Resultados de investigación

[Methods for processing the data] Records of Physalia physalis sightings are generated/obtained from various sources of information; individual informants who submit sightings electronically or verbally, press releases and notices from coastal monitoring stations., [Description] This dataset provides measurements of Physalia physalis abundance on the coast of the Gulf of Cádiz conducted over 2009-2022, covering Spanish and Portuguese coasts. The dataset is provided as [space] delimitated plain text file within a compressed folder that also includes a single README file (in text format) containing a detailed description of the data structure. For more details, see the publication: - Macías, D., García-San Martín, L., Prieto, L. (2025). The influence of atmospheric and oceanographic conditions on the occurrence of Portuguese Man-o-War (Physalia physalis) along Iberian coasts. The case of summer 2019 and potential future implications. (Manuscript accepted for publication in Frontiers in Marine Science). This research was funded by MarinERA (EU) (grant number CTM2008-04036-E/MAR "Inter-basin exchange in the changing Mediterranean Sea: Impact on the ecosystems in the vicinity of the Straits connecting the Mediterranean Sea with the adjacents Basins, proyect MedEx), Spanish Ministerio de Ciencia e Innovación (grant number CTM2011-22856 "Forzamientos físicos en la proliferación costera de organismos gelatinosos: un análisis combinado de modelado y experimentación, JELLY-PHYS), Seventh framework programme of the European Community for research and technological development including demonstration activities (grant number FP7-287600, PERSEUS), Spanish Ministerio de Economía y Competitividad (grant number CTM2016-75487-R “Respuesta de medusas mediterráneas al efecto interactivo de motores climáticos de impacto: supervivencia en un Mediterráneo más cálido y ácido”, proyect MED2CA), CSIC (grant number 201730I072 "Forzamientos físicos en la proliferación costera de organismos gelatinosos”) and the Contract Agreement “Detección de medusas en el mar Balear y su relación con las condiciones ambientales: hacia el desarrollo de un sistema de predicción pre-operacional” among Govern des Illes Balears, SOCIB and CSIC (Disposición 15052 del BOE núm. 310 de 2020). The dataset is subject to a Creative Commons License Attribution-ShareAlike 4.0 International., [General Notes] The data are provided under an Attribution-ShareAlike 4.0 International license. However, if you use the data, so as to support the authors, please consider citing the above mentioned article where data collection and analytical techniques are given in detail. Here we only give a brief details and a guide to the contents of the data files. Data files are in UTF8 encoding, plain text format with comma used as the delimiter. All data files have column titles as the first line. One column is written for each variable. Missing data are filled with NaN., [Geographical coordinates of the sampling area] coordinates.txt provides the geographical coordinates of the sampling area. ST.ID represents the code (used to link to other data tables) for each site. long and lat are longitude and latitude, respectively., This dataset includes data collected from ICMAN-CSIC (Spain) between 2009 and 2022 that have been used to estimate the seasonality and inter-annual variability of Physalia physalis abundance in the Gulf of Cádiz., This research was funded by MarinERA (EU) (grant number CTM2008-04036-E/MAR "Inter-basin exchange in the changing Mediterranean Sea: Impact on the ecosystems in the vicinity of the Straits connecting the Mediterranean Sea with the adjacents Basins, proyect MedEx), Spanish Ministerio de Ciencia e Innovación (grant number CTM2011-22856 "Forzamientos físicos en la proliferación costera de organismos gelatinosos: un análisis combinado de modelado y experimentación, JELLY-PHYS), Proyecto Integrado del Séptimo Programa Marco de la Unión Europea (grant number FP7-287600, PERSEUS), Spanish Ministerio de Economía y Competitividad (grant number CTM2016-75487-R “Respuesta de medusas mediterráneas al efecto interactivo de motores climáticos de impacto: supervivencia en un Mediterráneo más cálido y ácido”, proyect MED2CA), CSIC (grant number 201730I072 "Forzamientos físicos en la proliferación costera de organismos gelatinosos) and the Project Agreement “Detección de medusas en el mar Balear y su relación con las condiciones ambientales: hacia el desarrollo de un sistema de predicción pre-operacional” among Govern des Illes Balears, SOCIB and CSIC (Disposición 15052 del BOE núm. 310 de 2020)., Peer reviewed

Independent files with detailed numeric analysis of precipitation evolution and trends for different countries in the Mediterranean region., Peer reviewed

Additional file 1. Species and genome assembly accession numbers used. Taxonomic information is retrieved from The Plant Tree of Life., Ministerio de Ciencia e Innovación, Severo Ochoa Programme for Centres of Excellence in R&D CERCA Program / Generalitat de Catalunya, Consejo Superior de Investigaciones Cientificas (CSIC), Peer reviewed

Supplementary Material 1, Peer reviewed

Sunscreens are included among the contaminants of emerging concern (CECs) as their production and use have spread over years while damaging aquatic biota. Sunscreens can damage the photosynthetic systems and change the microbiome of seagrasses, triggering alterations in carbon metabolism –including primary production and dissolved organic carbon (DOC) fluxes– and ecological functions. Here, we conducted a 31-day mesocosm experiment exposing Cymodocea nodosa plants to a mixture of commercial sunscreens. Sunscreens produced a significant reduction on net production rates, switching the system from autotrophic to heterotrophic, which was ascribable to an increase in heterotrophic bacteria families (some known to degrade complex substrates) and, more importantly, to a significant reduction of photosynthetic pigments in plants. Moreover, a significant release of DOC at night attributed to exudation from disrupted roots was recorded, which accounted for the observed increase in bacteria abundance and family richness recorded in the phyllosphere. A higher accumulation of starch in rhizomes suggests a certain degree of resistance of this species. However, we observed a trend to reduce some protective bacteria taxa, whereas promoted the growth of other pathogenic ones for seagrasses, along with other taxa related with the consumption of plant-derived polysaccharides and lignin compounds. Therefore, our results indicated that this CEC may reduce the contribution of seagrasses to the blue carbon pool, among others ecosystem services, and suggest a possible prompt of seagrass diseases if stressing conditions are maintained over time., This study received Spanish national funds from project RECOUNT (PID2020-120237RJ-I00/AEI/10.13039/5011000 11033; PI, RJR); SERCADY [FEDER-UCA18- 107451; PI, LGE] and CREMAR [FEDER-UCA18-106672; PI, ARR], both co-financed by the European Union under the 2014-2020 ERDF Operational Programme and by the Department of Economic Transformation, Industry, Knowledge, and Universities of the Regional Government of Andalusia. The study was also supported by the iBesblue Spanish national project (PID2021-123597OB-I00) and the Spanish grant CNS2022-135160 funded by MCIN/AEI/ 10.13039/501100011033 and European Union NextGeneration EU/PRTR. MIV was supported by a FPU fellowship from the Spanish Ministry of Universities. EBCH postdoctoral contract was funded by the SERCADY project., Peer reviewed

Here, we collect an image dataset of Vipp1 polymerization dynamics on supported lipid bilayers using atomic force microscopy (AFM). A JPK NanoWizard Ultraspeed AFM (Bruker and JPK BioAFM) equipped with USC-F0.3-k0.3-10 cantilevers with spring constant of 0.3N nm−1, resonance frequency of about 300 kHz (Nanoworld), was employed for image acquisition. The AFM was operated in tapping mode with a cantilever oscillation frequency near to 150kHz. Both topographic and phase images were analysed using JPKSPM Data Processing, ImageJ, and WSxM software., Peer reviewed

The data and R codes that support the findings of the study Bricca et al. Biodiversity within and beyond the native distribution of Pinus nigra forests in Europe., Peer reviewed

A user-centred identifier enables verifiable and decentralized digital identity, and lead users to control and to generate their own identifiers using systems they trust. This is how Self-Sovereign Identity works. This paper presents the case of universities, where several different agents need their own identifier and shows a digital identity mathematical model for the academic context. Moreover, the Alastria model for the samecontext is detailed for a specific case of students’ mobility., This work was partially supported by Fundación Samuel Solórzano under grant no. FS/26-2020, and by the Spanish State Research Agency (AEI) of the Ministry of Science and Innovation (MICINN), project P2QProMeTe (PID2020-112586RB-I00/AEI/ 10.13039/501100011033)., Peer reviewed

Comprises 6 files: - ‘Figure S1_Bendou et al.docx’ comprises one single page: ‘Figure S1. Structure of the raw LEYQ data set and multivariate analyses applied to the data set using the ade4 package.’ - ‘TS1_TS5_Supplementary material_Bendou et al.xlsx’ comprises 5 sheets: ‘Table S1. Raw data set.’ ‘Table S2. Extreme outliers of the raw data set.’ ‘Table S3. Shapiro tests.’ ‘Table S4. Levene tests.’ ‘Table S5. Selection of tests (two-way, one-way Anova or T test) to be performed (if needed) according to the presence or absence of extreme outliers and the compliance with the assumptions of normal distribution and homocedasticity.’ -‘TS6_TS7_Supplementary material_Bendou et al.xlsx’ comprises 2 sheets: ‘Table S6. List of variables showing statistical significance after performing, firstly, two-way ANOVA and then one-way ANOVA or T test if there was no statistical significance for an interaction effect between factors.’ ‘Table S7. Summary of post-hoc tests.’ -‘TS8_TS10_Supplementary material_Bendou et al.xlsx’ comprises 3 sheets ‘Table S8. Dudi output elements of the BCA.’ ‘Table S9. Results of the BCA Monte-Carlo test (randtest in ade4).’ ‘Table S10. BCA column normed scores of the variables of the four meaningful blocks. -‘TS11_TS12_Supplementary material_Bendou et al.xlsx’ comprises 2 sheets ‘Table S11. Result of the COIA Monte-Carlo test (randtest in ade4).’ ‘Table S12. COIA loadings for the variables of the blocks of Yield and Quality.’ -‘TS13_TS15_Supplementary material_Bendou et al.xlsx’ comprises 3 sheets ‘Table S13. MBPLS regression using the grain yield as the dependent data block and flag leaves and ears as the explanatory blocks.’ ‘Table S14. Projection of the dependent variables on the LCs and loadings of the explanatory variables in the MBPLS regression.’ ‘Table S15. Determination of the cumulated variable importance index (vipc) to obtain the variables of the explanatory blocks (i.e., leaves and ears) that best explained the dependent block (i.e., grain yield) in the MBPLS regression., The effect of mild water deficit starting at the vegetative state on the physiological and biochemical response of wheat was investigated in a pot experiment. Wheat plants were grown in a controlled warming environment, in which the atmospheric CO2 concentration and temperatures were set to match those projected by the end of this century. Three wheat genotypes of different polyploidy level were selected: two bread (hexaploidy) genotypes named Gazul and HTWSN 41 respectively, and a durum (tetraploid) genotype named Regallo. The set of the potted plants of each genotype were split into two groups when they reached stage 14 within the decimal Zadoks growth scale. One was maintained under well water conditions, at field capacity, and another followed mild water deficit imposed at 65% of field capacity. At ear emergence, foliar pigments and leaf photosynthesis were measured. Additionally, flag leaves and ears from a subset of each group per genotype and water treatment were harvested to measure morphophysiological, water-related and biochemical traits. The remaining potted plants were left until maturity. The above- and belowground parts of the plants were harvested and the grains separated from the ears to quantify both yield- and quality-related traits. A total of 81 continuous measures were collected from the analyses performed on flag leaves and ears at ear emergence, and grains and total biomass at maturity. The variables were divided into four blocks named Leaf, Ear, Yield and Quality to performed supervised statistical multivariate analysis with the ade4 package. The statistical analysis of the results showed that three genotypes experienced reductions in leaf nitrogen balance and the number of productive tillers, though leaf photosynthesis and water use efficiency were rather stable. Ear water content and antioxidant status largely remained unchanged. Grain yield per plant decreased in the three genotypes, while grain yield per ear and grain biomass displayed reduced variability. Both leaves and ears equally contribute to grain yield. Under water deficit conditions, bread wheat genotypes showed a significant increase in nitrogen content, whereas Regallo maintained higher stable nitrogen content and better grain quality except for iron content. From a methodological viewpoint, the use of several functions maintaining the structure of an object of the subclass dudi (duality diagram) within the ade4 package open a new predictive statistical methodology in the screening of wheat with relevant organ and grain traits, This work was supported by Ministerio de Ciencia, Innovación y Universidades [grant numbers PID2019-107154RB-100 and PID2023-148311OB-I00, MICIU/AEI/10.13039/501100011033 and FEDER, UE] and the Junta de Castilla y León [grant number CSI260P20]. The Project ‘CLU-2019–05—IRNASA/CSIC Unit of Excellence’ funded by the Junta de Castilla y León and co-financed by the European Union (ERDF ‘Europe drives our growth’), the CSIC Interdisciplinary Thematic Platform (PTI) Optimization of Agricultural and Forestry Systems (PTI-AGRO4FOOD) and the CSIC scientific network WheatNet are also acknowledged., No

Data and Code for article "Combining hierarchical distribution models with dispersal simulations to predict the spread of invasive plant species", Peer reviewed