Examining widely held propositions on human dietary protein needs and benefits: a critical review of the science that shapes both the data and our understanding of an essential macronutrient - Mitchell M. Kanter; Sally Aaron; Steven N. Austad; Andrew W. Brown; Nicholas A. Burd; Wayne W. Campbell; Mark Cope; Teresa A. Davis; John W. Erdman; Miguel Freitas; Kristen Hicks-Roof; Samuel Klein; et al. (Critical Reviews in Food Science and Nutrition, 2026)

Microbial carbon use efficiency is governed by site-level soil and climate factors and does not explain soil carbon gains under diversified crop rotations - Timothy M. Bowles; Maria Mooshammer; A. Stuart Grandy; Kevin Geyer; Serita D. Frey; Francisco Calderón; Steve Culman; Bill Deen; Kari Dunfield; Virginia L. Jin; R. Michael Lehman; Shannon L. Osborne; et al. (Soil Biology and Biochemistry, 2026)

A horizon scan of biological conservation issues for 2026 - William J. Sutherland; Stuart H.M. Butchart; Stewart J. Clarke; Nigel R. Doar; Helen Doran; Imogen C. Douglas; Daniel J. Field; Erica Fleishman; Kevin J. Gaston; James E. Herbert-Read; Alice C. Hughes; Hermanni Kaartokallio; et al. (Trends in Ecology & Evolution, 2026)

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.

Global Marine Flyways Identified for Long‐Distance Migrating Seabirds From Tracking Data - Joanne M. Morten; Ana P. B. Carneiro; Martin Beal; Anne‐Sophie Bonnet‐Lebrun; Maria P. Dias; Marie‐Morgane Rouyer; Autumn‐Lynn Harrison; Jacob González‐Solís; Victoria R. Jones; Virginia A. Garcia Alonso; Michelle Antolos; Javier A. Arata; et al. (Global Ecology and Biogeography, 2025)
Aim To identify the broad‐scale oceanic migration routes (‘marine flyways’) used by multiple pelagic, long‐distance migratory seabirds based on a global compilation of tracking data. Location Global. Time Period 1989–2023. Major Taxa Studied Seabirds (Families: Phaethontidae, Hydrobatidae, Diomedeidae, Procellariidae, Laridae and Stercorariidae). Methods We collated a comprehensive global tracking dataset that included the migratory routes of 48 pelagic and long‐distance migrating seabird species across the Atlantic, Indian, Pacific and Southern Oceans. We grouped individuals that followed similar routes, independent of species or timings of migration, using a dynamic time warping clustering approach. We visualised the routes of each cluster using a line density analysis and used knowledge of seabird spatial ecology to combine the clusters to identify the broad‐scale flyways followed by most pelagic migratory seabirds tracked to‐date at an ocean‐basin scale. Results Six marine flyways were identified across the world's oceans: the Atlantic Ocean Flyway, North Indian Ocean Flyway, East Indian Ocean Flyway, West Pacific Ocean Flyway, Pacific Ocean Flyway and Southern Ocean Flyway. Generally, the flyways were used bidirectionally, and individuals either followed sections of a flyway, a complete flyway, or their movements linked two or more flyways. Transhemispheric figure‐of‐eight routes in the Atlantic and Pacific oceans, and a circumnavigation flyway in the Southern Ocean correspond with major wind ‐ driven ocean currents. Main Conclusions The marine flyways identified demonstrate that pelagic seabirds have similar and repeatable migration routes across ocean‐basin scales. Our study highlights the need to account for connectivity in seabird conservation and provides a framework for international cooperation.

Land Use Change Consistently Reduces α‐ But Not β‐ and γ‐Diversity of Bees - Toby P. N. Tsang; A. A. Amado De Santis; Gabriela Armas‐Quiñonez; John S. Ascher; Eva Samanta Ávila‐Gómez; András Báldi; Kimberly M. Ballare; Mario V. Balzan; Weronika Banaszak‐Cibicka; Svenja Bänsch; Yves Basset; Adam J. Bates; et al. (Global Change Biology, 2025)
Land use change threatens global biodiversity and compromises ecosystem functions, including pollination and food production. Reduced taxonomic α‐diversity is often reported under land use change, yet the impacts could be different at larger spatial scales (i.e., γ‐diversity), either due to reduced β‐diversity amplifying diversity loss or increased β‐diversity dampening diversity loss. Additionally, studies often focus on taxonomic diversity, while other important biodiversity components, including phylogenetic diversity, can exhibit differential responses. Here, we evaluated how agricultural and urban land use alters the taxonomic and phylogenetic α‐, β‐, and γ‐diversity of an important pollinator taxon—bees. Using a multicontinental dataset of 3117 bee assemblages from 157 studies, we found that taxonomic α‐diversity was reduced by 16%–18% in both agricultural and urban habitats relative to natural habitats. Phylogenetic α‐diversity was decreased by 11%–12% in agricultural and urban habitats. Compared with natural habitats, taxonomic and phylogenetic β‐diversity increased by 11% and 6% in urban habitats, respectively, but exhibited no systematic change in agricultural habitats. We detected a 22% decline in taxonomic γ‐diversity and a 17% decline in phylogenetic γ‐diversity in agricultural habitats, but γ‐diversity of urban habitats was not significantly different from natural habitats. These findings highlight the threat of agricultural expansions to large‐scale bee diversity due to systematic γ‐diversity decline. In addition, while both urbanization and agriculture lead to consistent declines in α‐diversity, their impacts on β‐ or γ‐diversity vary, highlighting the need to study the effects of land use change at multiple scales.

A horizon scan of global biological conservation issues for 2024 - William J. Sutherland; Craig Bennett; Peter N.M. Brotherton; Stuart H.M. Butchart; Holly M. Butterworth; Stewart J. Clarke; Nafeesa Esmail; Erica Fleishman; Kevin J. Gaston; James E. Herbert-Read; Alice C. Hughes; Jennifer James; et al. (Trends in Ecology & Evolution, 2024)

The effect of dietary carbohydrate to lipid ratios on growth performance in juvenile California yellowtail Seriola dorsalis - Jonas R. Miller; Guillaume P. Salze; Kevin R. Stuart; Mark A. Drawbridge; D. Allen Davis (Aquaculture, 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)

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.

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.

Controls over Ocean Mesopelagic Interior Carbon Storage (COMICS): Fieldwork, Synthesis, and Modeling Efforts - Richard J. Sanders; Stephanie A. Henson; Adrian P. Martin; Tom R. Anderson; Raffaele Bernardello; Peter Enderlein; Sophie Fielding; Sarah L. C. Giering; Manuela Hartmann; Morten Iversen; Samar Khatiwala; Phyllis Lam; et al. (Frontiers in Marine Science, 2016)

Climate change and Southern Ocean ecosystems I: how changes in physical habitats directly affect marine biota - Andrew J. Constable; Jessica Melbourne‐Thomas; Stuart P. Corney; Kevin R. Arrigo; Christophe Barbraud; David K. A. Barnes; Nathaniel L. Bindoff; Philip W. Boyd; Angelika Brandt; Daniel P. Costa; Andrew T. Davidson; Hugh W. Ducklow; et al. (Global Change Biology, 2014)
Antarctic and Southern Ocean ( ASO ) marine ecosystems have been changing for at least the last 30 years, including in response to increasing ocean temperatures and changes in the extent and seasonality of sea ice; the magnitude and direction of these changes differ between regions around Antarctica that could see populations of the same species changing differently in different regions. This article reviews current and expected changes in ASO physical habitats in response to climate change. It then reviews how these changes may impact the autecology of marine biota of this polar region: microbes, zooplankton, salps, Antarctic krill, fish, cephalopods, marine mammals, seabirds, and benthos. The general prognosis for ASO marine habitats is for an overall warming and freshening, strengthening of westerly winds, with a potential pole‐ward movement of those winds and the frontal systems, and an increase in ocean eddy activity. Many habitat parameters will have regionally specific changes, particularly relating to sea ice characteristics and seasonal dynamics. Lower trophic levels are expected to move south as the ocean conditions in which they are currently found move pole‐ward. For Antarctic krill and finfish, the latitudinal breadth of their range will depend on their tolerance of warming oceans and changes to productivity. Ocean acidification is a concern not only for calcifying organisms but also for crustaceans such as Antarctic krill; it is also likely to be the most important change in benthic habitats over the coming century. For marine mammals and birds, the expected changes primarily relate to their flexibility in moving to alternative locations for food and the energetic cost of longer or more complex foraging trips for those that are bound to breeding colonies. Few species are sufficiently well studied to make comprehensive species‐specific vulnerability assessments possible. Priorities for future work are discussed.

Evidence and Implications of Recent Climate Change in Northern Alaska and Other Arctic Regions - Larry D. Hinzman; Neil D. Bettez; W. Robert Bolton; F. Stuart Chapin; Mark B. Dyurgerov; Chris L. Fastie; Brad Griffith; Robert D. Hollister; Allen Hope; Henry P. Huntington; Anne M. Jensen; Gensuo J. Jia; et al. (Climatic Change, 2005)

Characterization of two class I genes from the H2-M region: evidence for a new subfamily - S. R. Arepalli; Elsy P. Jones; T. Kevin Howcroft; Irene Carlo; C.-R. Wang; K. Fischer Lindahl; Dinah S. Singer; Stuart Rudikoff (Immunogenetics, 1998)