Resultados de investigación

This dataset contains next-generation sequencing data regarding changes in the whole methylome of Daphnia magna following bystander experiments with realistic exposure concentrations of two metals (copper and cadmium). It comprises DNA sequences for each metal (minimally processed before deposit - see the associated Readme file for details), obtained from control, metal-exposed and bystander daphnids., El dataset se puede consultar y descargar en el siguiente enlace https://dunas.ua.pt/dataset.xhtml?persistentId=doi:10.48527/TF2RAG, European Union: 101078991 Portuguese Foundation of Science and Technology: UIDP/50017/2020 Portuguese Foundation of Science and Technology: UIDB/50017/2020 Portuguese Foundation of Science and Technology: LA/P/0094/2020 Portuguese Foundation of Science and Technology: SFRH/BD/139076/2018, Peer reviewed

Data and code from "From policy to practice: Progress towards data- and code-sharing in ecology and evolution", R.Z. was funded by the German Federal Environmental Foundation (DBU, 20021/752) and gratefully acknowledges the support of iDiv funded by the German Research Foundation (DFG–FZT 118, 202548816). G.W. was funded by the German Research Foundation (DFG–CRC TRR 212, 396782608). M.G.B. was funded by the Swedish Research Council Formas (2020-02293). Z.Z. was funded by the project SOSPEN (Spanish National Plan for Scientific and Technical Research and Innovation, 2021, PID2021-124831OA-I00) and the project SEASentinels (Spanish National Plan for Scientific and Technical Research and Innovation, 2023, CNS2022-135631) and acknowledges the Spanish government through the ‘Severo Ochoa Centre of Excellence’ accreditation (CEX2019-000928-S funded by MCIN/AEI 10.13039/501100011033, ICM-CSIC). This work was partially funded by the Center of Advanced Systems Understanding (CASUS), which is financed by Germany’s Federal Ministry of Education and Research (BMBF) and by the Saxon Ministry for Science, Culture and Tourism (SMWK) with tax funds on the basis of the budget approved by the Saxon State Parliament (via I.S.), Peer reviewed

This work was performed under the La Mar de Medusas project, which was funded by the Spanish Foundation for Science and Technology (FECYT) (Ref. FCT-2019-15322). In addition, the research was supported by the European project RESBIOS, which received funding from the European Union’s Horizon 2020 Research and Innovation Program under Grant Agreement No. 872146. Furthermore, the authors affiliated to the Institut de Ciències del Mar had the institutional support of the “Severo Ochoa Centre of Excellence” accreditation (CEX2019-000928-S). We acknowledge support of the publication fee by the CSIC Open Access Publication Support Initiative (PROA) through its Unit of Information Resources for Research (URICI), Peer reviewed

This dataset is used in an original research article submitted to Journal of Petrology: Michał Bukała, José Alberto Padrón-Navarta, Manuel D. Menzel, Vicente López Sánchez-Vizcaíno , Carlos J. Garrido; 2025. High-pressure carbon sequestration in hot subduction zones during deserpentinization driven by CO2-CH4 fluid infiltration (in review). Link to be added once available., The collection of data included in this repository was funded by RUSTED projects PID2022-136471NB-C21 & PID2022-136471NB-C22 funded by the Agencia Estatal de Investigación (MCIN/AEI/10.13039/501100011033), Spain, co-financed by the European Union ERDF – a way of making Europe. M.B acknowledges "Juan 694 de la Cierva" Fellowship (JFJC2021-047505-I) awarded by MCIN/AEI/10.13039/501100011033 and CSIC. M.D.M acknowledges a postdoctoral fellowship (Postdoc_21_00791) funded by the Junta de Andalucía (Consejeria de Conocimiento y Universidades) and cofunded by ERDF., Peer reviewed

The financial support for this research work was provided by Principado de Asturias (IDI/2021/000096) and MCIN/AEI/10.13039/501100011033 [PID2020-113558RB-C44 and European Union NextGeneration EU/PRTR (TED2021-129234B-I00)]., Peer reviewed

Peer reviewed

1 file, Data and plots comparing the perfomance of lactic acid bacteria (Levilactobacillus brevis and Lactiplantibacillus plantarum) and marine probiotic bacteria (Phaeobacter sp and Pseudomonas fluorescens growing in mollusca wastewater-based growth media and commercial media (Man Rogosa Sharpe Broth and Marine Broth), Peer reviewed

This research was born from the voluntary contribution of CREA and IREPA to support the PESCA-CHAIN project (May 17, 2022, protocol no. 0047530). This paper falls under FAO’s 17 Sustainable Development Goals (https://www.fao.org/sustainable-development-goals/goals/goal-1/en/ (accessed on 10 September 2025)) and specifically on SDG 14 (Conserve and sustainably use the oceans, seas and marine resources). D.C. was funded by the European Union under the Horizon Europe MSCA grant 101104596, This work contributes to the Institut de Ciències del Mar "Severo Ochoa Centre of Excellence" accreditation CEX2024-001494-S funded by AEI 10.13039/501100011033 of the Spanish Ministry of Science and Innovation, Peer reviewed

With the institutional support of the ‘Severo Ochoa Centre of Excellence’ accreditation (CEX2019-000928-S), Peer reviewed

Underwater images and manual tags of different fish taxa detected from the image repository of the OBSEA Cabled Observatory from January 2013 to December 2014. OBSEA station is located 4km off-the-coast of Vilanova i la Geltrú (Catalonia, Spain) at a depth of 20 meters . Tags are rectangles marking the fish position in a picture (region of interest), identified by their x/y vertix values (in pixels).The aim of this dataset is to train Artificial Intelligence (AI) algorithms to automatically detect and or classify fish specimens from underwater pictures.Two cameras were used (Sony SNC-RZ25N from 2013-01-01 to 2014-12-11 and Axis P1346-E from 2014-12-11 to 2014-12-31). 29 fish taxa have been visually identified and classified according to their taxa name. Unclassified fish have been marked as Unknown fish.The fish taxa recognized in the dataset are: Coris julis, Chromis chromis, Diplodus vulgaris, Diplodus sargus, Oblada melanura, Spondyliosoma cantharus, Diplodus cervinus, Diplodus annularis, Spicara maena, Dentex dentex, Diplodus puntazzo, Conger conger, Symphodus mediterraneus, Atherina sp., Scorpaena sp., Pagrus pagrus, Pagellus sp., Serranus cabrilla, Sciaena umbra, Sarpa salpa, Trachurus sp., Sparus aurata, Apogon sp., Seriola dumerili, Thalassoma pavo, Epinephelus marginatus, Boops boops, Symphodus cinereus, Symphodus tinca, Peer reviewed