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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: Nicolas Metzl; Jonathan Fin; Claire Lo Monaco; Claude Mignon; +30 Authors

    Total alkalinity (AT) and total dissolved inorganic carbon (CT) in the oceans are important properties to understand the ocean carbon cycle and its link with climate change (ocean carbon sinks and sources) or global change (ocean acidification). We present a data-base of more than 44 400 AT and CT observations in various ocean regions obtained since 1993 mainly in the frame of French projects. This includes both surface and water columns data acquired in open oceans, coastal zones and in the Mediterranean Sea and either from time-series or punctual cruises. Most AT and CT data in this synthesis were measured from discrete samples using the same closed-cell potentiometric titration calibrated with Certified Reference Material, with an overall accuracy of ± 4 µmol kg-1 for both AT and CT. Given the lack of observations in the Indian and Southern Oceans, we added sea surface underway AT and CT data obtained in 1998–2018 in the frame of OISO cruises and in 2019 during the CLIM-EPARSES cruise measured onboard using the same technique. Separate datasets for the global ocean, and for the Mediterranean Sea are provided in a single format (https://doi.org/10.17882/95414, Metzl et al., 2023) that offers a direct use for regional or global purposes, e.g. AT/Salinity relationships, long-term CT estimates, constraint and validation of diagnostics CT-AT reconstructed fields or ocean carbon and coupled climate/carbon models simulations, as well as data derived from BG-ARGO floats. When associated with other properties, these data can also be used to calculate pH, fugacity of CO2 (fCO2) and other carbon systems properties to derive ocean acidification rates or air-sea CO2 fluxes.

    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/ Earth System Science...arrow_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/
    Earth System Science Data (ESSD)
    Other literature type . 2023
    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/
    https://doi.org/10.5194/essd-2...
    Preprint . 2023 . Peer-reviewed
    License: CC BY
    Data sources: Crossref
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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: Panaïotis, Thelma; Babin, Marcel; Biard, Tristan; Carlotti, François; +12 Authors

    AbstractAimThe distribution of mesoplankton communities has been poorly studied at global scale, especially from in situ instruments. This study aims to (1) describe the global distribution of mesoplankton communities in relation to their environment and (2) assess the ability of various environmental‐based ocean regionalizations to explain the distribution of these communities.LocationGlobal ocean, 0–500 m depth.Time Period2008–2019.Major Taxa StudiedTwenty‐eight groups of large mesoplanktonic and macroplanktonic organisms, covering Metazoa, Rhizaria and Cyanobacteria.MethodsFrom a global data set of 2500 vertical profiles making use of the Underwater Vision Profiler 5 (UVP5), an in situ imaging instrument, we studied the global distribution of large (>600 μm) mesoplanktonic organisms. Among the 6.8 million imaged objects, 330,000 were large zooplanktonic organisms and phytoplankton colonies, the rest consisting of marine snow particles. Multivariate ordination (PCA) and clustering were used to describe patterns in community composition, while comparison with existing regionalizations was performed with regression methods (RDA).ResultsWithin the observed size range, epipelagic plankton communities were Trichodesmium‐enriched in the intertropical Atlantic, Copepoda‐enriched at high latitudes and in upwelling areas, and Rhizaria‐enriched in oligotrophic areas. In the mesopelagic layer, Copepoda‐enriched communities were also found at high latitudes and in the Atlantic Ocean, while Rhizaria‐enriched communities prevailed in the Peruvian upwelling system and a few mixed communities were found elsewhere. The comparison between the distribution of these communities and a set of existing regionalizations of the ocean suggested that the structure of plankton communities described above is mostly driven by basin‐level environmental conditions.Main ConclusionsIn both layers, three types of plankton communities emerged and seemed to be mostly driven by regional environmental conditions. This work sheds light on the role not only of metazoans, but also of unexpected large protists and cyanobacteria in structuring large mesoplankton communities.

    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/ Global Ecology and B...arrow_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/
    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/
    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/
    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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  • 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: Rubbens, Peter; Brodie, Stephanie; Cordier, Tristan; Destro Barcellos, Diogo; +35 Authors

    Machine learning covers a large set of algorithms that can be trained to identify patterns in data. Thanks to the increase in the amount of data and computing power available, it has become pervasive across scientific disciplines. We first highlight why machine learning is needed in marine ecology. Then we provide a quick primer on machine learning techniques and vocabulary. We built a database of ∼1000 publications that implement such techniques to analyse marine ecology data. For various data types (images, optical spectra, acoustics, omics, geolocations, biogeochemical profiles, and satellite imagery), we present a historical perspective on applications that proved influential, can serve as templates for new work, or represent the diversity of approaches. Then, we illustrate how machine learning can be used to better understand ecological systems, by combining various sources of marine data. Through this coverage of the literature, we demonstrate an increase in the proportion of marine ecology studies that use machine learning, the pervasiveness of images as a data source, the dominance of machine learning for classification-type problems, and a shift towards deep learning for all data types. This overview is meant to guide researchers who wish to apply machine learning methods to their marine datasets. Machine learning in marine ecology: an overview of techniques and applications

    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/ OceanReparrow_drop_down
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    OceanRep
    Article . 2023 . Peer-reviewed
    Data sources: OceanRep
    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/
    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/
    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/
    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/
    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/
    Lille Open Archive
    Review . 2023
    Data sources: Lille Open Archive
    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/
    Research@WUR
    Other literature type . 2023
    License: CC BY
    Data sources: Research@WUR
    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/
    Brage IMR
    Article . 2023
    Data sources: Brage IMR
    image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
    HAL AMU
    Article . 2023
    Data sources: HAL AMU
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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/ OceanReparrow_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/
      OceanRep
      Article . 2023 . Peer-reviewed
      Data sources: OceanRep
      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/
      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/
      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/
      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/
      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/
      Lille Open Archive
      Review . 2023
      Data sources: Lille Open Archive
      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/
      Research@WUR
      Other literature type . 2023
      License: CC BY
      Data sources: Research@WUR
      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/
      Brage IMR
      Article . 2023
      Data sources: Brage IMR
      image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
      HAL AMU
      Article . 2023
      Data sources: HAL AMU
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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: Oliver W. Moore; Lisa Curti; Clare Woulds; James A. Bradley; +10 Authors

    AbstractThe balance between degradation and preservation of sedimentary organic carbon (OC) is important for global carbon and oxygen cycles1. The relative importance of different mechanisms and environmental conditions contributing to marine sedimentary OC preservation, however, remains unclear2–8. Simple organic molecules can be geopolymerized into recalcitrant forms by means of the Maillard reaction5, although reaction kinetics at marine sedimentary temperatures are thought to be slow9,10. More recent work in terrestrial systems suggests that the reaction can be catalysed by manganese minerals11–13, but the potential for the promotion of geopolymerized OC formation at marine sedimentary temperatures is uncertain. Here we present incubation experiments and find that iron and manganese ions and minerals abiotically catalyse the Maillard reaction by up to two orders of magnitude at temperatures relevant to continental margins where most preservation occurs4. Furthermore, the chemical signature of the reaction products closely resembles dissolved and total OC found in continental margin sediments globally. With the aid of a pore-water model14, we estimate that iron- and manganese-catalysed transformation of simple organic molecules into complex macromolecules might generate on the order of approximately 4.1 Tg C yr−1 for preservation in marine sediments. In the context of perhaps only about 63 Tg C yr−1 variation in sedimentary organic preservation over the past 300 million years6, we propose that variable iron and manganese inputs to the ocean could exert a substantial but hitherto unexplored impact on global OC preservation over geological time.

    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/ OceanRep; Naturearrow_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/
    HAL AMU
    Article . 2023
    Data sources: HAL AMU
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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/ OceanRep; Naturearrow_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/
      HAL AMU
      Article . 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/
    Authors: Soto, Ismael; Cuthbert, Ross N.; Ahmed, Danish A.; Kouba, Antonín; +28 Authors

    AbstractAimInvasive alien species are a growing problem worldwide due to their ecological, economic and human health impacts. The “killer shrimp” Dikerogammarus villosus is a notorious invasive alien amphipod from the Ponto‐Caspian region that has invaded many fresh and brackish waters across Europe. Understandings of large‐scale population dynamics of highly impactful invaders such as D. villosus are lacking, inhibiting predictions of impact and efficient timing of management strategies. Hence, our aim was to assess trends and dynamics of D. villosus as well as its impacts in freshwater rivers and streams.LocationEurope.MethodsWe analysed 96 European time series between 1994 and 2019 and identified trends in the relative abundance (i.e. dominance %) of D. villosus in invaded time series, as well as a set of site‐specific characteristics to identify drivers and determinants of population changes and invasion dynamics using meta‐regression modelling. We also looked at the spread over space and time to estimate the invasion speed (km/year) of D. villosus in Europe. We investigated the impact of D. villosus abundance on recipient community metrics (i.e. abundance, taxa richness, temporal turnover, Shannon diversity and Pielou evenness) using generalized linear models.ResultsPopulation trends varied across the time series. Nevertheless, community dominance of D. villosus increased over time across all time series. The frequency of occurrences (used as a proxy for invader spread) was well described by a Pareto distribution, whereby we estimated a lag phase (i.e. the time between introduction and spatial expansion) of approximately 28 years, followed by a gradual increase before new occurrences declined rapidly in the long term. D. villosus population change was associated with decreased taxa richness, community turnover and Shannon diversity.Main ConclusionOur results show that D. villosus is well‐established in European waters and its abundance significantly alters ecological communities. However, the multidecadal lag phase prior to observed spatial expansion suggests that initial introductions by D. villosus are cryptic, thus signalling the need for more effective early detection methods.

    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/ NARCIS; Research@WURarrow_drop_down
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    Other literature type . Article . 2023
    License: CC BY
    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/
    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/
    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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  • 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: Xibin Lu; Jean-Marie Tarascon; Jiaqiang Huang;

    International audience; The battery is an indispensable puzzle in the current roadmap towards a carbon-neutral world. With the soaring production, the battery itself is unexpectedly becoming a sustainability problem for society. Increasing attention is thus placed on the life cycle of batteries entailing the second life and recycling of batteries, relying on the monitoring of batteries' state and the classification of retired batteries by sensors. Battery sensors that decode the fundamental physical/chemical processes are thus poised to maximize the quality, reliability, lifetime, and safety of batteries and to minimize the environmental footprint. Fiber optic sensors stand out by virtue of their miniature size, insulating nature, electromagnetic immunity, and versatile sensitivities. In this Perspective, we discuss the promise and challenges of commercializing smart sensing for batteries and highlight how fiber optic sensors can synergize with paradigm shifts, including cell to pack and cell to chassis technologies.

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    Authors: Baños, Isabel; Arístegui, Javier; Benavides, Mar; Gómez-Letona, Markel; +5 Authors

    Climate change is expected to alter the intensity and frequency of upwelling in high productive coastal regions, thus impacting nutrient fluxes, primary productivity and consequently carbon cycling. However, it is unknown how these changes will impact the planktonic (phytoplankton and bacteria) community structure, which affects community respiration (CR) and hence the carbon available for sequestration or transfer to upper trophic levels. Here we present results from a 37-day mesocosm experiment where we examined the response of CR to nutrient additions by simulating upwelling events at different intensities (low, medium, high and extreme) and modes (singular and recurring additions). We also analysed the potential contribution of different plankton size classes and functional groups to CR. The trend in accumulated CR with respect to nutrient fertilisation (total nitrogen added during the experiment) was linear in the two modes. Microplankton (mostly diatoms) and nanoplankton (small flagellates) dominated under extreme upwelling intensities and high CR in both singular and recurring upwelling modes, explaining >65% of the observed variability in CR. In contrast, prokaryotic picoplankton (heterotrophic bacteria and autotrophic cyanobacteria) explained <43% of the variance in CR under the rest of the upwelling intensities and modes tested. Changes in planktonic community structure, while modulating CR variability, would regulate the metabolic balance of the ecosystem, shifting it towards net-heterotrophy when the community is dominated by small heterotrophs and to net-autotrophy when large autotrophs prevail; although depending on the mode in which nutrients are supplied to the system. This shift in the dominance of planktonic organism will hence affect not only CR but also carbon sequestration in upwelling regions

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    Authors: Silva, Fabio; Coward, Fiona; Davies, Kimberley; Elliott, Sarah; +32 Authors

    Human beings are an active component of every terrestrial ecosystem on Earth. Although our local impact on the evolution of these ecosystems has been undeniable and extensively documented, it remains unclear precisely how our activities are altering them, in part because ecosystems are dynamic systems structured by complex, non-linear feedback processes and cascading effects. We argue that it is only by studying human–environment interactions over timescales that greatly exceed the lifespan of any individual human (i.e., the deep past or longue durée), we can hope to fully understand such processes and their implications. In this article, we identify some of the key challenges faced in integrating long-term datasets with those of other areas of sustainability science, and suggest some useful ways forward. Specifically, we (a) highlight the potential of the historical sciences for sustainability science, (b) stress the need to integrate theoretical frameworks wherein humans are seen as inherently entangled with the environment, and (c) propose formal computational modelling as the ideal platform to overcome the challenges of transdisciplinary work across large, and multiple, geographical and temporal scales. Our goal is to provide a manifesto for an integrated scientific approach to the study of socio-ecological systems over the long term. 1. Introduction 2. The Importance of the Longue Durée 3. The Knotty Problem of Humans 4. Transdisciplinary Integration through Computational Modelling 4.1. Modelling as a Platform 4.2. Data Challenges 4.3. The Question of Scale 5. The (Im)practicalities of Transdisciplinarity 6. Concluding Remarks

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    Sustainability
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    Apollo
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    Authors: Laetitia Drago; Thelma Panaïotis; Jean-Olivier Irisson; Marcel Babin; +16 Authors

    Zooplankton plays a major role in ocean food webs and biogeochemical cycles, and provides major ecosystem services as a main driver of the biological carbon pump and in sustaining fish communities. Zooplankton is also sensitive to its environment and reacts to its changes. To better understand the importance of zooplankton, and to inform prognostic models that try to represent them, spatially-resolved biomass estimates of key plankton taxa are desirable. In this study we predict, for the first time, the global biomass distribution of 19 zooplankton taxa (1-50 mm Equivalent Spherical Diameter) using observations with the Underwater Vision Profiler 5, a quantitative in situ imaging instrument. After classification of 466,872 organisms from more than 3,549 profiles (0-500 m) obtained between 2008 and 2019 throughout the globe, we estimated their individual biovolumes and converted them to biomass using taxa-specific conversion factors. We then associated these biomass estimates with climatologies of environmental variables (temperature, salinity, oxygen, etc.), to build habitat models using boosted regression trees. The results reveal maximal zooplankton biomass values around 60°N and 55°S as well as minimal values around the oceanic gyres. An increased zooplankton biomass is also predicted for the equator. Global integrated biomass (0-500 m) was estimated at 0.403 PgC. It was largely dominated by Copepoda (35.7%, mostly in polar regions), followed by Eumalacostraca (26.6%) Rhizaria (16.4%, mostly in the intertropical convergence zone). The machine learning approach used here is sensitive to the size of the training set and generates reliable predictions for abundant groups such as Copepoda (R2 ≈ 20-66%) but not for rare ones (Ctenophora, Cnidaria, R2 < 5%). Still, this study offers a first protocol to estimate global, spatially resolved zooplankton biomass and community composition from in situ imaging observations of individual organisms. The underlying dataset covers a period of 10 years while approaches that rely on net samples utilized datasets gathered since the 1960s. Increased use of digital imaging approaches should enable us to obtain zooplankton biomass distribution estimates at basin to global scales in shorter time frames in the future.

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    Authors: Haubrock, Phillip J.; Ahmed, Danish A.; Cuthbert, Ross N.; Stubbington, Rachel; +36 Authors

    Globalization has led to the introduction of thousands of alien species worldwide. With growing impacts by invasive species, understanding the invasion process remains critical for predicting adverse effects and informing efficient management. Theoretically, invasion dynamics have been assumed to follow an “invasion curve” (S-shaped curve of available area invaded over time), but this dynamic has lacked empirical testing using large-scale data and neglects to consider invader abundances. We propose an “impact curve” describing the impacts generated by invasive species over time based on cumulative abundances. To test this curve's large-scale applicability, we used the data-rich New Zealand mud snail Potamopyrgus antipodarum, one of the most damaging freshwater invaders that has invaded almost all of Europe. Using long-term (1979–2020) abundance and environmental data collected across 306 European sites, we observed that P. antipodarum abundance generally increased through time, with slower population growth at higher latitudes and with lower runoff depth. Fifty-nine percent of these populations followed the impact curve, characterized by first occurrence, exponential growth, then long-term saturation. This behaviour is consistent with boom-bust dynamics, as saturation occurs due to a rapid decline in abundance over time. Across sites, we estimated that impact peaked approximately two decades after first detection, but the rate of progression along the invasion process was influenced by local abiotic conditions. The S-shaped impact curve may be common among many invasive species that undergo complex invasion dynamics. This provides a potentially unifying approach to advance understanding of large-scale invasion dynamics and could inform timely management actions to mitigate impacts on ecosystems and economies. Bundesministerium für Bildung und Forschung http://dx.doi.org/10.13039/501100002347 Horizon 2020 Framework Programme http://dx.doi.org/10.13039/100010661 Kuwait Foundation for the Advancement of Sciences http://dx.doi.org/10.13039/501100003286 Leibniz Competition Leverhulme Trust http://dx.doi.org/10.13039/501100000275 Alexander von Humboldt Foundation http://dx.doi.org/10.13039/100005156 Gulf University for Science and Technology (GUST) http://dx.doi.org/10.13039/100016753 Peer Reviewed

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    Estudo Geral
    Article . 2022
    Data sources: Estudo Geral
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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: Nicolas Metzl; Jonathan Fin; Claire Lo Monaco; Claude Mignon; +30 Authors

    Total alkalinity (AT) and total dissolved inorganic carbon (CT) in the oceans are important properties to understand the ocean carbon cycle and its link with climate change (ocean carbon sinks and sources) or global change (ocean acidification). We present a data-base of more than 44 400 AT and CT observations in various ocean regions obtained since 1993 mainly in the frame of French projects. This includes both surface and water columns data acquired in open oceans, coastal zones and in the Mediterranean Sea and either from time-series or punctual cruises. Most AT and CT data in this synthesis were measured from discrete samples using the same closed-cell potentiometric titration calibrated with Certified Reference Material, with an overall accuracy of ± 4 µmol kg-1 for both AT and CT. Given the lack of observations in the Indian and Southern Oceans, we added sea surface underway AT and CT data obtained in 1998–2018 in the frame of OISO cruises and in 2019 during the CLIM-EPARSES cruise measured onboard using the same technique. Separate datasets for the global ocean, and for the Mediterranean Sea are provided in a single format (https://doi.org/10.17882/95414, Metzl et al., 2023) that offers a direct use for regional or global purposes, e.g. AT/Salinity relationships, long-term CT estimates, constraint and validation of diagnostics CT-AT reconstructed fields or ocean carbon and coupled climate/carbon models simulations, as well as data derived from BG-ARGO floats. When associated with other properties, these data can also be used to calculate pH, fugacity of CO2 (fCO2) and other carbon systems properties to derive ocean acidification rates or air-sea CO2 fluxes.

    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/ Earth System Science...arrow_drop_down
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    Earth System Science Data (ESSD)
    Other literature type . 2023
    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/
    https://doi.org/10.5194/essd-2...
    Preprint . 2023 . Peer-reviewed
    License: CC BY
    Data sources: Crossref
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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: Panaïotis, Thelma; Babin, Marcel; Biard, Tristan; Carlotti, François; +12 Authors

    AbstractAimThe distribution of mesoplankton communities has been poorly studied at global scale, especially from in situ instruments. This study aims to (1) describe the global distribution of mesoplankton communities in relation to their environment and (2) assess the ability of various environmental‐based ocean regionalizations to explain the distribution of these communities.LocationGlobal ocean, 0–500 m depth.Time Period2008–2019.Major Taxa StudiedTwenty‐eight groups of large mesoplanktonic and macroplanktonic organisms, covering Metazoa, Rhizaria and Cyanobacteria.MethodsFrom a global data set of 2500 vertical profiles making use of the Underwater Vision Profiler 5 (UVP5), an in situ imaging instrument, we studied the global distribution of large (>600 μm) mesoplanktonic organisms. Among the 6.8 million imaged objects, 330,000 were large zooplanktonic organisms and phytoplankton colonies, the rest consisting of marine snow particles. Multivariate ordination (PCA) and clustering were used to describe patterns in community composition, while comparison with existing regionalizations was performed with regression methods (RDA).ResultsWithin the observed size range, epipelagic plankton communities were Trichodesmium‐enriched in the intertropical Atlantic, Copepoda‐enriched at high latitudes and in upwelling areas, and Rhizaria‐enriched in oligotrophic areas. In the mesopelagic layer, Copepoda‐enriched communities were also found at high latitudes and in the Atlantic Ocean, while Rhizaria‐enriched communities prevailed in the Peruvian upwelling system and a few mixed communities were found elsewhere. The comparison between the distribution of these communities and a set of existing regionalizations of the ocean suggested that the structure of plankton communities described above is mostly driven by basin‐level environmental conditions.Main ConclusionsIn both layers, three types of plankton communities emerged and seemed to be mostly driven by regional environmental conditions. This work sheds light on the role not only of metazoans, but also of unexpected large protists and cyanobacteria in structuring large mesoplankton communities.

    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/ Global Ecology and B...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: Rubbens, Peter; Brodie, Stephanie; Cordier, Tristan; Destro Barcellos, Diogo; +35 Authors

    Machine learning covers a large set of algorithms that can be trained to identify patterns in data. Thanks to the increase in the amount of data and computing power available, it has become pervasive across scientific disciplines. We first highlight why machine learning is needed in marine ecology. Then we provide a quick primer on machine learning techniques and vocabulary. We built a database of ∼1000 publications that implement such techniques to analyse marine ecology data. For various data types (images, optical spectra, acoustics, omics, geolocations, biogeochemical profiles, and satellite imagery), we present a historical perspective on applications that proved influential, can serve as templates for new work, or represent the diversity of approaches. Then, we illustrate how machine learning can be used to better understand ecological systems, by combining various sources of marine data. Through this coverage of the literature, we demonstrate an increase in the proportion of marine ecology studies that use machine learning, the pervasiveness of images as a data source, the dominance of machine learning for classification-type problems, and a shift towards deep learning for all data types. This overview is meant to guide researchers who wish to apply machine learning methods to their marine datasets. Machine learning in marine ecology: an overview of techniques and applications

    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/ OceanReparrow_drop_down
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    OceanRep
    Article . 2023 . Peer-reviewed
    Data sources: OceanRep
    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/
    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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    Lille Open Archive
    Review . 2023
    Data sources: Lille Open Archive
    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/
    Research@WUR
    Other literature type . 2023
    License: CC BY
    Data sources: Research@WUR
    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/
    Brage IMR
    Article . 2023
    Data sources: Brage IMR
    image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
    HAL AMU
    Article . 2023
    Data sources: HAL AMU
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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/ OceanReparrow_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/
      OceanRep
      Article . 2023 . Peer-reviewed
      Data sources: OceanRep
      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/
      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/
      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/
      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/
      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/
      Lille Open Archive
      Review . 2023
      Data sources: Lille Open Archive
      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/
      Research@WUR
      Other literature type . 2023
      License: CC BY
      Data sources: Research@WUR
      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/
      Brage IMR
      Article . 2023
      Data sources: Brage IMR
      image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
      HAL AMU
      Article . 2023
      Data sources: HAL AMU
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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: Oliver W. Moore; Lisa Curti; Clare Woulds; James A. Bradley; +10 Authors

    AbstractThe balance between degradation and preservation of sedimentary organic carbon (OC) is important for global carbon and oxygen cycles1. The relative importance of different mechanisms and environmental conditions contributing to marine sedimentary OC preservation, however, remains unclear2–8. Simple organic molecules can be geopolymerized into recalcitrant forms by means of the Maillard reaction5, although reaction kinetics at marine sedimentary temperatures are thought to be slow9,10. More recent work in terrestrial systems suggests that the reaction can be catalysed by manganese minerals11–13, but the potential for the promotion of geopolymerized OC formation at marine sedimentary temperatures is uncertain. Here we present incubation experiments and find that iron and manganese ions and minerals abiotically catalyse the Maillard reaction by up to two orders of magnitude at temperatures relevant to continental margins where most preservation occurs4. Furthermore, the chemical signature of the reaction products closely resembles dissolved and total OC found in continental margin sediments globally. With the aid of a pore-water model14, we estimate that iron- and manganese-catalysed transformation of simple organic molecules into complex macromolecules might generate on the order of approximately 4.1 Tg C yr−1 for preservation in marine sediments. In the context of perhaps only about 63 Tg C yr−1 variation in sedimentary organic preservation over the past 300 million years6, we propose that variable iron and manganese inputs to the ocean could exert a substantial but hitherto unexplored impact on global OC preservation over geological time.

    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/ OceanRep; Naturearrow_drop_down
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    HAL AMU
    Article . 2023
    Data sources: HAL AMU
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      HAL AMU
      Article . 2023
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    Authors: Soto, Ismael; Cuthbert, Ross N.; Ahmed, Danish A.; Kouba, Antonín; +28 Authors

    AbstractAimInvasive alien species are a growing problem worldwide due to their ecological, economic and human health impacts. The “killer shrimp” Dikerogammarus villosus is a notorious invasive alien amphipod from the Ponto‐Caspian region that has invaded many fresh and brackish waters across Europe. Understandings of large‐scale population dynamics of highly impactful invaders such as D. villosus are lacking, inhibiting predictions of impact and efficient timing of management strategies. Hence, our aim was to assess trends and dynamics of D. villosus as well as its impacts in freshwater rivers and streams.LocationEurope.MethodsWe analysed 96 European time series between 1994 and 2019 and identified trends in the relative abundance (i.e. dominance %) of D. villosus in invaded time series, as well as a set of site‐specific characteristics to identify drivers and determinants of population changes and invasion dynamics using meta‐regression modelling. We also looked at the spread over space and time to estimate the invasion speed (km/year) of D. villosus in Europe. We investigated the impact of D. villosus abundance on recipient community metrics (i.e. abundance, taxa richness, temporal turnover, Shannon diversity and Pielou evenness) using generalized linear models.ResultsPopulation trends varied across the time series. Nevertheless, community dominance of D. villosus increased over time across all time series. The frequency of occurrences (used as a proxy for invader spread) was well described by a Pareto distribution, whereby we estimated a lag phase (i.e. the time between introduction and spatial expansion) of approximately 28 years, followed by a gradual increase before new occurrences declined rapidly in the long term. D. villosus population change was associated with decreased taxa richness, community turnover and Shannon diversity.Main ConclusionOur results show that D. villosus is well‐established in European waters and its abundance significantly alters ecological communities. However, the multidecadal lag phase prior to observed spatial expansion suggests that initial introductions by D. villosus are cryptic, thus signalling the need for more effective early detection methods.

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    Other literature type . Article . 2023
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    Authors: Xibin Lu; Jean-Marie Tarascon; Jiaqiang Huang;

    International audience; The battery is an indispensable puzzle in the current roadmap towards a carbon-neutral world. With the soaring production, the battery itself is unexpectedly becoming a sustainability problem for society. Increasing attention is thus placed on the life cycle of batteries entailing the second life and recycling of batteries, relying on the monitoring of batteries' state and the classification of retired batteries by sensors. Battery sensors that decode the fundamental physical/chemical processes are thus poised to maximize the quality, reliability, lifetime, and safety of batteries and to minimize the environmental footprint. Fiber optic sensors stand out by virtue of their miniature size, insulating nature, electromagnetic immunity, and versatile sensitivities. In this Perspective, we discuss the promise and challenges of commercializing smart sensing for batteries and highlight how fiber optic sensors can synergize with paradigm shifts, including cell to pack and cell to chassis technologies.

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    Authors: Baños, Isabel; Arístegui, Javier; Benavides, Mar; Gómez-Letona, Markel; +5 Authors

    Climate change is expected to alter the intensity and frequency of upwelling in high productive coastal regions, thus impacting nutrient fluxes, primary productivity and consequently carbon cycling. However, it is unknown how these changes will impact the planktonic (phytoplankton and bacteria) community structure, which affects community respiration (CR) and hence the carbon available for sequestration or transfer to upper trophic levels. Here we present results from a 37-day mesocosm experiment where we examined the response of CR to nutrient additions by simulating upwelling events at different intensities (low, medium, high and extreme) and modes (singular and recurring additions). We also analysed the potential contribution of different plankton size classes and functional groups to CR. The trend in accumulated CR with respect to nutrient fertilisation (total nitrogen added during the experiment) was linear in the two modes. Microplankton (mostly diatoms) and nanoplankton (small flagellates) dominated under extreme upwelling intensities and high CR in both singular and recurring upwelling modes, explaining >65% of the observed variability in CR. In contrast, prokaryotic picoplankton (heterotrophic bacteria and autotrophic cyanobacteria) explained <43% of the variance in CR under the rest of the upwelling intensities and modes tested. Changes in planktonic community structure, while modulating CR variability, would regulate the metabolic balance of the ecosystem, shifting it towards net-heterotrophy when the community is dominated by small heterotrophs and to net-autotrophy when large autotrophs prevail; although depending on the mode in which nutrients are supplied to the system. This shift in the dominance of planktonic organism will hence affect not only CR but also carbon sequestration in upwelling regions

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    Authors: Silva, Fabio; Coward, Fiona; Davies, Kimberley; Elliott, Sarah; +32 Authors

    Human beings are an active component of every terrestrial ecosystem on Earth. Although our local impact on the evolution of these ecosystems has been undeniable and extensively documented, it remains unclear precisely how our activities are altering them, in part because ecosystems are dynamic systems structured by complex, non-linear feedback processes and cascading effects. We argue that it is only by studying human–environment interactions over timescales that greatly exceed the lifespan of any individual human (i.e., the deep past or longue durée), we can hope to fully understand such processes and their implications. In this article, we identify some of the key challenges faced in integrating long-term datasets with those of other areas of sustainability science, and suggest some useful ways forward. Specifically, we (a) highlight the potential of the historical sciences for sustainability science, (b) stress the need to integrate theoretical frameworks wherein humans are seen as inherently entangled with the environment, and (c) propose formal computational modelling as the ideal platform to overcome the challenges of transdisciplinary work across large, and multiple, geographical and temporal scales. Our goal is to provide a manifesto for an integrated scientific approach to the study of socio-ecological systems over the long term. 1. Introduction 2. The Importance of the Longue Durée 3. The Knotty Problem of Humans 4. Transdisciplinary Integration through Computational Modelling 4.1. Modelling as a Platform 4.2. Data Challenges 4.3. The Question of Scale 5. The (Im)practicalities of Transdisciplinarity 6. Concluding Remarks

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    Sustainability
    Other literature type . Article . 2022 . Peer-reviewed
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    Apollo
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    Authors: Laetitia Drago; Thelma Panaïotis; Jean-Olivier Irisson; Marcel Babin; +16 Authors

    Zooplankton plays a major role in ocean food webs and biogeochemical cycles, and provides major ecosystem services as a main driver of the biological carbon pump and in sustaining fish communities. Zooplankton is also sensitive to its environment and reacts to its changes. To better understand the importance of zooplankton, and to inform prognostic models that try to represent them, spatially-resolved biomass estimates of key plankton taxa are desirable. In this study we predict, for the first time, the global biomass distribution of 19 zooplankton taxa (1-50 mm Equivalent Spherical Diameter) using observations with the Underwater Vision Profiler 5, a quantitative in situ imaging instrument. After classification of 466,872 organisms from more than 3,549 profiles (0-500 m) obtained between 2008 and 2019 throughout the globe, we estimated their individual biovolumes and converted them to biomass using taxa-specific conversion factors. We then associated these biomass estimates with climatologies of environmental variables (temperature, salinity, oxygen, etc.), to build habitat models using boosted regression trees. The results reveal maximal zooplankton biomass values around 60°N and 55°S as well as minimal values around the oceanic gyres. An increased zooplankton biomass is also predicted for the equator. Global integrated biomass (0-500 m) was estimated at 0.403 PgC. It was largely dominated by Copepoda (35.7%, mostly in polar regions), followed by Eumalacostraca (26.6%) Rhizaria (16.4%, mostly in the intertropical convergence zone). The machine learning approach used here is sensitive to the size of the training set and generates reliable predictions for abundant groups such as Copepoda (R2 ≈ 20-66%) but not for rare ones (Ctenophora, Cnidaria, R2 < 5%). Still, this study offers a first protocol to estimate global, spatially resolved zooplankton biomass and community composition from in situ imaging observations of individual organisms. The underlying dataset covers a period of 10 years while approaches that rely on net samples utilized datasets gathered since the 1960s. Increased use of digital imaging approaches should enable us to obtain zooplankton biomass distribution estimates at basin to global scales in shorter time frames in the future.

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    Article . 2022
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    Authors: Haubrock, Phillip J.; Ahmed, Danish A.; Cuthbert, Ross N.; Stubbington, Rachel; +36 Authors

    Globalization has led to the introduction of thousands of alien species worldwide. With growing impacts by invasive species, understanding the invasion process remains critical for predicting adverse effects and informing efficient management. Theoretically, invasion dynamics have been assumed to follow an “invasion curve” (S-shaped curve of available area invaded over time), but this dynamic has lacked empirical testing using large-scale data and neglects to consider invader abundances. We propose an “impact curve” describing the impacts generated by invasive species over time based on cumulative abundances. To test this curve's large-scale applicability, we used the data-rich New Zealand mud snail Potamopyrgus antipodarum, one of the most damaging freshwater invaders that has invaded almost all of Europe. Using long-term (1979–2020) abundance and environmental data collected across 306 European sites, we observed that P. antipodarum abundance generally increased through time, with slower population growth at higher latitudes and with lower runoff depth. Fifty-nine percent of these populations followed the impact curve, characterized by first occurrence, exponential growth, then long-term saturation. This behaviour is consistent with boom-bust dynamics, as saturation occurs due to a rapid decline in abundance over time. Across sites, we estimated that impact peaked approximately two decades after first detection, but the rate of progression along the invasion process was influenced by local abiotic conditions. The S-shaped impact curve may be common among many invasive species that undergo complex invasion dynamics. This provides a potentially unifying approach to advance understanding of large-scale invasion dynamics and could inform timely management actions to mitigate impacts on ecosystems and economies. Bundesministerium für Bildung und Forschung http://dx.doi.org/10.13039/501100002347 Horizon 2020 Framework Programme http://dx.doi.org/10.13039/100010661 Kuwait Foundation for the Advancement of Sciences http://dx.doi.org/10.13039/501100003286 Leibniz Competition Leverhulme Trust http://dx.doi.org/10.13039/501100000275 Alexander von Humboldt Foundation http://dx.doi.org/10.13039/100005156 Gulf University for Science and Technology (GUST) http://dx.doi.org/10.13039/100016753 Peer Reviewed

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    Article . 2022
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