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  • Energy Research
  • 13. Climate action
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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: Coni, Ericka O C; Nagelkerken, Ivan; Ferreira, Camilo M; Connell, Sean D; +1 Authors

    Poleward range extensions by warm-adapted sea urchins are switching temperate marine ecosystems from kelp-dominated to barren-dominated systems that favour the establishment of range-extending tropical fishes. Yet, such tropicalization may be buffered by ocean acidification, which reduces urchin grazing performance and the urchin barrens that tropical range-extending fishes prefer. Using ecosystems experiencing natural warming and acidification, we show that ocean acidification could buffer warming-facilitated tropicalization by reducing urchin populations (by 87%) and inhibiting the formation of barrens. This buffering effect of CO2 enrichment was observed at natural CO2 vents that are associated with a shift from a barren-dominated to a turf-dominated state, which we found is less favourable to tropical fishes. Together, these observations suggest that ocean acidification may buffer the tropicalization effect of ocean warming against urchin barren formation via multiple processes (fewer urchins and barrens) and consequently slow the increasing rate of tropicalization of temperate fish communities. In order to allow full comparability with other ocean acidification data sets, the R package seacarb (Gattuso et al, 2021) was used to compute a complete and consistent set of carbonate system variables, as described by Nisumaa et al. (2010). In this dataset the original values were archived in addition with the recalculated parameters (see related PI). The date of carbonate chemistry calculation by seacarb is 2021-07-26.

    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/ PANGAEA - Data Publi...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/
    B2FIND
    Dataset . 2021
    Data sources: B2FIND
    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/
    PANGAEA
    Dataset . 2021
    License: CC BY
    Data sources: PANGAEA
    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/
    PANGAEA
    Dataset . 2021
    Data sources: PANGAEA
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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/ PANGAEA - Data Publi...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/
      B2FIND
      Dataset . 2021
      Data sources: B2FIND
      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/
      PANGAEA
      Dataset . 2021
      License: CC BY
      Data sources: PANGAEA
      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/
      PANGAEA
      Dataset . 2021
      Data sources: PANGAEA
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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: Wang, Z; Tsementzi, Despina; Williams, Tiffany C; Juarez, Doris L; +6 Authors

    Ambient conditions shape microbiome responses to both short- and long-duration environment changes through processes including physiological acclimation, compositional shifts, and evolution. Thus, we predict that microbial communities inhabiting locations with larger diel, episodic, and annual variability in temperature and pH should be less sensitive to shifts in these climate-change factors. To test this hypothesis, we compared responses of surface ocean microbes from more variable (nearshore) and more constant (offshore) sites to short-term factorial warming (+3 °C) and/or acidification (pH -0.3). In all cases, warming alone significantly altered microbial community composition, while acidification had a minor influence. Compared with nearshore microbes, warmed offshore microbiomes exhibited larger changes in community composition, phylotype abundances, respiration rates, and metatranscriptomes, suggesting increased sensitivity of microbes from the less-variable environment. Moreover, while warming increased respiration rates, offshore metatranscriptomes yielded evidence of thermal stress responses in protein synthesis, heat shock proteins, and regulation. Future oceans with warmer waters may enhance overall metabolic and biogeochemical rates, but they will host altered microbial communities, especially in relatively thermally stable regions of the oceans. In order to allow full comparability with other ocean acidification data sets, the R package seacarb (Gattuso et al, 2019) was used to compute a complete and consistent set of carbonate system variables, as described by Nisumaa et al. (2010). In this dataset the original values were archived in addition with the recalculated parameters (see related PI). The date of carbonate chemistry calculation by seacarb is 2020-10-20.

    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/ PANGAEA - Data Publi...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/
    B2FIND
    Dataset . 2021
    Data sources: B2FIND
    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/
    PANGAEA
    Dataset . 2021
    Data sources: PANGAEA
    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/
    PANGAEA
    Dataset . 2020
    License: CC BY
    Data sources: PANGAEA
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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/ PANGAEA - Data Publi...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/
      B2FIND
      Dataset . 2021
      Data sources: B2FIND
      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/
      PANGAEA
      Dataset . 2021
      Data sources: PANGAEA
      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/
      PANGAEA
      Dataset . 2020
      License: CC BY
      Data sources: PANGAEA
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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: Schoepf, Verena; Grottoli, Andréa G; Warner, Mark E; Cai, Wei-Jun; +9 Authors

    Rising atmospheric CO2 concentrations threaten coral reefs globally by causing ocean acidification (OA) and warming. Yet, the combined effects of elevated pCO2 and temperature on coral physiology and resilience remain poorly understood. While coral calcification and energy reserves are important health indicators, no studies to date have measured energy reserve pools (i.e., lipid, protein, and carbohydrate) together with calcification under OA conditions under different temperature scenarios. Four coral species, Acropora millepora, Montipora monasteriata, Pocillopora damicornis, Turbinaria reniformis, were reared under a total of six conditions for 3.5 weeks, representing three pCO2 levels (382, 607, 741 µatm), and two temperature regimes (26.5, 29.0°C) within each pCO2 level. After one month under experimental conditions, only A. millepora decreased calcification (-53%) in response to seawater pCO2 expected by the end of this century, whereas the other three species maintained calcification rates even when both pCO2 and temperature were elevated. Coral energy reserves showed mixed responses to elevated pCO2 and temperature, and were either unaffected or displayed nonlinear responses with both the lowest and highest concentrations often observed at the mid-pCO2 level of 607 µatm. Biweekly feeding may have helped corals maintain calcification rates and energy reserves under these conditions. Temperature often modulated the response of many aspects of coral physiology to OA, and both mitigated and worsened pCO2 effects. This demonstrates for the first time that coral energy reserves are generally not metabolized to sustain calcification under OA, which has important implications for coral health and bleaching resilience in a high-CO2 world. Overall, these findings suggest that some corals could be more resistant to simultaneously warming and acidifying oceans than previously expected. In order to allow full comparability with other ocean acidification data sets, the R package seacarb (Lavigne et al, 2014) was used to compute a complete and consistent set of carbonate system variables, as described by Nisumaa et al. (2010). In this dataset the original values were archived in addition with the recalculated parameters (see related PI). The date of carbonate chemistry calculation is 2014-07-08. Supplement to: Schoepf, Verena; Grottoli, Andréa G; Warner, Mark E; Cai, Wei-Jun; Melman, Todd F; Hoadley, Kenneth D; Pettay, D Tye; Hu, Xinping; Li, Qian; Xu, Hui; Wang, Yujie; Matsui, Yohei; Baumann, Justin H (2013): Coral Energy Reserves and Calcification in a High-CO2 World at Two Temperatures. PLoS ONE, 8(10), e75049

    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/ PANGAEAarrow_drop_down
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    PANGAEA
    Dataset . 2014
    Data sources: PANGAEA
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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/ PANGAEAarrow_drop_down
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      PANGAEA
      Dataset . 2014
      Data sources: PANGAEA
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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: Nagelkerken, Ivan; Goldenberg, Silvan U; Ferreira, Camilo M; Ullah, Hadayet; +1 Authors

    As human activities intensify, the structures of ecosystems and their food webs often reorganize. Through the study of mesocosms harboring a diverse benthic coastal community, we reveal that food web architecture can be inflexible under ocean warming and acidification and unable to compensate for the decline or proliferation of taxa. Key stabilizing processes, including functional redundancy, trophic compensation, and species substitution, were largely absent under future climate conditions. A trophic pyramid emerged in which biomass expanded at the base and top but contracted in the center. This structure may characterize a transitionary state before collapse into shortened, bottom-heavy food webs that characterize ecosystems subject to persistent abiotic stress. We show that where food web architecture lacks adjustability, the adaptive capacity of ecosystems to global change is weak and ecosystem degradation likely. In order to allow full comparability with other ocean acidification data sets, the R package seacarb (Gattuso et al, 2021) was used to compute a complete and consistent set of carbonate system variables, as described by Nisumaa et al. (2010). In this dataset the original values were archived in addition with the recalculated parameters (see related PI). The date of carbonate chemistry calculation by seacarb is 2021-03-09.

    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/ PANGAEA - Data Publi...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/
    B2FIND
    Dataset . 2020
    Data sources: B2FIND
    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/
    PANGAEA
    Dataset . 2020
    Data sources: PANGAEA
    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/
    PANGAEA
    Dataset . 2021
    License: CC BY
    Data sources: PANGAEA
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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/ PANGAEA - Data Publi...arrow_drop_down
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      B2FIND
      Dataset . 2020
      Data sources: B2FIND
      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/
      PANGAEA
      Dataset . 2020
      Data sources: PANGAEA
      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/
      PANGAEA
      Dataset . 2021
      License: CC BY
      Data sources: PANGAEA
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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: Linhardt, Tobias; Levy, Joseph S; Thomas, Christoph K;

    From 26 December 2012 to 21 January 2013 we measured relevant parameters for surface energy and mass exchange calculation at three closely collocated sites near the Ross Sea shore in the valley floor of lower Taylor Valley, McMurdo Dry Valleys, Antarctica. At any time during the experiment, two surface energy balance stations were operated: One station was installed throughout the whole period at the investigated water track, referred to as WT. The other station was operated as a reference representing the dominant non-water track (NWT), bare soil surfaces in lower Taylor Valley; it was successively installed at two sites with different soil textures: PLD was located on a paleolake delta dominated by fine surficial sediments, while GT represented coarse glacial till. At each station the following instruments were installed: A net radiometer (NR01, Hukseflux Thermal Sensors B.V., Delft, NL) was used for measuring solar and terrestrial radiation, an ultrasonic anemometer (81000 VRE, R.M. Young Company, Traverse City, MI, USA) and an infrared gas analyzer (LI-7500, LI-COR Inc., Lincoln, NE, USA) recorded data for turbulent heat flux estimation via the eddy-covariance method. Thermistors and thermocouples recorded soil temperatures in several depths in the thawed layer. Additionally, we used a thermal properties analyzer (KD2 Pro, Decagon Devices, Pullman, WA, USA) for measuring soil thermal properties for several samples taken from the surface. Eddy-covariance processing was done with the bmmflux tool of the University of Bayreuth (see appendix in Thomas et al., 2009), including data quality assessment after Foken et al. (2004). Turbulent flux footprints were modeled with the TERRAFEX model of the University of Bayreuth (Göckede, 2001) which provided contributions of adjacent land cover types to the flux footprint. Further information on the experimental setup can be found in Linhardt et al. (2019).

    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/ PANGAEAarrow_drop_down
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    PANGAEA
    Other ORP type . 2019
    License: CC BY
    Data sources: PANGAEA
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      PANGAEA
      Other ORP type . 2019
      License: CC BY
      Data sources: PANGAEA
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    Authors: Dumitru, Oana-Alexandra; Austermann, Jacqueline; Polyak, Victor J; Fornós, Joan J; +4 Authors

    Reconstructing the evolution of sea level during past warmer epochs such as the Pliocene provides insight into the response of sea level and ice sheets to prolonged warming. Although estimates of global mean sea level (GMSL) during this time do exist, they vary by several tens of metres, hindering the assessment of past and future ice-sheet stability. Here we show that during the mid-Piacenzian Warm Period, which was on average 2-3 degrees Celsius warmer than the pre-industrial period, the GMSL (sea-level equivalent changes in global ice volume) was about 16.2 metres higher than today. During the even warmer Pliocene Climatic Optimum (about 4 degrees Celsius warmer than pre-industrial), our results show that GMSL was 23.5 metres above the present level (m.a.p.s.l.). We present six GMSL data points, ranging from 4.39 to 3.27 million years ago, that are based on overgrowths on phreatic (from water-filled caves) speleothems from the western Mediterranean Sea, near Mallorca, Spain. This record is unique owing to its clear relationship to sea level, its reliable U-Pb ages and its long timespan, which allows us to quantify uncertainties on potential uplift. Our data indicate that ice sheets are very sensitive to warming and provide important calibration targets for future ice-sheet models.

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    PANGAEA
    Other ORP type . 2019
    License: CC BY
    Data sources: PANGAEA
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      PANGAEA
      Other ORP type . 2019
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    Authors: Harsch, Melanie A; HilleRisLambers, Janneke;

    Using an extensive network of occurrence records for 293 plant species collected over the past 40 years across a climatically diverse geographic section of western North America, we find that plant species distributions were just as likely to shift upwards (i.e., towards higher elevations) as downward (i.e., towards lower elevations) – despite consistent warming across the study area. Although there was no clear directional response to climate warming across the entire study area, there was significant region-to region- variation in responses (i.e. from as many as 73% to as few as32% of species shifting upward or downward). To understand the factors that might be controlling region-specific distributional shifts, we explored the relationship between the direction of change in distribution limits and the nature of recent climate change. We found that the direction of distribution limit shifts was explained by an interaction between the rate of change in local summer temperatures and seasonal precipitation. Specifically, species shifted upward at their upper elevational limit when snowfall declined at slower rates and minimum temperatures increased. By contrast, species shifted upwards at their lower elevation limit when maximum temperatures increased or both temperature and precipitation decreased. Our results suggest that future species' elevational distribution shifts will be complex, depending on the interaction between seasonal temperature and precipitation change.

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    PANGAEA
    Other ORP type . 2015
    License: CC BY ND
    Data sources: PANGAEA
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      PANGAEA
      Other ORP type . 2015
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    Authors: Gómez, C E; Wickes, Leslie; Deegan, Dan; Etnoyer, Peter J; +1 Authors

    The global decrease in seawater pH known as ocean acidification has important ecological consequences and is an imminent threat for numerous marine organisms. Even though the deep sea is generally considered to be a stable environment, it can be dynamic and vulnerable to anthropogenic disturbances including increasing temperature, deoxygenation, ocean acidification and pollution. Lophelia pertusa is among the better-studied cold-water corals but was only recently documented along the US West Coast, growing in acidified conditions. In the present study, coral fragments were collected at ∼300 m depth along the southern California margin and kept in recirculating tanks simulating conditions normally found in the natural environment for this species. At the collection site, waters exhibited persistently low pH and aragonite saturation states (Omega arag) with average values for pH of 7.66 +- 0.01 and Omega arag of 0.81 +- 0.07. In the laboratory, fragments were grown for three weeks in “favorable” pH/Omega arag of 7.9/1.47 (aragonite saturated) and “unfavorable” pH/ Omega arag of 7.6/0.84 (aragonite undersaturated) conditions. There was a highly significant treatment effect (P < 0.001) with an average% net calcification for favorable conditions of 0.023 +- 0.009%/d and net dissolution of −0.010 +- 0.014%/d for unfavorable conditions. We did not find any treatment effect on feeding rates, which suggests that corals did not depress feeding in low pH/ Omega arag in an attempt to conserve energy. However, these results suggest that the suboptimal conditions for L. pertusa from the California margin could potentially threaten the persistence of this cold-water coral with negative consequences for the future stability of this already fragile ecosystem. In order to allow full comparability with other ocean acidification data sets, the R package seacarb (Gattuso et al, 2019) was used to compute a complete and consistent set of carbonate system variables, as described by Nisumaa et al. (2010). In this dataset the original values were archived in addition with the recalculated parameters (see related PI). The date of carbonate chemistry calculation by seacarb is 2020-06-12.

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    B2FIND
    Dataset . 2018
    Data sources: B2FIND
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    PANGAEA
    Dataset . 2018
    Data sources: PANGAEA
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    PANGAEA
    Dataset . 2020
    License: CC BY
    Data sources: PANGAEA
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      B2FIND
      Dataset . 2018
      Data sources: B2FIND
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      PANGAEA
      Dataset . 2018
      Data sources: PANGAEA
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      PANGAEA
      Dataset . 2020
      License: CC BY
      Data sources: PANGAEA
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    Authors: Jury, Christopher P; Delano, Mia N; Toonen, Robert J;

    Estimates of heritability inform evolutionary potential and the likely outcome of many management actions, but such estimates remain scarce for marine organisms. Here, we report high heritability of calcification rate among the eight most dominant Hawaiian coral species under reduced pH simulating future ocean conditions. Coral colonies were sampled from up to six locations across a natural mosaic in seawater chemistry throughout Hawaiʻi and fragmented into clonal replicates maintained under both ambient and high pCO2 conditions. Broad sense heritability of calcification rates was high among all eight species, ranging from a low of 0.32 in Porites evermanni to a high of 0.61 in Porites compressa. The overall results were inconsistent with short-term acclimatization to the local environment or adaptation to the mean or ideal conditions. Similarly, in 'local vs. foreign' and 'home vs. away' tests there was no clear signature of local adaptation. Instead, the data are most consistent with a protected polymorphism as the mechanism which maintains differential pH tolerance within the populations. Substantial individual variation, coupled with high heritability and large population sizes, imply considerable scope for natural selection and adaptive capacity, which has major implications for evolutionary potential and management of corals in response to climate change. In order to allow full comparability with other ocean acidification data sets, the R package seacarb (Gattuso et al, 2019) was used to compute a complete and consistent set of carbonate system variables, as described by Nisumaa et al. (2010). In this dataset the original values were archived in addition with the recalculated parameters (see related PI). The date of carbonate chemistry calculation by seacarb is 2020-05-6.

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    B2FIND
    Dataset . 2019
    Data sources: B2FIND
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    PANGAEA
    Dataset . 2019
    Data sources: PANGAEA
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    PANGAEA
    Dataset . 2019
    License: CC BY
    Data sources: PANGAEA
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      B2FIND
      Dataset . 2019
      Data sources: B2FIND
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      PANGAEA
      Dataset . 2019
      Data sources: PANGAEA
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      PANGAEA
      Dataset . 2019
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    Authors: Morato, Telmo; González-Irusta, José Manuel; Domínguez-Carrió, Carlos; Wei, C; +55 Authors

    We used environmental niche modelling along with the best available species occurrence data and environmental parameters to model habitat suitability for key cold-water coral and commercially important deep-sea fish species under present-day (1951-2000) environmental conditions and to forecast changes under severe, high emissions future (2081-2100) climate projections (RCP8.5 scenario) for the North Atlantic Ocean (from 18°N to 76°N and 36°E to 98°W). The VME indicator taxa included Lophelia pertusa , Madrepora oculata, Desmophyllum dianthus, Acanela arbuscula, Acanthogorgia armata, and Paragorgia arborea. The six deep-sea fish species selected were: Coryphaenoides rupestris, Gadus morhua, blackbelly Helicolenus dactylopterus, Hippoglossoides platessoides, Reinhardtius hippoglossoides, and Sebastes mentella. We used an ensemble modelling approach employing three widely-used modelling methods: the Maxent maximum entropy model, Generalized Additive Models, and Random Forest. This dataset contains: 1) Predicted habitat suitability index under present-day (1951-2000) and future (2081-2100; RCP8.5) environmental conditions for twelve deep-sea species in the North Atlantic Ocean, using an ensemble modelling approach. 2) Climate-induced changes in the suitable habitat of twelve deep-sea species in the North Atlantic Ocean, as determined by binary maps built with an ensemble modelling approach and the 10-percentile training presence logistic (10th percentile) threshold. 3) Forecasted present-day suitable habitat loss (value=-1), gain (value=1), and acting as climate refugia (value=2) areas under future (2081-2100; RCP8.5) environmental conditions for twelve deep-sea species in the North Atlantic Ocean. Areas were identified from binary maps built with an ensemble modelling approach and two thresholds: 10-percentile training presence logistic threshold (10th percentile) and maximum sensitivity and specificity (MSS). Refugia areas are those areas predicted as suitable both under present-day and future conditions. All predictions were projected with the Albers equal-area conical projection centred in the middle of the study area. The grid cell resolution is of 3x3 km.

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    B2FIND
    Dataset . 2019
    Data sources: B2FIND
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    PANGAEA
    Dataset . 2019
    License: CC BY
    Data sources: PANGAEA
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    PANGAEA
    Dataset . 2019
    Data sources: PANGAEA
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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/
      B2FIND
      Dataset . 2019
      Data sources: B2FIND
      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/
      PANGAEA
      Dataset . 2019
      License: CC BY
      Data sources: PANGAEA
      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/
      PANGAEA
      Dataset . 2019
      Data sources: PANGAEA
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25 Research products
  • 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: Coni, Ericka O C; Nagelkerken, Ivan; Ferreira, Camilo M; Connell, Sean D; +1 Authors

    Poleward range extensions by warm-adapted sea urchins are switching temperate marine ecosystems from kelp-dominated to barren-dominated systems that favour the establishment of range-extending tropical fishes. Yet, such tropicalization may be buffered by ocean acidification, which reduces urchin grazing performance and the urchin barrens that tropical range-extending fishes prefer. Using ecosystems experiencing natural warming and acidification, we show that ocean acidification could buffer warming-facilitated tropicalization by reducing urchin populations (by 87%) and inhibiting the formation of barrens. This buffering effect of CO2 enrichment was observed at natural CO2 vents that are associated with a shift from a barren-dominated to a turf-dominated state, which we found is less favourable to tropical fishes. Together, these observations suggest that ocean acidification may buffer the tropicalization effect of ocean warming against urchin barren formation via multiple processes (fewer urchins and barrens) and consequently slow the increasing rate of tropicalization of temperate fish communities. In order to allow full comparability with other ocean acidification data sets, the R package seacarb (Gattuso et al, 2021) was used to compute a complete and consistent set of carbonate system variables, as described by Nisumaa et al. (2010). In this dataset the original values were archived in addition with the recalculated parameters (see related PI). The date of carbonate chemistry calculation by seacarb is 2021-07-26.

    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/ PANGAEA - Data Publi...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/
    B2FIND
    Dataset . 2021
    Data sources: B2FIND
    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/
    PANGAEA
    Dataset . 2021
    License: CC BY
    Data sources: PANGAEA
    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/
    PANGAEA
    Dataset . 2021
    Data sources: PANGAEA
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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/ PANGAEA - Data Publi...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/
      B2FIND
      Dataset . 2021
      Data sources: B2FIND
      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/
      PANGAEA
      Dataset . 2021
      License: CC BY
      Data sources: PANGAEA
      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/
      PANGAEA
      Dataset . 2021
      Data sources: PANGAEA
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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: Wang, Z; Tsementzi, Despina; Williams, Tiffany C; Juarez, Doris L; +6 Authors

    Ambient conditions shape microbiome responses to both short- and long-duration environment changes through processes including physiological acclimation, compositional shifts, and evolution. Thus, we predict that microbial communities inhabiting locations with larger diel, episodic, and annual variability in temperature and pH should be less sensitive to shifts in these climate-change factors. To test this hypothesis, we compared responses of surface ocean microbes from more variable (nearshore) and more constant (offshore) sites to short-term factorial warming (+3 °C) and/or acidification (pH -0.3). In all cases, warming alone significantly altered microbial community composition, while acidification had a minor influence. Compared with nearshore microbes, warmed offshore microbiomes exhibited larger changes in community composition, phylotype abundances, respiration rates, and metatranscriptomes, suggesting increased sensitivity of microbes from the less-variable environment. Moreover, while warming increased respiration rates, offshore metatranscriptomes yielded evidence of thermal stress responses in protein synthesis, heat shock proteins, and regulation. Future oceans with warmer waters may enhance overall metabolic and biogeochemical rates, but they will host altered microbial communities, especially in relatively thermally stable regions of the oceans. In order to allow full comparability with other ocean acidification data sets, the R package seacarb (Gattuso et al, 2019) was used to compute a complete and consistent set of carbonate system variables, as described by Nisumaa et al. (2010). In this dataset the original values were archived in addition with the recalculated parameters (see related PI). The date of carbonate chemistry calculation by seacarb is 2020-10-20.

    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/ PANGAEA - Data Publi...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/
    B2FIND
    Dataset . 2021
    Data sources: B2FIND
    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/
    PANGAEA
    Dataset . 2021
    Data sources: PANGAEA
    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/
    PANGAEA
    Dataset . 2020
    License: CC BY
    Data sources: PANGAEA
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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/ PANGAEA - Data Publi...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/
      B2FIND
      Dataset . 2021
      Data sources: B2FIND
      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/
      PANGAEA
      Dataset . 2021
      Data sources: PANGAEA
      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/
      PANGAEA
      Dataset . 2020
      License: CC BY
      Data sources: PANGAEA
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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: Schoepf, Verena; Grottoli, Andréa G; Warner, Mark E; Cai, Wei-Jun; +9 Authors

    Rising atmospheric CO2 concentrations threaten coral reefs globally by causing ocean acidification (OA) and warming. Yet, the combined effects of elevated pCO2 and temperature on coral physiology and resilience remain poorly understood. While coral calcification and energy reserves are important health indicators, no studies to date have measured energy reserve pools (i.e., lipid, protein, and carbohydrate) together with calcification under OA conditions under different temperature scenarios. Four coral species, Acropora millepora, Montipora monasteriata, Pocillopora damicornis, Turbinaria reniformis, were reared under a total of six conditions for 3.5 weeks, representing three pCO2 levels (382, 607, 741 µatm), and two temperature regimes (26.5, 29.0°C) within each pCO2 level. After one month under experimental conditions, only A. millepora decreased calcification (-53%) in response to seawater pCO2 expected by the end of this century, whereas the other three species maintained calcification rates even when both pCO2 and temperature were elevated. Coral energy reserves showed mixed responses to elevated pCO2 and temperature, and were either unaffected or displayed nonlinear responses with both the lowest and highest concentrations often observed at the mid-pCO2 level of 607 µatm. Biweekly feeding may have helped corals maintain calcification rates and energy reserves under these conditions. Temperature often modulated the response of many aspects of coral physiology to OA, and both mitigated and worsened pCO2 effects. This demonstrates for the first time that coral energy reserves are generally not metabolized to sustain calcification under OA, which has important implications for coral health and bleaching resilience in a high-CO2 world. Overall, these findings suggest that some corals could be more resistant to simultaneously warming and acidifying oceans than previously expected. In order to allow full comparability with other ocean acidification data sets, the R package seacarb (Lavigne et al, 2014) was used to compute a complete and consistent set of carbonate system variables, as described by Nisumaa et al. (2010). In this dataset the original values were archived in addition with the recalculated parameters (see related PI). The date of carbonate chemistry calculation is 2014-07-08. Supplement to: Schoepf, Verena; Grottoli, Andréa G; Warner, Mark E; Cai, Wei-Jun; Melman, Todd F; Hoadley, Kenneth D; Pettay, D Tye; Hu, Xinping; Li, Qian; Xu, Hui; Wang, Yujie; Matsui, Yohei; Baumann, Justin H (2013): Coral Energy Reserves and Calcification in a High-CO2 World at Two Temperatures. PLoS ONE, 8(10), e75049

    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/ PANGAEAarrow_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/
    PANGAEA
    Dataset . 2014
    Data sources: PANGAEA
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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/ PANGAEAarrow_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/
      PANGAEA
      Dataset . 2014
      Data sources: PANGAEA
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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: Nagelkerken, Ivan; Goldenberg, Silvan U; Ferreira, Camilo M; Ullah, Hadayet; +1 Authors

    As human activities intensify, the structures of ecosystems and their food webs often reorganize. Through the study of mesocosms harboring a diverse benthic coastal community, we reveal that food web architecture can be inflexible under ocean warming and acidification and unable to compensate for the decline or proliferation of taxa. Key stabilizing processes, including functional redundancy, trophic compensation, and species substitution, were largely absent under future climate conditions. A trophic pyramid emerged in which biomass expanded at the base and top but contracted in the center. This structure may characterize a transitionary state before collapse into shortened, bottom-heavy food webs that characterize ecosystems subject to persistent abiotic stress. We show that where food web architecture lacks adjustability, the adaptive capacity of ecosystems to global change is weak and ecosystem degradation likely. In order to allow full comparability with other ocean acidification data sets, the R package seacarb (Gattuso et al, 2021) was used to compute a complete and consistent set of carbonate system variables, as described by Nisumaa et al. (2010). In this dataset the original values were archived in addition with the recalculated parameters (see related PI). The date of carbonate chemistry calculation by seacarb is 2021-03-09.

    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/ PANGAEA - Data Publi...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/
    B2FIND
    Dataset . 2020
    Data sources: B2FIND
    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/
    PANGAEA
    Dataset . 2020
    Data sources: PANGAEA
    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/
    PANGAEA
    Dataset . 2021
    License: CC BY
    Data sources: PANGAEA
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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/ PANGAEA - Data Publi...arrow_drop_down
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      B2FIND
      Dataset . 2020
      Data sources: B2FIND
      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/
      PANGAEA
      Dataset . 2020
      Data sources: PANGAEA
      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/
      PANGAEA
      Dataset . 2021
      License: CC BY
      Data sources: PANGAEA
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    Authors: Linhardt, Tobias; Levy, Joseph S; Thomas, Christoph K;

    From 26 December 2012 to 21 January 2013 we measured relevant parameters for surface energy and mass exchange calculation at three closely collocated sites near the Ross Sea shore in the valley floor of lower Taylor Valley, McMurdo Dry Valleys, Antarctica. At any time during the experiment, two surface energy balance stations were operated: One station was installed throughout the whole period at the investigated water track, referred to as WT. The other station was operated as a reference representing the dominant non-water track (NWT), bare soil surfaces in lower Taylor Valley; it was successively installed at two sites with different soil textures: PLD was located on a paleolake delta dominated by fine surficial sediments, while GT represented coarse glacial till. At each station the following instruments were installed: A net radiometer (NR01, Hukseflux Thermal Sensors B.V., Delft, NL) was used for measuring solar and terrestrial radiation, an ultrasonic anemometer (81000 VRE, R.M. Young Company, Traverse City, MI, USA) and an infrared gas analyzer (LI-7500, LI-COR Inc., Lincoln, NE, USA) recorded data for turbulent heat flux estimation via the eddy-covariance method. Thermistors and thermocouples recorded soil temperatures in several depths in the thawed layer. Additionally, we used a thermal properties analyzer (KD2 Pro, Decagon Devices, Pullman, WA, USA) for measuring soil thermal properties for several samples taken from the surface. Eddy-covariance processing was done with the bmmflux tool of the University of Bayreuth (see appendix in Thomas et al., 2009), including data quality assessment after Foken et al. (2004). Turbulent flux footprints were modeled with the TERRAFEX model of the University of Bayreuth (Göckede, 2001) which provided contributions of adjacent land cover types to the flux footprint. Further information on the experimental setup can be found in Linhardt et al. (2019).

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    PANGAEA
    Other ORP type . 2019
    License: CC BY
    Data sources: PANGAEA
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      PANGAEA
      Other ORP type . 2019
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    Authors: Dumitru, Oana-Alexandra; Austermann, Jacqueline; Polyak, Victor J; Fornós, Joan J; +4 Authors

    Reconstructing the evolution of sea level during past warmer epochs such as the Pliocene provides insight into the response of sea level and ice sheets to prolonged warming. Although estimates of global mean sea level (GMSL) during this time do exist, they vary by several tens of metres, hindering the assessment of past and future ice-sheet stability. Here we show that during the mid-Piacenzian Warm Period, which was on average 2-3 degrees Celsius warmer than the pre-industrial period, the GMSL (sea-level equivalent changes in global ice volume) was about 16.2 metres higher than today. During the even warmer Pliocene Climatic Optimum (about 4 degrees Celsius warmer than pre-industrial), our results show that GMSL was 23.5 metres above the present level (m.a.p.s.l.). We present six GMSL data points, ranging from 4.39 to 3.27 million years ago, that are based on overgrowths on phreatic (from water-filled caves) speleothems from the western Mediterranean Sea, near Mallorca, Spain. This record is unique owing to its clear relationship to sea level, its reliable U-Pb ages and its long timespan, which allows us to quantify uncertainties on potential uplift. Our data indicate that ice sheets are very sensitive to warming and provide important calibration targets for future ice-sheet models.

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    PANGAEA
    Other ORP type . 2019
    License: CC BY
    Data sources: PANGAEA
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      PANGAEA
      Other ORP type . 2019
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    Authors: Harsch, Melanie A; HilleRisLambers, Janneke;

    Using an extensive network of occurrence records for 293 plant species collected over the past 40 years across a climatically diverse geographic section of western North America, we find that plant species distributions were just as likely to shift upwards (i.e., towards higher elevations) as downward (i.e., towards lower elevations) – despite consistent warming across the study area. Although there was no clear directional response to climate warming across the entire study area, there was significant region-to region- variation in responses (i.e. from as many as 73% to as few as32% of species shifting upward or downward). To understand the factors that might be controlling region-specific distributional shifts, we explored the relationship between the direction of change in distribution limits and the nature of recent climate change. We found that the direction of distribution limit shifts was explained by an interaction between the rate of change in local summer temperatures and seasonal precipitation. Specifically, species shifted upward at their upper elevational limit when snowfall declined at slower rates and minimum temperatures increased. By contrast, species shifted upwards at their lower elevation limit when maximum temperatures increased or both temperature and precipitation decreased. Our results suggest that future species' elevational distribution shifts will be complex, depending on the interaction between seasonal temperature and precipitation change.

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    PANGAEA
    Other ORP type . 2015
    License: CC BY ND
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      PANGAEA
      Other ORP type . 2015
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    Authors: Gómez, C E; Wickes, Leslie; Deegan, Dan; Etnoyer, Peter J; +1 Authors

    The global decrease in seawater pH known as ocean acidification has important ecological consequences and is an imminent threat for numerous marine organisms. Even though the deep sea is generally considered to be a stable environment, it can be dynamic and vulnerable to anthropogenic disturbances including increasing temperature, deoxygenation, ocean acidification and pollution. Lophelia pertusa is among the better-studied cold-water corals but was only recently documented along the US West Coast, growing in acidified conditions. In the present study, coral fragments were collected at ∼300 m depth along the southern California margin and kept in recirculating tanks simulating conditions normally found in the natural environment for this species. At the collection site, waters exhibited persistently low pH and aragonite saturation states (Omega arag) with average values for pH of 7.66 +- 0.01 and Omega arag of 0.81 +- 0.07. In the laboratory, fragments were grown for three weeks in “favorable” pH/Omega arag of 7.9/1.47 (aragonite saturated) and “unfavorable” pH/ Omega arag of 7.6/0.84 (aragonite undersaturated) conditions. There was a highly significant treatment effect (P < 0.001) with an average% net calcification for favorable conditions of 0.023 +- 0.009%/d and net dissolution of −0.010 +- 0.014%/d for unfavorable conditions. We did not find any treatment effect on feeding rates, which suggests that corals did not depress feeding in low pH/ Omega arag in an attempt to conserve energy. However, these results suggest that the suboptimal conditions for L. pertusa from the California margin could potentially threaten the persistence of this cold-water coral with negative consequences for the future stability of this already fragile ecosystem. In order to allow full comparability with other ocean acidification data sets, the R package seacarb (Gattuso et al, 2019) was used to compute a complete and consistent set of carbonate system variables, as described by Nisumaa et al. (2010). In this dataset the original values were archived in addition with the recalculated parameters (see related PI). The date of carbonate chemistry calculation by seacarb is 2020-06-12.

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    B2FIND
    Dataset . 2018
    Data sources: B2FIND
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    PANGAEA
    Dataset . 2018
    Data sources: PANGAEA
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    PANGAEA
    Dataset . 2020
    License: CC BY
    Data sources: PANGAEA
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      B2FIND
      Dataset . 2018
      Data sources: B2FIND
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      PANGAEA
      Dataset . 2018
      Data sources: PANGAEA
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      PANGAEA
      Dataset . 2020
      License: CC BY
      Data sources: PANGAEA
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    Authors: Jury, Christopher P; Delano, Mia N; Toonen, Robert J;

    Estimates of heritability inform evolutionary potential and the likely outcome of many management actions, but such estimates remain scarce for marine organisms. Here, we report high heritability of calcification rate among the eight most dominant Hawaiian coral species under reduced pH simulating future ocean conditions. Coral colonies were sampled from up to six locations across a natural mosaic in seawater chemistry throughout Hawaiʻi and fragmented into clonal replicates maintained under both ambient and high pCO2 conditions. Broad sense heritability of calcification rates was high among all eight species, ranging from a low of 0.32 in Porites evermanni to a high of 0.61 in Porites compressa. The overall results were inconsistent with short-term acclimatization to the local environment or adaptation to the mean or ideal conditions. Similarly, in 'local vs. foreign' and 'home vs. away' tests there was no clear signature of local adaptation. Instead, the data are most consistent with a protected polymorphism as the mechanism which maintains differential pH tolerance within the populations. Substantial individual variation, coupled with high heritability and large population sizes, imply considerable scope for natural selection and adaptive capacity, which has major implications for evolutionary potential and management of corals in response to climate change. In order to allow full comparability with other ocean acidification data sets, the R package seacarb (Gattuso et al, 2019) was used to compute a complete and consistent set of carbonate system variables, as described by Nisumaa et al. (2010). In this dataset the original values were archived in addition with the recalculated parameters (see related PI). The date of carbonate chemistry calculation by seacarb is 2020-05-6.

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    B2FIND
    Dataset . 2019
    Data sources: B2FIND
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    PANGAEA
    Dataset . 2019
    Data sources: PANGAEA
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    PANGAEA
    Dataset . 2019
    License: CC BY
    Data sources: PANGAEA
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      B2FIND
      Dataset . 2019
      Data sources: B2FIND
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      PANGAEA
      Dataset . 2019
      Data sources: PANGAEA
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      PANGAEA
      Dataset . 2019
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      Data sources: PANGAEA
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    Authors: Morato, Telmo; González-Irusta, José Manuel; Domínguez-Carrió, Carlos; Wei, C; +55 Authors

    We used environmental niche modelling along with the best available species occurrence data and environmental parameters to model habitat suitability for key cold-water coral and commercially important deep-sea fish species under present-day (1951-2000) environmental conditions and to forecast changes under severe, high emissions future (2081-2100) climate projections (RCP8.5 scenario) for the North Atlantic Ocean (from 18°N to 76°N and 36°E to 98°W). The VME indicator taxa included Lophelia pertusa , Madrepora oculata, Desmophyllum dianthus, Acanela arbuscula, Acanthogorgia armata, and Paragorgia arborea. The six deep-sea fish species selected were: Coryphaenoides rupestris, Gadus morhua, blackbelly Helicolenus dactylopterus, Hippoglossoides platessoides, Reinhardtius hippoglossoides, and Sebastes mentella. We used an ensemble modelling approach employing three widely-used modelling methods: the Maxent maximum entropy model, Generalized Additive Models, and Random Forest. This dataset contains: 1) Predicted habitat suitability index under present-day (1951-2000) and future (2081-2100; RCP8.5) environmental conditions for twelve deep-sea species in the North Atlantic Ocean, using an ensemble modelling approach. 2) Climate-induced changes in the suitable habitat of twelve deep-sea species in the North Atlantic Ocean, as determined by binary maps built with an ensemble modelling approach and the 10-percentile training presence logistic (10th percentile) threshold. 3) Forecasted present-day suitable habitat loss (value=-1), gain (value=1), and acting as climate refugia (value=2) areas under future (2081-2100; RCP8.5) environmental conditions for twelve deep-sea species in the North Atlantic Ocean. Areas were identified from binary maps built with an ensemble modelling approach and two thresholds: 10-percentile training presence logistic threshold (10th percentile) and maximum sensitivity and specificity (MSS). Refugia areas are those areas predicted as suitable both under present-day and future conditions. All predictions were projected with the Albers equal-area conical projection centred in the middle of the study area. The grid cell resolution is of 3x3 km.

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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/
    B2FIND
    Dataset . 2019
    Data sources: B2FIND
    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/
    PANGAEA
    Dataset . 2019
    License: CC BY
    Data sources: PANGAEA
    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/
    PANGAEA
    Dataset . 2019
    Data sources: PANGAEA
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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/ PANGAEA - Data Publi...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/
      B2FIND
      Dataset . 2019
      Data sources: B2FIND
      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/
      PANGAEA
      Dataset . 2019
      License: CC BY
      Data sources: PANGAEA
      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/
      PANGAEA
      Dataset . 2019
      Data sources: PANGAEA
      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.