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.

Challenges in cybersecurity: Lessons from biological defense systems - Edward Schrom; Ann Kinzig; Stephanie Forrest; Andrea L. Graham; Simon A. Levin; Carl T. Bergstrom; Carlos Castillo-Chavez; James P. Collins; Rob J. de Boer; Adam Doupé; Roya Ensafi; Stuart Feldman; et al. (Mathematical Biosciences, 2023)

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)

Common, low-frequency, rare, and ultra-rare coding variants contribute to COVID-19 severity - Chiara Fallerini; Nicola Picchiotti; Margherita Baldassarri; Kristina Zguro; Sergio Daga; Francesca Fava; Elisa Benetti; Sara Amitrano; Mirella Bruttini; Maria Palmieri; Susanna Croci; Mirjam Lista; et al. (Human Genetics, 2022)
The combined impact of common and rare exonic variants in COVID-19 host genetics is currently insufficiently understood. Here, common and rare variants from whole-exome sequencing data of about 4000 SARS-CoV-2-positive individuals were used to define an interpretable machine-learning model for predicting COVID-19 severity. First, variants were converted into separate sets of Boolean features, depending on the absence or the presence of variants in each gene. An ensemble of LASSO logistic regression models was used to identify the most informative Boolean features with respect to the genetic bases of severity. The Boolean features selected by these logistic models were combined into an Integrated PolyGenic Score that offers a synthetic and interpretable index for describing the contribution of host genetics in COVID-19 severity, as demonstrated through testing in several independent cohorts. Selected features belong to ultra-rare, rare, low-frequency, and common variants, including those in linkage disequilibrium with known GWAS loci. Noteworthily, around one quarter of the selected genes are sex-specific. Pathway analysis of the selected genes associated with COVID-19 severity reflected the multi-organ nature of the disease. The proposed model might provide useful information for developing diagnostics and therapeutics, while also being able to guide bedside disease management.

Extended Pelagic Life in a Bathybenthic Octopus - Roger Villanueva; Vladimir V. Laptikhovsky; Stuart B. Piertney; Fernando Ángel Fernández-Álvarez; Martin A. Collins; Jonathan D. Ablett; Alejandro Escánez (Frontiers in Marine Science, 2020)
Planktonic stages of benthic octopuses can reach relatively large sizes in some species, usually in oceanic, epipelagic waters while living as part of the macroplankton. These young octopuses appear to delay settlement on the seabed for an undetermined period of time that is probably longer than for those octopus paralarvae living in coastal, neritic waters. The reason for this delay is unknown and existing information about their biology is very scarce. Here we report on the presence of juvenile and subadult forms of the bathybenthic octopus Pteroctopus tetracirrhus in oceanic waters of the South and North Atlantic and its association with the pyrosomid species Pyrosoma atlanticum , apparently used by the octopus as a refuge or shelter. The relatively large size of the P. tetracirrhus living in oceanic waters as the individuals reported here, together with the morphological characteristics of this bathybenthic species including its gelatinous body, minute suckers embedded in swollen skin and the deep interbrachial web, indicates that P. tetracirrhus may be considered a model of a transitional octopus species that is colonizing the pelagic environment by avoiding descending to the bathyal benthos. This process seems to occur in the same way as in the supposed origin of the ctenoglossan holopelagic octopods of the families Amphitretidae, Bolitaenidae, and Vitreledonellidae, which have arisen via neoteny from the planktonic paralarval stages of benthic octopuses.

Using Modern Conservation Tools for Innovative Management of Coral Reefs: The MANACO Consortium - Oliver Selmoni; Gaël Lecellier; Lara Ainley; Antoine Collin; Raimana Doucet; Vaimiti Dubousquet; Hudson Feremaito; Edouard Ito Waia; Stuart Kininmonth; Hélène Magalon; Siola’a Malimali; Ateliana Maugateau; et al. (Frontiers in Marine Science, 2020)

TRY plant trait database – enhanced coverage and open access - Jens Kattge; Gerhard Bönisch; Sandra Díaz; Sandra Lavorel; Iain Colin Prentice; Paul Leadley; Susanne Tautenhahn; Gijsbert D. A. Werner; Tuomas Aakala; Mehdi Abedi; Alicia T. R. Acosta; George C. Adamidis; et al. (Global Change Biology, 2020)
Plant traits—the morphological, anatomical, physiological, biochemical and phenological characteristics of plants—determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait‐based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits—almost complete coverage for ‘plant growth form’. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait–environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives.

Taxonomy of the order Mononegavirales: update 2018 - Gaya K. Amarasinghe; Nidia G. Aréchiga Ceballos; Ashley C. Banyard; Christopher F. Basler; Sina Bavari; Andrew J. Bennett; Kim R. Blasdell; Thomas Briese; Alexander Bukreyev; Yíngyún Caì; Charles H. Calisher; Cristine Campos Lawson; et al. (Archives of Virology, 2018)

Intakes of fat and micronutrients between ages 13 and 18 years and the incidence of proliferative benign breast disease - Xuefen Su; Caroline E. Boeke; Laura C. Collins; Heather J. Baer; Walter C. Willett; Stuart J. Schnitt; James L. Connolly; Bernard Rosner; Graham A. Colditz; Rulla M. Tamimi (Cancer Causes & Control, 2015)

MDMA Increases Glutamate Release and Reduces Parvalbumin-Positive GABAergic Cells in the Dorsal Hippocampus of the Rat: Role of Cyclooxygenase - John H. Anneken; Jacobi I. Cunningham; Stuart A. Collins; Bryan K. Yamamoto; Gary A. Gudelsky (Journal of Neuroimmune Pharmacology, 2013)

Lifetime physical activity and the incidence of proliferative benign breast disease - Michelle M. Jung; Graham A. Colditz; Laura C. Collins; Stuart J. Schnitt; James L. Connolly; Rulla M. Tamimi (Cancer Causes & Control, 2011)

Integrated catchment management—interweaving social process and science knowledge - A Fenemor; C Phillips; W Allen; RG Young; G Harmsworth; B Bowden; L Basher; PA Gillespie; M Kilvington; R Davies‐Colley; J Dymond; A Cole; et al. (New Zealand Journal of Marine and Freshwater Research, 2011)
This paper provides an overview of the Motueka integrated catchment management (ICM) research programme. This research was based on the thesis that achieving ecosystem resilience at a catchment scale requires active measures to develop community resilience. We define a generic adaptive planning and action process, with associated knowledge management and stakeholder involvement processes, and illustrate those processes with observations from five research themes: (1) water allocation; (2) land use effects on water; (3) land and freshwater impacts on the coast; (4) integrative tools and processes for managing cumulative effects; and (5) building human capital and facilitating community action. Our research clearly illustrates the benefits for effective decision‐making of carrying out catchment scale science and management within collaborative processes which patiently develop trusting relationships. We conclude that coastal catchments should be managed as a holistic continuum from ridge tops to the sea and that some processes like floods or loss of community resilience have decadal consequences, which support the need for long‐term monitoring and investment.

Intake of fiber and nuts during adolescence and incidence of proliferative benign breast disease - Xuefen Su; Rulla M. Tamimi; Laura C. Collins; Heather J. Baer; Eunyoung Cho; Laura Sampson; Walter C. Willett; Stuart J. Schnitt; James L. Connolly; Bernard A. Rosner; Graham A. Colditz (Cancer Causes & Control, 2010)