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  • Digital.CSIC

  • 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: Civantos-Gómez, Iciar; Rubio Teso, María Luisa; Galeano, Javier; Rubiales, Diego; +2 Authors

    Crop Wild Relatives (CWR) are a valuable source of genetic diversity that can be transferred to commercial crops, so their conservation will become a priority in the face of climate change. Bizarrely, in situ conserved CWR populations and the traits one might wish to preserve in them are themselves vulnerable to climate change. In this study, we used a quantitative machine learning predictive approach to project the resistance of CWR populations of lentils to a common disease, lentil rust, caused by fungus Uromyces viciae-fabae. Resistance is measured through a proxy quantitative value, DSr (Disease Severity relative), quite complex and expensive to get. Therefore, machine learning is a convenient tool to predict this magnitude using a well-curated georeferenced calibration set. Previous works have provided a binary outcome (resistant vs. non-resistant), but that approach is not fine enough to answer three practical questions: which variables are key to predict rust resistance, which CWR populations are resistant to rust under current environmental conditions, and which of them are likely to keep this trait under different climate change scenarios. We first predict rust resistance in present time for crop wild relatives that grow up inside protected areas. Then, we use the same models under future climate IPCC (Intergovernmental Panel on Climate Change) scenarios to predict future DSr values. Populations that are rust-resistant by now and under future conditions are optimal candidates for further evaluation and in situ conservation of this valuable trait. We have found that rust-resistance variation as a result of climate change is not uniform across the geographic scope of the study (the Mediterranean basin), and that candidate populations share some interesting common environmental conditions. Peer reviewed

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    Digital.CSIC
    Dataset . 2022 . Peer-reviewed
    Data sources: Digital.CSIC
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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/ Recolector de Cienci...arrow_drop_down
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      Digital.CSIC
      Dataset . 2022 . Peer-reviewed
      Data sources: Digital.CSIC
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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: Sanchez Vidal, Anna; CSIC - Unidad de Tecnología Marina (UTM);

    In the FAR-DWO DS1 oceanographic cruise we analyze the hydrographic and sedimentological variability of the Denmark Strait Overflow using water column and seafloor observation and sampling techniques. We also deploy multi-instrumented mooring lines at depths between 1000 m and 2000 m to record information of the dense current during a whole year. The FAR-DWO DS1 cruise will last from July 19th to August 12th 2023 onboard the oceanographic vessel Sarmiento de Gamboa (CSIC). We are a team of around thirty experts from the Universitat de Barcelona (UB), Universidad de Las Palmas de Gran Canaria (ULPGC), Institut Français de Recherche pour l'Exploitation de la Mer (IFREMER), University of Iceland (UI), and the company specialized in satellite technology Lobelia Earth, and we count on the technical support of Unidad de Tecnología Marina (UTM-CSIC). Oceanographic data acquired during the FAR-DWO_DS1 Cruise (29SG20230719) on board the Research Vessel Sarmiento de Gamboa in 2023.

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    Digital.CSIC
    Dataset . 2023
    Data sources: Digital.CSIC
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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/ Recolector de Cienci...arrow_drop_down
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      Digital.CSIC
      Dataset . 2023
      Data sources: Digital.CSIC
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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: Villegas-Fernández, Ángel M.; Rubiales, Diego;

    Characterization data of a Vicia faba germplams collection grown at Córdoba, Spain at three sites during 2022 and 2023.

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    Digital.CSIC
    Dataset . 2024
    Data sources: Datacite
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      Digital.CSIC
      Dataset . 2024
      Data sources: Datacite
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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: Villanueva, Joan; CSIC - Unidad de Tecnología Marina (UTM);

    The aim of the project is to develop an innovative palaeo-proxy approach to investigate the natural range of variability of the Hadley circulation during past episodes of extreme warmth and cold. The approach relies on the exploitation as climate proxy of an untapped but widespread material in marine sediments: windborne pyrogenic carbon (PyC) derived from savannah and grassland fires in the tropics. Through the geochemical and isotopic spatial characterization of PyC, along with the analysis of mineral dust in the modern tropical deep ocean, and a PyC biogeochemical model, we will build an interpretative framework of PyC deposition in deep-sea sediments. Its application in Pliocene-Pleistocene sequences from the Atlantic and the Pacific will allow the reconstruction of past meridional and zonal shifts in the Intertropical Convergence Zone and the Southern hemisphere westerlies, and provide new constraints on the natural variability of the Hadley circulation and associated hydroclimates. PYROWIND Cruise (29HE20220426) carried out on the Research Vessel Hespérides in 2022.

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    Digital.CSIC
    Dataset . 2022
    Data sources: Digital.CSIC
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      Digital.CSIC
      Dataset . 2022
      Data sources: Digital.CSIC
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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: CSIC - Unidad de Tecnología Marina (UTM);

    Oceanographic data acquired during the ANTARLOG_LEG2 Cruise (29SG20161203) on board the Research Vessel Sarmiento de Gamboa in 2016. Logistic voyage without any scientific work.

    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/ Recolector de Cienci...arrow_drop_down
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    Digital.CSIC
    Dataset . 2022
    Data sources: Digital.CSIC
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      Digital.CSIC
      Dataset . 2022
      Data sources: Digital.CSIC
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    Authors: Catalán, Manuel; CSIC - Unidad de Tecnología Marina (UTM);

    Oceanographic data acquired during theZEE-2021 Cruise (29HE20210325) on board the Research Vessel Hespérides in 2021 ZEE-2021: Study of the Spanish Economic Zone in the Canary Islands.

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    Digital.CSIC
    Dataset . 2021
    Data sources: Digital.CSIC
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      Digital.CSIC
      Dataset . 2021
      Data sources: Digital.CSIC
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  • Authors: Fernández-Benito, Amparo; Rivera-Gálvez, Francisco J.; Cisneros-Ruiz, P.; Sanz-Horta, Raúl; +3 Authors
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    Authors: Gasol, Josep M.; CSIC - Unidad de Tecnología Marina (UTM);

    The MIAU-DCM campaign will study the biological characteristics of the deep chlorophyll maximum in the Northwest Mediterranean. To do this, the first 150-200 meters of the water column will be sampled with CTD along a transect between the towns of Blanes and a point near Cape Formentor, and from the continental shelf (depth 40-50 meters). Once the depth of the DCM has been defined, and its variability along the transect, the stations in which biological sampling will be carried out will be defined, which will consist of taking samples from approximately 100 m and the surface. In addition, station D (in the middle of the basin) will be characterized up to 2500 meters. Oceanographic data acquired during the MIAU-DCM Cruise (29GD20210601) on board the Research Vessel García del Cid in 2021.

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    Digital.CSIC
    Dataset . 2021
    Data sources: Digital.CSIC
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      Digital.CSIC
      Dataset . 2021
      Data sources: Digital.CSIC
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    Authors: Sbay, Hassan; Zas Arregui, Rafael;

    Methodology: The genetic material comprise 57 populations (8 of Brutia pine and 49 of Aleppo pine) originating from 7 countries of the Mediterranean Basin (Italy, Tunisia, Spain, Turkey, France, Greece and Morocco). Trials were established in 1992 and assessments were carried out 1, 6, 9, 12, 14, 17 and 21 years after planting. Assessed variables are listed within the Excel file (Readme sheet). Access and reuse: This dataset is subject to a Creative Commons Reconocimiento-NoComercial-CompartirIgual 4.0 Internacional License. This dataset compiles phenotypic information of height and diameter growth, survival and defoliation by the processionary moth (Thaumetopoea pityocampa) assessed at different ages (up to 22 years-old) in two provenance tests (Izarene and Chatba) of Pinus halepensis and Pinus brutia established in Morocco. This research was founded by the National Forest Research Centre budget, Morocco. RZ received support from the Grant FUTURPIN AGL2015-68274-C03-02R founded by MINECO/FEDER. No

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    Digital.CSIC
    Dataset . 2018
    License: CC BY NC SA
    Data sources: Datacite
    Digital.CSIC
    Dataset . 2018
    Data sources: Digital.CSIC
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      Digital.CSIC
      Dataset . 2018
      License: CC BY NC SA
      Data sources: Datacite
      Digital.CSIC
      Dataset . 2018
      Data sources: Digital.CSIC
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    Authors: Orejas, Covadonga; CSIC - Unidad de Tecnología Marina (UTM);

    iMIRABILIS-2 is an international multidisciplinary expedition with activities contributing to many tasks across iAtlantic’s workpackages. At sea activities will include the study of both the water column and the seafloor. iMIRABILIS-2 mobilises state-of-the-art seabed survey equipment including the Autonomous Underwater vehicle (AUV) Autosub6000 and the Remotely Operated Vehicle (ROV) Luso. This advanced technology allows iAtlantic to explore benthic ecosystems in great detail producing large high-resolution photographic results that will be processed automatically using new machine learning approaches. The results of these surveys will be used to produce high resolution habitat maps off Cabo Verde from which scarce information is currently available. Moreover, the ROV Luso will allow collection of selected specimens for taxonomic purposes and for dating. Furthermore, new technologies will be tested during the cruise including the eDNA ‘RoCSI’ sampler recently developed by researchers from the National Oceanography Centre (NOC, UK). Seabed lander equipment will also be deployed to obtain in situ information on environmental parameters and demersal deep-sea fish fauna. Ex situ experimental work will also take place on the ship, including short-term aquaria experiments with specimens collected with the ROV and incubations of sediment cores, collected by multicore. Oceanographic data acquired during the iMIRABILIS-2_LEG1 Cruise (29SG20210731) on board the Research Vessel Sarmiento de Gamboa in 2021.

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    Digital.CSIC
    Dataset . 2021
    Data sources: Digital.CSIC
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      Digital.CSIC
      Dataset . 2021
      Data sources: Digital.CSIC
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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: Civantos-Gómez, Iciar; Rubio Teso, María Luisa; Galeano, Javier; Rubiales, Diego; +2 Authors

    Crop Wild Relatives (CWR) are a valuable source of genetic diversity that can be transferred to commercial crops, so their conservation will become a priority in the face of climate change. Bizarrely, in situ conserved CWR populations and the traits one might wish to preserve in them are themselves vulnerable to climate change. In this study, we used a quantitative machine learning predictive approach to project the resistance of CWR populations of lentils to a common disease, lentil rust, caused by fungus Uromyces viciae-fabae. Resistance is measured through a proxy quantitative value, DSr (Disease Severity relative), quite complex and expensive to get. Therefore, machine learning is a convenient tool to predict this magnitude using a well-curated georeferenced calibration set. Previous works have provided a binary outcome (resistant vs. non-resistant), but that approach is not fine enough to answer three practical questions: which variables are key to predict rust resistance, which CWR populations are resistant to rust under current environmental conditions, and which of them are likely to keep this trait under different climate change scenarios. We first predict rust resistance in present time for crop wild relatives that grow up inside protected areas. Then, we use the same models under future climate IPCC (Intergovernmental Panel on Climate Change) scenarios to predict future DSr values. Populations that are rust-resistant by now and under future conditions are optimal candidates for further evaluation and in situ conservation of this valuable trait. We have found that rust-resistance variation as a result of climate change is not uniform across the geographic scope of the study (the Mediterranean basin), and that candidate populations share some interesting common environmental conditions. Peer reviewed

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    Digital.CSIC
    Dataset . 2022 . Peer-reviewed
    Data sources: Digital.CSIC
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      Digital.CSIC
      Dataset . 2022 . Peer-reviewed
      Data sources: Digital.CSIC
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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: Sanchez Vidal, Anna; CSIC - Unidad de Tecnología Marina (UTM);

    In the FAR-DWO DS1 oceanographic cruise we analyze the hydrographic and sedimentological variability of the Denmark Strait Overflow using water column and seafloor observation and sampling techniques. We also deploy multi-instrumented mooring lines at depths between 1000 m and 2000 m to record information of the dense current during a whole year. The FAR-DWO DS1 cruise will last from July 19th to August 12th 2023 onboard the oceanographic vessel Sarmiento de Gamboa (CSIC). We are a team of around thirty experts from the Universitat de Barcelona (UB), Universidad de Las Palmas de Gran Canaria (ULPGC), Institut Français de Recherche pour l'Exploitation de la Mer (IFREMER), University of Iceland (UI), and the company specialized in satellite technology Lobelia Earth, and we count on the technical support of Unidad de Tecnología Marina (UTM-CSIC). Oceanographic data acquired during the FAR-DWO_DS1 Cruise (29SG20230719) on board the Research Vessel Sarmiento de Gamboa in 2023.

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    Digital.CSIC
    Dataset . 2023
    Data sources: Digital.CSIC
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      Digital.CSIC
      Dataset . 2023
      Data sources: Digital.CSIC
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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: Villegas-Fernández, Ángel M.; Rubiales, Diego;

    Characterization data of a Vicia faba germplams collection grown at Córdoba, Spain at three sites during 2022 and 2023.

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    Digital.CSIC
    Dataset . 2024
    Data sources: Datacite
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      Digital.CSIC
      Dataset . 2024
      Data sources: Datacite
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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: Villanueva, Joan; CSIC - Unidad de Tecnología Marina (UTM);

    The aim of the project is to develop an innovative palaeo-proxy approach to investigate the natural range of variability of the Hadley circulation during past episodes of extreme warmth and cold. The approach relies on the exploitation as climate proxy of an untapped but widespread material in marine sediments: windborne pyrogenic carbon (PyC) derived from savannah and grassland fires in the tropics. Through the geochemical and isotopic spatial characterization of PyC, along with the analysis of mineral dust in the modern tropical deep ocean, and a PyC biogeochemical model, we will build an interpretative framework of PyC deposition in deep-sea sediments. Its application in Pliocene-Pleistocene sequences from the Atlantic and the Pacific will allow the reconstruction of past meridional and zonal shifts in the Intertropical Convergence Zone and the Southern hemisphere westerlies, and provide new constraints on the natural variability of the Hadley circulation and associated hydroclimates. PYROWIND Cruise (29HE20220426) carried out on the Research Vessel Hespérides in 2022.

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    Digital.CSIC
    Dataset . 2022
    Data sources: Digital.CSIC
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      Digital.CSIC
      Dataset . 2022
      Data sources: Digital.CSIC
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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: CSIC - Unidad de Tecnología Marina (UTM);

    Oceanographic data acquired during the ANTARLOG_LEG2 Cruise (29SG20161203) on board the Research Vessel Sarmiento de Gamboa in 2016. Logistic voyage without any scientific work.

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    Digital.CSIC
    Dataset . 2022
    Data sources: Digital.CSIC
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      Digital.CSIC
      Dataset . 2022
      Data sources: Digital.CSIC
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    Authors: Catalán, Manuel; CSIC - Unidad de Tecnología Marina (UTM);

    Oceanographic data acquired during theZEE-2021 Cruise (29HE20210325) on board the Research Vessel Hespérides in 2021 ZEE-2021: Study of the Spanish Economic Zone in the Canary Islands.

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    Digital.CSIC
    Dataset . 2021
    Data sources: Digital.CSIC
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      Digital.CSIC
      Dataset . 2021
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  • Authors: Fernández-Benito, Amparo; Rivera-Gálvez, Francisco J.; Cisneros-Ruiz, P.; Sanz-Horta, Raúl; +3 Authors
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    Authors: Gasol, Josep M.; CSIC - Unidad de Tecnología Marina (UTM);

    The MIAU-DCM campaign will study the biological characteristics of the deep chlorophyll maximum in the Northwest Mediterranean. To do this, the first 150-200 meters of the water column will be sampled with CTD along a transect between the towns of Blanes and a point near Cape Formentor, and from the continental shelf (depth 40-50 meters). Once the depth of the DCM has been defined, and its variability along the transect, the stations in which biological sampling will be carried out will be defined, which will consist of taking samples from approximately 100 m and the surface. In addition, station D (in the middle of the basin) will be characterized up to 2500 meters. Oceanographic data acquired during the MIAU-DCM Cruise (29GD20210601) on board the Research Vessel García del Cid in 2021.

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    Digital.CSIC
    Dataset . 2021
    Data sources: Digital.CSIC
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      Digital.CSIC
      Dataset . 2021
      Data sources: Digital.CSIC
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    Authors: Sbay, Hassan; Zas Arregui, Rafael;

    Methodology: The genetic material comprise 57 populations (8 of Brutia pine and 49 of Aleppo pine) originating from 7 countries of the Mediterranean Basin (Italy, Tunisia, Spain, Turkey, France, Greece and Morocco). Trials were established in 1992 and assessments were carried out 1, 6, 9, 12, 14, 17 and 21 years after planting. Assessed variables are listed within the Excel file (Readme sheet). Access and reuse: This dataset is subject to a Creative Commons Reconocimiento-NoComercial-CompartirIgual 4.0 Internacional License. This dataset compiles phenotypic information of height and diameter growth, survival and defoliation by the processionary moth (Thaumetopoea pityocampa) assessed at different ages (up to 22 years-old) in two provenance tests (Izarene and Chatba) of Pinus halepensis and Pinus brutia established in Morocco. This research was founded by the National Forest Research Centre budget, Morocco. RZ received support from the Grant FUTURPIN AGL2015-68274-C03-02R founded by MINECO/FEDER. No

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    Digital.CSIC
    Dataset . 2018
    License: CC BY NC SA
    Data sources: Datacite
    Digital.CSIC
    Dataset . 2018
    Data sources: Digital.CSIC
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      Digital.CSIC
      Dataset . 2018
      License: CC BY NC SA
      Data sources: Datacite
      Digital.CSIC
      Dataset . 2018
      Data sources: Digital.CSIC
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    Authors: Orejas, Covadonga; CSIC - Unidad de Tecnología Marina (UTM);

    iMIRABILIS-2 is an international multidisciplinary expedition with activities contributing to many tasks across iAtlantic’s workpackages. At sea activities will include the study of both the water column and the seafloor. iMIRABILIS-2 mobilises state-of-the-art seabed survey equipment including the Autonomous Underwater vehicle (AUV) Autosub6000 and the Remotely Operated Vehicle (ROV) Luso. This advanced technology allows iAtlantic to explore benthic ecosystems in great detail producing large high-resolution photographic results that will be processed automatically using new machine learning approaches. The results of these surveys will be used to produce high resolution habitat maps off Cabo Verde from which scarce information is currently available. Moreover, the ROV Luso will allow collection of selected specimens for taxonomic purposes and for dating. Furthermore, new technologies will be tested during the cruise including the eDNA ‘RoCSI’ sampler recently developed by researchers from the National Oceanography Centre (NOC, UK). Seabed lander equipment will also be deployed to obtain in situ information on environmental parameters and demersal deep-sea fish fauna. Ex situ experimental work will also take place on the ship, including short-term aquaria experiments with specimens collected with the ROV and incubations of sediment cores, collected by multicore. Oceanographic data acquired during the iMIRABILIS-2_LEG1 Cruise (29SG20210731) on board the Research Vessel Sarmiento de Gamboa in 2021.

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    Digital.CSIC
    Dataset . 2021
    Data sources: Digital.CSIC
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      Digital.CSIC
      Dataset . 2021
      Data sources: Digital.CSIC
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