Review of APSIM's soil nitrogen modelling capability for agricultural systems analyses - Kirsten Verburg; Heather R. Pasley; Jody S. Biggs; Iris Vogeler; Enli Wang; Henrike Mielenz; Val O. Snow; Chris J. Smith; Chiara Pasut; Andrea D. Basche; Di He; Sotirios V. Archontoulis; et al. (Agricultural Systems, 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.

Global patterns in endemicity and vulnerability of soil fungi - Leho Tedersoo; Vladimir Mikryukov; Alexander Zizka; Mohammad Bahram; Niloufar Hagh‐Doust; Sten Anslan; Oleh Prylutskyi; Manuel Delgado‐Baquerizo; Fernando T. Maestre; Jaan Pärn; Maarja Öpik; Mari Moora; et al. (Global Change Biology, 2022)
Fungi are highly diverse organisms, which provide multiple ecosystem services. However, compared with charismatic animals and plants, the distribution patterns and conservation needs of fungi have been little explored. Here, we examined endemicity patterns, global change vulnerability and conservation priority areas for functional groups of soil fungi based on six global surveys using a high‐resolution, long‐read metabarcoding approach. We found that the endemicity of all fungi and most functional groups peaks in tropical habitats, including Amazonia, Yucatan, West‐Central Africa, Sri Lanka, and New Caledonia, with a negligible island effect compared with plants and animals. We also found that fungi are predominantly vulnerable to drought, heat and land‐cover change, particularly in dry tropical regions with high human population density. Fungal conservation areas of highest priority include herbaceous wetlands, tropical forests, and woodlands. We stress that more attention should be focused on the conservation of fungi, especially root symbiotic arbuscular mycorrhizal and ectomycorrhizal fungi in tropical regions as well as unicellular early‐diverging groups and macrofungi in general. Given the low overlap between the endemicity of fungi and macroorganisms, but high conservation needs in both groups, detailed analyses on distribution and conservation requirements are warranted for other microorganisms and soil organisms.

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)

Development and molecular cytogenetic characterization of Thinopyrum bessarabicum introgression lines in hexaploid and tetraploid wheats - Amit K. Singh; Peng Zhang; Chongmei Dong; Jianbo Li; Smriti Singh; Richard M. Trethowan; Peter J. Sharp (Theoretical and Applied Genetics, 2020)

Reference points for predators will progress ecosystem‐based management of fisheries - Simeon L. Hill; Jefferson Hinke; Sophie Bertrand; Lowell Fritz; Robert W. Furness; James N. Ianelli; Matthew Murphy; Ricardo Oliveros‐Ramos; Lorien Pichegru; Rowland Sharp; Richard A. Stillman; Peter J. Wright; et al. (Fish and Fisheries, 2020)
Ecosystem‐based management of fisheries aims to allow sustainable use of fished stocks while keeping impacts upon ecosystems within safe ecological limits. Both the FAO Code of Conduct for Responsible Fisheries and the Aichi Biodiversity Targets promote these aims. We evaluate implementation of ecosystem‐based management in six case‐study fisheries in which potential indirect impacts upon bird or mammal predators of fished stocks are well publicized and well studied. In particular, we consider the components needed to enable management strategies to respond to information from predator monitoring. Although such information is available in all case‐studies, only one has a reference point defining safe ecological limits for predators and none has a method to adjust fishing activities in response to estimates of the state of the predator population. Reference points for predators have been developed outside the fisheries management context, but adoption by fisheries managers is hindered a lack of clarity about management objectives and uncertainty about how fishing affects predator dynamics. This also hinders the development of adjustment methods because these generally require information on the state of ecosystem variables relative to reference points. Nonetheless, most of the case‐studies include precautionary measures to limit impacts on predators. These measures are not used tactically and therefore risk excessive restrictions on sustainable use. Adoption of predator reference points to inform tactical adjustment of precautionary measures would be an appropriate next step towards ecosystem‐based management.

The structure and context of male and female song in White-throated Dippers - Lucy Magoolagan; Peter J. Mawby; Flora A. Whitehead; Stuart P. Sharp (Journal of Ornithology, 2019)

Assessing uncertainties in crop and pasture ensemble model simulations of productivity and N 2 O emissions - Fiona Ehrhardt; Jean‐François Soussana; Gianni Bellocchi; Peter Grace; Russel McAuliffe; Sylvie Recous; Renáta Sándor; Pete Smith; Val Snow; Massimiliano de Antoni Migliorati; Bruno Basso; Arti Bhatia; et al. (Global Change Biology, 2018)
Simulation models are extensively used to predict agricultural productivity and greenhouse gas emissions. However, the uncertainties of (reduced) model ensemble simulations have not been assessed systematically for variables affecting food security and climate change mitigation, within multi‐species agricultural contexts. We report an international model comparison and benchmarking exercise, showing the potential of multi‐model ensembles to predict productivity and nitrous oxide (N 2 O) emissions for wheat, maize, rice and temperate grasslands. Using a multi‐stage modelling protocol, from blind simulations (stage 1) to partial (stages 2–4) and full calibration (stage 5), 24 process‐based biogeochemical models were assessed individually or as an ensemble against long‐term experimental data from four temperate grassland and five arable crop rotation sites spanning four continents. Comparisons were performed by reference to the experimental uncertainties of observed yields and N 2 O emissions. Results showed that across sites and crop/grassland types, 23%–40% of the uncalibrated individual models were within two standard deviations ( SD ) of observed yields, while 42 (rice) to 96% (grasslands) of the models were within 1 SD of observed N 2 O emissions. At stage 1, ensembles formed by the three lowest prediction model errors predicted both yields and N 2 O emissions within experimental uncertainties for 44% and 33% of the crop and grassland growth cycles, respectively. Partial model calibration (stages 2–4) markedly reduced prediction errors of the full model ensemble E‐median for crop grain yields (from 36% at stage 1 down to 4% on average) and grassland productivity (from 44% to 27%) and to a lesser and more variable extent for N 2 O emissions. Yield‐scaled N 2 O emissions (N 2 O emissions divided by crop yields) were ranked accurately by three‐model ensembles across crop species and field sites. The potential of using process‐based model ensembles to predict jointly productivity and N 2 O emissions at field scale is discussed.

In vitro Approaches to Support Bioequivalence and Substitutability of Generic Proton Pump Inhibitors via Nasogastric Tube Administration - Ping Ren; Minglei Cui; Om Anand; Li Xia; Zhuojun J. Zhao; Dajun Sun; Trueman Sharp; Dale P. Conner; John Peters; Wenlei Jiang; Ethan Stier; Xiaojian Jiang (The AAPS Journal, 2017)

Maximizing information from space data resources: a case for expanding integration across research disciplines - Nandu Goswami; Jerry J. Batzel; Gilles Clément; T. Peter Stein; Alan R. Hargens; M. Keith Sharp; Andrew P. Blaber; Peter G. Roma; Helmut G. Hinghofer-Szalkay (European Journal of Applied Physiology, 2013)

Discovery of gonadotropin-inhibitory hormone in a domesticated bird, its mode of action and functional significance - Kazuyoshi Tsutsui; Takayoshi Ubuka; Hong Yin; Tomohiro Osugi; Kazuyoshi Ukena; George E. Bentley; Peter J. Sharp; John C. Wingfield (Journal of Ornithology, 2007)

Diversity arrays technology (DArT) for high-throughput profiling of the hexaploid wheat genome - Mona Akbari; Peter Wenzl; Vanessa Caig; Jason Carling; Ling Xia; Shiying Yang; Grzegorz Uszynski; Volker Mohler; Anke Lehmensiek; Haydn Kuchel; Mathew J. Hayden; Neil Howes; et al. (Theoretical and Applied Genetics, 2006)

A proteomic approach to the identification and characterisation of protein composition in wheat germ - Yunxian Mak; Daniel J. Skylas; Robert Willows; Angela Connolly; Stuart J. Cordwell; Colin W. Wrigley; Peter J. Sharp; Les Copeland (Functional & Integrative Genomics, 2006)

Starch branching enzyme IIb in wheat is expressed at low levels in the endosperm compared to other cereals and encoded at a non-syntenic locus - Ahmed Regina; Behjat Kosar-Hashemi; Zhongyi Li; Andrew Pedler; Yasuhiko Mukai; Maki Yamamoto; Kevin Gale; Peter J. Sharp; Matthew K. Morell; Sadequr Rahman (Planta, 2005)

Genotypic and phenotypic characterization of six new recombinant congenic strains derived from NOD/Shi and CBA/J genomes - Peter C. Reifsnyder; Jeffry C. Flynn; Amanda L. Gavin; Eric A. Simone; John J. Sharp; Lieselotte Herberg; Edward H. Leiter (Mammalian Genome, 1999)