Resultados de investigación

This research was funded by the project “SUMMER: Sustainable Management of Mesopelagic Resources” from European Union Horizon 2020 Research and Innovation Program (GA 817806). With funding form the Spanish government through the "Severa Ochoa Centre of Excellence" accreditation (CEX2019-000928-S)., Peer reviewed

Se evaluó la distribución espacial, en términos de probabilidad de ocurrencia y biomasa, de las tres principales especies de pequeños peces pelágicos, anchoa (Engraulis encrasicolus), sardina (Sardina pilchardus) y alacha (Sardinella aurita), en la plataforma continental ibérica dentro de la subárea geográfica (GSA) 06, con especial atención a la Zona de Especial Protección para las Aves (ZEPA) ES0000512. Para realizar estas estimaciones, se integraron tres bases de datos independientes: datos de campañas oceanográficas MEDITS (1999-2023), registros de capturas reportadas en los diarios de pesca de buques arrastreros y cerqueros (2020-2024), y variables ambientales (1999-2025), todo ello incorporado en modelos avanzados de distribución de especies. En general, las áreas altamente productivas situadas alrededor y al sur del Delta del Ebro concentran, de forma consistente a lo largo de la serie temporal (1999-2025), las mayores probabilidades de ocurrencia y biomasas para las tres especies. También se observan probabilidades de ocurrencia y biomasa relativamente elevadas en el área marina comprendida entre el Cabo de la Nao y el Cabo de Palos, aunque la biomasa estimada en esta zona es comparativamente menor que en las aguas circundantes al Delta del Ebro. Las limitaciones inherentes a las metodologías empleadas en la recopilación y análisis de los datos, junto con las características de los modelos desarrollados, sugieren que los mapas de probabilidad de ocurrencia basados en datos MEDITS constituyen la representación más realista y verosímil de la distribución espacial de estas especies. No obstante, cabe señalar que las series temporales alternativas permiten una reconstrucción estacional más detallada de la distribución de las especies, ya que no están restringidas a los meses de muestreo de MEDITS, que se limita a un periodo concreto del año (junio y julio). Esta complementariedad metodológica puede ser útil para abordar dinámicas anuales que no quedan reflejadas en los mapas basados exclusivamente en datos MEDITS, Proyecto StelarMed (Pleamar) financiado por Corys.-- 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, 1. INTRODUCCIÓN. 2. MATERIALES Y MÉTODOS. 2.1 Área de Estudio y Datos de las Especies. 2.2 Datos Ambientales. 2.3 Análisis exploratorio. 2.4 Modelos de distribución de especies. 2.4.1 Bondad de ajuste. 2.4.2 Influencia de las variables. 2.4.3 Validación de la predicción. 2.5 Comparación espacial cuantitativa de los mapas. 3. RESULTADOS. 3.1 Datos MEDITS. 3.1.1 Patrones espaciales. 3.1.2 Patrones temporales. 3.1.3 Validación de las predicciones. 3.2 Datos VMS-OTB (arrastreros). 3.2.1 Patrones espaciales. 3.2.2 Patrones temporales. 3.2.3 Validación de las predicciones. 3.3 Datos VMS-PS (cerqueros). 3.3.1 Patrones espaciales. 3.3.2 Patrones temporales. 3.3.3 Validación de las predicciones. 3.4 Comparación entre los resultados de las distintas fuentes de datos. 4. DISCUSIÓN. 4.1 Patrones espaciales. 4.2 Tendencias temporales. 5. CONCLUSIONES. 6. Acceso al código. 7. REFERENCIAS. APÉNDICE A. Mapas de las variables ambientales. APÉNDICE B. Mapas anuales MEDITS. APÉNDICE C. Mapas anuales VMS-OTB (arrastreros). APÉNDICE D. Mapas anuales VMS-PS (cerqueros), Peer reviewed

Esta base de datos contiene medias y desviaciones estándar semanales, mensuales, y estacionales, así como climatologías de temperatura (°C), salinidad, amonio (µmol/L), Fosfato (µmol/L), nitrato (µmol/L), nitrito (µmol/L), silicato (µmol/L), oxígeno (µmol/kg), saturación de oxígeno (µmol/kg), clorofila (µg/L), pH y alcalinidad (µmol/kg). Se calcularon las medias de todas las estaciones para la Ría de Arousa y de Vigo, así como las medias de 0 a 20 m de profundidad, Esta base de datos forma parte de los resultados obtenidos bajo un convenio con el MITERD: MINISTERIO PARA TRANSICION ECOLOGICA Y EL RETO DEMOGRAFICO, dentro del proyecto OCEANS+, Eje 3: Modelización de impactos del Cambio Climático, Tarea 3.14: Análisis de las series temporales de los indicadores desde 1992 a 2021 en sistemas costeros afectados por el afloramiento costero (Rías Baixas). Este contiene las anomalías mensuales de temperatura, salinidad, amonio, fosfato, nitrato, nitrito, silicato, oxígeno, saturación de oxígeno, Clorofila GFD, Clorofila, GFF, pH y alcalinidad. Se calcularon considerando todas las estaciones de cada Ría, Arousa y Vigo, y todas las profundidades (0-5, 5-10, 10-15m) desde 1992 hasta 2019, Esta investigación está financiada por la Unión Europea -NexGenerationEU- como parte del programa del MITECO para el Plan de Recuperación, Transformación y Resiliencia español (Mecanismo de Recuperación y Resiliencia de la Unión Europea establecido por el Reglamento (EU) 2020/2094), y está asignada al CSIC, AZTI, SOCIB y las universidades de Vigo y Cádiz, Peer reviewed

Raw data associated with the publication "SOS1-dependent vacuolar sodium accumulation revealed by elemental cryo-imaging". Files contain raw images of SOS1-GFP and SOS1-mCitrine protein localization data used for quantifications under control, salt stress conditions, as well as the chemical treatments for localization assessment. Folders named according to line, conditions and treatment. The folder `Ramakrishna_et_al_CryoSEM-NanoSIMS` contains the correlative CryoSEM image as well as the CryoNanoSIMS image files for all treatments and conditions for both rice and Arabidopsis. For analysis of the CryoNanoSIMS images please refer to the materials and methods of the manuscript. For any further details please contact the corresponding authors., Peer reviewed

1 file, This database was obtained during the project e-IMPACT (PID2019-109084RB-C21 and -C22) led by Arístegui, J. and Álvarez-Salgado, X.A., funded by MCIN/AEI/10.13039/501100011033, Peer reviewed

[Data availability] S. arcturi and the related genomic study were assigned to Tree of Life ID (ToLID) 'xcStiArct1' and all sample, sequence, and assembly information are available under the umbrella BioProject PRJEB81320. The sample information is available at the following BioSample accessions: SAMEA114541340, SAMEA114541342, SAMEA114541343, and SAMEA114541354. The genome assembly is accessible from ENA under accession number GCA_964276865.1. Sequencing data produced as part of this project are available from ENA at the following accessions: ERX13202607, ERX13202608, ERX13202609 and ERX13202610. Documentation related to the genome assembly and curation can be found in the ERGA Assembly Report (EAR) document available at https://github.com/ERGA-consortium/EARs/tree/main/Assembly_Reports/Stigmatoteuthis_arcturi/xcStiArct1. Further details and data about the project are hosted on the ERGA portal at https://portal.erga-biodiversity.eu/data_portal/2053936., The Stigmatoteuthis arcturi reference genome offers a valuable resource for understanding the evolutionary patterns of oceanic squids, who perform important ecological roles as both predators and prey in mesopelagic and deep-sea environments, while their genomes remain understudied. The entirety of the genome sequence was assembled into 46 contiguous chromosomal pseudomolecules. This chromosome-level assembly encompasses 3.25 Gb, composed of 1,268 contigs and 497 scaffolds, with contig and scaffold N50 values of 11.0 Mb and 74.6 Mb, respectively., This project has received funding from the European Union’s Horizon Europe research and innovation programme under grant agreement No 101059492 (Biodiversity Genomics Europe [BGE]). This project received funding from Horizon Europe under the Biodiversity, Circular Economy and Environment (REA.B.3); co-funded by the Swiss State Secretariat for Education, Research and Innovation (SERI) under contract numbers 22.00173 and 24.00054; and by the UK Research and Innovation (UKRI) under the Department for Business, Energy and Industrial Strategy’s Horizon Europe Guarantee Scheme. Funding was provided by the Spanish Ministry of Science, Innovation and Universities (OCTOSET, Ref. RTI2018-097908-B-I00; ECOPHYN, Ref. PID2021-126824NB-C32; MCIU/AEI/FEDER, EU), and the Spanish government through the “Severo Ochoa Center of Excellence” accreditation (CEX2019-000928-S). F.Á.F.-Á. was supported by a Beatriu de Pinós fellowship from Secretaria d ́Universitats i Recerca del Departament de Recerca i Universitats of the Generalitat de Catalunya (Ref. BP 2021 00035) and a Ramón y Cajal fellowship (Ref. RYC2023-043494-I) funded by MCIN/AEI /10.13039/501100011033 and FSE+. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript., With funding form the Spanish government through the "Severa Ochoa Centre of Excellence" accreditation (CEX2019-000928-S)., Peer reviewed

[Aim] As a consequence of globalisation, biological invasions have become an increasing concern due to multifaceted ecological and socio-economic impacts on biodiversity and ecosystem services. Despite the increasing availability and accessibility of data, a comprehensive assessment of established non-native species and their distribution in the Iberian Peninsula has not been conducted so far., [Location] Iberian Peninsula, including Spain, Portugal, Andorra, and Gibraltar., [Methods] We compiled a harmonised dataset of 1273 established non-native species from multiple regional, national, and global sources. We analysed taxonomic composition, introduction pathways, and native biogeographic realms. Temporal patterns were assessed using first-record data, while spatial patterns were mapped using high-resolution occurrence data from GBIF and national databases., [Results] The majority of established non-native species are vascular plants and insects, specifically of the classes Magnoliopsida and Insecta and the families Asteraceae and Formicidae, respectively. Overall, the most common pathways of introduction were escapes from human facilities and transport-related mechanisms (contaminant and stowaway), but their importance varies among countries. Established non-native species were mostly native to the other regions within the Palearctic, followed by the Nearctic and Neotropical realms. Regarding the time of introduction, first records increased steadily until the last decades of the 20th century, when the introduction rate slowed down; yet new introductions persist. Finally, our spatial analysis identified that areas with high human population density and coastal zones recorded the highest number of established non-native species., [Main Conclusion] The Iberian Peninsula hosts a high number and diversity of established non-native species. Given the ongoing rise in cumulative introductions and the role of unintentional human-driven pathways, strengthening prevention measures is vital to reduce future invasions. However, with many non-native species already established, effective management efforts are equally crucial to curb further spread and mitigate consequent impacts, especially in areas of conservation interest., RS was supported by the Portuguese Foundation for Science and Technology (FCT) through national funds under the project MULTI-CRASH: Multi-dimensional ecological cascades triggered by an invasive species in pristine habitats (PTDC/CTA-AMB/0510/2021) (https://doi.org/10.54499/PTDC/CTA-AMB/0510/2021). FR is supported by an individual contract from FCT (CEEC/0482/2020) and by the project MEGAPREDATOR: A giant on the water: from predation pressure to population control of the European catfish (Silurus glanis) (https://doi.org/10.54499/PTDC/ASP-PES/4181/2021). EGB and CMM received financial support from the Spanish Ministry of Science, Innovation, and Universities (MICIU/AEI/ https://doi.org/10.13039/501100011033) and the European Union (NextGenerationEU/PRTR) through projects PID2019-103936GB-C21, FJC2021-047559-I, TED2021-129889B-I00, and RED2022-134338-T. CCB benefited from a postdoctoral contract Ref. JDC2023-052358-I, funded by the Spanish Ministry of Science, Innovation, and Universities, the Agencia Estatal de Investigación (MICIU/AEI/10.13039/501100011033) and the FSE+., Peer reviewed

This study was supported by the projects CHALLENGE (PID2019-107979RB-100 funded by MICIU/AEI/10.13039/501100011033) and CHALLENGE-2 (PID2022-141628NB-I00 funded by MICIU/AEI/10.13039/501100011033 and ERDF, EU) led by CA. TA-G was financed by a Severo Ochoa FPI predoctoral grant (PRE2020-096185) of the Spanish government through the “Severo Ochoa Centre of Excellence” Institute of Marine Sciences (ICM-CSIC) of Barcelona. TA-G and BF acknowledge the institutional support of the ‘Severo Ochoa Centre of Excellence’ accreditation (CEX2019-000928-S). BF has received funding from a Ramón y Cajal grant (RYC2022-036268-I) funded by MICIU/AEI/10.13039/501100011033 and FSE+ and from the MedCalRes project Grant PID2021-125323OAI00 funded by MCIN/AEI/10.13039/501100011033 and by ‘ERDF A way of making Europe’. PB-C was supported by a Humboldt Postdoctoral Fellowship. BF is part of the Marine Conservation research group funded by Generalitat de Catalunya (2021 SGR 01073). CA is part of the Marine Biodiversity and Evolution research group funded by Generalitat de Catalunya (2021 SGR 01271), Peer reviewed

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