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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

    Abstract 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. 80 7

    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/
    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
    Article . 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
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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/
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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
      Article . 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: Benjamin Buchovecky; Graeme A. MacGilchrist; Mitchell Bushuk; F. Alexander Haumann; +3 Authors

    This work was supported by the High Meadows Environmental Institute at Princeton University and the NSF's Southern Ocean Carbon and Climate Observations and Modeling (SOCCOM) Project under the NSF Award PLR-1425989. F.A.H. was supported by NASA Grant 80NSSC19K1115 and by the European Union (ERC, VERTEXSO, 101041743). G.A.M was supported under SOCCOM and UKRI Grant MR/W013835/1. T.L.F was supported by Swiss National Science Foundation (Grant P00P2_198897) and the Swiss National Supercomputing Centre. N.L was supported by the European Union's Horizon 2020 research and innovation program under Grant 820989 (project COMFORT) and no. 862923 (project AtlantECO) as well as the Bretscher Funds. Every austral spring when Antarctic sea ice melts, favorable growing conditions lead to an intense phytoplankton bloom, which supports much of the local marine ecosystem. Recent studies have found that Antarctic sea ice is predictable several years in advance, suggesting that the spring bloom might exhibit similar predictability. Using a suite of perfect model predictability experiments, we find that November net primary production (NPP) is potentially predictable 7 to 10 years in advance in many Southern Ocean regions. Sea ice extent predictability peaks in late winter, followed by absorbed shortwave radiation and NPP with a 2 to 3 months lag. This seasonal progression of predictability supports our hypothesis that sea ice and light limitation control the inherent predictability of the spring bloom. Our results suggest skillful interannual predictions of NPP may be achievable, with implications for managing fisheries and the marine ecosystem, and guiding conservation policy in the Southern Ocean. Peer reviewed

    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/10.2...arrow_drop_down
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    https://doi.org/10.22541/essoa...
    Preprint . 2023
    License: CC BY NC ND
    Data sources: Crossref
    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/
    St Andrews Research Repository
    Article . 2023 . Peer-reviewed
    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/
    Geophysical Research Letters
    Article . 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/ https://doi.org/10.2...arrow_drop_down
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      https://doi.org/10.22541/essoa...
      Preprint . 2023
      License: CC BY NC ND
      Data sources: Crossref
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      St Andrews Research Repository
      Article . 2023 . Peer-reviewed
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      Geophysical Research Letters
      Article . 2023 . Peer-reviewed
      License: CC BY
      Data sources: Crossref
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  • Authors: Rodrigo Martinez-Abarca;
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  • Authors: Rodrigo Martinez-Abarca;
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  • Authors: Sarah Metcalfe;
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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: Oehri, Jacqueline; Schaepman-Strub, Gabriela; Kim, Jin-Soo; Grysko, Raleigh; +74 Authors

    Despite the importance of high-latitude surface energy budgets (SEBs) for land-climate interactions in the rapidly changing Arctic, uncertainties in their prediction persist. Here, we harmonize SEB observations across a network of vegetated and glaciated sites at circumpolar scale (1994-2021). Our variance-partitioning analysis identifies vegetation type as an important predictor for SEB-components during Arctic summer (June-August), compared to other SEB-drivers including climate, latitude and permafrost characteristics. Differences among vegetation types can be of similar magnitude as between vegetation and glacier surfaces and are especially high for summer sensible and latent heat fluxes. The timing of SEB-flux summer-regimes (when daily mean values exceed 0 Wm(-2)) relative to snow-free and -onset dates varies substantially depending on vegetation type, implying vegetation controls on snow-cover and SEB-flux seasonality. Our results indicate complex shifts in surface energy fluxes with land-cover transitions and a lengthening summer season, and highlight the potential for improving future Earth system models via a refined representation of Arctic vegetation types.An international team of researchers finds high potential for improving climate projections by a more comprehensive treatment of largely ignored Arctic vegetation types, underscoring the importance of Arctic energy exchange measuring stations. Peer reviewed

    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; Utrecht Univ...arrow_drop_down
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    MPG.PuRe
    Article . 2022
    Data sources: MPG.PuRe
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    Nature Communications
    Article . 2022
    Data sources: DOAJ
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    Nature Communications
    Article . 2022
    Data sources: NARCIS
    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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    MPG.PuRe
    Article . 2022
    License: CC BY
    Data sources: MPG.PuRe
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      MPG.PuRe
      Article . 2022
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      Nature Communications
      Article . 2022
      Data sources: DOAJ
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      Nature Communications
      Article . 2022
      Data sources: NARCIS
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      MPG.PuRe
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    Authors: Rodrigo Martínez-Abarca; Michelle Abstein; Philipp Hoelzmann; David Hodell; +14 Authors

    Lake Petén Itzá (Guatemala) possesses one of the longest lacustrine sediment records in the northern Neotropics, which enabled study of paleoclimate variability in the region during the last ∼400 000 years. We used geochemical (Ti, Ca/(Ti+Fe) and Mn/Fe) and mineralogical (carbonates, gypsum, quartz, clay) data from sediment core PI-2 to infer past changes in runoff, lake evaporation, organic matter sources and redox conditions in the water column, caused by hydrological changes in the northern Neotropics during Marine Isotope Stages (MISs) 3–2. From 59 to 39 cal ka BP climate conditions were relatively wet, and the lake was marked by higher primary productivity and anoxic bottom waters. This wet environment was interrupted for two periods of possible low water level at 52 and 46 cal ka BP, when our data suggest higher evaporation, high terrestrial organic matter input and persistent oxic conditions. Between 39 and 23 cal ka BP, evaporation and input of terrestrial organic matter increased considerably, lake level declined, and lake bottom waters generally became oxic. These conditions reversed during the Last Glacial Maximum (23.5–18.0 cal ka BP), when runoff and lake productivity increased, and rising lake level caused bottom waters to again become anoxic. Comparison of our hydrologic proxy data with sea surface temperature anomalies between the eastern Pacific and the Caribbean suggests that changes in the intensity of the Caribbean Low-Level Jet (CLLJ) may have influenced long-term changes in runoff during MISs 3–2. Higher intensity of the CLLJ during the onset of MIS 3 and the LGM might have led to greater runoff into the lake, whereas the MIS 3–2 transition experienced a weaker CLLJ and consequently less runoff. A refined, high-resolution age–depth model for the PI-2 sediment core enabled us to identify millennial-scale Greenland interstadials (GIs) 14–2, Greenland stadials (GSs) 14–2 and Heinrich stadials (HSs) 5–1. In general, HSs and GSs were characterized by drier conditions. In contrast to GSs and HSs, GIs were characterized by greater runoff and overall wetter conditions, with the most pronounced GI peaks between 40 and 30 cal ka BP. Whereas GSs 9, 8, 7 and 6 began with abrupt increases in evaporation and ended with gradual increases in humidity, GSs 11 and 10 showed reversed patterns. The Lake Petén Itzá paleohydrology record, along with other regional paleoclimate records, led us to conclude that shifts in the position of the Intertropical Convergence Zone (ITCZ) altered moisture delivery to the lake on millennial timescales. During GSs and HSs, high evaporation from Petén Itzá (dry climate conditions) was associated with a more southerly position of the ITCZ, whereas wetter GIs prevailed during a more northerly ITCZ position. Although abrupt millennial-scale shifts in ITCZ and hydroclimate between GSs/HSs and GIs can be linked to instabilities in the Atlantic Meridional Overturning Circulation (AMOC), longer-term changes were additionally influenced by changes in atmospheric convection linked to modulations of the CLLJ in response to ΔSST between the equatorial Pacific and tropical Atlantic.

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    Copernicus Publications
    Other literature type . 2023
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    https://doi.org/10.5194/egusph...
    Preprint . 2022 . Peer-reviewed
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      https://doi.org/10.5194/egusph...
      Preprint . 2022 . Peer-reviewed
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    Authors: Schmitz, Désirée A; Allen, Richard C; Kümmerli, Rolf;

    Bacterial infections are often polymicrobial, leading to intricate pathogen-pathogen and pathogen-host interactions. There is increasing interest in studying the molecular basis of pathogen interactions and how such mechanisms impact host morbidity. However, much less is known about the ecological dynamics between pathogens and how they affect virulence and host survival. Here we address these open issues by co-infecting larvae of the insect model hostGalleria mellonellawith one, two, three or four bacterial species, all of which are opportunistic human pathogens. We found that host mortality was always determined by the most virulent species regardless of the number of species and pathogen combinations injected. In certain combinations, the more virulent pathogen simply outgrew the less virulent pathogen. In other combinations, we found evidence for negative interactions between pathogens inside the host, whereby the more virulent pathogen typically won a competition. Taken together, our findings reveal positive associations between a pathogen’s growth inside the host, its competitiveness towards other pathogens, and its virulence. Beyond being generalizable across species combinations, our findings predict that treatments against polymicrobial infections should target the most virulent species to reduce host morbidity, a prediction we validated experimentally.ImportanceThere is increasing evidence that polymicrobial infections are common and that host morbidity is impacted by interactions between the co-infecting pathogens. In this study, we infected the larvae of the insect hostGalleria mellonellawith four opportunistic human pathogens as mono or multispecies bacterial infections in all possible combinations and followed host survival and pathogen interactions over time. We discovered that species followed the exact same rank order in terms of their virulence, their growth inside the host, and their competitive ability against co-infecting pathogens. As consequence of this consistent rank order, we found that the most virulent species determines host survival dynamics in mixed infections. Beyond revealing a generalizable predictive pattern for virulence outcomes, our findings also predict that treatments should target the most virulent species in polymicrobial infections, a prediction we validated experimentally.

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    Proceedings of the Royal Society B Biological Sciences
    Article . 2023 . Peer-reviewed
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    https://doi.org/10.5167/uzh-22...
    Other literature type . 2022
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      Proceedings of the Royal Society B Biological Sciences
      Article . 2023 . Peer-reviewed
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      https://doi.org/10.5167/uzh-22...
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    Authors: Ramos-Roman, Maria J.; De Jonge, Cindy; Magyari, Eniko; Veres, Daniel; +3 Authors

    To reconstruct changes in vegetation, temperature, and sediment geochemistry through the last 6.5 cal ka BP, in the Subcarpathian belt of the Eastern Carpathians (Romania), pollen, branched glycerol dialkyl glycerol tetraethers (brGDGTs) and X-ray fluorescence analyses have been integrated. Pollen and brGDGTs (a bacterial lipid biomarker proxy) are used as paleothermometers for reconstructing the mean annual air temperature (MAAT) and mean temperature above freezing (MAF), respectively. Both proxies show roughly consistent records. The highest MAAT and MAF occurs during the oldest part of the record (from 6.5 to 4.2 cal ka BP), and the Middle to the Late Holocene shift is marked by a prominent decrease in temperature between 5.4 and 4.2 cal ka BP, coinciding with Bond event 4 and 3. This transition is coeval with a decrease in summer insolation, shift from consistent NAO-conditions to a predominance of NAO+ phase and coincides with the beginning of the Neoglacial cooling in northern latitudes. The warm bias in the MAF reconstruction during the Late Holocene is explained as a change in the lipid provenance or in the composition of the brGDGT producers after 4.2 cal ka BP. Global and Planetary Change, 215 ISSN:0921-8181

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    Global and Planetary Change
    Article . 2022 . Peer-reviewed
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    Research Collection
    Article . 2022
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      Global and Planetary Change
      Article . 2022 . Peer-reviewed
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    Authors: Lena Thöle; Xuyuan Ai; Alexandra Auderset; Mareike Schmitt; +9 Authors

    Abstract The Southern Hemisphere Westerly Winds (SWW) drive upwelling south of the Antarctic Polar Front (PF) that vents CO2 to the atmosphere. During the ice ages, a northward (equatorward) shift of the PF may have reduced this CO2 venting, helping to explain the lower atmospheric CO2 concentration of those times. However, evidence of PF migration is lacking. Here, we report biomarker–based sea surface temperature (SST) reconstructions from two marine sediment cores at different latitudes in the Southern Indian Ocean across the last glacial cycle. Using a quantitative framework for the effect of the PF on meridional SST gradient, we show that the PF underwent an equatorward shift during the ice ages. The PF latitude reconstruction, when compared with other data, also suggests a role for Earth’s axial tilt in the strength and latitude range of SWW-driven upwelling, which may explain previously noted deviations in atmospheric CO2 from a simple correlation with Antarctic climate.

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    https://doi.org/10.21203/rs.3....
    Preprint . 2022
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      https://doi.org/10.21203/rs.3....
      Preprint . 2022
      License: CC BY
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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

    Abstract 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. 80 7

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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/
    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
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    Research@WUR
    Article . 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
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    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
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      OceanRep
      Article . 2023 . Peer-reviewed
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      Lille Open Archive
      Review . 2023
      Data sources: Lille Open Archive
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      Research@WUR
      Article . 2023
      License: CC BY
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      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: Benjamin Buchovecky; Graeme A. MacGilchrist; Mitchell Bushuk; F. Alexander Haumann; +3 Authors

    This work was supported by the High Meadows Environmental Institute at Princeton University and the NSF's Southern Ocean Carbon and Climate Observations and Modeling (SOCCOM) Project under the NSF Award PLR-1425989. F.A.H. was supported by NASA Grant 80NSSC19K1115 and by the European Union (ERC, VERTEXSO, 101041743). G.A.M was supported under SOCCOM and UKRI Grant MR/W013835/1. T.L.F was supported by Swiss National Science Foundation (Grant P00P2_198897) and the Swiss National Supercomputing Centre. N.L was supported by the European Union's Horizon 2020 research and innovation program under Grant 820989 (project COMFORT) and no. 862923 (project AtlantECO) as well as the Bretscher Funds. Every austral spring when Antarctic sea ice melts, favorable growing conditions lead to an intense phytoplankton bloom, which supports much of the local marine ecosystem. Recent studies have found that Antarctic sea ice is predictable several years in advance, suggesting that the spring bloom might exhibit similar predictability. Using a suite of perfect model predictability experiments, we find that November net primary production (NPP) is potentially predictable 7 to 10 years in advance in many Southern Ocean regions. Sea ice extent predictability peaks in late winter, followed by absorbed shortwave radiation and NPP with a 2 to 3 months lag. This seasonal progression of predictability supports our hypothesis that sea ice and light limitation control the inherent predictability of the spring bloom. Our results suggest skillful interannual predictions of NPP may be achievable, with implications for managing fisheries and the marine ecosystem, and guiding conservation policy in the Southern Ocean. Peer reviewed

    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/10.2...arrow_drop_down
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    https://doi.org/10.22541/essoa...
    Preprint . 2023
    License: CC BY NC ND
    Data sources: Crossref
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    St Andrews Research Repository
    Article . 2023 . Peer-reviewed
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    Geophysical Research Letters
    Article . 2023 . Peer-reviewed
    License: CC BY
    Data sources: Crossref
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      https://doi.org/10.22541/essoa...
      Preprint . 2023
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      St Andrews Research Repository
      Article . 2023 . Peer-reviewed
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      Geophysical Research Letters
      Article . 2023 . Peer-reviewed
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  • Authors: Rodrigo Martinez-Abarca;
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  • Authors: Rodrigo Martinez-Abarca;
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  • Authors: Sarah Metcalfe;
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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: Oehri, Jacqueline; Schaepman-Strub, Gabriela; Kim, Jin-Soo; Grysko, Raleigh; +74 Authors

    Despite the importance of high-latitude surface energy budgets (SEBs) for land-climate interactions in the rapidly changing Arctic, uncertainties in their prediction persist. Here, we harmonize SEB observations across a network of vegetated and glaciated sites at circumpolar scale (1994-2021). Our variance-partitioning analysis identifies vegetation type as an important predictor for SEB-components during Arctic summer (June-August), compared to other SEB-drivers including climate, latitude and permafrost characteristics. Differences among vegetation types can be of similar magnitude as between vegetation and glacier surfaces and are especially high for summer sensible and latent heat fluxes. The timing of SEB-flux summer-regimes (when daily mean values exceed 0 Wm(-2)) relative to snow-free and -onset dates varies substantially depending on vegetation type, implying vegetation controls on snow-cover and SEB-flux seasonality. Our results indicate complex shifts in surface energy fluxes with land-cover transitions and a lengthening summer season, and highlight the potential for improving future Earth system models via a refined representation of Arctic vegetation types.An international team of researchers finds high potential for improving climate projections by a more comprehensive treatment of largely ignored Arctic vegetation types, underscoring the importance of Arctic energy exchange measuring stations. Peer reviewed

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    MPG.PuRe
    Article . 2022
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    Nature Communications
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    Authors: Rodrigo Martínez-Abarca; Michelle Abstein; Philipp Hoelzmann; David Hodell; +14 Authors

    Lake Petén Itzá (Guatemala) possesses one of the longest lacustrine sediment records in the northern Neotropics, which enabled study of paleoclimate variability in the region during the last ∼400 000 years. We used geochemical (Ti, Ca/(Ti+Fe) and Mn/Fe) and mineralogical (carbonates, gypsum, quartz, clay) data from sediment core PI-2 to infer past changes in runoff, lake evaporation, organic matter sources and redox conditions in the water column, caused by hydrological changes in the northern Neotropics during Marine Isotope Stages (MISs) 3–2. From 59 to 39 cal ka BP climate conditions were relatively wet, and the lake was marked by higher primary productivity and anoxic bottom waters. This wet environment was interrupted for two periods of possible low water level at 52 and 46 cal ka BP, when our data suggest higher evaporation, high terrestrial organic matter input and persistent oxic conditions. Between 39 and 23 cal ka BP, evaporation and input of terrestrial organic matter increased considerably, lake level declined, and lake bottom waters generally became oxic. These conditions reversed during the Last Glacial Maximum (23.5–18.0 cal ka BP), when runoff and lake productivity increased, and rising lake level caused bottom waters to again become anoxic. Comparison of our hydrologic proxy data with sea surface temperature anomalies between the eastern Pacific and the Caribbean suggests that changes in the intensity of the Caribbean Low-Level Jet (CLLJ) may have influenced long-term changes in runoff during MISs 3–2. Higher intensity of the CLLJ during the onset of MIS 3 and the LGM might have led to greater runoff into the lake, whereas the MIS 3–2 transition experienced a weaker CLLJ and consequently less runoff. A refined, high-resolution age–depth model for the PI-2 sediment core enabled us to identify millennial-scale Greenland interstadials (GIs) 14–2, Greenland stadials (GSs) 14–2 and Heinrich stadials (HSs) 5–1. In general, HSs and GSs were characterized by drier conditions. In contrast to GSs and HSs, GIs were characterized by greater runoff and overall wetter conditions, with the most pronounced GI peaks between 40 and 30 cal ka BP. Whereas GSs 9, 8, 7 and 6 began with abrupt increases in evaporation and ended with gradual increases in humidity, GSs 11 and 10 showed reversed patterns. The Lake Petén Itzá paleohydrology record, along with other regional paleoclimate records, led us to conclude that shifts in the position of the Intertropical Convergence Zone (ITCZ) altered moisture delivery to the lake on millennial timescales. During GSs and HSs, high evaporation from Petén Itzá (dry climate conditions) was associated with a more southerly position of the ITCZ, whereas wetter GIs prevailed during a more northerly ITCZ position. Although abrupt millennial-scale shifts in ITCZ and hydroclimate between GSs/HSs and GIs can be linked to instabilities in the Atlantic Meridional Overturning Circulation (AMOC), longer-term changes were additionally influenced by changes in atmospheric convection linked to modulations of the CLLJ in response to ΔSST between the equatorial Pacific and tropical Atlantic.

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    Copernicus Publications
    Other literature type . 2023
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    https://doi.org/10.5194/egusph...
    Preprint . 2022 . Peer-reviewed
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      https://doi.org/10.5194/egusph...
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    Authors: Schmitz, Désirée A; Allen, Richard C; Kümmerli, Rolf;

    Bacterial infections are often polymicrobial, leading to intricate pathogen-pathogen and pathogen-host interactions. There is increasing interest in studying the molecular basis of pathogen interactions and how such mechanisms impact host morbidity. However, much less is known about the ecological dynamics between pathogens and how they affect virulence and host survival. Here we address these open issues by co-infecting larvae of the insect model hostGalleria mellonellawith one, two, three or four bacterial species, all of which are opportunistic human pathogens. We found that host mortality was always determined by the most virulent species regardless of the number of species and pathogen combinations injected. In certain combinations, the more virulent pathogen simply outgrew the less virulent pathogen. In other combinations, we found evidence for negative interactions between pathogens inside the host, whereby the more virulent pathogen typically won a competition. Taken together, our findings reveal positive associations between a pathogen’s growth inside the host, its competitiveness towards other pathogens, and its virulence. Beyond being generalizable across species combinations, our findings predict that treatments against polymicrobial infections should target the most virulent species to reduce host morbidity, a prediction we validated experimentally.ImportanceThere is increasing evidence that polymicrobial infections are common and that host morbidity is impacted by interactions between the co-infecting pathogens. In this study, we infected the larvae of the insect hostGalleria mellonellawith four opportunistic human pathogens as mono or multispecies bacterial infections in all possible combinations and followed host survival and pathogen interactions over time. We discovered that species followed the exact same rank order in terms of their virulence, their growth inside the host, and their competitive ability against co-infecting pathogens. As consequence of this consistent rank order, we found that the most virulent species determines host survival dynamics in mixed infections. Beyond revealing a generalizable predictive pattern for virulence outcomes, our findings also predict that treatments should target the most virulent species in polymicrobial infections, a prediction we validated experimentally.

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    Proceedings of the Royal Society B Biological Sciences
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    https://doi.org/10.5167/uzh-22...
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      Proceedings of the Royal Society B Biological Sciences
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    Authors: Ramos-Roman, Maria J.; De Jonge, Cindy; Magyari, Eniko; Veres, Daniel; +3 Authors

    To reconstruct changes in vegetation, temperature, and sediment geochemistry through the last 6.5 cal ka BP, in the Subcarpathian belt of the Eastern Carpathians (Romania), pollen, branched glycerol dialkyl glycerol tetraethers (brGDGTs) and X-ray fluorescence analyses have been integrated. Pollen and brGDGTs (a bacterial lipid biomarker proxy) are used as paleothermometers for reconstructing the mean annual air temperature (MAAT) and mean temperature above freezing (MAF), respectively. Both proxies show roughly consistent records. The highest MAAT and MAF occurs during the oldest part of the record (from 6.5 to 4.2 cal ka BP), and the Middle to the Late Holocene shift is marked by a prominent decrease in temperature between 5.4 and 4.2 cal ka BP, coinciding with Bond event 4 and 3. This transition is coeval with a decrease in summer insolation, shift from consistent NAO-conditions to a predominance of NAO+ phase and coincides with the beginning of the Neoglacial cooling in northern latitudes. The warm bias in the MAF reconstruction during the Late Holocene is explained as a change in the lipid provenance or in the composition of the brGDGT producers after 4.2 cal ka BP. Global and Planetary Change, 215 ISSN:0921-8181

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    Global and Planetary Change
    Article . 2022 . Peer-reviewed
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      Global and Planetary Change
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    Authors: Lena Thöle; Xuyuan Ai; Alexandra Auderset; Mareike Schmitt; +9 Authors

    Abstract The Southern Hemisphere Westerly Winds (SWW) drive upwelling south of the Antarctic Polar Front (PF) that vents CO2 to the atmosphere. During the ice ages, a northward (equatorward) shift of the PF may have reduced this CO2 venting, helping to explain the lower atmospheric CO2 concentration of those times. However, evidence of PF migration is lacking. Here, we report biomarker–based sea surface temperature (SST) reconstructions from two marine sediment cores at different latitudes in the Southern Indian Ocean across the last glacial cycle. Using a quantitative framework for the effect of the PF on meridional SST gradient, we show that the PF underwent an equatorward shift during the ice ages. The PF latitude reconstruction, when compared with other data, also suggests a role for Earth’s axial tilt in the strength and latitude range of SWW-driven upwelling, which may explain previously noted deviations in atmospheric CO2 from a simple correlation with Antarctic climate.

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    Preprint . 2022
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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/
    https://doi.org/10.21203/rs.3....
    Preprint . 2022
    License: CC BY
    Data sources: Crossref
    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/
    MPG.PuRe
    Preprint . 2022
    Data sources: MPG.PuRe
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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/ MPG.PuRearrow_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/
      MPG.PuRe
      Preprint . 2022
      Data sources: MPG.PuRe
      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/10.21203/rs.3....
      Preprint . 2022
      License: CC BY
      Data sources: Crossref
      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/
      MPG.PuRe
      Preprint . 2022
      Data sources: MPG.PuRe
      addClaim

      This Research product is the result of merged Research products in OpenAIRE.

      You have already added works in your ORCID record related to the merged Research product.