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This item is made of 2 files: the dataset in netcdf format, a Readme.txt file including a small description of the computed variables, and 1 figure showing the instrument used, Wave parameters obtained from RBR Duo in Cabo do mar from October 2021 to June 2022 under the framework of the STRAUSS project in order to evaluate the effects of ocean waves in selected biological case studies of the Rías Baixas Upwelling System, Funding for this deployment was provided by Project 𝐏𝐈𝐃𝟐𝟎𝟏𝟗-𝟏𝟎𝟔𝟎𝟎𝟖𝐑𝐁-𝐂𝟐𝟏, funded by MCIN/AEI/10.13039/501100011033 in the R&D Projects “Research Challenges” modality, Peer reviewed

Data acquisition: Satellite: ESA SMOS mission (Soil Moisture and Ocean Salinity), ECMWF skin temperature at 12 UTC and 16-dayTerra MODIS NDVI version 6.1 Filenames: BEC_SM____SMOS__EUM_L4__X_YYYYMMDDTHHMMSS_001km_1d_REP_v6.1.nc, being: - X the half-orbit type (A for ascending and D for descending), - YYYYMMDDTHHMMSS the central date (year, month, day, hour, minute and second) in Coordinated Universal Time (UTC) of the period covered by the file. Time resolution: Daily. Maps frequency generation: Daily. Sensor: Satellite SMOS / MIRAS. Spatial resolution: 1 km x 1 km. Spatial grid: WGS_84 / EASE2_M01km, Improvement of the current SMOS soil moisture products produced by the Barcelona Expert Centre (BEC) and development of new added-value products and/or applications over land., INTERACT. Enfoques sinergéticos para una nueva generación de productos y aplicaciones de observación de la Tierra (PID2020-114623RB-C31). Ministerio de Ciencia e Innovación a través de PN2020 - PROY I+D+I – Programa Estatal de I+D+I Orientada a los Retos de la Sociedad – Plan Estatal de Investigación Científica Técnica y de Innovación 2017-2020., · Surface soil moisture (SM) · Quality flag of surface soil moisture (quality_flag) · Time (time) · Latitude (lat) · Longitude (lon) · Coordinate reference system (crs), Peer reviewed

This item is made of 2 files: the dataset in netcdf format, a Readme.txt file including a small description of the computed variables, and 1 figure showing the instrument used, Wave parameters obtained from RBR Duo in Limens from February 2021 to May 2021 under the framework of the STRAUSS project in order to evaluate the effects of ocean waves in selected biological case studies of the Rías Baixas Upwelling System, Funding for this deployment was provided by Project 𝐏𝐈𝐃𝟐𝟎𝟏𝟗-𝟏𝟎𝟔𝟎𝟎𝟖𝐑𝐁-𝐂𝟐𝟏, funded by MCIN/AEI/10.13039/501100011033 in the R&D Projects “Research Challenges” modality, Peer reviewed

This item is made of 2 files: the dataset in netcdf format, a Readme.txt file including a small description of the computed variables, and 1 figure showing the instrument used, Wave parameters obtained from ACDP currents of a RDI 600-kHz Workhorse Acoustic Doppler Current Profiler (ADCP) in Cíes Sur from May 2022 to June 2022 under the framework of the STRAUSS project in order to evaluate the effects of ocean waves in selected biological case studies of the Rías Baixas Upwelling System, Funding for this deployment was provided by Project 𝐏𝐈𝐃𝟐𝟎𝟏𝟗-𝟏𝟎𝟔𝟎𝟎𝟖𝐑𝐁-𝐂𝟐𝟏, funded by MCIN/AEI/10.13039/501100011033 in the R&D Projects “Research Challenges” modality, Peer reviewed

This dataset corresponds to a comprehensive study of splice-site variants of the breast cancer susceptibility gene CHEK2. Variant data have been obtained from the large-scale sequencing project BRIDGES that sequenced 34 genes in 113,000 women. A set of 128 CHEK2 variants at the intron-exon boundaries were identified, 52 of which were predicted spliceogenic. These were introduced into the three minigene constructs by site-directed mutagenesis and tested in MCF-7 cells. Forty-six variants impaired splicing, 26 of which were classified as pathogenic/likely pathogenic variants according to ACMG/AMP-based guidelines, so carrier patients and families may benefit from tailored prevention protocols and personalized therapies., Eladio A. Velasco (EAV) has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement no. 634935. EAV lab is supported by grants from the Spanish Ministry of Science and Innovation, Plan Nacional de I+D+I 2013-2016, ISCIII (PI17/00227 and PI20/00225) co-funded by FEDER from Regional Development European Funds (European Union) and from the Consejería de Educación, Junta de Castilla y León, ref. CSI242P18 (actuación cofinanciada P.O. FEDER 2014-2020 de Castilla y León). Lara Sanoguera-Miralles is supported by a predoctoral fellowship from the AECC-Scientific Foundation, Sede Provincial de Valladolid (2019–2023). Elena Bueno-Martínez is a postdoctoral researcher funded by the University of Valladolid (POSTDOC-UVA05, 2022-2025)., Folder: cDNA_Sequences. Transcript Sequencing. Sub-Folders: cDNA microdeletions CHEK2 1-7 c.684-2G; cDNA_minigenes CHEK2 1-7; cDNA_minigenes CHEK2 6-10; cDNA_minigenes CHEK2 6-14 WT y mutantes; cDNA_minigenes CHEK2 11-15; cDNA_minigenes WT.-- Folder: Fragment_Analysis. Fluorescent Fragment Analysis. Sub-Folders: Fragment_Analysis_microdeletions CHEK2 1-7 c.684-2G; Fragment_Analysis_minigenes CHEK2 1-7; Fragment_Analysis_minigenes CHEK2 6-10; Fragment_Analysis_minigenes CHEK2 6-14 y mutantes; Fragment_Analysis_minigenes CHEK2 11-15; Fragment_Analysis_minigenes WT.-- Folder: Minigenes_Sequences. Sequence files of wild type and mutant constructs. Sub-folders: Microdeletions_CHEK2 1-7-c.684-2G; Minigene_CHEK2 1-7; Minigene_CHEK2 6-10; Minigene_CHEK2 6-14 WT y mutant; Minigene_CHEK2 11-15; minigene_WT., Peer reviewed

[Methods] Data are compiled from published references, in all cases, the reference is provided., 1. Many internal (inherent) and environmental (imposed) factors control seed dormancy and germina-tion from which we can derive three basic dormancy-release pathways: Maternal structures and embryo physiology control inherent dormancy that is broken by various types of scarification and physiological changes, followed by imposed-dormancy release when replaced by certain ‘standard’ environmental conditions that stimulate germination (pathway 1); imposed dormancy prevails even if inherent dorman-cy is broken or not applicable that is released when replaced by certain ‘standard’ environmental condi-tions which stimulate germination (pathway 2); release from inherent dormancy by light/dark or cold stratification is contingent on existing presence of certain ‘standard’ environmental conditions that stim-ulate germination (pathway 3). 2. On-plant seed storage (serotiny) and frugivorous seeds are recognized here as representing special types of physical dormancy, as their properties are consistent with those of hard diaspores. Warm stratification does not require seeds to be moist as it is just a physical response. Heat may promote germination of non-hard, as well as hard, seeds as it may also increase their permeability. 3. Levels of germination gauge the net effect of inherent- and imposed-dormancy release so that it only possible to identify the extent of inherent-dormancy release when conditions for germination are optimal (imposed dormancy has been annulled). While imposed dormancy may be protracted after inherent dormancy is broken by heat or chilling during the dry or cold seasons, release from both states may effectively coincide if smoke chemicals or light are received during the (wet) growing sea-son. 4. We suggest reserving the term secondary dormancy for seeds that return to (inherent or imposed) dormancy due to changed environmental conditions. Under seasonal climates, fluctuations in envi-ronmental conditions can lead to secondary dormancy and even dormancy cycling. 5. We recognize four types of functional interactions between any two environmental factors that induce inherent-dormancy release: binary interactions are either ineffective, only one effective, non-additive or additive/synergistic. Two environmental stimuli that individually break dormancy but have no additive effect must be affecting the same process; this was demonstrated here for some interac-tions between heat and smoke. 6. The three dormancy-release pathways, together with internal, seasonal and stochastic interact ions, are coordinated by the non-dormant seed to ensure maximum germination under optimal conditions. To ignore any aspect outlined here leads to an impoverished understanding of the disparate seed ecol-ogy of species adapted to different stressful and disturbance-prone habitats., Generalitat Valenciana, Award: PROMETEO/2021/040 (FocScales)., Peer reviewed

[Methods] ABR DATA: obtained by ABR recording in a Tucker David Technology RZ6 Auditory Workstation using BioSigRZ software EVANS BLUE DATA: obtained by fluorimetry in a Glomax™ Luminometer and Microplate Reader (Promega) (620/680 nm excitation/emission wavelength). GENE EXPRESSION DATA: obtained by Real-Time PCR and analyzed by QuantStudio™ Real-Time PCR software 1.3. PCR array obtained using the PCR array RT² Profiler™ Rat Innate & Adaptive Immune Responses (Qiagen, #PARN-052Z) and analyzed with Geneglobe (Qiagen). MRI DATA: images obtained with a horizontal 7.0-Tesla Bruker BioSpec® system (Bruker Medical GmbH) running ParaVision 6.0.1 on a Linux environment. Data analysis was performed with Fiji software. OPTICAL IMAGING DATA: images obtained with a Zeiss AxioPhot microscope (Carl Zeiss). Data analysis was performed with Fiji software. FLUORESCENCE DATA: images obtained with an epifluorescence (Nikon 90i) and confocal laser-scanning (Zeiss LSM710) microscopes. Data analysis was performed with Fiji software. WB DATA: Immunoreactive bands revealed using the Clarity™ Western ECL Substrate (Bio-Rad), and images were captured with the ImageQuant LAS4000 mini digital camera using ImageQuant TL software 8.1 (GE Healthcare)., SPIRALTH-CIBERER ER17PE12., 1) ABR DATA ABR_DATA ANALYSIS ABRA_RAW DATA 2) EVANS BLUE DATA EVANS BLUE RAW DATA EVANS BLUE ANALYSIS 3) GENE EXPRESSION DATA 3.1) HEATMAP HEATMAPPER DATASET HEATMAP IN HOUSE ANALYSIS HEATMAP RT2 PROFILER PCR ARRAY DATA ANALYSIS_Placa3693-3694 3.2) QPCR PLS PLUS SPT-2101 QPCR SELECCION ARRAY 3.3) QPCR LPS TIME COURSE SPSS LPS TIME COURSE LPS TIME COURSE STATISTICS 3.4) QPCR STRIAL DAMAGE STRIAL GENES DATA ANALYSIS QPCR STRIAL GENES 4) MRI DATA MRI RAW DATA MRI LPS PLUS TREATMENTS_DATA ANALYSIS MRI_LPS TIME COURSE DATA ANALYSIS 5) OPTICAL AND FLUORESCENCE MICROSCOPY DATA 5.1) HAIR CELL-SYNAPSIS HC-SYNAPSIS RAW DATA STATISTICS HCs STATISTICS SYNAPSIS 5.2) IF STRIA SPSS DESMIN COVERAGE STATISTICS DESMIN COVERAGE DESMIN COVERAGE 5.3)STRIA AREA STRIA MORPHOLOGY RAW DATA STRIA AREA DATA ANALYSIS 5.4) IF SPIRAL GANGLION AND LIGAMENT IBA1 GANGL DATA IBA1 LIG DATA IBA1 GANGL ANALYSIS IBA1 LIG DATA ANALYSIS 6) WB DATA WB NLRP2 AND NRF2 DATA NLRP3 IMAGES NRF2 IMAGES VINCULIN IMAGES, Peer reviewed

[Methodology] We sampled the insect assemblage visiting flowers in the arborescent scrublands with Ziziphus lotus (Habitat 5520*, Habitat Directive EU) to characterize the plant-floral visitor networks of these threatened habitats in the semiarid southeast of the Iberian Peninsula, mainly in Almería province (Andalucia, Spain). We selected 6 localities with the presence of this Ziziphus lotus habitat: i) 2 localities in habitat dominated by Ziziphus lotus individuals (ZIZ); ii) 2 localities in habitat dominated by Maytenus senegalensis with Ziziphus lotus (ZIZMAY); iii) 2 localities in habitat dominated by Chamaerops humilis with Ziziphus lotus (ZIZCHA). To study the community of insect floral visitors and the flowering plant species community (floral resources) in these habitats, 6-7 transects of [50 m x 2 m] were defined in each population, which were sampled by 50 min-censuses from February-July at 3 different times (pre-spring + spring + summer; total transects sampled = 39 transects x 3 censuses = 117 transects). The sampled transects were randomly distributed, trying to cover the largest possible area within each population to avoid sampling bias. We recorded the insect community visiting flowers (plant-floral visitor interactions) in terms of richness and abundance per transect and population. We only recorded xenogamic plant-insect interactions (as a proxy for pollen movements between different plant individuals) since they are related to more effective pollination events than geitonogamic interactions. The censuses were carried out on sunny days with low winds (<12Km/h), between 9:00-17:00, during the period of maximum insect activity. The richness and abundance of plant-floral visitor interactions by transect were pooled by population ('Interaction_data_pop.csv' file). R software (R Core, 2021) was used to calculate the summaries showed in .csv files. References: - R Core Team (2021). R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. URL: https://www.R-project.org/, [Files] Interaction_data_pop.csv [reports the data of detected plant-insect interactions].-- Population_and_sampling_info.csv [has information of samplings per population according to the data of Interaction_data_pop.csv' file].-- Metada.csv [reports information about the meaning of columns in 'Interaction_data_pop.csv' and 'Population_and_sampling_info.csv' files], Our aim was to described the plant-floral visitor interactions to characterize the plant-floral visitor networks of arborescent scrublands with Ziziphus lotus (Habitat 5520*, Habitat Directive EU) in the semiarid southeast of the Iberian Peninsula, mainly in Almería province (Andalucia, Spain). We differentiated three habitat subtypes with Ziziphus lotus: i) habitat dominated by Ziziphus lotus individuals (ZIZ); ii) habitat dominated by Maytenus senegalensis with Ziziphus lotus (ZIZMAY); iii) habitat dominated by Chamaerops humilis with Ziziphus lotus (ZIZCHA), This study was funded by MICINN through European Regional Development Fund [SUMHAL, LIFEWATCH-2019-09-CSIC-4, POPE 2014-2020] [Work Package 9. Task 9.3.2. Model impact of land use change], Junta de Andalucía Excelencia RNM-766 project, and by funds from Fondo Europeo de Desarrollo Regional (FEDER- UJA 1261180 project, FEDER Andalucía operative programme). CSIC is acknowledged for supporting Open Access publication., Please, see Metadata.csv file., Peer reviewed

[Methodology] We selected 40 paired olive groves from 20 localities, covering a cultivated area circa 35 km2 and encompassing a distance of 310 km between the most distant ones, hence widely distributed across the Guadalquivir Valley (Andalucía, Spain). Localities were selected to cover a wide gradient in landscape complexity, from landscapes dominated by olive groves to landscapes including a large fraction of natural (forests, scrublands, streams and pastures with native plants) or semi-natural habitats (gullies, vegetated edges and field margins) or other woody and annual crops. At each locality, the pair of olive groves differed in the herb cover management (20 low-intensity and 20 intensive groves) in 2016 while some of them changed their management in 2019, while sharing the same landscape context. Farm size and climatic and edaphic condition varied between localities but were relatively similar between the pair of farms within locality. Low-intensity management involved the maintenance of the ground herb cover most of the year through agroecological practices, such as grazing (mainly with sheep), mowing or stand maintaining between olive trees. Some of these low-intensity managed olive farms where also organic when, in addition, there was no use of pesticides nor synthesis fertilizers. In contrast, intensive management persistently reduced herb cover by herbicides and/or recurrent tillage. The landscape of each locality was classified in simple (characterized by vast extensions of olive groves with very few natural habitat patches), intermediate (olive groves are intermingled with annual crops and with greater extension of natural habitats) or complex (olive groves are scarcer and the area covered by forests, shrublands, streams and grasslands with native plants is larger). The community of herb species was monthly sampled in each olive groves from April to June in 2016 and 2019, using 1-m2 quadrats. We surveyed 4-6 herbs quadrats per grove (in olive field habitats), depending on the orchard size (4 sampling points in small groves [<10 ha]; 6 sampling points in large groves [>10 ha]) and 2-4 herbs quadrats per olive grove in semi-natural habitats adjacent to olive field. Substantial work was done in the lab for the classification of the many species that we were not able to determine at species level in the field. BBDD_Herbs_sps_habitat_farm.csv ', [Files] BBDD_Farm_info.csv [shows the location and characteristics of sampled olive farms].-- BBDD_Herbs_sps_habitat_farm.csv [shows herb community detected per habitat within Olive_farm].-- Metada.csv [records information about the meaning of columns in ' Farm_info.csv, 'Plant_database_Habitats_ziziphus.csv', ', Our aim was to characterize the species composition of ground herb covers present in the olive groves and their semi-natural adjacent habitats of the southern Iberian Peninsula (Andalucia, Spain), according to herb cover management and landscape complexity of each grove. We selected 40 paired olive farms from 20 localities across Andalucía., This data set was compilated with funds by MICINN through European Regional Development Fund [SUMHAL, LIFEWATCH-2019-09-CSIC-4, POPE 2014-2020] [Work Package 9. Task 9.3.2. Model impact of land use change]. Data comes mainly from LIFE project OLIVARES VIVOS (LIFE14 NAT/ ES/1001094) of the European Commission and complemented partially with additional surveys under LIFEWATCH SUMHAL. CSIC is acknowledged for supporting Open Access publication., Please, see Metadata.csv file., Peer reviewed

The temperature-size rule states that as the temperature increases, the body size of organisms decreases. This rule has been observed in a wide range of organisms, including marine phytoplankton and it is particularly important to model and predict the effects of global warming on the structure and functioning of marine ecosystems. This is so because the size of marine phytoplankton is a critical trait that determines their ecological and biogeochemical roles in marine ecosystems. The size of marine phytoplankton is also affected by resource availability, which relates to growth rates. Here, we compare the effects of a long-term exposure to several temperatures on the cell size of three marine microalgae during their growth curves. The species chosen were the cryptophyte Rhodomonas salina, the dinoflagellate Heterocapsa niei, and the diatom Conticribra (previously Thalassiosira) weissflogii. All algae conformed the temperature-size rule during all the phases of the growth curve. However, the size variations of the microalgae in each of the phases were species-specific. R. salina and H. niei showed higher volumes in the exponential growth phase than during the decline of growth and early stationary phases. Contrarily, the diatom showed smaller volumes during the exponential phase of growth than during the other phases. Overall, the effects of growth rate on cell size exceeded those of temperature for the expected ocean warming by the end of the century. These results also partially support the higher relevance of resource supply than temperature in explaining the variability of phytoplankton size structure in marine ecosystems, This research was funded by Grant PID2020-118645RB-I00 by Ministerio de Ciencia e innovación (MCIN)/AEI/ 10.13039/501100011033 and by “ERDF A way of making Europe”. With the institutional support of the ‘Severo Ochoa Centre of Excellence’ accreditation (CEX2019-000928-S), Para las tres microalgas, Rhodomonas salina, Heterocapsa niei, Conticribra weissflogii, abundancias, y volumen a diferentes temperaturas, Peer reviewed