548–480 Ma plate motions in the Adelaide Orogen record coeval interactions between proximal (W–E) and distal (N–S) plates, producing arc formation and trench rollback - Timothy H. Bell; Clement Fay (Gondwana Research, 2026)

Beach law in the anthropocene - Timothy F. Smith; Justine Bell-James; John Page; Anja Scheffers; Giorgio Cataldo; Jennifer Corrin; Hossein Esmaeili; Miguel Frohlich; Adrienne Paul; Thomas Perroud; Jill Robbie; Hui Wang (Ocean & Coastal Management, 2026)

Small amphipathic amino acids imprint the active site of extant E. coli aminoacyl-tRNA synthetases - Douglas Iverson; Crystal Serrano; Kalii Faustino; Elena Hauf-Pisoni; Timothy Jordan; Japeth Mobisa; Dhathry Doppalapudi; Amran Mohamed; Nicholas Panuco; Daniel Ghebreigziabher; Anthony J. Bell (BioSystems, 2026)

Patterns in biodiversity and richness in macrofaunal fouling communities on Tampa Bay floating docks - Cassidy C. Bell; J. S. Doody; Timothy Henkel; Heather Judkins (Aquatic Ecology, 2025)

Putting Regional Fisheries Management Organisations' Climate Change House in Order - Kamal Azmi; Graham Pilling; Johann Bell; Yi‐Jay Chang; Adele Dutilloy; Timothy H. Frawley; Paul Hamer; John Hampton; Quentin Hanich; Tyla Hill‐Moana; Jhen Hsu; Glenn Hurry; et al. (Fish and Fisheries, 2025)
Climate change is expected to have significant impacts on the biology, abundance and distribution of transboundary fish stocks, not only among neighbouring countries within the jurisdictions of regional fisheries management organisations (RFMOs) but also between adjacent RFMOs. Using South Pacific albacore tuna ( Thunnus alalunga ) as a case study, we highlight how RFMOs need to understand the impacts of climate change on transboundary stocks under their purview with greater certainty. We identify four areas of research that should assist RFMOs to adapt their scientific processes—strengthened understanding of changes in the biology of target stocks; enhanced collection of data to support modelling; improved modelling of catch‐per‐unit of effort (CPUE) to better reflect climate change impacts on stock abundance for assessments; and ensuring that scientific advice is adaptive and robust to climate change, including through implementation of tested harvest strategies. Investments in these research areas should enable RFMOs to improve the science underpinning management measures designed to sustain transboundary stocks and increase fishery performance during climate change.

Proteomic analysis resulting in species‐level identification of recently diverged North American arvicoline rodents - Erin M. Keenan Early; Christopher J. Bell; Matthew J. Collins; Timothy M. Shanahan (Journal of Quaternary Science, 2025)
North American arvicoline rodents have long been considered to have high biogeographic, biochronologic, and paleoecological value. They provide relative dating of faunal assemblages when absolute dating is not possible and contribute to paleobiome characterization. However, the scientific value of Arvicolinae is often limited by the level of taxonomic identification achievable by morphological analyses. ZooMS (zooarchaeology by mass spectrometry) is a proteomic method that permits taxonomic identification of bone material. We added 19 North American arvicoline species to the ZooMS reference database to assess the level of taxonomic resolution between those species using ZooMS. Results show species‐level taxonomic resolution for all tested arvicolines that diverged up to just under 1 mya. We estimate species‐level taxonomic resolution is achievable for arvicolines that diverged up to 273 kya and up to 170.5 kya for members of Microtus . Application to arvicoline fossils demonstrates the presence of previously unidentified species of Microtus in the Great Basin, that isolated molars are sufficient for taxonomic identification, and provides results consistent with the morphological hypothesis that Microtus paroperarius and Alexandromys oeconomus are not conspecific. ZooMS can drastically improve taxonomic identification of arvicolines, and may increase their utility for biochronological, biogeographic, and paleoecological interpretations of Pleistocene faunal response to climatic and other environmental changes.

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.

Identifying predictors of translocation success in rare plant species - Joe Bellis; Oyomoare Osazuwa‐Peters; Joyce Maschinski; Matthew J. Keir; Elliott W. Parsons; Thomas N. Kaye; Michael Kunz; Jennifer Possley; Eric Menges; Stacy A. Smith; Daniela Roth; Debbie Brewer; et al. (Conservation Biology, 2024)
The fundamental goal of a rare plant translocation is to create self‐sustaining populations with the evolutionary resilience to persist in the long term. Yet, most plant translocation syntheses focus on a few factors influencing short‐term benchmarks of success (e.g., survival and reproduction). Short‐term benchmarks can be misleading when trying to infer future growth and viability because the factors that promote establishment may differ from those required for long‐term persistence. We assembled a large ( n = 275) and broadly representative data set of well‐documented and monitored (7.9 years on average) at‐risk plant translocations to identify the most important site attributes, management techniques, and species’ traits for six life‐cycle benchmarks and population metrics of translocation success. We used the random forest algorithm to quantify the relative importance of 29 predictor variables for each metric of success. Drivers of translocation outcomes varied across time frames and success metrics. Management techniques had the greatest relative influence on the attainment of life‐cycle benchmarks and short‐term population trends, whereas site attributes and species’ traits were more important for population persistence and long‐term trends. Specifically, large founder sizes increased the potential for reproduction and recruitment into the next generation, whereas declining habitat quality and the outplanting of species with low seed production led to increased extinction risks and a reduction in potential reproductive output in the long‐term, respectively. We also detected novel interactions between some of the most important drivers, such as an increased probability of next‐generation recruitment in species with greater seed production rates, but only when coupled with large founder sizes. Because most significant barriers to plant translocation success can be overcome by improving techniques or resolving site‐level issues through early intervention and management, we suggest that by combining long‐term monitoring with adaptive management, translocation programs can enhance the prospects of achieving long‐term success.

An interaction of inorganic arsenic exposure with body weight and composition on type 2 diabetes indicators in Diversity Outbred mice - James G. Xenakis; Christelle Douillet; Timothy A. Bell; Pablo Hock; Joseph Farrington; Tianyi Liu; Caroline E. Y. Murphy; Avani Saraswatula; Ginger D. Shaw; Gustavo Nativio; Qing Shi; Abhishek Venkatratnam; et al. (Mammalian Genome, 2022)

Low-Cost, Deep-Sea Imaging and Analysis Tools for Deep-Sea Exploration: A Collaborative Design Study - Katherine L. C. Bell; Jennifer Szlosek Chow; Alexis Hope; Maud C. Quinzin; Kat A. Cantner; Diva J. Amon; Jessica E. Cramp; Randi D. Rotjan; Lehua Kamalu; Asha de Vos; Sheena Talma; Salome Buglass; et al. (Frontiers in Marine Science, 2022)
A minuscule fraction of the deep sea has been scientifically explored and characterized due to several constraints, including expense, inefficiency, exclusion, and the resulting inequitable access to tools and resources around the world. To meet the demand for understanding the largest biosphere on our planet, we must accelerate the pace and broaden the scope of exploration by adding low-cost, scalable tools to the traditional suite of research assets. Exploration strategies should increasingly employ collaborative, inclusive, and innovative research methods to promote inclusion, accessibility, and equity to ocean discovery globally. Here, we present an important step toward this new paradigm: a collaborative design study on technical capacity needs for equitable deep-sea exploration. The study focuses on opportunities and challenges related to low-cost, scalable tools for deep-sea data collection and artificial intelligence-driven data analysis. It was conducted in partnership with twenty marine professionals worldwide, covering a broad representation of geography, demographics, and domain knowledge within the ocean space. The results of the study include a set of technical requirements for low-cost deep-sea imaging and sensing systems and automated image and data analysis systems. As a result of the study, a camera system called Maka Niu was prototyped and is being field-tested by thirteen interviewees and an online AI-driven video analysis platform is in development. We also identified six categories of open design and implementation questions highlighting participant concerns and potential trade-offs that have not yet been addressed within the scope of the current projects but are identified as important considerations for future work. Finally, we offer recommendations for collaborative design projects related to the deep sea and outline our future work in this space.

Hurricane Harvey Delivered a Massive Load of Mercury-Rich Sediment to Galveston Bay, TX, USA - Timothy M. Dellapenna; Christena Hoelscher; Lisa Hill; Lindsay Critides; Victoria Salgado; Mason Bell; Mohammad E. Al Mukaimi; Jaibi Du; Kyeong Park; Anthony H. Knap (Estuaries and Coasts, 2022)

Reptile responses to anthropogenic habitat modification: A global meta‐analysis - Tim S. Doherty; Sara Balouch; Kristian Bell; Thomas J. Burns; Anat Feldman; Charles Fist; Timothy F. Garvey; Tim S. Jessop; Shai Meiri; Don A. Driscoll (Global Ecology and Biogeography, 2020)
Aim The aim was to determine how reptile populations respond to anthropogenic habitat modification and determine whether species traits and environmental factors influence such responses. Location Global. Time period 1981–2018. Major taxa studied Squamata. Methods We compiled a database of 56 studies reporting how habitat modification affects reptile abundance and calculated standardized mean differences in abundance (Hedges’ g ). We used Bayesian meta‐analytical models to test whether responses to habitat modification depended on body size, clutch size, reproductive mode, habitat specialization, range size, disturbance type, vegetation type, temperature and precipitation. Results Based on 815 effect sizes from 376 species, we found an overall negative effect of habitat modification on reptile abundance (mean Hedges’ g = −0.43, 95% credible intervals = −0.61 to −0.26). Reptile abundance was, on average, one‐third lower in modified compared with unmodified habitats. Small range sizes and small clutch sizes were associated with more negative responses to habitat modification, although the responses were weak and the credible intervals overlapped zero. We detected no effects of body size, habitat specialization, reproductive mode (egg‐laying or live‐bearing), temperature or precipitation. Some families exhibited more negative responses than others, although overall there was no phylogenetic signal in the data. Mining had the most negative impacts on reptile abundance, followed by agriculture, grazing, plantations and patch size reduction, whereas the mean effect of logging was neutral. Main conclusions Habitat modification is a key cause of reptile population declines, although there is variability in responses both within and between species, families and vegetation types. The effect of disturbance type appeared to be related to the intensity of habitat modification. Ongoing development of environmentally sustainable practices that ameliorate anthropogenic impacts is urgently needed to prevent declines in reptile populations.

Effects of life history and reproduction on recruitment time lags in reintroductions of rare plants - Matthew A. Albrecht; Oyomoare L. Osazuwa‐Peters; Joyce Maschinski; Timothy J. Bell; Marlin L. Bowles; William E. Brumback; Janice Duquesnel; Michael Kunz; Jimmy Lange; Kimberlie A. McCue; A. Kathryn McEachern; Sheila Murray; et al. (Conservation Biology, 2019)
Reintroductions are important components of conservation and recovery programs for rare plant species, but their long‐term success rates are poorly understood. Previous reviews of plant reintroductions focused on short‐term (e.g., ≤3 years) survival and flowering of founder individuals rather than on benchmarks of intergenerational persistence, such as seedling recruitment. However, short‐term metrics may obscure outcomes because the unique demographic properties of reintroductions, including small size and unstable stage structure, could create lags in population growth. We used time‐to‐event analysis on a database of unusually well‐monitored and long‐term (4–28 years) reintroductions of 27 rare plant species to test whether life‐history traits and population characteristics of reintroductions create time‐lagged responses in seedling recruitment (i.e., recruitment time lags [RTLs]), an important benchmark of success and indicator of persistence in reintroduced populations. Recruitment time lags were highly variable among reintroductions, ranging from

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)

Quantitative and qualitative assessment of pollen DNA metabarcoding using constructed species mixtures - Karen L. Bell; Kevin S. Burgess; Jamieson C. Botsch; Emily K. Dobbs; Timothy D. Read; Berry J. Brosi (Molecular Ecology, 2019)
Pollen DNA metabarcoding—marker‐based genetic identification of potentially mixed‐species pollen samples—has applications across a variety of fields. While basic species‐level pollen identification using standard DNA barcode markers is established, the extent to which metabarcoding (a) correctly assigns species identities to mixes (qualitative matching) and (b) generates sequence reads proportionally to their relative abundance in a sample (quantitative matching) is unclear, as these have not been assessed relative to known standards. We tested the quantitative and qualitative robustness of metabarcoding in constructed pollen mixtures varying in species richness (1–9 species), taxonomic relatedness (within genera to across class) and rarity (5%–100% of grains), using Illumina MiSeq with the markers rbcL and ITS 2. Qualitatively, species composition determinations were largely correct, but false positives and negatives occurred. False negatives were typically driven by lack of a barcode gap or rarity in a sample. Species richness and taxonomic relatedness, however, did not strongly impact correct determinations. False positives were likely driven by contamination, chimeric sequences and/or misidentification by the bioinformatics pipeline. Quantitatively, the proportion of reads for each species was only weakly correlated with its relative abundance, in contrast to suggestions from some other studies. Quantitative mismatches are not correctable by consistent scaling factors, but instead are context‐dependent on the other species present in a sample. Together, our results show that metabarcoding is largely robust for determining pollen presence/absence but that sequence reads should not be used to infer relative abundance of pollen grains.

The control of deformation partitioning and strain localization on porphyroblast behaviour in rocks and experiments - Timothy H. Bell; Ioan V. Sanislav; Jyotindra Sapkota (Geosciences Journal, 2018)

Calcium Phosphate Particles as Pulmonary Delivery System for Interferon-α in Mice - Tülin Morçöl; Jessica M. Weidner; Anand Mehta; Stephen J.D. Bell; Timothy Block (AAPS PharmSciTech, 2018)

Research priorities for managing the impacts and dependencies of business upon food, energy, water and the environment - Jonathan M. H. Green; Gemma R. Cranston; William J. Sutherland; Hannah R. Tranter; Sarah J. Bell; Tim G. Benton; Eva Blixt; Colm Bowe; Sarah Broadley; Andrew Brown; Chris Brown; Neil Burns; et al. (Sustainability Science, 2017)

The Collaborative Cross as a Resource for Modeling Human Disease: CC011/Unc, a New Mouse Model for Spontaneous Colitis - Allison R. Rogala; Andrew P. Morgan; Alexis M. Christensen; Terry J. Gooch; Timothy A. Bell; Darla R. Miller; Virginia L. Godfrey; Fernando Pardo-Manuel de Villena (Mammalian Genome, 2014)

Ability of Matrix Models to Explain the Past and Predict the Future of Plant Populations - ELIZABETH E. CRONE; MARTHA M. ELLIS; WILLIAM F. MORRIS; AMANDA STANLEY; TIMOTHY BELL; PAULETTE BIERZYCHUDEK; JOHAN EHRLÉN; THOMAS N. KAYE; TIFFANY M. KNIGHT; PETER LESICA; GERARD OOSTERMEIJER; PEDRO F. QUINTANA‐ASCENCIO; et al. (Conservation Biology, 2013)
Uncertainty associated with ecological forecasts has long been recognized, but forecast accuracy is rarely quantified. We evaluated how well data on 82 populations of 20 species of plants spanning 3 continents explained and predicted plant population dynamics. We parameterized stage‐based matrix models with demographic data from individually marked plants and determined how well these models forecast population sizes observed at least 5 years into the future. Simple demographic models forecasted population dynamics poorly; only 40% of observed population sizes fell within our forecasts’ 95% confidence limits. However, these models explained population dynamics during the years in which data were collected; observed changes in population size during the data‐collection period were strongly positively correlated with population growth rate. Thus, these models are at least a sound way to quantify population status. Poor forecasts were not associated with the number of individual plants or years of data. We tested whether vital rates were density dependent and found both positive and negative density dependence. However, density dependence was not associated with forecast error. Forecast error was significantly associated with environmental differences between the data collection and forecast periods. To forecast population fates, more detailed models, such as those that project how environments are likely to change and how these changes will affect population dynamics, may be needed. Such detailed models are not always feasible. Thus, it may be wiser to make risk‐averse decisions than to expect precise forecasts from models. Habilidad de los Modelos Matriciales para Explicar el Pasado y Predecir el Futuro de las Poblaciones de Plantas

Could some coral reefs become sponge reefs as our climate changes? - James J. Bell; Simon K. Davy; Timothy Jones; Michael W. Taylor; Nicole S. Webster (Global Change Biology, 2013)
Coral reefs across the world have been seriously degraded and have a bleak future in response to predicted global warming and ocean acidification ( OA ). However, this is not the first time that biocalcifying organisms, including corals, have faced the threat of extinction. The end‐Triassic mass extinction (200 million years ago) was the most severe biotic crisis experienced by modern marine invertebrates, which selected against biocalcifiers; this was followed by the proliferation of another invertebrate group, sponges. The duration of this sponge‐dominated period far surpasses that of alternative stable‐ecosystem or phase‐shift states reported on modern day coral reefs and, as such, a shift to sponge‐dominated reefs warrants serious consideration as one future trajectory of coral reefs. We hypothesise that some coral reefs of today may become sponge reefs in the future, as sponges and corals respond differently to changing ocean chemistry and environmental conditions. To support this hypothesis, we discuss: (i) the presence of sponge reefs in the geological record; (ii) reported shifts from coral‐ to sponge‐dominated systems; and (iii) direct and indirect responses of the sponge holobiont and its constituent parts (host and symbionts) to changes in temperature and pH . Based on this evidence, we propose that sponges may be one group to benefit from projected climate change and ocean acidification scenarios, and that increased sponge abundance represents a possible future trajectory for some coral reefs, which would have important implications for overall reef functioning.

Matrix population models from 20 studies of perennial plant populations - Martha M. Ellis; Jennifer L. Williams; Peter Lesica; Timothy J. Bell; Paulette Bierzychudek; Marlin Bowles; Elizabeth E. Crone; Daniel F. Doak; Johan Ehrlén; Albertine Ellis-Adam; Kathryn McEachern; Rengaian Ganesan; et al. (Ecology, 2012)
Demographic transition matrices are among the most commonly applied population models for both basic and applied ecological research. The relatively simple framework of these models and simple, easily interpretable summary statistics they produce have prompted the wide use of these models across an exceptionally broad range of taxa. Here, we provide annual transition matrices and observed stage structures/population sizes for 20 perennial plant species which have been the focal species for long‐term demographic monitoring. These data were assembled as part of the “Testing Matrix Models” working group through the National Center for Ecological Analysis and Synthesis (NCEAS). The data represent 82 populations with >460 total population‐years of observations. It is our hope that making these data available will help promote and improve our ability to monitor and understand plant population dynamics. The complete data sets corresponding to abstracts published in the Data Papers section of the journal are published electronically in Ecological Archives at 〈 http://esapubs.org/archive 〉. (The accession number for each Data Paper is given directly beneath the title.)

Trophic level asynchrony in rates of phenological change for marine, freshwater and terrestrial environments - STEPHEN J. THACKERAY; TIMOTHY H. SPARKS; MORTEN FREDERIKSEN; SARAH BURTHE; PHILIP J. BACON; JAMES R. BELL; MARC S. BOTHAM; TOM M. BRERETON; PAUL W. BRIGHT; LAURENCE CARVALHO; TIM CLUTTON‐BROCK; ALISTAIR DAWSON; et al. (Global Change Biology, 2010)
Recent changes in the seasonal timing (phenology) of familiar biological events have been one of the most conspicuous signs of climate change. However, the lack of a standardized approach to analysing change has hampered assessment of consistency in such changes among different taxa and trophic levels and across freshwater, terrestrial and marine environments. We present a standardized assessment of 25 532 rates of phenological change for 726 UK terrestrial, freshwater and marine taxa. The majority of spring and summer events have advanced, and more rapidly than previously documented. Such consistency is indicative of shared large scale drivers. Furthermore, average rates of change have accelerated in a way that is consistent with observed warming trends. Less coherent patterns in some groups of organisms point to the agency of more local scale processes and multiple drivers. For the first time we show a broad scale signal of differential phenological change among trophic levels; across environments advances in timing were slowest for secondary consumers, thus heightening the potential risk of temporal mismatch in key trophic interactions. If current patterns and rates of phenological change are indicative of future trends, future climate warming may exacerbate trophic mismatching, further disrupting the functioning, persistence and resilience of many ecosystems and having a major impact on ecosystem services.

Variability in the spatial association patterns of sponge assemblages in response to environmental heterogeneity - James J. Bell; Jade Berman; Timothy Jones; Leanne J. Hepburn (Marine Biology, 2010)

THE SPECIFICITY OF PHENOTYPIC INDUCTION OF MOUSE AND HUMAN STEM CELLS BY SIGNALING COMPLEXES - JIANWU DAI; JANARDAN KUMAR; YAJUN FENG; ROSE ASRICAN; JUNG KIM; TIMOTHY FOFONOFF; VLADIMIR RUSSAKOVSKY; RYAN CHURCHILL; NILOY ROY; EUGENE BELL (In Vitro Cellular & Developmental Biology - Animal, 2002)