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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/

    The goal of WP3 is to develop a design framework for novel ground (slinky/earth basket) type shallow heat exchangers. This design framework, based on developing theoretical models of heat transfer and on experimental data, will be implemented in a design- and engineering calculation tool to support the implementation of these new technologies in the market. The design framework defines the goals of the (thermal and hydraulic) design (especially sizing) of the ground source heat exchanger, as a function of different boundary conditions (building energy demand, soil thermal parameters, required system performance etc.). Moreover, an engineering tool it is aimed at the overall system design and will support the engineer in the choices of heat exchanger technology (vertical, horizontal or earth basket/slinky) and other design parameterizations. This deliverable describes the overall design process and provides information and procedures for data collection and evaluation. The detailed description of the design process for different types of Ground Heat Exchangers is based on the design of the actual GHEX systems implemented in the demo sites of the Geofit project and includes vertical borehole heat exchangers, shallow slinky heat exchangers and earth basket type heat exchangers. This deliverable is suited to be implemented in a design handbook or procedure that can be part of an integrated quality control system.

    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ ZENODOarrow_drop_down
    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    ZENODO
    Project deliverable . 2019
    License: CC BY
    Data sources: Datacite
    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    ZENODO
    Other literature type . 2019
    License: CC BY
    Data sources: ZENODO
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    ZENODO
    Project deliverable . 2019
    License: CC BY
    Data sources: Datacite
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      ZENODO
      Project deliverable . 2019
      License: CC BY
      Data sources: Datacite
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      ZENODO
      Other literature type . 2019
      License: CC BY
      Data sources: ZENODO
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      ZENODO
      Project deliverable . 2019
      License: CC BY
      Data sources: Datacite
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    Authors: Marques, Carlos; Silva, Mafalda; Kumar, Shravan; Goumas, Giorgos; +13 Authors

    The EMB3Rs Unified Modelling Platform is a tool to assist on modelling the recovery of excess heat and its reuse to meet final energy demand within and beyond the boundaries of industrial sites. The tool consists of a knowledge base and several simulation modules. This database comprises the research data generated in the course of the EMB3Rs project by using the EMB3Rs platform. The pdf file contains the detailed description of the database content It has been deposited at Zenodo’s open data repository with DOI 10.5281/zenodo.7994255.

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    ZENODO
    Dataset . 2023
    License: CC BY
    Data sources: Datacite
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    ZENODO
    Dataset . 2023
    License: CC BY
    Data sources: Datacite
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    ZENODO
    Dataset . 2023
    License: CC BY
    Data sources: ZENODO
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      ZENODO
      Dataset . 2023
      License: CC BY
      Data sources: Datacite
      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
      ZENODO
      Dataset . 2023
      License: CC BY
      Data sources: Datacite
      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
      ZENODO
      Dataset . 2023
      License: CC BY
      Data sources: ZENODO
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    Authors: Borjas, Zulema; orcid Ortiz, Juan M.;
    Ortiz, Juan M.
    ORCID
    Harvested from ORCID Public Data File

    Ortiz, Juan M. in OpenAIRE
    Aldaz Riera, Antonio; orcid Feliu, Juan M.;
    Feliu, Juan M.
    ORCID
    Harvested from ORCID Public Data File

    Feliu, Juan M. in OpenAIRE
    +1 Authors

    Microbial electrochemical technologies (METs) constitute the core of a number of emerging technologies with a high potential for treating urban wastewater due to a fascinating reaction mechanism—the electron transfer between bacteria and electrodes to transform metabolism into electrical current. In the current work, we focus on the model electroactive microorganism Geobacter sulfurreducens to explore both the design of new start-up procedures and electrochemical operations. Our chemostat-grown plug and play cells, were able to reduce the start-up period by 20-fold while enhancing chemical oxygen demand (COD) removal by more than 6-fold during this period. Moreover, a filter-press based bioreactor was successfully tested for both acetate-supplemented synthetic wastewater and real urban wastewater. This proof-of-concept pre-pilot treatment included a microbial electrolysis cell (MEC) followed in time by a microbial fuel cell (MFC) to finally generate electrical current of ca. 20 A·m−2 with a power of 10 W·m−2 while removing 42 g COD day−1·m−2. The effective removal of acetate suggests a potential use of this modular technology for treating acetogenic wastewater where Geobacter sulfurreducens outcompetes other organisms.

    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/ Energiesarrow_drop_down
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    Energies
    Article . 2015 . Peer-reviewed
    License: CC BY
    Data sources: Crossref
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    Energies
    Article
    License: CC BY
    Data sources: UnpayWall
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    Energies
    Article . 2015
    Data sources: DOAJ
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      Energies
      Article . 2015 . Peer-reviewed
      License: CC BY
      Data sources: Crossref
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      Energies
      Article
      License: CC BY
      Data sources: UnpayWall
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      Energies
      Article . 2015
      Data sources: DOAJ
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    Authors: orcid Giampieri, Alessandro;
    Giampieri, Alessandro
    ORCID
    Harvested from ORCID Public Data File

    Giampieri, Alessandro in OpenAIRE
    orcid Ma, Zhiwei;
    Ma, Zhiwei
    ORCID
    Harvested from ORCID Public Data File

    Ma, Zhiwei in OpenAIRE
    orcid Smallbone, Andrew;
    Smallbone, Andrew
    ORCID
    Harvested from ORCID Public Data File

    Smallbone, Andrew in OpenAIRE
    orcid Roskilly, Anthony Paul;
    Roskilly, Anthony Paul
    ORCID
    Harvested from ORCID Public Data File

    Roskilly, Anthony Paul in OpenAIRE

    Abstract In an effort to minimise electricity consumption and greenhouse gases emissions, the heating, ventilation and air-conditioning sector has focused its attention on developing alternative solutions to electrically-driven vapour-compression cooling. Liquid desiccant air-conditioning systems represent an energy-efficient and more environmentally friendly alternative technology for dehumidification and cooling, particularly in those cases with high latent loads to maintain indoor air quality and comfort conditions. This technology is considered particularly efficient in hot and humid climates. As a matter of fact, the choice of the desiccant solution influences the overall performance of the system. The current paper reviews the working principle of liquid desiccant systems, focusing on the thermodynamic properties of the desiccant solutions and describes an evaluation of the reference thermodynamic properties of different desiccant solutions to identify which thermodynamic, physical, transport property influences the liquid desiccant process and to what extent. The comparison of these thermodynamic properties for the commonly used desiccants is conducted to estimate which fluid could perform most favourably in the system. The economic factors and the effect of different applications and climatic conditions on the system performance are also described. The paper is intended to be the first step in the evaluation of alternative desiccant fluids able to overcome the problems related to the use of the common desiccant solutions, such as crystallization and corrosion to metals. Ionic liquids seem a promising alternative working fluid in liquid desiccant air-conditioning systems and their characteristics and cost are discussed.

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    Applied Energy
    Article
    License: CC BY NC ND
    Data sources: UnpayWall
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    Applied Energy
    Article . 2018 . Peer-reviewed
    License: Elsevier TDM
    Data sources: Crossref
    Applied Energy
    Article . 2018 . Peer-reviewed
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      Applied Energy
      Article
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      Applied Energy
      Article . 2018 . Peer-reviewed
      License: Elsevier TDM
      Data sources: Crossref
      Applied Energy
      Article . 2018 . Peer-reviewed
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    Authors: Adrian, Benjamin; Upwards Consortium;

    This dataset was used in Deliverable 6.6 of Upwards. It contains turbine properties of turbines in a simulation of the Lillgrund wind park. The simulation was conducted for different yaw misalignments of the turbines in the freestream. Thus this dataset contains 4 folders which each correspond to one yaw misalignment. The folder name indicates the yaw misalignment where 270 corresponds to a yaw misalignment of 0° while 260 corresponds to -10°. The files in each folder contain the following properties: time torqueGen powerRotor rotSpeed thrust torqueRotor These properties are available for all turbines in the park. Further the accumulated properties are available for each row of turbines and the whole park.

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    ZENODO
    Dataset . 2022
    License: CC BY
    Data sources: Datacite
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    ZENODO
    Dataset . 2022
    License: CC BY
    Data sources: Datacite
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    ZENODO
    Dataset . 2022
    License: CC BY
    Data sources: ZENODO
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      ZENODO
      Dataset . 2022
      License: CC BY
      Data sources: Datacite
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      ZENODO
      Dataset . 2022
      License: CC BY
      Data sources: Datacite
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      ZENODO
      Dataset . 2022
      License: CC BY
      Data sources: ZENODO
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    Authors: Li, Ru; Perdana, Sigit; Vielle, Marc;

    This dataset contains the underlying data for the following publication: Li, R., Perdana, S., Vielle, M. (2021), Potential integration of Chinese and European emissions trading market: welfare distribution analysis, Mitigation and Adaptation Strategies for Global Change, 26:22 https://doi.org/10.1007/s11027-021-09960-7.

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    ZENODO
    Dataset . 2021
    License: CC BY
    Data sources: Datacite
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    ZENODO
    Dataset . 2021
    License: CC BY
    Data sources: Datacite
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    ZENODO
    Dataset . 2021
    License: CC BY
    Data sources: ZENODO
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    influenceAverage
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    downloaddownloads1
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      ZENODO
      Dataset . 2021
      License: CC BY
      Data sources: Datacite
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      ZENODO
      Dataset . 2021
      License: CC BY
      Data sources: Datacite
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      ZENODO
      Dataset . 2021
      License: CC BY
      Data sources: ZENODO
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    Authors: orcid bw D'Amario, Barbara;
    D'Amario, Barbara
    ORCID
    Derived by OpenAIRE algorithms or harvested from 3rd party repositories

    D'Amario, Barbara in OpenAIRE
    orcid bw Pérez-Mejías, Carlos;
    Pérez-Mejías, Carlos
    ORCID
    Derived by OpenAIRE algorithms or harvested from 3rd party repositories

    Pérez-Mejías, Carlos in OpenAIRE
    orcid bw Grelaud, Michaël;
    Grelaud, Michaël
    ORCID
    Derived by OpenAIRE algorithms or harvested from 3rd party repositories

    Grelaud, Michaël in OpenAIRE
    Paraskevi, Pitta; +2 Authors

    Mesocosm experiments have been fundamental to investigate the effects of elevated CO2 and ocean acidification (OA) on planktic communities. However, few of these experiments have been conducted using naturally nutrient-limited waters and/or considering the combined effects of OA and ocean warming (OW). Coccolithophores are a group of calcifying phytoplankton that can reach high abundances in the Mediterranean Sea, and whose responses to OA are modulated by temperature and nutrients. We present the results of the first land-based mesocosm experiment testing the effects of combined OA and OW on an oligotrophic Eastern Mediterranean coccolithophore community. Coccolithophore cell abundance drastically decreased under OW and combined OA and OW (greenhouse, GH) conditions. Emiliania huxleyi calcite mass decreased consistently only in the GH treatment; moreover, anomalous calcifications (i.e. coccolith malformations) were particularly common in the perturbed treatments, especially under OA. Overall, these data suggest that the projected increase in sea surface temperatures, including marine heatwaves, will cause rapid changes in Eastern Mediterranean coccolithophore communities, and that these effects will be exacerbated by OA. 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 2021-05-11.

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    B2FIND
    Dataset . 2020
    Data sources: B2FIND
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    PANGAEA
    Dataset . 2021
    License: CC BY
    Data sources: PANGAEA
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    PANGAEA
    Dataset . 2020
    Data sources: PANGAEA
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      B2FIND
      Dataset . 2020
      Data sources: B2FIND
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      PANGAEA
      Dataset . 2021
      License: CC BY
      Data sources: PANGAEA
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      PANGAEA
      Dataset . 2020
      Data sources: PANGAEA
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    Authors: Norris, Federico;

    Questionnaires provided within the Hit2Gap H2020 project. Lsits needs and requirements of the different actors of the project; these actors are at different responsibilities of a building.

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    ZENODO
    Dataset . 2017
    License: CC BY
    Data sources: Datacite
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    ZENODO
    Dataset . 2017
    License: CC BY
    Data sources: ZENODO
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      ZENODO
      Dataset . 2017
      License: CC BY
      Data sources: Datacite
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      ZENODO
      Dataset . 2017
      License: CC BY
      Data sources: ZENODO
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    Authors: orcid bw Eschenbacher, Roman;
    Eschenbacher, Roman
    ORCID
    Derived by OpenAIRE algorithms or harvested from 3rd party repositories

    Eschenbacher, Roman in OpenAIRE
    orcid bw Hemauer, Felix;
    Hemauer, Felix
    ORCID
    Derived by OpenAIRE algorithms or harvested from 3rd party repositories

    Hemauer, Felix in OpenAIRE
    Franz, Evanie; Leng, Andreas; +11 Authors

    Raw Data, evaluated files and a list of experiments is provided.

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    ZENODO
    Dataset . 2023
    License: CC BY
    Data sources: Datacite
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    ZENODO
    Dataset . 2023
    License: CC BY
    Data sources: ZENODO
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    ZENODO
    Dataset . 2023
    License: CC BY
    Data sources: ZENODO
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    ZENODO
    Dataset . 2023
    License: CC BY
    Data sources: Datacite
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      ZENODO
      Dataset . 2023
      License: CC BY
      Data sources: Datacite
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      ZENODO
      Dataset . 2023
      License: CC BY
      Data sources: ZENODO
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      ZENODO
      Dataset . 2023
      License: CC BY
      Data sources: ZENODO
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      ZENODO
      Dataset . 2023
      License: CC BY
      Data sources: Datacite
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    Authors: orcid bw Bennett, Scott;
    Bennett, Scott
    ORCID
    Derived by OpenAIRE algorithms or harvested from 3rd party repositories

    Bennett, Scott in OpenAIRE
    orcid bw Marba, Nuria;
    Marba, Nuria
    ORCID
    Derived by OpenAIRE algorithms or harvested from 3rd party repositories

    Marba, Nuria in OpenAIRE
    Vaquer-Sunyer, Raquel; orcid bw Jordá, Gabriel;
    Jordá, Gabriel
    ORCID
    Derived by OpenAIRE algorithms or harvested from 3rd party repositories

    Jordá, Gabriel in OpenAIRE
    +2 Authors

    [Experimental design: thermal performance experiments] All experiments were run in climate-controlled incubation facilities of the Institut Mediterrani d’Estudis Avançats (Mallorca, Spain). Following 48 hrs under ambient (collection site) conditions, samples were transferred to individual experimental aquaria, which consisted of a double layered transparent plastic bag filled with 2 L of filtered seawater (60 μm) (following Savva et al. 2018). 16 experimental bags were suspended within 80L temperature-controlled baths. In total, ten baths were used, one for each experimental temperature treatment. Bath temperatures were initially set to the acclimatization temperature (i.e. in situ temperatures) and were subsequently increased or decreased by 1 °C every 24 hours until the desired experimental temperature was achieved. Experimental temperatures were: 15, 18, 21, 24, 26, 28, 30, 32, 34 and 36°C (Table S2). For each species, four replicate aquarium bags were used for each temperature treatment with three individually marked seagrass shoots or three algal fragments placed into each bag. For P. oceanica, each marked plant was a single shoot including leaves, vertical rhizome and roots. For C. nodosa, each marked individual consisted of a 10 cm fragment of horizontal rhizome containing three vertical shoots. Individually marked seaweeds contained the holdfast, and 4-5 fronds of P. pavonica (0.98 ± 0.06 g FW; mean ± SE) or a standardised 5-8 cm fragment with meristematic tip for C. compressa (3.67 ± 0.1 g FW; mean ± SE). Experimental plants were cleaned of conspicuous epiphytes. Once the targeted temperatures were reached in all of the baths, experiments ran for 14 days for the algal species and 21 days for seagrasses to allow for measurable growth in all species at the end of the experiment. Experiments were conducted inside a temperature-controlled chamber at constant humidity and air temperature (15 °C). Bags were arranged in a 4x4 grid within each bath, enabling four species/population treatments to be run simultaneously. Bags were mixed within each bath so that one replicate bag was in each row and column of the grid, to minimise any potential within bath effects of bag position. Replicate bags were suspended with their surface kept open to allow gas exchange and were illuminated with a 14h light:10h dark photoperiod through fluorescent aquarium growth lamps. The water within the bags were mixed with aquaria pumps. The light intensity within each bag was measured via a photometric bulb sensor (LI-COR) and ranged between 180-258 μmol m-2 s-1. Light intensity was constant between experiments and did not significantly differ between experimental treatments (p > 0.05). The temperature in the baths was controlled and recorded with an IKS-AQUASTAR system, which was connected to heaters and thermometers. The seawater within the bags was renewed every 72 hrs and salinity was monitored daily with an YSI multi-parameter meter. Distilled water was added when necessary to ensure salinity levels remained within the range of 36-39 PSU, typical of the study region. Carbon and Nitrogen concentrations in the leaf tissue were measured at the end of the experiment for triplicates of the 24ºC treatment for each species and location (Fig. S2) at Unidade de Técnicas Instrumentais de Análise (University of Coruña, Spain) with an elemental analyser FlashEA112 (ThermoFinnigan). [Species description and distribution] The species used in this study are all common species throughout the Mediterranean Sea, although differ in their biological traits, evolutionary histories and thermo-geographic affinities (Fig. S1). P. oceanica is endemic to the Mediterranean Sea with the all other Posidonia species found in temperate Australia (Aires et al. 2011). The distribution of P. oceanica is restricted to the Mediterranean, spanning from Gibraltar in the west to Cyprus in the east and north into the Aegean and Adriatic seas (Telesca et al. 2015) (Fig. S1A). C. nodosa distribution extends across the Mediterranean Sea and eastern Atlantic Ocean, where it is found from south west Portugal, down the African coast to Mauritania and west to Macaronesia (Alberto et al. 2008) (Fig. S1B). Congeneric species of C. nodosa are found in tropical waters of the Red Sea and Indo-Pacific, suggesting origins in the region at least prior to the closure of the Suez Isthmus, approximately 10Mya. Like C. nodosa, Cystoseira compressa has a distribution that extends across the Mediterranean and into the eastern Atlantic, where it is found west to Macaronesia and south to northwest Africa (Fig. S1C). The genus Cystoseira has recently been reclassified to include just four species with all congeneric Cystoseira spp. having warm-temperate distributions from the Mediterranean to the eastern Atlantic (Orellana et al. 2019). The distribution of Padina pavonica is conservatively considered to resemble C. nodosa and C. compressa, spanning throughout the Mediterranean and into the eastern Atlantic. We considered the poleward distribution limit of P. pavonica to be the British Isles 50ºN (Herbert et al. 2016). P. pavonica was previously thought to have a global distribution, but molecular analysis of the genus has found no evidence to support this (Silberfeld et al. 2013). Instead it has been suggested that P. pavonica was potentially misclassified outside of the Mediterranean, due to morphological similarity with congeneric species (Silberfeld et al. 2013). Padina is a monophyletic genus with a worldwide distribution from tropical to cold temperate waters (Silberfeld et al. 2013). Most species have a regional distribution, with few confirmed examples of species spanning beyond a single marine realm (sensu Spalding et al. 2007). [Metabolic rates] Net production (NP), gross primary production (GPP) and respiration (R) were measured for all species from the four sites for five different experimental temperatures containing the in-situ temperature during sampling up to a 6ºC warming (see SM Table S3 for details). Individuals of the different species were moved to methacrylate cylinders containing seawater treated with UV radiation to remove bacteria and phytoplankton, in incubation tanks at the 5 selected temperatures. Cylinders were closed using gas-tight lids that prevent gas exchange with the atmosphere, containing an optical dissolved oxygen sensor (ODOS® IKS), with a measuring range from 0-200 % saturation and accuracy at 25ºC of 1% saturation, and magnetic stirrers inserted to ensure mixing along the height of the core. Triplicates were measured for each species and location, along with controls consisting in cylinders filled with the UV-treated seawater, in order to account for any residual production or respiration derived from microorganisms (changes in oxygen in controls was subtracted from treatments). Oxygen was measured continuously and recorded every 15 minutes for 24 hours. Changes in the dissolved oxygen (DO) were assumed to result from the biological metabolic processes and represent NP. During the night, changes in DO are assumed to be driven by R, as in the absence of light, no photosynthetic production can occur. R was calculated from the rate of change in oxygen at night, from half an hour after lights went off to half an hour before light went on (NP in darkness equalled R). NP was calculated from the rate of change in DO, at 15 min intervals, accumulated over each 24 h period. Assuming that daytime R equals that during the night, GPP was estimated as the sum of NP and R. To derive daily metabolic rates, we accumulated individual estimates of GPP, NP, and R resolved at 15 min intervals over each 24 h period during experiments and reported them in mmol O2 m−3 day−1. A detailed description of calculation of metabolic rates can be found at Vaquer-Sunyer et al. (Vaquer-Sunyer et al. 2015). [Thermal distribution and thermal safety margins] We estimated the realised thermal distribution for the four experimental species by downloading occurrence records from the Global Biodiversity Information Facility (GBIF.org (11/03/2020) GBIF Occurrence Download). Occurrence records from GBIF were screened for outliers and distributions were verified from the primary literature (Alberto et al. 2008, Draisma et al. 2010, Ni-Ni-Win et al. 2010, Silberfeld et al. 2013, Telesca et al. 2015, Orellana et al. 2019) and Enrique Ballesteros (pers. comms) (Fig. S1). Mean, 1st and 99th percentiles of daily SST’s were downloaded for each occurrence site for the period between 1981-2019 using the SST products described above (Table S4). Thermal range position of species at each experimental site were standardised by their global distribution using a Range Index (RI; Sagarin & Gaines 2002). Median SST at the experimental collection sites were standardized relative to the thermal range observed across a species realized distribution, using the equation: RI = 2(SM- DM)/DB where SM = the median temperature at the experimental collection site, Dm = the thermal midpoint of the species global thermal distribution and DB = range of median temperatures (ºC) that a species experiences across its distribution. The RI scales from -1 to 1, whereby ‘-1’ represents the cool, leading edge of a species distribution, ‘0’ represents the thermal midpoint of a species distribution and ‘1’ represents the warm, trailing edge of a species distribution (Sagarin & Gaines 2002). Thermal safety margins for each population were calculated as the difference between empirically derived upper thermal limits for each population and the maximum long term habitat temperatures recorded at collection sites. Each population’s thermal safety margin was plotted against its range position to examine patterns in thermal sensitivity across a species distribution. [Growth measurements and statistical analyses] Net growth rate of seagrass shoots was measured using leaf piercing-technique (Short & Duarte 2001). At the beginning of the experiment seagrass shoots were pierced just below the ligule with a syringe needle and shoot growth rate was estimated as the elongation of leaf tissue in between the ligule and the mark position of all leaves in a shoot at the end of the experiment, divided by the experimental duration. Net growth rate of macroalgae individuals was measured as the difference in wet weight at the end of the experiment from the beginning of the experiment divided by the duration of the experiment. Moisture on macroalgae specimens was carefully removed before weighing them. Patterns of growth in response to temperature were examined for each experimental population using a gaussian function: g = ke[-0.5(TMA-μ)2/σ2], where k = amplitude, μ = mean and σ = standard deviation of the curve. Best fit values for each parameter were determined using a non-linear least squares regression using the ‘nlstools’ package (Baty et al. 2015) in R (Team 2020). 95% CI for each of the parameters were calculated using non-parametric bootstrapping of the mean centred residuals. The relationship between growth metrics and the best-fit model was determined by comparing the sum of squared deviations (SS) of the observed data from the model, to the SS of 104 randomly resampled datasets. Growth metrics were considered to display a significant relationship to the best-fit model if the observed SS was smaller than the 5th percentile of randomised SS. Upper thermal limits were defined as the optimal temperature + 2 standard deviations (95th percentile of curve) or where net growth = 0. Samples that had lost all pigment or structural integrity by the end of the experiment were considered dead and any positive growth was treated as zero. Comparative patterns in thermal performance between populations have fundamental implications for a species thermal sensitivity to warming and extreme events. Despite this, within-species variation in thermal performance is seldom measured. Here we compare thermal performance between-species variation within communities, for two species of seagrass (Posidonia oceanica and Cymodocea nodosa) and two species of seaweed (Padina pavonica and Cystoseira compressa). Experimental populations from four locations spanning approximately 75% of each species global distribution and a 6ºC gradient in summer temperatures were exposed to 10 temperature treatments (15ºC to 36ºC), reflecting median, maximum and future temperatures. Experimental thermal performance displayed the greatest variability between species, with optimal temperatures differing by over 10ºC within the same location. Within-species differences in thermal performance were also important for P. oceanica which displayed large thermal safety margins within cool and warm-edge populations and small safety margins within central populations. Our findings suggest patterns of thermal performance in Mediterranean seagrasses and seaweeds retain deep ‘pre-Mediterranean’ evolutionary legacies, suggesting marked differences in sensitivity to warming within and between benthic marine communities. [Sample collection] Sample collections were conducted at two sites, separated by approximately 1 km, within each location. Collections were conducted at the same depth (1-3 m) at each location and were spaced across the reef or meadow to try and minimise relatedness between shoots or fragments. Upon collection, fragments were placed into a mesh bag and transported back to holding tanks in cool, damp, dark conditions (following Bennett et al. 2021). Fragments were kept in aerated holding tanks in the collection sites at ambient seawater temperature and maintained under a 14:10 light-dark cycle until transport back to Mallorca, where experiments were performed. Prior to transport, P. oceanica shoots were clipped to 25 cm length (from meristem to tip), to standardise initial conditions and remove old tissue for transport. For transport back to Mallorca, fragments were packed in layers within cool-boxes. Cool-packs were wrapped in damp tea towels (rinsed in seawater) and placed between layers of samples. Samples from Catalonia, Crete and Cyprus experienced approximately 12hrs of transit time. On arrival at the destination, samples were returned to holding tanks with aerated seawater and a 14:10 light-dark cycle. [Sea temperature measurements and reconstruction] Sea surface temperature data for each collection site were based on daily SST maps with a spatial resolution of 1/4°, obtained from the National Center for Environmental Information (NCEI, https://www.ncdc.noaa.gov/oisst (Reynolds et al. 2007). These maps have been generated through the optimal interpolation of Advanced Very High Resolution Radiometer (AVHRR) data for the period 1981-2019. Underwater temperature loggers (ONSET Hobo pro v2 Data logger) were deployed at each site and recorded hourly temperatures throughout one year. In order to obtain an extended time series of temperature at each collection site, a calibration procedure was performed comparing logger data with sea surface temperature from the nearest point on SST maps. In particular, SST data were linearly fitted to logger data for the common period. Then, the calibration coefficients were applied to the whole SST time series to obtain corrected-SST data and reconstruct daily habitat temperatures from 1981-2019. [Field collections] Thermal tolerance experiments were conducted on two seagrass species (P. oceanica and Cymodocea nodosa) and two brown seaweed species (Cystoseira compressa and P. pavonica) from four locations spanning 8 degrees in latitude and 30 degrees in longitude across the Mediterranean (Fig. 1, Table S1). These four species were chosen as they are dominant foundation species and cosmopolitan across the Mediterranean Sea. Thermal performance experiments from Catalonia and Mallorca were conducted simultaneously in June 2016 for seaweeds (P. pavonica and C. compressa) and in August 2016 for seagrasses (P. oceanica and C. nodosa). Experiments for all four species were conducted in July 2017 for Crete and in September 2017 for Cyprus. Horizon 2020 Framework Programme, Award: 659246; Juan de la Cierva Formacion, Award: FJCI-2016-30728; Spanish Ministry of Economy, Industry and Competitiveness, Award: MedShift, CGL2015-71809-P; Spanish Ministry of Science, Innovation and Universities, Award: SUMAECO, RTI2018-095441-B-C21

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