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A process-based evaluation of biases in extratropical stratosphere–troposphere coupling in subseasonal forecast systems
Get PDFFunding: Chaim I. Garfinkel and Jian Rao are supported by the ISF–NSFC joint research program (Israel Science Foundation grant no. 3065/23 and National Natural Science Foundation of China grant no. 42361144843). Chaim I. Garfinkel and Judah Cohen are supported by the NSF–BSF joint research program (National Science Foundation grant no. AGS-2140909 and United States–Israel Binational Science Foundation grant no. 2021714). Irene Erner and Alexey Y. Karpechko are supported by the Research Council of Finland (grant no. 355792). The work of Marisol Osman is supported by UBACyT (project nos. 20020220100075BA, PIP 11220200102038CO, and PICT-2021-GRF-TI-00498). The work of Alvaro de la Cámara is funded by the Spanish Ministry of Science, Innovation and Universities (project no. PID2022-136316NB-I00). Marta Abalos, Blanca Ayarzagüena, and Natalia Calvo are supported by the Spanish Ministry of Science, Innovation and Universities through the RecO3very project (no. PID2021-124772OB-I00). Froila M. Palmeiro and Javier García-Serrano have been partially supported by the Spanish ATLANTE project (no. PID2019-110234RB-C21) and Ramón y Cajal program (no. RYC-2016-21181), respectively. Neil P. Hindley and Corwin J. Wright are supported by the UK Natural Environment Research Council (NERC; grant no. NE/S00985X/1). Corwin J. Wright is also supported by a Royal Society University Research Fellowship (grant no. URF/R/221023). Seok-Woo Son and Hera Kim are supported by the National Research Foundation of Korea (NRF) grant funded by the Korean government (Ministry of Science and Information and Communication Technology, MSIT) (grant no. 2023R1A2C3005607). The work of Rachel W.-Y. Wu is funded through ETH (grant no. ETH-05 19-1). Daniela I. V. Domeisen is supported by the Swiss National Science Foundation (project no. PP00P2_198896). This material is based upon work supported by the U.S. Department of Energy Office of Science Biological and Environmental Research (BER) program Regional and Global Model Analysis (RGMA) component of the Earth and Environment Systems Modeling program (award no. DE-SC0022070) and National Science Foundation (NSF; grant no. IA 1947282). This work was also supported by the National Center for Atmospheric Research (NCAR), which is a major facility sponsored by the NSF (cooperative agreement no. 1852977). Zachary D. Lawrence was partially supported by NOAA (award no. NA20NWS4680051).Two-way coupling between the stratosphere and troposphere is recognized as an important source of subseasonal-to-seasonal (S2S) predictability and can open windows of opportunity for improved forecasts. Model biases can, however, lead to a poor representation of such coupling processes; drifts in a model's circulation related to model biases, resolution, and parameterizations have the potential to feed back on the circulation and affect stratosphere–troposphere coupling. We introduce a set of diagnostics using readily available data that can be used to reveal these biases and then apply these diagnostics to 22 S2S forecast systems. In the Northern Hemisphere, nearly all S2S forecast systems underestimate the strength of the observed upward coupling from the troposphere to the stratosphere, downward coupling within the stratosphere, and the persistence of lower-stratospheric temperature anomalies. While downward coupling from the lower stratosphere to the near surface is well represented in the multi-model ensemble mean, there is substantial intermodel spread likely related to how well each model represents tropospheric stationary waves. In the Southern Hemisphere, the stratospheric vortex is oversensitive to upward-propagating wave flux in the forecast systems. Forecast systems generally overestimate the strength of downward coupling from the lower stratosphere to the troposphere, even as most underestimate the radiative persistence in the lower stratosphere. In both hemispheres, models with higher lids and a better representation of tropospheric quasi-stationary waves generally perform better at simulating these coupling processes.Peer reviewe
Contrasting constructs or continuum? : Examining the dimensionality of body appreciation and body dissatisfaction
Get PDFIndividuals experiencing body dissatisfaction have poorer health outcomes in part due to engaging in less physical activity. Body appreciation is protective of health behaviors and proposed to be conceptually different from body dissatisfaction. Two studies evaluated whether body appreciation and dissatisfaction represented two distinct dimensions, and whether body appreciation and dissatisfaction would interact in their effect on activity-related motivation and behavior. Study 1 (n = 313) was prospective and utilized a self-report measure of physical activity whereas Study 2 (n = 123) was prospective and used an objective measure. All hypotheses and analyses were pre-registered. A multiverse approach was taken to demonstrate the robustness of results. In exploratory factor analyses, body appreciation and dissatisfaction did not represent two distinct dimensions of body image as both loaded onto the same factor. This result was largely supported by latent profile analyses, which revealed that participants scored high, moderate, or low on both body satisfaction and appreciation. Additionally, body appreciation did not buffer the negative impact of body dissatisfaction on activity-related motivation and behavior. This study provides the first statistical evaluation of the theoretical proposition that body appreciation and dissatisfaction may be distinct constructs with distinct relationships to outcomes.Peer reviewe
Trends in marine species distribution models : a review of methodological advances and future challenges
Get PDFFunding: The project that gave rise to these results received the support of a fellowship from the ‘la Caixa' Foundation (ID 100010434) to MK. The fellowship code is (LCF/BQ/DI23/11990054). TAM thanks partial support by CEAUL (funded by FCT – Fundação para a Ciência e a Tecnologia, Portugal, DOI:10.54499/UIDB/00006/2020). FA and MF had the support of FCT throughout the strategic projects UIDB/04292/2020 granted to MARE and LA/P/0069/2020 granted to the Associate Laboratory ARNET. FA was also supported by an FCT research contract under the Scientific Employment Stimulus Call (https://doi.org/10.54499/2023.08949.CEECIND/CP2851/) and MF by the Atlantic Whale Deal project (EAPA_0004/2022) cofinanced by the Interreg Atlantic Area 2021–2027.Correlative species distribution models (SDMs) are quantitative tools in biogeography and macroecology. Building upon the ecological niche concept, they correlate environmental covariates to species presence to model habitat suitability and predict species distributions. Since their development, SDMs have undergone substantial advances in their predictive accuracy, benefiting from increased data availability, advanced machine learning algorithms, novel data integration procedures, refined model validation techniques, and incorporation of biotic predictors. Although initially applied in terrestrial systems, these models are now also widely used in the marine environment, recognized for their value in conservation planning, fisheries management, and understanding species responses to climate variability and change. Despite their increased application, SDMs face unique challenges when applied in the marine environment. These challenges include the three-dimensional complexity of marine ecosystems, the availability of environmental covariates across suitable spatial and temporal scales, the dynamic properties of these covariates, and unique dispersal patterns and mobility traits of marine species. Here, we review recent methodological advances and emerging trends in marine SDMs. We highlight three-dimensional modelling approaches that capture species distributions below the sea surface and assess the importance of temporal resolution, particularly for modelling highly mobile marine species in dynamic marine environments. Further, we discuss the expansion in the types of occurrence data being used, including fishery-dependent and fishery-independent sources, citizen science contributions, and satellite tracking data, along with the methods used to address their associated biases. We also explore and discuss novel methodologies for environmental data collection, such as remote-sensing technologies and numeric ocean models, considering the existing limitations in spatial and temporal resolution. Together, our review synthesizes methodological innovations, highlights ongoing challenges, and discusses emerging trends within the extensive literature on marine SDMs.Peer reviewe
Palladium-catalyzed heteroannulation of Bdan-capped alkynes : rapid access to complex indole scaffolds
Get PDFFunding: J.M.H.-M. and M.V. thank the EaSI-CAT Centre for Doctoral Training for PhD studentships. D.D.R. and A.J.B.W. thank the EPSRC Programme Grant “Boron: Beyond the Reagent” (EP/W007517/1) for support.We report the synthesis of 2-indolylboramides via a palladium (Pd)-catalyzed heteroannulation of 2-iodoaniline derivatives and Bdan-capped alkynes (Bdan, 1,8-diaminonaphthalene boronamide). The process is highly regioselective, affording a diverse range of C2-borylated indoles. The synthetic utility of the process is demonstrated through the concise synthesis of the Tetradium alkaloid skeleton.Peer reviewe
Resolving uncertainties in the legality of wildlife trade to support better outcomes for wildlife and people
Get PDFFunding: This work was supported by the A.G. Leventis Foundation, Africa-Oxford Initiative (AfOx), Levine Family Foundation and UK Research & Innovation's Global Challenges Research Fund (UKRI GCRF).Wildlife use and trade support the livelihoods of millions of people worldwide but also threaten thousands of species. Legal instruments, when effectively designed and implemented, can help regulate trade and mitigate negative impacts. However, activities along supply chains are rarely categorically legal or illegal, with considerable uncertainties regarding legality in the wildlife trade. These uncertainties can compromise the success of efforts to ensure, or improve, sustainability, but are often overlooked. Here, we categorize legal uncertainties in wildlife trade into three dimensions: institutional, operational, and perceptual. We explore their implications for sustainable management and discuss potential interventions to address them, drawing on examples from wildlife management and other sectors. Resolving these uncertainties can reduce unsustainable and illegal trade, strengthen traceability and enforcement, and promote equitable benefit-sharing among actors. Our findings offer actionable insights for policymakers, practitioners, and researchers to improve the clarity and effectiveness of wildlife trade management, advancing both conservation and socio-economic objectives.Peer reviewe
Dysregulated inflammation in solid tumor malignancy patients shapes polyfunctional antibody responses to COVID-19 vaccination
Get PDFFunding: This research was funded in whole or part by the National Health and Medical Research Council (NHMRC). NHMRC EL2 Investigator grant #2008092 was awarded to A.W.C. and NHMRC L2 Investigator grant #2033783 was awarded to K.K. A.K.W., W.S.L., T.H.O.N., K.S., S.J.K., and K.J.S. are also supported by NHMRC Investigator grants. O.H.L.W. is supported by an NHMRC Ideas grant #2029642 to S.J.R. This study was further supported by a Medical Research Future Fund (MRFF) grant #2016062 to J.A.T., A.K.W., T.H.O.N., K.K., S.J.K., and A.W.C. The COVID PROFILE study was supported by WHO Unity funds (2020/1085469-0), and WEHI philanthropic funds. The DISCOVER-HCP study was supported by the National Institute of Allergy and Infectious Diseases, National Institutes of Health, Department of Health and Human Services, Centers of Excellence for Influenza Research and Response (CEIRR) grant #HHSN272201400005C to the University of Rochester and a subcontract to KS. This work was made possible through Victorian State Government Operational Infrastructure Support and Australian Government NHMRC IRIISS.Solid tumor malignancy (STM) patients experience increased risk of breakthrough SARS-CoV-2 infection owing to reduced COVID-19 vaccine immunogenicity. However, the underlying immunological causes of impaired neutralization remain poorly characterized. Furthermore, non-neutralizing antibody functions can contribute to reduced disease severity but remain understudied within high-risk populations. We dissected polyfunctional antibody responses in STM patients and age-matched controls who received adenoviral vector- or mRNA-based COVID-19 vaccine regimens. Elevated inflammatory biomarkers, including agalactosylated IgG, interleukin (IL)-6, IL-18, and an expanded population of CD11c−CD21− double negative 3 (DN3) B cells were observed in STM patients and were associated with impaired neutralization. In contrast, mRNA vaccination induced Fc effector functions that were comparable in patients and controls and were cross-reactive against SARS-CoV-2 variants. These data highlight the resilience of Fc functional antibodies and identify systemic inflammatory biomarkers that may underpin impaired neutralizing antibody responses, suggesting potential avenues for immunomodulation via rational vaccine design.Peer reviewe
Performance of semiempirical DFT methods for the supramolecular assembly of Janus-face cyclohexanes
Get PDFFunding: B. A. P. and R. A. C. acknowledge the São Paulo Research Foundation (FAPESP) for a scholarship (#2022/10156-7 and #2023/14064-2) and a young research award (#2018/03910-1), respectively.A series of GFN-xTB methods were benchmarked against high-level DFT and ab initio thermodynamic data for a set of conformational equilibria and driving forces for the formation of non-covalent complexes involving the Janus-face fluorocyclohexanes based on the all-syn-C6FnR12−n motif (n = 3, 5, 6). When used alone, GFN methods showed moderate performance, with mean absolute errors (MAEs) from the high-level benchmarks of approximately 2.5 kcal mol−1 for conformational equilibria and ∼5.0 kcal mol−1 for molecular complexes. However, applying DFT-level single-point energy corrections on GFN-optimised geometries significantly improved the accuracy, reducing MAEs to ∼0.2 and ∼1.0 kcal mol−1 for the same systems. This hybrid approach achieves DFT-D3-level accuracy while maintaining a low computational cost, offering up to a 50-fold reduction in computational time. As such, it provides a new cost-efficient and accurate tool for the computational modeling of Janus-face systems. An illustrative application to a flexible system, C6F5H6O2C(CH2)3NHCOC6H2(OR)3, is reported (R = alkyl), highlighting the relative stabilities of folded and extended forms and their supramolecular assembly into helical stacks.Peer reviewe
Conference report: The second bacterial genome sequencing Pan-European Network conference
Get PDFFunding: We thank the University of Zurich and the Swedish “Nyckelfonden” - Örebro University hospital research Foundation, Akershus University Hospital, Genomic Medicine Sweden, and the Norwegian Surveillance Programme for Antimicrobial Resistance (NORM) for financial support of the conference. The UK Embassy in Switzerland provided a grant to invite two speakers.Peer reviewe
Volcanic ash drives contrasting redox shifts and biogeochemical feedbacks in ancient marine and lacustrine systems
Get PDFFunding: This work was financially supported by the National Natural Science Foundation of China (Grant Nos. 42325101, 42401182), the Fundamental Research Funds for the Central Universities (Grant No. 2412022QD005), and the Science and Technology Research Project of the Education Department of Jilin Province (Grant No. JJKH20250315KJ).Volcanic eruptions are major perturbations to Earth’s biogeochemical cycles, yet their long-term effects on nutrient dynamics and ecosystem recovery remain unclear. Here we present high-resolution geochemical records from Late Ordovician marine and Middle Triassic lacustrine successions to investigate how airborne volcanic ash influenced carbon and nitrogen cycling. Our results reveal that volcanic ash deposition triggered contrasting redox responses in marine and lacustrine systems. In marine systems, ash input promoted persistent anoxia, suppressed nitrogen cycling, and delayed ecosystem recovery for millennia, and was further amplified by enrichment in toxic elements. In lacustrine systems, ash enhanced water-column oxygenation, reduced toxic stress, which stimulated nitrogen fixation and the growth of cyanobacteria, facilitating ecological recovery within decades. These findings demonstrate that volcanic ash drives contrasting biogeochemical responses in marine and lacustrine ecosystems, provide mechanistic insights into past ecosystem resilience, and offer a framework for predicting recovery under future volcanic and climatic disturbances.Peer reviewe
Exploiting a variational auto-encoder to represent the evolution of sudden stratospheric warmings
Get PDFFunding: Y-C Chen, Y-C Liang, Yih Wang, and Yi-Jhen Zeng are supported by grants from the National Science and Technology Council (110-2111-M-002-019-MY2, 111-2628-M-002-011, and 112-2628-M-002-009) to National Taiwan University. S H Lee acknowledges support from National Science Foundation Grant AGS-1914569 to Columbia University.Sudden stratospheric warmings (SSWs) are the most dramatic events in the wintertime stratosphere. Such extreme events are characterized by substantial disruption to the stratospheric polar vortex, which can be categorized into displacement and splitting types depending on the morphology of the disrupted vortex. Moreover, SSWs are usually followed by anomalous tropospheric circulation regimes that are important for subseasonal-to-seasonal prediction. Thus, monitoring the genesis and evolution of SSWs is crucial and deserves further advancement. Despite several analysis methods that have been used to study the evolution of SSWs, the ability of deep learning methods has not yet been explored, mainly due to the relative scarcity of observed events. To overcome the limited observational sample size, we use data from historical simulations of the Whole Atmosphere Community Climate Model version 6 to identify thousands of simulated SSWs, and use their spatial patterns to train the deep learning model. We utilize a convolutional neural network combined with a variational auto-encoder (VAE)—a generative deep learning model—to construct a phase diagram that characterizes the SSW evolution. This approach not only allows us to create a latent space that encapsulates the essential features of the vortex structure during SSWs, but also offers new insights into its spatiotemporal evolution mapping onto the phase diagram. The constructed phase diagram depicts a continuous transition of the vortex pattern during SSWs. Notably, it provides a new perspective for discussing the evolutionary paths of SSWs: the VAE gives a better-reconstructed vortex morphology and more clearly organized vortex regimes for both displacement-type and split-type events than those obtained from principal component analysis. Our results provide an innovative phase diagram to portray the evolution of SSWs, in which particularly the splitting SSWs are better characterized. Our findings support the future use of deep learning techniques to study the underlying dynamics of extreme stratospheric vortex phenomena, and to establish a benchmark to evaluate model performance in simulating SSWs.Peer reviewe
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