the same months (September and October) in 2019, providing a direct comparison of animal populations in 2 years that includes data from both during and before the COVID‐19 pandemic. All data were managed by the eMammal system, with all species identifications checked by at least two reviewers. In total, we recorded 117,415 detections of 78 species of wild mammals, 9236 detections of at least 43 species of birds, 15,851 detections of six domestic animals and 23,825 detections of humans or their vehicles. Spatial differences across arrays explained more variation in the relative abundance than temporal variation across years for all 38 species modeled, although there are examples of significant site‐level differences among years for many species. Temporal results show how species allocate their time and can be used to study species interactions, including between humans and wildlife. These data provide a snapshot of the mammal community of the USA for 2020 and will be useful for exploring the drivers of spatial and temporal changes in relative abundance and distribution, and the impacts of species interactions on daily activity patterns. There are no copyright restrictions, and please cite this paper when using these data, or a subset of these data, for publication.

Corrigendum: Rise of the machines: Best practices and experimental evaluation of computer-assisted dorsal fin image matching systems for bottlenose dolphins - Reny B. Tyson Moore; Kim W. Urian; Jason B. Allen; Carolyn Cush; Jason R. Parham; Drew Blount; Jason Holmberg; Jamie W. Thompson; Randall S. Wells (Frontiers in Marine Science, 2022)

Predictive value of common genetic variants in idiopathic pulmonary fibrosis survival - Patrícia Caetano Mota; Miguel Luz Soares; Carlos Daniel Vasconcelos; António Carlos Ferreira; Bruno A. Lima; Elisabetta Manduchi; Jason H. Moore; Natália Melo; Hélder Novais-Bastos; José Miguel Pereira; Susana Guimarães; Conceição Souto Moura; et al. (Journal of Molecular Medicine, 2022)

The promise of automated machine learning for the genetic analysis of complex traits - Elisabetta Manduchi; Joseph D. Romano; Jason H. Moore (Human Genetics, 2022)
The genetic analysis of complex traits has been dominated by parametric statistical methods due to their theoretical properties, ease of use, computational efficiency, and intuitive interpretation. However, there are likely to be patterns arising from complex genetic architectures which are more easily detected and modeled using machine learning methods. Unfortunately, selecting the right machine learning algorithm and tuning its hyperparameters can be daunting for experts and non-experts alike. The goal of automated machine learning (AutoML) is to let a computer algorithm identify the right algorithms and hyperparameters thus taking the guesswork out of the optimization process. We review the promises and challenges of AutoML for the genetic analysis of complex traits and give an overview of several approaches and some example applications to omics data. It is our hope that this review will motivate studies to develop and evaluate novel AutoML methods and software in the genetics and genomics space. The promise of AutoML is to enable anyone, regardless of training or expertise, to apply machine learning as part of their genetic analysis strategy.

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)

Bridge to the future: Important lessons from 20 years of ecosystem observations made by the OzFlux network - Jason Beringer; Caitlin E. Moore; Jamie Cleverly; David I. Campbell; Helen Cleugh; Martin G. De Kauwe; Miko U. F. Kirschbaum; Anne Griebel; Sam Grover; Alfredo Huete; Lindsay B. Hutley; Johannes Laubach; et al. (Global Change Biology, 2022)
In 2020, the Australian and New Zealand flux research and monitoring network, OzFlux, celebrated its 20 th anniversary by reflecting on the lessons learned through two decades of ecosystem studies on global change biology. OzFlux is a network not only for ecosystem researchers, but also for those ‘next users’ of the knowledge, information and data that such networks provide. Here, we focus on eight lessons across topics of climate change and variability, disturbance and resilience, drought and heat stress and synergies with remote sensing and modelling. In distilling the key lessons learned, we also identify where further research is needed to fill knowledge gaps and improve the utility and relevance of the outputs from OzFlux. Extreme climate variability across Australia and New Zealand (droughts and flooding rains) provides a natural laboratory for a global understanding of ecosystems in this time of accelerating climate change. As evidence of worsening global fire risk emerges, the natural ability of these ecosystems to recover from disturbances, such as fire and cyclones, provides lessons on adaptation and resilience to disturbance. Drought and heatwaves are common occurrences across large parts of the region and can tip an ecosystem's carbon budget from a net CO 2 sink to a net CO 2 source. Despite such responses to stress, ecosystems at OzFlux sites show their resilience to climate variability by rapidly pivoting back to a strong carbon sink upon the return of favourable conditions. Located in under‐represented areas, OzFlux data have the potential for reducing uncertainties in global remote sensing products, and these data provide several opportunities to develop new theories and improve our ecosystem models. The accumulated impacts of these lessons over the last 20 years highlights the value of long‐term flux observations for natural and managed systems. A future vision for OzFlux includes ongoing and newly developed synergies with ecophysiologists, ecologists, geologists, remote sensors and modellers.

Rise of the Machines: Best Practices and Experimental Evaluation of Computer-Assisted Dorsal Fin Image Matching Systems for Bottlenose Dolphins - Reny B. Tyson Moore; Kim W. Urian; Jason B. Allen; Carolyn Cush; Jason R. Parham; Drew Blount; Jason Holmberg; Jamie W. Thompson; Randall S. Wells (Frontiers in Marine Science, 2022)
Photographic-identification (photo-ID) of bottlenose dolphins using individually distinctive features on the dorsal fin is a well-established and useful tool for tracking individuals; however, this method can be labor-intensive, especially when dealing with large catalogs and/or infrequently surveyed populations. Computer vision algorithms have been developed that can find a fin in an image, characterize the features of the fin, and compare the fin to a catalog of known individuals to generate a ranking of potential matches based on dorsal fin similarity. We examined if and how researchers use computer vision systems in their photo-ID process and developed an experiment to evaluate the performance of the most commonly used, recently developed, systems to date using a long-term photo-ID database of known individuals curated by the Chicago Zoological Society’s Sarasota Dolphin Research Program. Survey results obtained for the “Rise of the machines – Application of automated systems for matching dolphin dorsal fins: current status and future directions” workshop held at the 2019 World Marine Mammal Conference indicated that most researchers still rely on manual methods for comparing unknown dorsal fin images to reference catalogs of known individuals. Experimental evaluation of the finFindR R application, as well as the CurvRank, CurvRank v2, and finFindR implementations in Flukebook suggest that high match rates can be achieved with these systems, with the highest match rates found when only good to excellent quality images of fins with average to high distinctiveness are included in the matching process: for the finFindR R application and the CurvRank and CurvRank v2 algorithms within Flukebook more than 98.92% of correct matches were in the top 50-ranked positions, and more than 91.94% of correct matches were returned in the first ranked position. Our results offer the first comprehensive examination into the performance and accuracy of computer vision algorithms designed to assist with the photo-ID process of bottlenose dolphins and can be used to build trust by researchers hesitant to use these systems. Based on our findings and discussions from the “Rise of the Machines” workshop we provide recommendations for best practices for using computer vision systems for dorsal fin photo-ID.

Nutrient identity modifies the destabilising effects of eutrophication in grasslands - Oliver Carroll; Evan Batzer; Siddharth Bharath; Elizabeth T. Borer; Sofía Campana; Ellen Esch; Yann Hautier; Timothy Ohlert; Eric W. Seabloom; Peter B. Adler; Jonathan D. Bakker; Lori Biederman; et al. (Ecology Letters, 2022)
Nutrient enrichment can simultaneously increase and destabilise plant biomass production, with co‐limitation by multiple nutrients potentially intensifying these effects. Here, we test how factorial additions of nitrogen (N), phosphorus (P) and potassium with essential nutrients (K+) affect the stability (mean/standard deviation) of aboveground biomass in 34 grasslands over 7 years. Destabilisation with fertilisation was prevalent but was driven by single nutrients, not synergistic nutrient interactions. On average, N‐based treatments increased mean biomass production by 21–51% but increased its standard deviation by 40–68% and so consistently reduced stability. Adding P increased interannual variability and reduced stability without altering mean biomass, while K+ had no general effects. Declines in stability were largest in the most nutrient‐limited grasslands, or where nutrients reduced species richness or intensified species synchrony. We show that nutrients can differentially impact the stability of biomass production, with N and P in particular disproportionately increasing its interannual variability.

Runaway evolution from male‐male competition - Allen J. Moore; Joel W. McGlothlin; Jason B. Wolf (Ecology Letters, 2022)
Wondrously elaborate weapons and displays that appear to be counter to ecological optima are widespread features of male contests for mates across the animal kingdom. To understand how such diverse traits evolve, here we develop a quantitative genetic model of sexual selection for a male signaling trait that mediates aggression in male‐male contests and show that an honest indicator of aggression can generate selection on itself by altering the social environment. This can cause selection to accelerate as the trait is elaborated, leading to runaway evolution. Thus, an evolving source of selection provided by the social environment is the fundamental unifying feature of runaway sexual selection driven by either male‐male competition or female mate choice. However, a key difference is that runaway driven by male‐male competition requires signal honesty. Our model identifies simple conditions that provide clear, testable predictions for empirical studies using standard quantitative genetic methods.

The Human Lumbar Spine During High-Rate Under Seat Loading: A Combined Metric Injury Criteria - Maria Ortiz-Paparoni; Joost Op ’t Eynde; Jason Kait; Brian Bigler; Jay Shridharani; Allison Schmidt; Courtney Cox; Concetta Morino; Frank Pintar; Narayan Yoganandan; Jason Moore; JiangYue Zhang; et al. (Annals of Biomedical Engineering, 2021)

Forest responses to last‐millennium hydroclimate variability are governed by spatial variations in ecosystem sensitivity - Christine R. Rollinson; Andria Dawson; Ann M. Raiho; John W. Williams; Michael C. Dietze; Thomas Hickler; Stephen T. Jackson; Jason McLachlan; David JP Moore; Benjamin Poulter; Tristan Quaife; Jörg Steinkamp; et al. (Ecology Letters, 2021)
Forecasts of future forest change are governed by ecosystem sensitivity to climate change, but ecosystem model projections are under‐constrained by data at multidecadal and longer timescales. Here, we quantify ecosystem sensitivity to centennial‐scale hydroclimate variability, by comparing dendroclimatic and pollen‐inferred reconstructions of drought, forest composition and biomass for the last millennium with five ecosystem model simulations. In both observations and models, spatial patterns in ecosystem responses to hydroclimate variability are strongly governed by ecosystem sensitivity rather than climate exposure. Ecosystem sensitivity was higher in models than observations and highest in simpler models. Model‐data comparisons suggest that interactions among biodiversity, demography and ecophysiology processes dampen the sensitivity of forest composition and biomass to climate variability and change. Integrating ecosystem models with observations from timescales extending beyond the instrumental record can better understand and forecast the mechanisms regulating forest sensitivity to climate variability in a complex and changing world.

American Lobster, Homarus americanus, Reproduction and Recruitment in a New England Estuary - Elizabeth M. Moore; Thomas G. Langley; Jason S. Goldstein; Winsor H. Watson (Estuaries and Coasts, 2020)

Utility of Kinetic and Kinematic Jumping and Landing Variables as Predictors of Injury Risk: A Systematic Review - Jason S. Pedley; Rhodri S. Lloyd; Paul J. Read; Isabel S. Moore; Mark De Ste Croix; Gregory D. Myer; Jon L. Oliver (Journal of Science in Sport and Exercise, 2020)
Purpose Jump-landing assessments provide a means to quantify an individual’s ability to attenuate ground reaction forces, generate lower limb explosive power and maintain joint alignment. In order to identify risk factors that can be targeted through appropriate training interventions, it is necessary to establish which (scalar) objective kinetic, kinematic, and performance measures are most associated with lower-extremity injury. Methods Online searches of MEDLINE, SCOPUS, EBSCOHost, SPORTDiscus and PubMed databases were completed for all articles published before March 2020 in accordance with PRISMA guidelines. Results 40 articles investigating nine jump-landing assessments were included in this review. The 79% of studies using drop jump ( n = 14) observed an association with future injury, while only 8% of countermovement jump studies ( n = 13) observed an association with injury risk. The 57% of studies using unilateral assessments found associations with risk of injury ( n = 14). Studies using performance measures (jump height/distance) as outcome measure were only associated with injury risk in 30% of cases. However, those using kinetic and/or kinematic analyses (knee abduction moment, knee valgus angle, knee separation distance, peak ground reaction force) found associations with injury in 89% of studies. Conclusion The landing element of jump-landing assessments appears to be superior for identifying individuals at greater risk of injury; likely due to a closer representation of the injury mechanism. Consequently, jump-landing assessments that involve attenuation of impact forces such as the drop jump appear most suited for this purpose but should involve assessment of frontal plane knee motion and ground reaction forces.

Detection of the rare Australian endemic blind cave eel (Ophisternon candidum) with environmental DNA: implications for threatened species management in subterranean environments - Nicole E. White; Michelle T. Guzik; Andrew D. Austin; Glenn I. Moore; William F. Humphreys; Jason Alexander; Michael Bunce (Hydrobiologia, 2020)

Restoration Scaling Approaches to Addressing Ecological Injury: The Habitat-Based Resource Equivalency Method - Mary Baker; Adam Domanski; Terill Hollweg; Jason Murray; Diana Lane; Kristin Skrabis; Robert Taylor; Tom Moore; Lisa DiPinto (Environmental Management, 2020)
Natural resource trustee agencies must determine how much, and what type of environmental restoration will compensate for injuries to natural resources that result from releases of hazardous substances or oil spills. To fulfill this need, trustees, and other natural resource damage assessment (NRDA) practitioners have relied on a variety of approaches, including habitat equivalency analysis (HEA) and resource equivalency analysis (REA). The purpose of this paper is to introduce the Habitat-Based Resource Equivalency Method (HaBREM), which integrates REA’s reproducible injury metrics and population modeling with HEA’s comprehensive habitat approach to restoration. HaBREM is intended to evaluate injury and restoration using organisms that use the habitat to represent ecological habitat functions. This paper seeks to expand and refine the use of organism-based metrics (biomass-based REA), providing an opportunity to integrate sublethal injuries to multiple species, as well as the potential to include error rates for injury and restoration parameters. Applied by NRDA practitioners in the appropriate context, this methodology can establish the relationship between benefits of compensatory restoration projects and injuries to plant or animal species within an affected habitat. HaBREM may be most effective where there are appropriate data supporting the linkage between habitat and species gains (particularly regionally specific habitat information), as well as species-specific monitoring data and predictions on the growth, density, productivity (i.e., rate of generation of biomass or individuals), and age distributions of indicator species.

Human Lumbar Spine Responses from Vertical Loading: Ranking of Forces Via Brier Score Metrics and Injury Risk Curves - Narayan Yoganandan; Nicholas DeVogel; Jason Moore; Frank Pintar; Anjishnu Banerjee; JiangYue Zhang (Annals of Biomedical Engineering, 2020)

Synergies in Operational Oceanography: The Intrinsic Need for Sustained Ocean Observations - Fraser Davidson; Aida Alvera-Azcárate; Alexander Barth; Gary B. Brassington; Eric P. Chassignet; Emanuela Clementi; Pierre De Mey-Frémaux; Prasanth Divakaran; Christopher Harris; Fabrice Hernandez; Patrick Hogan; Lars R. Hole; et al. (Frontiers in Marine Science, 2019)

Correction to: Are soils beneath coniferous tree stands more acidic than soils beneath deciduous tree stands? - Jason R. Burgess-Conforti; Philip A. Moore; Phillip R. Owens; David M. Miller; Amanda J. Ashworth; Phillip D. Hays; Michelle A. Evans-White; Kelsey R. Anderson (Environmental Science and Pollution Research, 2019)

Are soils beneath coniferous tree stands more acidic than soils beneath deciduous tree stands? - Jason R. Burgess-Conforti; Philip A. Moore; Phillip R. Owens; David M. Miller; Amanda J. Ashworth; Phillip D. Hays; Michelle A. Evans-White; Kelsey R. Anderson (Environmental Science and Pollution Research, 2019)

The North Atlantic Aerosol and Marine Ecosystem Study (NAAMES): Science Motive and Mission Overview - Michael J. Behrenfeld; Richard H. Moore; Chris A. Hostetler; Jason Graff; Peter Gaube; Lynn M. Russell; Gao Chen; Scott C. Doney; Stephen Giovannoni; Hongyu Liu; Christopher Proctor; Luis M. Bolaños; et al. (Frontiers in Marine Science, 2019)

Jittered echo-delay resolution in bottlenose dolphins (Tursiops truncatus) - James J. Finneran; Ryan Jones; Jason Mulsow; Dorian S. Houser; Patrick W. Moore (Journal of Comparative Physiology A, 2019)

Leaf functional trait responses to changes in water status differ among three oak (Quercus) species - Caitlyn E. Cooper; Jason G. Vogel; James P. Muir; Georgianne W. Moore (Plant Ecology, 2018)

Facility inspection using UAVs: a case study in the University of Georgia campus - Julian Moore; Harshitha Tadinada; Kevin Kirsche; Jason Perry; Fred Remen; Zion Tsz Ho Tse (International Journal of Remote Sensing, 2018)

GPU Accelerated Browser for Neuroimaging Genomics - Bob Zigon; Huang Li; Xiaohui Yao; Shiaofen Fang; Mohammad Al Hasan; Jingwen Yan; Jason H. Moore; Andrew J. Saykin; Li Shen (Neuroinformatics, 2018)

Genomes of ubiquitous marine and hypersaline Hydrogenovibrio , Thiomicrorhabdus and Thiomicrospira spp. encode a diversity of mechanisms to sustain chemolithoautotrophy in heterogeneous environments - Kathleen M. Scott; John Williams; Cody M. B. Porter; Sydney Russel; Tara L. Harmer; John H. Paul; Kirsten M. Antonen; Megan K. Bridges; Gary J. Camper; Christie K. Campla; Leila G. Casella; Eva Chase; et al. (Environmental Microbiology, 2018)
Summary Chemolithoautotrophic bacteria from the genera Hydrogenovibrio, Thiomicrorhabdus and Thiomicrospira are common, sometimes dominant, isolates from sulfidic habitats including hydrothermal vents, soda and salt lakes and marine sediments. Their genome sequences confirm their membership in a deeply branching clade of the Gammaproteobacteria . Several adaptations to heterogeneous habitats are apparent. Their genomes include large numbers of genes for sensing and responding to their environment (EAL‐ and GGDEF‐domain proteins and methyl‐accepting chemotaxis proteins) despite their small sizes (2.1–3.1 Mbp). An array of sulfur‐oxidizing complexes are encoded, likely to facilitate these organisms' use of multiple forms of reduced sulfur as electron donors. Hydrogenase genes are present in some taxa, including group 1d and 2b hydrogenases in Hydrogenovibrio marinus and H. thermophilus MA2‐6, acquired via horizontal gene transfer. In addition to high‐affinity cbb 3 cytochrome c oxidase, some also encode cytochrome bd‐ type quinol oxidase or ba 3 ‐ type cytochrome c oxidase, which could facilitate growth under different oxygen tensions, or maintain redox balance. Carboxysome operons are present in most, with genes downstream encoding transporters from four evolutionarily distinct families, which may act with the carboxysomes to form CO 2 concentrating mechanisms. These adaptations to habitat variability likely contribute to the cosmopolitan distribution of these organisms.

BioTIME: A database of biodiversity time series for the Anthropocene - Maria Dornelas; Laura H. Antão; Faye Moyes; Amanda E. Bates; Anne E. Magurran; Dušan Adam; Asem A. Akhmetzhanova; Ward Appeltans; José Manuel Arcos; Haley Arnold; Narayanan Ayyappan; Gal Badihi; et al. (Global Ecology and Biogeography, 2018)
Motivation The BioTIME database contains raw data on species identities and abundances in ecological assemblages through time. These data enable users to calculate temporal trends in biodiversity within and amongst assemblages using a broad range of metrics. BioTIME is being developed as a community‐led open‐source database of biodiversity time series. Our goal is to accelerate and facilitate quantitative analysis of temporal patterns of biodiversity in the Anthropocene. Main types of variables included The database contains 8,777,413 species abundance records, from assemblages consistently sampled for a minimum of 2 years, which need not necessarily be consecutive. In addition, the database contains metadata relating to sampling methodology and contextual information about each record. Spatial location and grain BioTIME is a global database of 547,161 unique sampling locations spanning the marine, freshwater and terrestrial realms. Grain size varies across datasets from 0.0000000158 km 2 (158 cm 2 ) to 100 km 2 (1,000,000,000,000 cm 2 ). Time period and grain BioTIME records span from 1874 to 2016. The minimal temporal grain across all datasets in BioTIME is a year. Major taxa and level of measurement BioTIME includes data from 44,440 species across the plant and animal kingdoms, ranging from plants, plankton and terrestrial invertebrates to small and large vertebrates. Software format .csv and .SQL.

Seasonal, interannual and decadal drivers of tree and grass productivity in an Australian tropical savanna - Caitlin E. Moore; Jason Beringer; Randall J. Donohue; Bradley Evans; Jean‐François Exbrayat; Lindsay B. Hutley; Nigel J. Tapper (Global Change Biology, 2018)
Tree–grass savannas are a widespread biome and are highly valued for their ecosystem services. There is a need to understand the long‐term dynamics and meteorological drivers of both tree and grass productivity separately in order to successfully manage savannas in the future. This study investigated the interannual variability ( IAV ) of tree and grass gross primary productivity ( GPP ) by combining a long‐term (15 year) eddy covariance flux record and model estimates of tree and grass GPP inferred from satellite remote sensing. On a seasonal basis, the primary drivers of tree and grass GPP were solar radiation in the wet season and soil moisture in the dry season. On an interannual basis, soil water availability had a positive effect on tree GPP and a negative effect on grass GPP . No linear trend in the tree–grass GPP ratio was observed over the 15‐year study period. However, the tree–grass GPP ratio was correlated with the modes of climate variability, namely the Southern Oscillation Index. This study has provided insight into the long‐term contributions of trees and grasses to savanna productivity, along with their respective meteorological determinants of IAV .

Leveraging epigenomics and contactomics data to investigate SNP pairs in GWAS - Elisabetta Manduchi; Scott M. Williams; Alessandra Chesi; Matthew E. Johnson; Andrew D. Wells; Struan F. A. Grant; Jason H. Moore (Human Genetics, 2018)

Emergent climate and CO 2 sensitivities of net primary productivity in ecosystem models do not agree with empirical data in temperate forests of eastern North America - Christine R. Rollinson; Yao Liu; Ann Raiho; David J. P. Moore; Jason McLachlan; Daniel A. Bishop; Alex Dye; Jaclyn H. Matthes; Amy Hessl; Thomas Hickler; Neil Pederson; Benjamin Poulter; et al. (Global Change Biology, 2017)
Ecosystem models show divergent responses of the terrestrial carbon cycle to global change over the next century. Individual model evaluation and multimodel comparisons with data have largely focused on individual processes at subannual to decadal scales. Thus far, data‐based evaluations of emergent ecosystem responses to climate and CO 2 at multidecadal and centennial timescales have been rare. We compared the sensitivity of net primary productivity ( NPP ) to temperature, precipitation, and CO 2 in ten ecosystem models with the sensitivities found in tree‐ring reconstructions of NPP and raw ring‐width series at six temperate forest sites. These model‐data comparisons were evaluated at three temporal extents to determine whether the rapid, directional changes in temperature and CO 2 in the recent past skew our observed responses to multiple drivers of change. All models tested here were more sensitive to low growing season precipitation than tree‐ring NPP and ring widths in the past 30 years, although some model precipitation responses were more consistent with tree rings when evaluated over a full century. Similarly, all models had negative or no response to warm‐growing season temperatures, while tree‐ring data showed consistently positive effects of temperature. Although precipitation responses were least consistent among models, differences among models to CO 2 drive divergence and ensemble uncertainty in relative change in NPP over the past century. Changes in forest composition within models had no effect on climate or CO 2 sensitivity. Fire in model simulations reduced model sensitivity to climate and CO 2 , but only over the course of multiple centuries. Formal evaluation of emergent model behavior at multidecadal and multicentennial timescales is essential to reconciling model projections with observed ecosystem responses to past climate change. Future evaluation should focus on improved representation of disturbance and biomass change as well as the feedbacks with moisture balance and CO 2 in individual models.

Aerosol Deposition Impacts on Land and Ocean Carbon Cycles - Natalie M. Mahowald; Rachel Scanza; Janice Brahney; Christine L. Goodale; Peter G. Hess; J. Keith Moore; Jason Neff (Current Climate Change Reports, 2017)

Identifying gene–gene interactions that are highly associated with four quantitative lipid traits across multiple cohorts - Rishika De; Shefali S. Verma; Emily Holzinger; Molly Hall; Amber Burt; David S. Carrell; David R. Crosslin; Gail P. Jarvik; Helena Kuivaniemi; Iftikhar J. Kullo; Leslie A. Lange; Matthew B. Lanktree; et al. (Human Genetics, 2017)

Phytoplankton responses to nitrogen enrichment in Pacific Northwest, USA Mountain Lakes - Jason J. Williams; Marc Beutel; Andrea Nurse; Barry Moore; Stephanie E. Hampton; Jasmine E. Saros (Hydrobiologia, 2016)

Harnessing publicly available genetic data to prioritize lipid modifying therapeutic targets for prevention of coronary heart disease based on dysglycemic risk - Vinicius Tragante; Folkert W. Asselbergs; Daniel I. Swerdlow; Tom M. Palmer; Jason H. Moore; Paul I. W. de Bakker; Brendan J. Keating; Michael V. Holmes (Human Genetics, 2016)

Publishing and sharing multi-dimensional image data with OMERO - Jean-Marie Burel; Sébastien Besson; Colin Blackburn; Mark Carroll; Richard K. Ferguson; Helen Flynn; Kenneth Gillen; Roger Leigh; Simon Li; Dominik Lindner; Melissa Linkert; William J. Moore; et al. (Mammalian Genome, 2015)

Developing Critical Loads of Nitrate and Sulfate Deposition to Watersheds of the Great Smoky Mountains National Park, USA - Qingtao Zhou; Charles T. Driscoll; Stephen E. Moore; Matt A. Kulp; James R. Renfro; John S. Schwartz; Meijun Cai; Jason A. Lynch (Water, Air, & Soil Pollution, 2015)

Fire in Australian savannas: from leaf to landscape - Jason Beringer; Lindsay B. Hutley; David Abramson; Stefan K. Arndt; Peter Briggs; Mila Bristow; Josep G. Canadell; Lucas A. Cernusak; Derek Eamus; Andrew C. Edwards; Bradley J. Evans; Benedikt Fest; et al. (Global Change Biology, 2015)
Savanna ecosystems comprise 22% of the global terrestrial surface and 25% of Australia (almost 1.9 million km 2 ) and provide significant ecosystem services through carbon and water cycles and the maintenance of biodiversity. The current structure, composition and distribution of Australian savannas have coevolved with fire, yet remain driven by the dynamic constraints of their bioclimatic niche. Fire in Australian savannas influences both the biophysical and biogeochemical processes at multiple scales from leaf to landscape. Here, we present the latest emission estimates from Australian savanna biomass burning and their contribution to global greenhouse gas budgets. We then review our understanding of the impacts of fire on ecosystem function and local surface water and heat balances, which in turn influence regional climate. We show how savanna fires are coupled to the global climate through the carbon cycle and fire regimes. We present new research that climate change is likely to alter the structure and function of savannas through shifts in moisture availability and increases in atmospheric carbon dioxide, in turn altering fire regimes with further feedbacks to climate. We explore opportunities to reduce net greenhouse gas emissions from savanna ecosystems through changes in savanna fire management.

SNP characteristics predict replication success in association studies - Ivan P. Gorlov; Jason H. Moore; Bo Peng; Jennifer L. Jin; Olga Y. Gorlova; Christopher I. Amos (Human Genetics, 2014)

Genetic analysis of quantitative phenotypes in AD and MCI: imaging, cognition and biomarkers - Li Shen; Paul M. Thompson; Steven G. Potkin; Lars Bertram; Lindsay A. Farrer; Tatiana M. Foroud; Robert C. Green; Xiaolan Hu; Matthew J. Huentelman; Sungeun Kim; John S. K. Kauwe; Qingqin Li; et al. (Brain Imaging and Behavior, 2014)

Towards improved socio-economic assessments of ocean acidification’s impacts - Nathalie Hilmi; Denis Allemand; Sam Dupont; Alain Safa; Gunnar Haraldsson; Paulo A. L. D. Nunes; Chris Moore; Caroline Hattam; Stéphanie Reynaud; Jason M. Hall-Spencer; Maoz Fine; Carol Turley; et al. (Marine Biology, 2013)

Plant pest and disease diagnosis using electronic nose and support vector machine approach - Reza Ghaffari; Jullada Laothawornkitkul; Daciana Iliescu; Evor Hines; Mark Leeson; Richard Napier; Jason P Moore; Nigel D Paul; C Nicholas Hewitt; Jane E Taylor (Journal of Plant Diseases and Protection, 2012)

SLC39A2 and FSIP1 polymorphisms as potential modifiers of arsenic-related bladder cancer - Margaret R. Karagas; Angeline S. Andrew; Heather H. Nelson; Zhongze Li; Tracy Punshon; Alan Schned; Carmen J. Marsit; J. Steven Morris; Jason H. Moore; Anna L. Tyler; Diane Gilbert-Diamond; Mary-Lou Guerinot; et al. (Human Genetics, 2012)

Ion channels and schizophrenia: a gene set-based analytic approach to GWAS data for biological hypothesis testing - Kathleen Askland; Cynthia Read; Chloe O’Connell; Jason H. Moore (Human Genetics, 2012)

Cucurbit[7]uril Disrupts Aggregate Formation Between Rhodamine B Dyes Covalently Attached to Glass Substrates - Ronald L. Halterman; Jason L. Moore; Wai Tak Yip (Journal of Fluorescence, 2011)

Genes in the insulin and insulin-like growth factor pathway and odds of metachronous colorectal neoplasia - Elizabeth C. LeRoy; Jason H. Moore; Chengcheng Hu; María Elena Martínez; Peter Lance; David Duggan; Patricia A. Thompson (Human Genetics, 2011)

A novel survival multifactor dimensionality reduction method for detecting gene–gene interactions with application to bladder cancer prognosis - Jiang Gui; Jason H. Moore; Karl T. Kelsey; Carmen J. Marsit; Margaret R. Karagas; Angeline S. Andrew (Human Genetics, 2011)

Exploiting graphics processing units for computational biology and bioinformatics - Joshua L. Payne; Nicholas A. Sinnott-Armstrong; Jason H. Moore (Interdisciplinary Sciences: Computational Life Sciences, 2010)

Evidence for indirect effects of plant diversity and composition on net nitrification - Daniel C. Laughlin; Stephen C. Hart; Jason P. Kaye; Margaret M. Moore (Plant and Soil, 2010)

A meta‐analysis of context‐dependency in plant response to inoculation with mycorrhizal fungi - Jason D. Hoeksema; V. Bala Chaudhary; Catherine A. Gehring; Nancy Collins Johnson; Justine Karst; Roger T. Koide; Anne Pringle; Catherine Zabinski; James D. Bever; John C. Moore; Gail W. T. Wilson; John N. Klironomos; et al. (Ecology Letters, 2010)
Ecology Letters (2010) 13: 394–407 Abstract Mycorrhizal fungi influence plant growth, local biodiversity and ecosystem function. Effects of the symbiosis on plants span the continuum from mutualism to parasitism. We sought to understand this variation in symbiotic function using meta‐analysis with information theory‐based model selection to assess the relative importance of factors in five categories: (1) identity of the host plant and its functional characteristics, (2) identity and type of mycorrhizal fungi (arbuscular mycorrhizal vs. ectomycorrhizal), (3) soil fertility, (4) biotic complexity of the soil and (5) experimental location (laboratory vs. field). Across most subsets of the data, host plant functional group and N‐fertilization were surprisingly much more important in predicting plant responses to mycorrhizal inoculation (‘plant response’) than other factors. Non‐N‐fixing forbs and woody plants and C 4 grasses responded more positively to mycorrhizal inoculation than plants with N‐fixing bacterial symbionts and C 3 grasses. In laboratory studies of the arbuscular mycorrhizal symbiosis, plant response was more positive when the soil community was more complex. Univariate analyses supported the hypothesis that plant response is most positive when plants are P‐limited rather than N‐limited. These results emphasize that mycorrhizal function depends on both abiotic and biotic context, and have implications for plant community theory and restoration ecology.

Bladder cancer SNP panel predicts susceptibility and survival - Angeline S. Andrew; Jiang Gui; Arthur C. Sanderson; Rebecca A. Mason; Elaine V. Morlock; Alan R. Schned; Karl T. Kelsey; Carmen J. Marsit; Jason H. Moore; Margaret R. Karagas (Human Genetics, 2009)

Intrascleral Drug Delivery to the Eye Using Hollow Microneedles - Jason Jiang; Jason S. Moore; Henry F. Edelhauser; Mark R. Prausnitz (Pharmaceutical Research, 2009)

Pathways-based analyses of whole-genome association study data in bipolar disorder reveal genes mediating ion channel activity and synaptic neurotransmission - Kathleen Askland; Cynthia Read; Jason Moore (Human Genetics, 2009)

Exploiting the proteome to improve the genome-wide genetic analysis of epistasis in common human diseases - Kristine A. Pattin; Jason H. Moore (Human Genetics, 2008)

Case Study of an Integrated Framework for Quantifying Agroecosystem Health - Krishna Prasad Vadrevu; John Cardina; Fred Hitzhusen; Isaac Bayoh; Richard Moore; Jason Parker; Ben Stinner; Deb Stinner; Casey Hoy (Ecosystems, 2008)

The effects of polymorphisms in genes from the renin–angiotensin, bradykinin, and fibrinolytic systems on plasma t-PA and PAI-1 levels are dependent on environmental context - Folkert W. Asselbergs; Scott M. Williams; Patricia R. Hebert; Christopher S. Coffey; Hans L. Hillege; Harold Snieder; Gerjan Navis; Douglas E. Vaughan; Wiek H. van Gilst; Jason H. Moore (Human Genetics, 2007)

Evidence for epistasis between SLC6A4 and ITGB3 in autism etiology and in the determination of platelet serotonin levels - Ana M. Coutinho; Inês Sousa; Madalena Martins; Catarina Correia; Teresa Morgadinho; Celeste Bento; Carla Marques; Assunção Ataíde; Teresa S. Miguel; Jason H. Moore; Guiomar Oliveira; Astrid M. Vicente (Human Genetics, 2007)

Elevated male European and female African contributions to the genomes of African American individuals - Joanne M. Lind; Holli B. Hutcheson-Dilks; Scott M. Williams; Jason H. Moore; Myron Essex; Eduardo Ruiz-Pesini; Douglas C. Wallace; Sarah A. Tishkoff; Stephen J. O’Brien; Michael W. Smith (Human Genetics, 2006)

Annual basal area increment and growth duration of Pinus taeda in response to eight years of free‐air carbon dioxide enrichment - DAVID J. P. MOORE; SUSANNE AREF; RINGO M. HO; JEFFREY S. PIPPEN; JASON G. HAMILTON; EVAN H. DE LUCIA (Global Change Biology, 2006)
Rising CO 2 is predicted to increase forest productivity, although the duration of the response and how it might be altered by variation in rainfall, temperature and other environmental variables are not well understood. We measured the basal area of rapidly growing Pinus taeda trees exposed to free‐air CO 2 enrichment for 8 years and used these measurements to estimate monthly and annual growth. We used these measurements in a statistical model to estimate the start and end of growth in each year. Elevated CO 2 increased the basal area increment ( BAI ) of trees by 13–27%. In most years, exposure to elevated CO 2 increased the growth rate but not the duration of the active growth period. With the exception of 1 year following an extreme drought and a severe ice storm, BAI was positively correlated with the amount of rainfall during the active growth period. The interannual variation in the relative enhancement of BAI caused by elevated CO 2 was strongly related to temperature and rainfall, and was greatest in years with high vapor pressure deficit. There was no evidence of a systematic reduction in the stimulation of growth during the first 8 years of this experiment, suggesting that the hypothesized limitation of the CO 2 response caused by nitrogen availability has yet to occur.

Microinfusion Using Hollow Microneedles - Wijaya Martanto; Jason S. Moore; Osama Kashlan; Rachna Kamath; Ping M. Wang; Jessica M. O'Neal; Mark R. Prausnitz (Pharmaceutical Research, 2006)

Exploring the Relationship Between Hydrologic Parameters and Nutrient Loads Using Digital Elevation Model and GIS – A Case Study from Sugarcreek Headwaters, Ohio, U.S.A. - V. Krishna Prasad; Ariel Ortiz; Ben Stinner; David Mccartney; Jason Parker; Deana Hudgins; Casey Hoy; Richard Moore (Environmental Monitoring and Assessment, 2005)