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The following results are related to European Marine Science. Are you interested to view more results? Visit OpenAIRE - Explore.
103 Research products

  • European Marine Science
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  • 2014-2023
  • Open Access
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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/

    {"references": ["Hassell et al., (2020). cfdm: A Python reference implementation of the CF data model. Journal of Open Source Software, 5(54), 2717, https://doi.org/10.21105/joss.02717"]} A Python reference implementation of the CF data model.

    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ ZENODOarrow_drop_down
    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    ZENODO
    Software . 2023
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    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    ZENODO
    Software . 2020
    Data sources: ZENODO
    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    ZENODO
    Software . 2020
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    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    ZENODO
    Software . 2023
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    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    ZENODO
    Software . 2021
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    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    ZENODO
    Software . 2020
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    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    ZENODO
    Software . 2023
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    ZENODO
    Software . 2020
    Data sources: ZENODO
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      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
      ZENODO
      Software . 2020
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      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
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      Software . 2020
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      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
      ZENODO
      Software . 2023
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      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
      ZENODO
      Software . 2021
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      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
      ZENODO
      Software . 2020
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      ZENODO
      Software . 2023
      Data sources: Datacite
      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
      ZENODO
      Software . 2020
      Data sources: ZENODO
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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: Hassell, David; Gregory, Jonathan; Bartholomew, Sadie L.;

    {"references": ["Hassell, D., Gregory, J., Blower, J., Lawrence, B. N., and Taylor, K. E.: A data model of the Climate and Forecast metadata conventions (CF-1.6) with a software implementation (cf-python v2.1), Geosci. Model Dev., 10, 4619\u20134646, https://doi.org/10.5194/gmd-10-4619-2017, 2017.", "Hassell et al., (2020). cfdm: A Python reference implementation of the CF data model. Journal of Open Source Software, 5(54), 2717, https://doi.org/10.21105/joss.02717"]} A CF-compliant Earth Science data analysis library Version 3.14.0 is the first to use Dask.

    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ ZENODOarrow_drop_down
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    ZENODO
    Software . 2023
    Data sources: ZENODO
    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
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    ZENODO
    Software . 2023
    Data sources: Datacite
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      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ ZENODOarrow_drop_down
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      ZENODO
      Software . 2023
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      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
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      ZENODO
      Software . 2023
      Data sources: Datacite
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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: Podbielski, Imke Anna; Schmittmann, Lara; Sanders, Trystan; Melzner, Frank;

    Climate change is predicted to alter salinity in many coastal regions. This exerts significant physiological stress on coastal invertebrates whose body fluid osmolality follows that of seawater ('osmoconformers'). Osmolytes are the cellular actors in osmoconformers that regulate acclimation to salinity changes. Inspite of their cellular importance in salinity tolerance, cellular volume regulation and its osmotic components, are not sufficiently understood. Which compounds are commonly used as osmolytes? Are inorganic and organic osmolytes used in long-term salinity acclimation? Are there taxonomic- or tissue specific differences? By conducting an extensive literature search, this study aimed to answer these questions. By using a meta-analysis approach over an ordinary literature review we were able to statistically evaluate the individual effect sizes by computing a summary effect for multiple studies to estimate the mean of the distribution of the true effect sizes. Meta-analysis is useful to reveal research gaps, common actors across taxa, or overall effects of biotic factors. We thus conducted a systematic review and meta-analysis of osmolyte data (both organic and inorganic) utilized by osmoconforming marine invertebrates during a >14-day acclimation to reduced salinity. This study offers a valuable overview of the various listed organic compounds across species and whether and in which organisms they are used as osmolytes under low salinity stress. This study thereby creates a valuable baseline for future research. 2389 studies were screened according to standard systematic review procedures (title scan, abstract scan and full-exam) resulting a total of 56 studies that fulfilled the search criteria. The data includes the list of all papers that underwent a full-exam in the systematic review process and passed the search criteria and study details of the studies used for meta-analysis. For all included studies the input data necessary to conduct a meta-analysis with a hedge's g effect size is given. Namely, mean osmolyte concentrations, variance measure and replicate numbers are given for the high and low salinity treatment. The data for any benthic osmoconforming species and any osmolyte type is included. The data table is sorted by study but gives additional information on taxonomy, experimental details, study design, osmolyte type, tissue type, etc. Additionally, data is available for a number of studies that reported an extensive osmolyte budget (i.e. multiple compounds). Here, for each study and study organism osmolytes (that were present in more than one study) are listed as percent of the total organic osmolyte pool. This dataset is the first systematically compiled list of studies investigating osmolyte concentrations in osmoconformers after long-term (>14 days) acclimation to low salinity. Data can be used to compare own osmolyte data (species/osmolyte compound) with a comprehensive list of osmolyte literature data. Additionally, this data can be used to address other hypotheses via meta-analysis. As this was a systematic review, no biological samples were collected in this study. Information of the origin of the data from each of the included studies can be found in the list of all included studies.

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    Authors: Romero-Alvarez, Johana; Lupaşcu, Aurelia; Lowe, Douglas; Badia, Alba; +4 Authors

    Tropospheric ozone (O3) concentrations depend on a combination of hemispheric, regional, and local-scale processes. Estimates of how much O3 is produced locally vs. transported from further afield are essential in air quality management and regulatory policies. Here, a tagged-ozone mechanism within the Weather Research and Forecasting model coupled with chemistry (WRF-Chem) is used to quantify the contributions to surface O3 in the UK from anthropogenic nitrogen oxide (NOx) emissions from inside and outside the UK during May–August 2015. The contribution of the different source regions to three regulatory O3 metrics is also examined. It is shown that model simulations predict the concentration and spatial distribution of surface O3 with a domain-wide mean bias of −3.7 ppbv. Anthropogenic NOx emissions from the UK and Europe account for 13 % and 16 %, respectively, of the monthly mean surface O3 in the UK, as the majority (71 %) of O3 originates from the hemispheric background. Hemispheric O3 contributes the most to concentrations in the north and the west of the UK with peaks in May, whereas European and UK contributions are most significant in the east, south-east, and London, i.e. the UK's most populated areas, intensifying towards June and July. Moreover, O3 from European sources is generally transported to the UK rather than produced in situ. It is demonstrated that more stringent emission controls over continental Europe, particularly in western Europe, would be necessary to improve the health-related metric MDA8 O3 above 50 and 60 ppbv. Emission controls over larger areas, such as the Northern Hemisphere, are instead required to lessen the impacts on ecosystems as quantified by the AOT40 metric.

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      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ Atmospheric Chemistr...arrow_drop_down
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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: McLean, Dianne L.; Ferreira, Luciana C.; Benthuysen, Jessica A.; Miller, Karen J.; +42 Authors

    This research was supported by the National Decommissioning Research Initiative (NDRI Australia). We acknowledge the time contribution of all co-authors and additionally via research undertaken through the UKRI INSITE Programme including projects ANChor, CHASANS (NE/T010886/1), EcoConnect, EcoSTAR (NE/T010614/1), FuECoMMS (NE/T010800/1), MAPS, NSERC. DMP was supported through The Marine Alliance for Science and Technology for Scotland (MASTS) funded by the Scottish Funding Council and contributing institutions. SNRB and KH (Cefas) were funded by Cefas and the UK INSITE North Sea programme. Offshore platforms, subsea pipelines, wells and related fixed structures supporting the oil and gas (O&G) industry are prevalent in oceans across the globe, with many approaching the end of their operational life and requiring decommissioning. Although structures can possess high ecological diversity and productivity, information on how they interact with broader ecological processes remains unclear. Here, we review the current state of knowledge on the role of O&G infrastructure in maintaining, altering or enhancing ecological connectivity with natural marine habitats. There is a paucity of studies on the subject with only 33 papers specifically targeting connectivity and O&G structures, although other studies provide important related information. Evidence for O&G structures facilitating vertical and horizontal seascape connectivity exists for larvae and mobile adult invertebrates, fish and megafauna; including threatened and commercially important species. The degree to which these structures represent a beneficial or detrimental net impact remains unclear, is complex and ultimately needs more research to determine the extent to which natural connectivity networks are conserved, enhanced or disrupted. We discuss the potential impacts of different decommissioning approaches on seascape connectivity and identify, through expert elicitation, critical knowledge gaps that, if addressed, may further inform decision making for the life cycle of O&G infrastructure, with relevance for other industries (e.g. renewables). The most highly ranked critical knowledge gap was a need to understand how O&G structures modify and influence the movement patterns of mobile species and dispersal stages of sessile marine species. Understanding how different decommissioning options affect species survival and movement was also highly ranked, as was understanding the extent to which O&G structures contribute to extending species distributions by providing rest stops, foraging habitat, and stepping stones. These questions could be addressed with further dedicated studies of animal movement in relation to structures using telemetry, molecular techniques and movement models. Our review and these priority questions provide a roadmap for advancing research needed to support evidence-based decision making for decommissioning O&G infrastructure. Publisher PDF Peer reviewed

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    Authors: Marwan, Norbert;

    The data file `CENOGRID_Loess_20.txt` contains the astronomically tuned deep-sea benthic foraminifer carbon (������C) and oxygen (�������O) isotope reference records uniformly covering the entire Cenozoic. The first column is the tuned age in Ma, the second column the ������C, and the third column the �������O record. The original calculations were performed using the CRP Toolbox for MATLAB. In order to avoid installing the toolbox and for better performance, the functions for calculating RP and RQA were here reimplemented, providing identical result. To reproduce the RPs in Fig. 2, use the script `perform_rp.m`, for reproducing the determinism values and upper confidence bounds, use the script `perform_rqa.m`. {"references": ["T. Westerhold, N. Marwan, et al: An astronomically dated record of Earth's climate and its predictability over the last 66 million years, Science, 369(6509), 1383\u20131387 (2020)"]}

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    Authors: Healy, Susan D.; Patton, B. Wren;

    But fish cognitive ecology did not begin in rivers and streams. Rather, one of the starting points for work on fish cognitive ecology was work done on the use of visual cues by homing pigeons. Prior to working with fish, Victoria Braithwaite helped to establish that homing pigeons rely not just on magnetic and olfactory cues but also on visual cues for successful return to their home loft. Simple, elegant experiments on homing established Victoria's ability to develop experimental manipulations to examine the role of visual cues in navigation by fish in familiar areas. This work formed the basis of a rich seam of work whereby a fish's ecology was used to propose hypotheses and predictions as to preferred cue use, and then cognitive abilities in a variety of fish species, from model systems (Atlantic salmon and sticklebacks) to the Panamanian Brachyraphis episcopi. Cognitive ecology in fish led to substantial work on fish pain and welfare, but was never left behind, with some of Victoria's last work addressed to determining the neural instantiation of cognitive variation. Publisher PDF Peer reviewed

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    Authors: Valente, André; Sathyendranath, Shubha; Brotas, Vanda; Groom, Steve; +73 Authors

    A global compilation of in situ data is vital to evaluate the quality of ocean-colour satellite data records. Here, we describe data compiled for the validation of ocean-colour products from the ESA Ocean Colour Climate Change Initiative (OC-CCI). The data were acquired from several sources (including, inter alia, MOBY, BOUSSOLE, AERONET-OC, SeaBASS, NOMAD, MERMAID, AMT, ICES, HOT, GeP&CO) and span the period from 1997 to 2021. Observations of the following variables were compiled: spectral remote-sensing reflectance, concentration of chlorophyll-a, spectral inherent optical properties, spectral diffuse attenuation coefficient and total suspended matter. The data were obtained from multi-project archives acquired via open internet services, or from individual projects, acquired directly from data providers. Methodologies were implemented for homogenisation, quality control and merging of all data. No changes were made to the original data, other than averaging of observations that were close in time and space, elimination of some points after quality control and conversion to a standard format. The result is a merged table available in text format. Metadata of each in situ measurement (original source, cruise or experiment, principal investigator) were propagated throughout the work and made available in the final table. By making the metadata available, provenance is better documented, and it is also possible to analyse each set of data separately. This paper also describes the changes that were made to the compilation in relation to the previous version.

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    Authors: Takeshita, Ryan; Bursian, Steven J; Colegrove, Kathleen M; Collier, Tracy K; +23 Authors

    This research was made possible by a grant from The Gulf of Mexico Research Initiative. This publication is UMCES contribution No. 6045 and Ref. No. [UMCES] CBL 2022-008. This is National Marine Mammal Foundation Contribution #314 to peer-reviewed scientific literature. In the wake of the Deepwater Horizon (DWH) oil spill, a number of government agencies, academic institutions, consultants, and nonprofit organizations conducted lab- and field-based research to understand the toxic effects of the oil. Lab testing was performed with a variety of fish, birds, turtles, and vertebrate cell lines (as well as invertebrates); field biologists conducted observations on fish, birds, turtles, and marine mammals; and epidemiologists carried out observational studies in humans. Eight years after the spill, scientists and resource managers held a workshop to summarize the similarities and differences in the effects of DWH oil on vertebrate taxa and to identify remaining gaps in our understanding of oil toxicity in wildlife and humans, building upon the cross-taxonomic synthesis initiated during the Natural Resource Damage Assessment. Across the studies, consistency was found in the types of toxic response observed in the different organisms. Impairment of stress responses and adrenal gland function, cardiotoxicity, immune system dysfunction, disruption of blood cells and their function, effects on locomotion, and oxidative damage were observed across taxa. This consistency suggests conservation in the mechanisms of action and disease pathogenesis. From a toxicological perspective, a logical progression of impacts was noted: from molecular and cellular effects that manifest as organ dysfunction, to systemic effects that compromise fitness, growth, reproductive potential, and survival. From a clinical perspective, adverse health effects from DWH oil spill exposure formed a suite of signs/symptomatic responses that at the highest doses/concentrations resulted in multi-organ system failure. Publisher PDF Peer reviewed

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    Authors: Clyne, Margot; Lamarque, Jean-Francois; Mills, Michael J.; Khodri, Myriam; +19 Authors

    As part of the Model Intercomparison Project on the climatic response to Volcanic forcing (VolMIP), several climate modeling centers performed a coordinated pre-study experiment with interactive stratospheric aerosol models simulating the volcanic aerosol cloud from an eruption resembling the 1815 Mt. Tambora eruption (VolMIP-Tambora ISA ensemble). The pre-study provided the ancillary ability to assess intermodel diversity in the radiative forcing for a large stratospheric-injecting equatorial eruption when the volcanic aerosol cloud is simulated interactively. An initial analysis of the VolMIP-Tambora ISA ensemble showed large disparities between models in the stratospheric global mean aerosol optical depth (AOD). In this study, we now show that stratospheric global mean AOD differences among the participating models are primarily due to differences in aerosol size, which we track here by effective radius. We identify specific physical and chemical processes that are missing in some models and/or parameterized differently between models, which are together causing the differences in effective radius. In particular, our analysis indicates that interactively tracking hydroxyl radical (OH) chemistry following a large volcanic injection of sulfur dioxide (SO2) is an important factor in allowing for the timescale for sulfate formation to be properly simulated. In addition, depending on the timescale of sulfate formation, there can be a large difference in effective radius and subsequently AOD that results from whether the SO2 is injected in a single model grid cell near the location of the volcanic eruption, or whether it is injected as a longitudinally averaged band around the Earth.

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    {"references": ["Hassell et al., (2020). cfdm: A Python reference implementation of the CF data model. Journal of Open Source Software, 5(54), 2717, https://doi.org/10.21105/joss.02717"]} A Python reference implementation of the CF data model.

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    Authors: Hassell, David; Gregory, Jonathan; Bartholomew, Sadie L.;

    {"references": ["Hassell, D., Gregory, J., Blower, J., Lawrence, B. N., and Taylor, K. E.: A data model of the Climate and Forecast metadata conventions (CF-1.6) with a software implementation (cf-python v2.1), Geosci. Model Dev., 10, 4619\u20134646, https://doi.org/10.5194/gmd-10-4619-2017, 2017.", "Hassell et al., (2020). cfdm: A Python reference implementation of the CF data model. Journal of Open Source Software, 5(54), 2717, https://doi.org/10.21105/joss.02717"]} A CF-compliant Earth Science data analysis library Version 3.14.0 is the first to use Dask.

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    Authors: Podbielski, Imke Anna; Schmittmann, Lara; Sanders, Trystan; Melzner, Frank;

    Climate change is predicted to alter salinity in many coastal regions. This exerts significant physiological stress on coastal invertebrates whose body fluid osmolality follows that of seawater ('osmoconformers'). Osmolytes are the cellular actors in osmoconformers that regulate acclimation to salinity changes. Inspite of their cellular importance in salinity tolerance, cellular volume regulation and its osmotic components, are not sufficiently understood. Which compounds are commonly used as osmolytes? Are inorganic and organic osmolytes used in long-term salinity acclimation? Are there taxonomic- or tissue specific differences? By conducting an extensive literature search, this study aimed to answer these questions. By using a meta-analysis approach over an ordinary literature review we were able to statistically evaluate the individual effect sizes by computing a summary effect for multiple studies to estimate the mean of the distribution of the true effect sizes. Meta-analysis is useful to reveal research gaps, common actors across taxa, or overall effects of biotic factors. We thus conducted a systematic review and meta-analysis of osmolyte data (both organic and inorganic) utilized by osmoconforming marine invertebrates during a >14-day acclimation to reduced salinity. This study offers a valuable overview of the various listed organic compounds across species and whether and in which organisms they are used as osmolytes under low salinity stress. This study thereby creates a valuable baseline for future research. 2389 studies were screened according to standard systematic review procedures (title scan, abstract scan and full-exam) resulting a total of 56 studies that fulfilled the search criteria. The data includes the list of all papers that underwent a full-exam in the systematic review process and passed the search criteria and study details of the studies used for meta-analysis. For all included studies the input data necessary to conduct a meta-analysis with a hedge's g effect size is given. Namely, mean osmolyte concentrations, variance measure and replicate numbers are given for the high and low salinity treatment. The data for any benthic osmoconforming species and any osmolyte type is included. The data table is sorted by study but gives additional information on taxonomy, experimental details, study design, osmolyte type, tissue type, etc. Additionally, data is available for a number of studies that reported an extensive osmolyte budget (i.e. multiple compounds). Here, for each study and study organism osmolytes (that were present in more than one study) are listed as percent of the total organic osmolyte pool. This dataset is the first systematically compiled list of studies investigating osmolyte concentrations in osmoconformers after long-term (>14 days) acclimation to low salinity. Data can be used to compare own osmolyte data (species/osmolyte compound) with a comprehensive list of osmolyte literature data. Additionally, this data can be used to address other hypotheses via meta-analysis. As this was a systematic review, no biological samples were collected in this study. Information of the origin of the data from each of the included studies can be found in the list of all included studies.

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    Authors: Romero-Alvarez, Johana; Lupaşcu, Aurelia; Lowe, Douglas; Badia, Alba; +4 Authors

    Tropospheric ozone (O3) concentrations depend on a combination of hemispheric, regional, and local-scale processes. Estimates of how much O3 is produced locally vs. transported from further afield are essential in air quality management and regulatory policies. Here, a tagged-ozone mechanism within the Weather Research and Forecasting model coupled with chemistry (WRF-Chem) is used to quantify the contributions to surface O3 in the UK from anthropogenic nitrogen oxide (NOx) emissions from inside and outside the UK during May–August 2015. The contribution of the different source regions to three regulatory O3 metrics is also examined. It is shown that model simulations predict the concentration and spatial distribution of surface O3 with a domain-wide mean bias of −3.7 ppbv. Anthropogenic NOx emissions from the UK and Europe account for 13 % and 16 %, respectively, of the monthly mean surface O3 in the UK, as the majority (71 %) of O3 originates from the hemispheric background. Hemispheric O3 contributes the most to concentrations in the north and the west of the UK with peaks in May, whereas European and UK contributions are most significant in the east, south-east, and London, i.e. the UK's most populated areas, intensifying towards June and July. Moreover, O3 from European sources is generally transported to the UK rather than produced in situ. It is demonstrated that more stringent emission controls over continental Europe, particularly in western Europe, would be necessary to improve the health-related metric MDA8 O3 above 50 and 60 ppbv. Emission controls over larger areas, such as the Northern Hemisphere, are instead required to lessen the impacts on ecosystems as quantified by the AOT40 metric.

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    Authors: McLean, Dianne L.; Ferreira, Luciana C.; Benthuysen, Jessica A.; Miller, Karen J.; +42 Authors

    This research was supported by the National Decommissioning Research Initiative (NDRI Australia). We acknowledge the time contribution of all co-authors and additionally via research undertaken through the UKRI INSITE Programme including projects ANChor, CHASANS (NE/T010886/1), EcoConnect, EcoSTAR (NE/T010614/1), FuECoMMS (NE/T010800/1), MAPS, NSERC. DMP was supported through The Marine Alliance for Science and Technology for Scotland (MASTS) funded by the Scottish Funding Council and contributing institutions. SNRB and KH (Cefas) were funded by Cefas and the UK INSITE North Sea programme. Offshore platforms, subsea pipelines, wells and related fixed structures supporting the oil and gas (O&G) industry are prevalent in oceans across the globe, with many approaching the end of their operational life and requiring decommissioning. Although structures can possess high ecological diversity and productivity, information on how they interact with broader ecological processes remains unclear. Here, we review the current state of knowledge on the role of O&G infrastructure in maintaining, altering or enhancing ecological connectivity with natural marine habitats. There is a paucity of studies on the subject with only 33 papers specifically targeting connectivity and O&G structures, although other studies provide important related information. Evidence for O&G structures facilitating vertical and horizontal seascape connectivity exists for larvae and mobile adult invertebrates, fish and megafauna; including threatened and commercially important species. The degree to which these structures represent a beneficial or detrimental net impact remains unclear, is complex and ultimately needs more research to determine the extent to which natural connectivity networks are conserved, enhanced or disrupted. We discuss the potential impacts of different decommissioning approaches on seascape connectivity and identify, through expert elicitation, critical knowledge gaps that, if addressed, may further inform decision making for the life cycle of O&G infrastructure, with relevance for other industries (e.g. renewables). The most highly ranked critical knowledge gap was a need to understand how O&G structures modify and influence the movement patterns of mobile species and dispersal stages of sessile marine species. Understanding how different decommissioning options affect species survival and movement was also highly ranked, as was understanding the extent to which O&G structures contribute to extending species distributions by providing rest stops, foraging habitat, and stepping stones. These questions could be addressed with further dedicated studies of animal movement in relation to structures using telemetry, molecular techniques and movement models. Our review and these priority questions provide a roadmap for advancing research needed to support evidence-based decision making for decommissioning O&G infrastructure. Publisher PDF Peer reviewed

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    Authors: Marwan, Norbert;

    The data file `CENOGRID_Loess_20.txt` contains the astronomically tuned deep-sea benthic foraminifer carbon (������C) and oxygen (�������O) isotope reference records uniformly covering the entire Cenozoic. The first column is the tuned age in Ma, the second column the ������C, and the third column the �������O record. The original calculations were performed using the CRP Toolbox for MATLAB. In order to avoid installing the toolbox and for better performance, the functions for calculating RP and RQA were here reimplemented, providing identical result. To reproduce the RPs in Fig. 2, use the script `perform_rp.m`, for reproducing the determinism values and upper confidence bounds, use the script `perform_rqa.m`. {"references": ["T. Westerhold, N. Marwan, et al: An astronomically dated record of Earth's climate and its predictability over the last 66 million years, Science, 369(6509), 1383\u20131387 (2020)"]}

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