BUSCADOR RECOLECTA

Gridded monthly climate projection dataset underpinning the IPCC AR6 Interactive Atlas for the impact-relevant variables and indices., The IPCC WG1 Interactive Atlas is an online tool that provides interactive visualizations and geospatial data related to the physical scientific basis of climate change. This platform allows users to explore and visualize geographical information interactively and dynamically. It presents data using maps, charts, and other visualizations, enabling users to understand complex information spatially and temporally. The interactive Atlas includes climate data for relevant variables, key climate indicators, and trends, all derived from climate model simulations., The IPCC-WGI AR6 Interactive Atlas dataset comprises monthly gridded data from global (CMIP5, CMIP6) and regional (CORDEX) model projections for the impact-relevant variables and indices featured in the IPCC Interactive Atlas (https://interactive-atlas.ipcc.ch)., Peer reviewed, 2

Gridded monthly climate projection dataset underpinning the IPCC AR6 Interactive Atlas for the impact-relevant variables and indices., The IPCC WG1 Interactive Atlas is an online tool that provides interactive visualizations and geospatial data related to the physical scientific basis of climate change. This platform allows users to explore and visualize geographical information interactively and dynamically. It presents data using maps, charts, and other visualizations, enabling users to understand complex information spatially and temporally. The interactive Atlas includes climate data for relevant variables, key climate indicators, and trends, all derived from climate model simulations., The IPCC-WGI AR6 Interactive Atlas dataset comprises monthly gridded data from global (CMIP5, CMIP6) and regional (CORDEX) model projections for the impact-relevant variables and indices featured in the IPCC Interactive Atlas (https://interactive-atlas.ipcc.ch)., Peer reviewed, 2

[Description of methods used for collection/generation of data] Periodically water sampling for dissolved oxygen (DO) and total alkalinity (TA) was done during the sensor maintenance campaigns of BOATS. In two sites, monthly samples were collected from the same depth as the sensors of the BOATS stations, at 1m at the oceanographic buoy, and 4m in PN Cabrera. Samples were taken for dissolved methane (CH4), dissolved oxygen (DO), total alkalinity (TA), dissolved organic carbon (DOC), Chlorophyll a (Chl a), In both stations monthly discrete samples were collected, at 1 m in the Bay of Palma, Surface for Cap ses Salines and at 4 m depth in Cabrera. Samples were collected by submerging a hose connected to a pump at the sensor height of the BOATS stations in Cabrera and the Bay of Palma. At the third site, the lighthouse of Cap ses Salines, a bucket was used to obtain surface water samples., readme provides background information for xlsx datafiles., Methane (CH4) gas is the most important greenhouse gas (GHG) after carbon dioxide, with open ocean areas acting as discreet CH4 sources and coastal regions as intense but variable CH4 sources to the atmosphere. In this database we report measured CH4 concentrations and calculated air-sea fluxes in three sites of the coastal area of the Balearic Islands Archipelago (Western Mediterranean Basin). CH4 levels and related biogeochemical variables were measured in three coastal sampling sites between 2019 and 2021. CH4 concentrations in seawater ranged from 2.7 to 10.9 nM, without significant differences between the sampling sites. Averaged estimated CH4 fluxes during the sampling period for the three stations oscillated between 0.2 and 9.7 μmol m−2 d−1 following a seasonal pattern and in general all sites behaved as weak CH4 sources throughout the sampling period., Funding for this work was provided by the projects RTI2018-095441-B-C21 (SuMaEco) and, the BBVA Foundation project Posi-COIN and the Balearic Islands Government project SEPPO (PRD2018/18). This work is a contribution to CSIC’s Thematic Interdisciplinary Platform PTI OCEANS+., Peer reviewed

Gridded monthly climate projection dataset underpinning the IPCC AR6 Interactive Atlas for the impact-relevant variables and indices., The IPCC WG1 Interactive Atlas is an online tool that provides interactive visualizations and geospatial data related to the physical scientific basis of climate change. This platform allows users to explore and visualize geographical information interactively and dynamically. It presents data using maps, charts, and other visualizations, enabling users to understand complex information spatially and temporally. The interactive Atlas includes climate data for relevant variables, key climate indicators, and trends, all derived from climate model simulations., The IPCC-WGI AR6 Interactive Atlas dataset comprises monthly gridded data from global (CMIP5, CMIP6) and regional (CORDEX) model projections for the impact-relevant variables and indices featured in the IPCC Interactive Atlas (https://interactive-atlas.ipcc.ch)., Peer reviewed, 2

Samples were collected in the tropical and subtropical Atlantic during the MAFIA cruise (April 2015) on board the BIO Hespérides. Seawater samples were collected at 13 stations (from the Brazilian coast to the Canary Islands), from the surface down to 3500 m, using a General Oceanics oceanographic rosette equipped with 24 l PVC Niskin bottles. Abundance and cell characteristics (high nucleic acid content fraction, cell volume, viability) were based on measurements performed with a FACSCalibur (Becton-Dickinson) flow cytometer. Leucine incorporation rates were estimated with tritiated leucine (Kirchman et al. 1985) using centrifugation and filtration methods (Smith and Azam 1992). The aim of this dataset was to estimate the influence of surface productivity on the standing stock, characteristics and activity (as leucine incorporation) of prokaryotes across the water column, This dataset contains the results of the characterisation of the prokaryotic community by flow cytometry and tritiated leucine incorporation from the MAFIA cruise (Migrants and Active Flux In the Atlantic ocean), Horizon 2020 (H2020), grant/award no. 817806: Sustainable management of mesopelagic resources; Ministerio de Ciencia e Innovación (MICINN), grant/award no. CTM2012-39587-C04: Migrants and Active Flux In the Atlantic Ocean; Ministerio de Ciencia e Innovación (MICINN), grant/award no. CTM2015-69392-C3: Constraining organic carbon fluxes in an eastern boundary upwelling ecosystem (NW Africa): the role of non-sinking carbon in the context of the biological pump; Ministerio de Ciencia e Innovación (MICINN), grant/award no. CTM2017-83362-R: INTERES: Papel de las interacciones fitoplancton-bacterias en la respuesta del plancton microbiano a la entrada de nutrientes alóctonos; Ministerio de Ciencia e Innovación (MICINN), grant/award no. PID2019-109084RB-C21: Biogeochemical impact of mesoscale and sub-mesoscale processes along the life history of cyclonic and anticyclonic eddies: plankton variability and productivity, With the institutional support of the ‘Severo Ochoa Centre of Excellence’ accreditation (CEX2019-000928-S), No

Data acquisition: Satellite: ESA SMOS mission (Soil Moisture and Ocean Salinity). Filenames: BEC_SSS___SMOS__SO__L3__B_YYYYMMDDT120000_25km__9d_REP_v100.nc YYYYMMDD: central date BEC ftp service: We serve netCDF data by means of a secure ftp server. NetCDF files from which the maps were made (and other additional data) can be downloaded from sftp address becftp.icm.csic.es at port 27500. If your browser is sftp compatible you can browse directly from sftp://becftp.icm.csic.es:27500 address. In order to download data you should be registered in our BEC ftp service. Registration is free, you can register just by filling the following form: http://bec.icm.csic.es/bec-ftp-service-registration/ If you need a dedicated ftp client (for instance FileZilla https://filezilla-project.org/) you should use the following configuration: Host: sftp://becftp.icm.csic.es Username: your username. Password: your password. Port: 27500, Dedicated regional Sea Surface Salinity (SSS) product in the Southern Ocean. Level 3 9-day maps. Data acquisition: Satellite ESA SMOS mission (Soil Moisture and Ocean Salinity). Time coverage 01 February 2011 - 31 December 2022. Time resolution: 9-day. Maps frequency generation: Daily. Spatial coverage: Latitude range: 30ºS-90ºS Longitude range: 180ºW-180ºE. Spatial resolution: 25 km (EASE-SL grid). Sensor Satellite SMOS / MIRAS. Format NetCDF. Climate and Forecast (CF) conventions version: 1.6, With the institutional support of the ‘Severo Ochoa Centre of Excellence’ accreditation (CEX2019-000928-S), Peer reviewed

The study of a species' thermal tolerance and vital rate responses provides useful metrics to characterize its vulnerability to ocean warming. Under prolonged thermal stress, plastic and adaptive processes can adjust the physiology of organisms. Yet it is uncertain whether the species can expand their upper thermal limits to cope with rapid and extreme changes in environmental temperature. In this study, we reared the marine copepod Paracartia grani at control (19°C) and warmer conditions (25°C) for >18 generations and assessed their survival and fecundity under short-term exposure to a range of temperatures (11-34°C). After multigenerational warming, the upper tolerance to acute exposure (24 hours) increased by 1-1.3°C, although this enhancement decreased to 0.3-0.8°C after longer thermal stress (7 days). Warm-reared copepods were smaller and produced significantly fewer offspring at the optimum temperature. No shift in the thermal breadth of the reproductive response was observed. Yet the fecundity rates of the warm-reared copepods in the upper thermal range were up to 21-fold higher than the control. Our results show that chronic warming improved tolerance to stress temperatures and fecundity of P. grani, therefore enhancing its chances to persist under extreme heat events, This research was funded by Grants CTM2017-84288-R and PID2020-118645RB-I00 by MCIN/AEI/10.13039/501100011033 and by “ERDF A way of making Europe”. “ERDF A way of making Europe” C. J. was supported by Grant [PRE2018-084738] funded by MCIN/AEI/10.13039/501100011033 and by “ESF Investing in your future”, With the institutional support of the ‘Severo Ochoa Centre of Excellence’ accreditation (CEX2019-000928-S), Rearing temperature, generation, exposure temperature, survival 24h, survival 7d, egg production rate, fitness index, egg diameter, female prosome length, Peer reviewed

This form consists of five parts: METADATA (L10-L20), COMMON DATA (L24-L40), LOCATION CODES (L42-L52), TREATMENT LEGEND (L54-L58) AND SAMPLE DATA (L61-). The formulae used in this sheet are based on Keuskamp et al. 2013 (http://onlinelibrary.wiley.com/enhanced/doi/10.1111/2041-210X.12097/). For more information please refer to the manual included with this file. Please fill out the data in the purple cells, and optionally in the blue cells and send form to tbiteam@decolab.org or upload it on www.teatime4science.org, Coordinador del proyecto: Johann G. Zaller de BOKU., [EN] This data set was collected in 16 vineyards belonging to the DO Montilla-Moriles to determine the decomposition rate of plant material through the tea bag index (TBI) with different soil cover management (bare soil and cover crop)., [ES] Este conjunto de datos se recogió en 16 viñedos pertenecientes a la DO Montilla-Moriles para determinar la tasa de descomposición del material vegetal a través del índice de la bolsa de té (TBI) con diferentes manejos de la cobertura del suelo (suelo desnudo y cubierta vegetal)., Convocatoria del vinedivers fue la BiodivERsA/ FACCE-JPI 2013-2014., Peer reviewed

S1. Experimental Section: S1.1. Synthesis and Characterization Data. S1.2. Fluorescence Measurements. S1.3. Zeta Potential Measurements. S1.4. Dynamic Light Scattering Measurements. S1.5. Circular Dichroism Spectra. S1.6. Agarose Gel Electrophoresis. S1.7. Atomic Force Microscopy (AFM). S1.8. In Vitro Assays S1.9. Transfection Assays. S1.10. Chlamydomonas reinhardtii Nuclear Transformation. S2. Results and Discussion: S2.1. Characterization of Monomers and Polyurethanes. S2.2. Formation of the polyplexes PUMan/ctDNA. Figures: Fig. S1. FTIR spectra of PUMan and (MBocCis)DTDI. Fig. S2. SEC chromatogram of (MAL)DTDI. Fig. S3. SEC chromatogram of (MBocCis)DTDI. Fig. S4. SEC chromatogram of PUMan. Fig. S5. 1H NMR of (MAL)DTDI. Fig. S6. 1H NMR of (MBocCis)DTDI. Fig. S7. 1H NMR of PUMan. Fig. S8. TGA curve of PUMan. Fig. S9. Plot of EB emission intensities at different N/P values, circular dichroism spectra, zeta potential and hydrodynamic diameters of the PUMan-based polyplexes. Fig.S10. Electrophoresis of polyplexes PUMan/digested pEGFP-C1 and PUMan/digested Phyco69 at different N/P ratios. Fig.S11. Percentage of GFP positive cells after transfection with 3 μg of the plasmid pEGFP-C1 with the indicated reagents. The molar ratio PUMan:FuGENE and PUMan:DOPE was 1:1. Tables: Table S1. Thermal properties of PUMan and its precursors., Peer reviewed

[Description of methods used for collection/generation of data] Los talasónimos fueron recopilados de diversas fuentes. Hemos utilizado visores en línea como los catálogos de la OHI y el IGME (https://www.ngdc.noaa.gov/iho/; http://info.igme.es/visor/), así como publicaciones científicas de recopilaciones de nombres de lugares marinos. Los datos batimétricos se descargaron del geoportal EMODnet y los límites de demarcación marina se obtuvieron del sitio web del Ministerio de Transición Ecológica y Reto Demográfico de España., [ES] Esta base de datos es una recopilación de los talasónimos en las subdivisiones marinas españolas (Atlántico Norte, Atlántico Sur, Estrecho y Alborán, Levantino-Balear y Canarias). Mediante la identificación sistemática de estas características en las subdivisiones, se llevó a cabo una extensa investigación bibliográfica y de bases de datos para asignar nombres de lugar adecuados a cada elemento. Se han reconocido diez tipos principales de talasónimos geográficos, personales, descripciones de forma, conmemorativos, culturales, nombres de pescadores, nombres de embarcaciones y expediciones, otros y desconocidos. Los nombres más comunes son ubicaciones geográficas, seguidos de nombres de personalidades históricas. Esta nueva base de datos está abierta a modificaciones y nuevos nombres que podrían agregarse en el futuro. Igualmente, si se detecta algún error se puede enviar a los autores para su corrección., [EN] This database is a compilation of thalassonyms or submarine toponyms within the Spanish marine subdivisions (North Atlantic, South Atlantic, Strait of Gibraltar and Alboran, Levantine-Balearic, and Canary Islands). Through the systematic identification of these features within the subdivisions, extensive bibliographic and database research was conducted to assign appropriate place names to each element. Ten main types of thalassonyms have been identified: geographical, personal, shape descriptions, commemorative, cultural, fishermen’s names, vessel and expedition names, others, and unknown. The most common names are geographical locations, followed by historical figures’ names. This new database is open to modifications, and new names may be added in the future. Likewise, if any errors are detected, they can be submitted to the authors for correction., Proyecto Estrategías Marinas Españolas (EsMarEs). https://www.miteco.gob.es/es/costas/temas/proteccion-medio-marino/estrategias-marinas/default.aspx). Más específicamente este trabajo corresponde a la acción C12A2 del proyecto ESMARES, Caracterización de la naturaleza y composición del fondo marino de las demarcaciones marinas españolas y la generación de capas de información para su mejor gestión., Peer reviewed