Resultados de investigación

SM1. Study area: The south of the Mallorca channel (Balearic Islands, western Mediterranean, Z1) is characterized by the oligotrophy of its waters but considered as a hotspot of biological activity and biodiversity in the deep-sea (Massutí et al., 2021). In contrast, the Alborán Sea (Z2), unlike the general oligotrophy dominating most of the Mediterranean, holds two anticyclonic gyres of high biological productivity (Bárcena et al., 2004). This area together with the Gulf of Cádiz (Z3) is considered a transition zone between the Atlantic Ocean and the Mediterranean Sea, with water-mass exchange through the Strait of Gibraltar. This region couples the convergence of critical water masses regarding the Atlantic Meridional Overturning Circulation with a semi-permanent upwelling regime, itself connected to the larger dynamic cells off northwest Africa (Penaud et al., 2016). The area off Lisbon (Portugal, Z4) is characterized by a coastal upwelling, intensified during the summer when upwelled waters occupy the surface layers over the whole western shelf and part of the upper slope off Portugal (Fiuza, 1983). This scenario is also found in the Galician coast (Z5), showing upwelling favorable conditions during spring-summer (Villegas-Ríos et al., 2011). [...], This work was supported by projects “Sustainable Management of Mesopelagic Resources” (SUMMER, H2020, Grant agreement No 817806), “DisEntangling Seasonality of Active Flux In the Ocean” (DESAFÍO, PID2020-118118RB-100), and IMDEEP (CajaCanarias-LaCaixa, ref. 2022CLISA15). María Couret was supported by a postgraduate grant (TESIS2022010116) co-financed by the Agencia Canaria de Investigación, Innovación y Sociedad de la Información de la Consejería de Universidades, Ciencia e Innovación y Cultura and by the Fondo Social Europeo Plus (FSE+) Programa Operativo Integrado de Canarias 2021-2027, Eje 3 Tema Prioritario 74 (85%). JDP by a postgraduate grant (ULPGC2022-2) from Universidad de Las Palmas de Gran Canaria. ASL by a postgraduate grant (IN606B-2024/018) from the “Agencia Gallega de Innovación”, Peer reviewed

This dataset contains AI-based fish detections at the OBSEA Underwater Observatory (NW Mediterranean sea). The model is a YOLOv8 xlarge trained with labeled underwater pictures from OBSEA. The model can be found here. The pictures where taken at OBSEA area with cameras pointing to an artifical biotop developed in the framework of the Slagreef project, Ministerio de Ciencia, Innovación y Universidades TED2021-129760B-I00. European Commission Horizon Europe 101058625 iMagine - Imaging data and services for aquatic science, 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, The data file in CSV format includes the following columns: timestamp: Time instance when the picture was taken (in UTC). SourceImage: URL of the source image. ProcessedImage: URL of the processed image with detections + bounding boxes. SENSOR_ID: Name of the camera that took the picture. Diplodus puntazzo: Number of s. Oblada melanurus: Number of specimens detected. Parablennius gattorugine: Number of specimens detected. Sarpa salpa: Number of specimens detected.Seriola dumerili: Number of specimens detected. Serranus cabrilla: Number of specimens detected. Sparus aurata: Number of specimens detected. Symphodus mediterraneus: Number of specimens detected. Diplodus sargus: Number of specimens detected. Diplodus vulgaris: Number of specimens detected. Epinephelus costae: Number of specimens detected. Aetomylaeus bovinus: Number of specimens detected. Chromis chromis: Number of specimens detected. Coris julis: Number of specimens detected. Dentex dentex: Number of specimens detected. Diplodus cervinus: Number of specimens detected. Epinephelus marginatus: Number of specimens detected. Mullus surmuletus: Number of specimens detected. Muraena helena: Number of specimens detected. Oblada melanurus: Number of specimens detected. Parablennius gattorugine: Number of specimens detected. Sarpa salpa: Number of specimens detected. Seriola dumerili: Number of specimens detected. Serranus cabrilla: Number of specimens detected. Sparus aurata: Number of specimens detected. Symphodus mediterraneus: Number of specimens detected, Peer reviewed

This xarray dataset ('mvomstein_ds_vibrotactile_spatial_acuity.nc') contains high-resolution vibrotactile spatial acuity data collected from 33 participants across five large-area body sites (forearm, abdomen, lower back near-spine area (NSA), lower back peripheral-spine area (PSA), and thigh). The data were obtained using a fully automated experimental setup that employs Bayesian adaptive parameter estimation to generate continuous psychometric functions. The dataset supports the findings of the study "Data-driven design guide for vibrotactile display layouts by continuous mapping", which is published at Scientific Reports (Nature Research). Additionally, the supplementary files ('mvomstein_[...].xlsx') provide statistical analyses for the figures presented in the manuscript, including detailed results for comparisons across body sites, anisotropy effects, and regional sensitivity gradients, 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

Benthic megafauna invertebrate (animals > 10 mm) observations from seabed imagery data collected across the Clarion Clipperton Zone, in the NE Pacific abyss: 53512 specimens classified in 400+ morphotypes (13 Phyla) based on the APSMA catalogue (see https://zenodo.org/record/7765164)., Peer reviewed

The non-rarefied Patescibacteria ASV and taxonomic tables are provided as Tables S1 and S2, This work was funded by the Spanish Ministry of Science, Innovation and Universities (MICINN) through the GRAMMI (RTI2018-099740-J-I00) and MINIOM projects (PID2022-142480NB-I00) and the Ramon y Cajal contract (RYC2019-026758-I), and additional support from projects Medistraes (PID2019-11021RB-C22) and MuchoGusto (PID2022-140862OB-C21/C22). F.M.C.-C. was supported by the Spanish Ministry of Science and Innovation (‘Ramon y Cajal’ fellowship; RYC2021-032949-I), D.R.-G. by a FPI fellowship (PRE2020-095468) and C.M. by a Juan de la Cierva-formación fellowship (FJC2021-047745-I), funded by the Spanish Ministry of Science and Innovation (MCIN/AEI) and the EU (“NextGenerationEU”/PRTR). The institutional support of the ‘Severo Ochoa Centre of Excellence’ accreditation (CEX2024-001494-S) is also acknowledged, Peer reviewed

G.B.C., E.S.-L., B.F.M.F, T.G.D., D.O.B.J., and A.G.G. received funding from the UK Natural Environmental Research Council (NERC) Seabed Mining And Resilience To Experimental impact (SMARTEX) project (Grant Reference NE/T003537/1), and G.B.C., A.G.G., T.G.D., H.W., E.S-.L., and D.O.B.J. received funding from The Metals Company Inc. (TMC) through its subsidiary Nauru Ocean Resources Inc. (NORI). NORI holds exploration rights to the NORI-D contract area in the CCZ regulated by the International Seabed Authority and sponsored by the government of Nauru. M.V.K. received funding from the National Council for Scientific and Technological Development (CNPq #305274/2021-0) and the São Paulo Research Foundation (FAPESP, Processes #2014/01332-0 and #2021/06866-6). E.S.-L. received financial support from the Spanish Research State Agency (MCIN/AEI/10.13039/501100011033) and the European Union Next Generation EU/PRTR (grant agreement No RyC2023-043275-I), 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

Table S1. List of product ions and their corresponding precursor ions. The table also details the applied colli-sion energies, accurate mass measurements, and the IMS system used for CCS measurements. Table S2. Calculated CCSs values for PLTXstd, OVTX-a, and OVTX-b, measured and estimated using DTIMS and TWIMS. *Refer to Table S1 for product ions. Table S3. Key hydrogen bonds stablished during the 1 μs simulations for each of the 15 independent replicates of the two OVTX-b adducts. Averaged occupancies were calculated from the complete independent trajecto-ries. Only hydrogen bonds with occupancies greater than 20% of the simulation are included. Fig. S1. Various perspectives of Na and Ca atoms coordination in the [M+H+2Na]3+ and [M+H+Ca]3+ adduct ions during the conformational simulation (example of the OVTX-b structure). The colored spheres indi-cate reference positions to enhance visualization of the three-dimensional structure, while yellow dashed lines illustrate Na/Ca coordination. Figure S2. Hydrogen bonds of the (a) [M+H+2Na]3+ and (b) [M+H+Ca]3+ ions observed during the conforma-tional simulation (example of OVTX-b structure). Only hydrogen bonds with occupancies greater than 20% of the simulation are included (see Table S3 for occupancy details). Figure S3. Radius variation of the [M+H+Ca]3+ and [M+H+2Na]3+ ions during the conformational simulation (example of the OVTX-b structure). Figure S4. Hydroxyls groups in the inner (grey) and outer (blue) part of the clustered structures of (a) [M+H+2Na]3+ and (b) [M+H+Ca]3+ ions (example of the OVTX-b structure). Figure S5. Fragmentation of the [M+2H+Na−3H2O]3+ (blue diamond) at CE 35 V for the different ion mobility peaks observed for the OVTX-a using TIMS. Figure S6. Correlation between CCS values measured using TWIMS or DTIMS instrument, with Dextran or PLTX standard as calibrants, Open Access funding provided thanks to the CRUE-CSIC agreement with Springer Nature. This work was financially supported by several institutions and funding agencies. AGAUR (Government of Catalonia) provided a fellowship to NI Medina-Pérez (FI-SDUR2020-00254). The Spanish Ministry of Science, Innovation and Universities supported this research through project PID2021-122743NB-I00 (MICIU/AEI/https://doi.org/10.13039/501100011033 and FEDER funds, UE). Additional support was received from AGAUR (Generalitat de Catalunya) through project 2021 SGR 00281. The Water Research Institute (IdRA, University of Barcelona, Spain) also contributed to this work. Funding was further provided by the European Union (Grant No. 690462) and FORMAS (SE) through the CoCliME project (ERA4CS network, ERA-NET, initiated by JPI Climate), as well as by the European Research Council under the ERC-2019-CoG-863934-GlycoSpec, 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

This dataset contains the data and code used in Fernández-Corredor et al. 2025. Pelagic productivity and abundance of competitors modulate trophic niche segregation between large predators. Proceedings of the Royal Society B. It includes: Stable Isotopes data (SIA.zip): - Raw values from the stable isotopes analysis - MixSIAR inputs - Kernel Utilization Densities results Spatial layers (spatial.zip) - Cummulative fishing effort raster calculated from Global Fishing Watch data (Kroodsma et al. 2018) - Environmental data obtained from EU-Copernicus Marine Environment Monitoring Service (https://marine.copernicus.eu/). - Ocean Productivity available to Fish’ (OPFish) from Druon (2021) - A shapefile with the grid used for predictions Standardized catch per unit effort (nCPUE; number of individuals per thousand hooks)(CPUE.zip) Rmarkdowns with the code used in the analysis, E.F.-C. was supported by an FPU grant from the Spanish Ministry of Universities (FPU20/05523). A.F.-A. received funding from the Spanish project ProOceans through an FPI grant (Ministerio de Ciencia e Innovación, Proyectos de I + D + I, RETOS PID2020-118097RB-I00). M.C. acknowledges partial funding from the European Union’s Horizon 2020 research and innovation program under grant agreements no. 869300 (FutureMares) and no. 101059877 (Ges4Seas). The sampling has been funded by the EU through the European Maritime and Fisheries Fund (EMFF) within the National Program for the management and use of data from the fisheries sector and support for scientific advice on the Common Fisheries Policy. This project was supported by the Generalitat de Catalunya through the iMARES research group at the ICM-CSIC (AGAUR-SGR-Cat 2021) and by the COTI project (PLEAMAR Program, co-financed by the European Union through the FEMPA). [...] This work also acknowledges the 'Severo Ochoa Centre of Excellence' accreditation (CEX2024-001494-S) to the ICM-CSIC. Thais work has been carried out within the framework of the Biodiversity PhD program of the Autonomous University of Barcelona, Peer reviewed

In the open ocean, large pelagic predators often share similar food resources and feeding grounds, likely avoiding competition and coexisting through niche partitioning. Building on this hypothesis, we combined spatial distribution data with isotopic niche metrics and diet reconstructions based on N and C stable isotopes to describe intra- and interspecific competition between three sympatric predators: swordfish (Xiphias gladius), blue shark (Prionace glauca), and shortfin mako (Isurus oxyrinchus). We then evaluated the role of biological (competitor abundance), environmental (pelagic productivity), and anthropogenic (fishing pressure) drivers in shaping competition metrics within and between species. Shortfin makos had a high isotopic niche overlap with blue sharks (>80%), feeding on similar prey. Swordfish isotopic niche was narrower than and highly overlapped with blue shark niche in the Mediterranean, although diet estimates in this area suggest that swordfish rely more on fish while blue sharks rely more on squid. On average, the potential for intraspecific competition was highest for swordfish and lowest for shortfin makos. Our results suggest that pelagic productivity and competitor abundance are key drivers of intra- and interspecific trophic niche segregation between large pelagic predators, respectively. They support the hypothesis that niche partitioning is reduced under a high resource availability scenario, E.F.-C. was supported by an FPU grant from the Spanish Ministry of Universities (FPU20/05523). A.F.-A. received funding from the Spanish project ProOceans through an FPI grant (Ministerio de Ciencia e Innovación, Proyectos de I + D + I, RETOS PID2020-118097RB-I00). M.C. acknowledges partial funding from the European Union’s Horizon 2020 research and innovation program under grant agreements no. 869300 (FutureMares) and no. 101059877 (Ges4Seas). The sampling has been funded by the EU through the European Maritime and Fisheries Fund (EMFF) within the National Program for the management and use of data from the fisheries sector and support for scientific advice on the Common Fisheries Policy. This project was supported by the Generalitat de Catalunya through the iMARES research group at the ICM-CSIC (AGAUR-SGR-Cat 2021) and by the COTI project (PLEAMAR Program, co-financed by the European Union through the FEMPA). [...] This work also acknowledges the 'Severo Ochoa Centre of Excellence' accreditation (CEX2024-001494-S) to the ICM-CSIC. Thais work has been carried out within the framework of the Biodiversity PhD program of the Autonomous University of Barcelona, Peer reviewed

- Supplementary Methods - Figs. S1 to S46 - Tables S1 to S3 - References, This study was supported by the National Key Research and Development Program of China (2024YFF0808200 and 2024YFF0809600). J.P.M.’s contribution was supported by the NSFC grant 92058212. L.L.’s study was additionally supported by the Tuguangchi Award for Excellent Young Scholar (TGC202101) and the “14th Five-Year Plan” independent plan of the GIGCAS, 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