BUSCADOR RECOLECTA

Explanation note: table S1. Definitions of the response variables used to classify impact types on native species (i.e. individuals of the same taxon) and communities (i.e. individuals of several species at a site). table S2. Publication level information in PLANTIMPACTSEUROPE_publicationLevel. xlsx. The PLANTIMPACTSEUROPE database can be accessed at https://figshare.com/s/0a890d22bf5632fe5cb5. table S3. Invasive plant information and field studies testing for impacts in PLANTIMPACTSEUROPE_impactsDatabase. xlsx. The PLANTIMPACTSEUROPE database can be accessed at https://figshare.com/s/0a890d22bf5632fe5cb5. Storage location and medium: The PLANTIMPACTSEUROPE database can be accessed at https://figshare.com/s/0a890d22bf5632fe5cb5. (1) PLANTIMPACTSEUROPE_publicationLevel. xlsx: 266 publications with indication of countries, habitats and study locations, 312 entries (rows excluding the header), 8 columns, 59 KB. (2) PLANTIMPACTSEUROPE_impactsDatabase. xlsx: 4259 impacts (rows excluding the header), 16 columns, 348 KB., This dataset is made available under the Open Database License (http://opendatacommons.org/licenses/odbl/1.0/). The Open Database License (ODbL) is a license agreement intended to allow users to freely share, modify, and use this Dataset while maintaining this same freedom for others, provided that the original source and author(s) are credited., Peer reviewed

File List: Fig 1 F1b: Size histogram of Ba40Dy60 NPs F1c: EDX spectrum of Ba40Dy60 NPs F1e: Size histogram of Ba51Dy49 NPs F1f: F1c: EDX spectrum of Ba51Dy49 NPs Fig 2 F2: Experimental XRD patterns of Ba40Dy60 and Ba51Dy49 samples Fig 3 F3b: XRD patterns of the precipitates obtained in the conditions used for the synthesis of Ba51Dy49 NPs but using different aging times F3c: Unit cell parameters and Ba/(Ba+Dy) ratio of the precipitates versus aging time Fig 4 F4a: DLS intensity curves of the Ba51Dy49 NPs suspended in water after different periods of time at rest F4b: FTIR spectrum of the Ba51Dy49 NPs Fig 5 F5g: Total number of cells per well after exposure to increasing concentration of NPs F5h: Percentage of dead cells after exposure to increasing concentration of Ba51Dy49 NPs. F5i: MTT assay of cells exposed to increasing concentration of Ba51Dy49 NPs Fig 6 F6a: 1/T2 values obtained in aqueous suspensions of Ba51Dy49 NPs at 9.4 T and 1.44 T versus Dy concentration of the suspensions Fig 7 F7b: X-ray attenuation at 80 kVp, in Hounsfield Units (HU), of aqueous suspensions containing Ba51Dy49 NPs and Iohexol, versus suspension concentration. F7c: X-ray attenuation, in HU, of aqueous suspensions containing 20.0 mg·mL-1 of Ba51Dy49 and DyF3 NPs, versus working voltage, Bimodal medical imaging based on Magnetic Resonance Imaging (MRI) and Computed Tomography (CT) is a well-known strategy to increase diagnostic accuracy. The most recent advances in MRI and CT instrumentation are related to the use of ultrahigh magnetic fields (UHF-MRI) and different working voltages (spectral CT), respectively. Such advances require the parallel development of bimodal contrast agents (CAs) that are efficient under the new instrumental conditions. In this work, we have synthesized, through a precipitation reaction from a glycerol solution of the precursors, uniform barium dysprosium fluoride nanospheres with cubic fluorite structure, whose size was found to depend on the Ba/(Ba+Dy) ratio of the starting solution. Moreover, irrespective of the starting Ba/(Ba+Dy) ratio, the experimental Ba/(Ba+Dy) values were always lower than those used in the starting solutions. This result was assigned to a lower precipitation kinetics of barium fluoride compared to dysprosium fluoride, as inferred from the detailed analysis of the effect of reaction time on the chemical composition of the precipitates. A sample composed of 34 nm nanospheres with a Ba0.51Dy0.49F2.49 stoichiometry, showed a transversal relaxivity (r2) value of 147.11 mM-1·s-1 at 9.4 T and gave a high negative contrast in the phantom image. Likewise, it produced high X-ray attenuation in a large range of working voltages (from 80 KVp to 140 KVp), which can be attributed to the presence of different K-edge values, high Z elements (Ba and Dy) in the nanospheres. Finally, these nanospheres showed negligible cytotoxicity for different biocompatibility tests. Taken together, these results show that the reported nanoparticles (NPs) are excellent candidates as UHF MRI/Spectral CT bimodal imaging CAs., This publication is part of the I + D + I Grants PID2021-122328OB-I00 and PID2020-118448RB-C21 funded by MCIN/AEI/10.13039/501100011033 and by “ERDF A way of making Europe”. This work was supported as well by Junta de Andalucía under grant no. P20_00182, co-financed by EU FEDER funds. High-field relaxivity measurements were performed at the ICTS “NANBIOSIS”, specifically in Unit 28 at the “Instituto de Investigación Biomédica de Málaga y Plataforma en Nanomedicina (IBIMA Plataforma BIONAND)”., Peer reviewed

The excel file includes different spreadsheet including, first, every stalagmite (age model, d18O and d13C, Mg/Ca and other trace elements when available) and, second, every composite record produced by ISCAM. The word document is the U-Th table with all the dates used in constructing the age models. This dataset corresponds to our manuscript published as a preprint in Climate of the Past: https://cp.copernicus.org/preprints/cp-2023-54/, Peer reviewed

Contents: S1 Geographical description of the German Part of the Elbe River basin – S1.-- S2 Drought indices – S9.-- S3 Aspects of the socio-economic drought impacts – S13.-- References, Peer reviewed

Table S1. Statistics of the co-registration statistics between the external DEMs and the ICESat-2 snow-off DEM.-- Table S2. Statistics of the snow depth residuals for different snow-off Digital Elevation Models (DEMs) on 12 March 2019. The ICESat-2-ASO product is shown in detail on Figure 3. All residuals are shown in Figure 5 and S4.-- Table S3. Statistics of the co-registration statistics between the Pléiades and Copernicus DEMs to the ASO DEM at15 m. All these DEMs were previously co-registered to the ICESat-2 snow-off points.-- Figure S1. Map of the mean annual snow cover duration in the upper Tuolumne basin calculated from a time series of MODIS images (MOD10A1).-- Figure S2. Optimization of the kappa index to determine the photon count threshold defining snow-on and snow-off points based on MODIS snow cover area data.-- Figure S3. Vertical uncertainty of the ATL06 elevation (sigma_h_mean) against along-track slope (dh_fit_dx). The along-track slope (dh_fit_dx) is directly provided in ATL06.-- Figure S4. Same figure as Figure 5 but with snow depth derived from ICESat-2 and the ASO DEM (green, identical to Fig. 5) and ICESat-2 and the Copernicus DEM (purple). Note the different y-scale compared to Figure 5.-- Figure S5. Same as Figure 5 but selecting ICESat-2 ATL06 snow-on points of the strong beams only.-- Figure S6. Same as Figure 5 but selecting ICESat-2 ATL06 snow-on points of the weak beams only.-- Figure S7. Same as Figure 5 but calculating the relative snow depth error (ICESat-2 derived snow depth minus ASO snow depth divided by ASO snow depth) rather than the absolute snow depth error (ICESat-2 derived snow depth minus ASO snow depth).-- Figure S8. Distribution of the snow-off residual (ICESat-2 minus DEM) before (black line) and after coregistration (color) for the ASO DTM (left), the Pléiades DEM (middle) and the Copernicus DEM (right). The vertical lines show the median plus/minus the NMAD after coregistration.-- Figure S9. Snow depth (colored boxes) and snow-off (white boxes) residuals for ICESat-2 – ASO (left) and ICESat-2 – Pléiades (right). Transparent boxplots show the data where less than 100 points were available.-- Figure S10. Elevation difference of the snow-off DEMs, the difference between the Copernicus 30 DEM and the ASO DEM (a) and the Pléiades DEM and the ASO DEM (b). All DEMs were individually co-registered on the ICESat-2 snow-off points. © Author(s) 2023. CC BY 4.0 License. The copyright of individual parts of the supplement might differ from the article licence., Peer reviewed

This PDF file includes: Supplementary Fig. 1 to 5 and Supplementary Table 1., Peer reviewed

2. Experimental runs An exemplary for an entire isothermal experiment is given in Fig. 2. It shows the initial conditioning, consisting of ten redox cycles, followed by the actual experiment, consisting of seven isothermal plateaus. These isothermal plateaus each consist of four redox cylces employing the following H2 volume fractions: 50, 50, 30, 16.66 vol%. The 50 vol% run was repeated to possibly detect inconsistencies introduced through the preceding temperature change. Between reduction and oxidation or when changing from one temperature to another, the system was purged with nitrogen. 3. Reproducibility In order to reach the kinetic regime small sample masses (< 2 mg) and high gas flow rates (> 300 ml · min−1) were required. The reproducibility of the measurements was assessed at these conditions. All isothermal runs were repeated six times, all on different days using fresh solid samples and the same TGA programs. Fig. 3 shows the conversion rate dX/dt. for the individual runs during reduction at T = 900 ◦C. Even though, there were noticeable deviations between individual sets, the overall reproducibility of results was convenient. 4. Gas conversion The hydrogen conversion XH2 during the TGA experiments was estimated to ensure sufficient gas supply and negligible impact of steam produced. Low gas conversion signifies that enough gas was present and the atmosphere did not change significantly during the experiments. The mass balance ˙V | in · ci{nz· yH2,i}n n˙ H2,in − (m0 − m∞) MO · (dX/dt)max = ˙V| out · cou{tz· yH2,ou}t n˙ H2,out (1) was used calculate the molar flow n˙ H2,out of unreacted H2 leaving the reactor at maximum reactivity. This gives the highest possible gas conversion for a specific case, i.e. the worst case scenario for reaching the kinetic regime. The n˙ H2,out was used to calculate the conversion XH2 = n˙ H2,in − n˙ H2,out n˙ H2 in at different temperatures and H2 contents. The results are summarized in Table 1. As can be seen, the hydrogen conversion XH2 was low (< 2 %) for all cases, which means that neither gas starvation nor limitations due to steam generation should have played a significant role. 5. Isoconversional methods The additional plots for the isoconversional methods (i.e. evaluation of linear regression and R2) which were referenced in our main work are given in this section. Figure 4 shows the differential isoconversional method for one exemplary experiment with higher mass at 50 vol%H2. Except for the first point (X=0.1) a reasonably high R2 was again achieved. Figure 5 depicts the analysis of the nonisothermal reductions with the differential isoconversional method. Figure 6 shows the results for the integral isoconversional KAS method [1]. For both methods high R2 values were achieved.-- Under a Creative Commons license CC-BY 4.0 Deed., 1. TGA setup.-- 2. Experimental runs.-- 3. Reproducibility.-- 4. Gas conversion.-- 5. Isoconversional methods.-- 6. CFD study.-- 1. TGA setup: A schematic of the experimental setup is given in Fig. 1. The TGA experiments were performed with a NETZSCH STA 449 F3 Jupiter. It consisted of an inner reactor and an outer shell, both made of Al2O3. Different sample holders (crucible, plate, basket) could be mounted on top of a vertical sample carrier at the center of the inner reactor. If not stated differently, the experiments were conducted with the plate (NETZSCH alumina slipon plate, diameter 17 mm). The solid sample was placed on this sample holder. A type S thermocouple within the vertical sample carrier was used for temperature measurements. It had been calibrated with calcium oxalate and pure metal melting points (In, Sn, Bi, Zn, Al, Ag) prior to the experiments. Two different gas flows were relevant in the TGA setup. Firstly, a protective gas flow (20 ml · min−1 N2), which was always switched on, entered the reactor below the sample carrier. Secondly, the main gas flow (H2, O2, N2 and mixtures thereof) entered a water vapor generator, where a predefined mass flow of H2O could be added. The gas mixture was preheated to 180 ◦C and then entered the TGA system from the side. It was heated to the desired temperature during the upwards flow in the outer shell. After reaching the top of the reactor, the gases flowed downwards into the inner reaction chamber, which contained the solid sample, before leaving the reactor via the gas outlet. Both, the main and protective gas flows, were controlled by Bronkhorst mass flow controllers (MFC, 0-250 ml · min−1). 6. CFD study A small, transient CFD study of the TGA was conducted to gauge the temporal evolution of the hydrogen concentration above the solid sample. The TGA geometry of Fig. 1 was simplified (mostly at the inlet and the outlet). Simulations were performed in ANSYS Fluent 2023 R1 using the lamiar flow model and a fixed hydrogen diffusivity of 5·10−4 m2 · s−1. Heat transfer was considered via conduction, convection and radiation (Discrete Ordinate model). A homogeneous velocity distribution was assumed at the inlet (T = 200 ◦C, yH2 = 0.5). The heating was simulated via isothermal walls (T = 800 ◦C) which quickly heated the gases to the operating temperature. At the outlet, a simple pressure outlet condition was chosen. The discretization methods for momentum, mass and heat transfer were set to second order (only Discrete Ordinate was first order), and a first order implicit time solver (time step of 0.1 s) was chosen. Fig. 7 (a) shows the simplified TGA model, Fig. 7 (b) shows the velocity profile in steadystate and Fig. 7 (c) shows the H2 concentration profile at t = 7 s for one exemplary case. As can be seen, the flow around the plate leads to nearly zero velocity at the sample, which could possibly lead to diffusion limitations. More importantly, Fig. 7 (c) suggests an appreciable spatial gradient of hydrogen due to axial dispersion. The temporal evolution of the hydrogen concentration above the plate was given in our main work., Peer reviewed

PDF file contains: Suplemmentary Figures S1-S11 and Suplemmentary Tables S1-S2. © Author(s) 2023. CC BY 4.0 License. The copyright of individual parts of the supplement might differ from the article licence., Peer reviewed

Peer reviewed

SedDARE-IB (Sediment Data REpository of IBeria and its continental margins) is an open access database that stores available data available data of the depth to the Base Cenozoic and Top Paleozoic stratigraphic markers. SedDARE-IB include data on onshore basins of the Iberian Peninsula (Ebro, Duero, Tajo and Gualdalquivir basins), the Lusitanian and Lower Tagus basins, and many other small basins. Offshore, SedDARE-IB comprises sedimentary data from the Atlantic Margin (Alentejo, Peniche, Northern Lusitanian Basin and deep offshore depocentres), the Gulf of Cadiz region (Algarve Basin and its surroundings) and the base of the Cenozoic marker for the Western Mediterranean Neogene basins, e.g., Valencia Trough and Alboran Basin, also comprising the acoustic basement for the rest of the Western Mediterranean region. By following the FAIR (Findable, Accessible, Interoperable and Reusable) principles of data management and having regular updates, it brings endless research and teaching opportunities to the scientific, industrial and educational communities., Sediments provide valuable information for geologists and geophysicists whenever they strive to understand, and reproduce, the geological evolution, lithology, rock properties, seismic response, and geohazards of a region. The analysis of sedimentary sequences is thus useful to the interpretation of depositional environments, sea-level change, climate change, and to a recognition of the sediments’ source areas, amongst other aspects. By integrating sedimentary data in geophysical modelling, such interpretations are improved in terms of their accuracy and reliability. To help our further understanding of Iberia’s geological evolution, geological resources and geohazards, this work presents to the scientific community the SedDARE-IB data repository. SedDARE-IB includes data on onshore basins as varied as the foreland basins of the Pyrenean-Cantabrian (Ebro and Duero basins) and Betic Cordillera (Guadalquivir Basin), the Lusitanian and Lower Tagus basins, and many other small basins. Offshore, SedDARE-IB comprises sedimentary data from the Atlantic Margin (Alentejo, Peniche, Northern Lusitanian Basin and deep offshore depocentres), the Gulf of Cadiz region (Algarve Basin and its surroundings) and the base of the Cenozoic marker for the Western Mediterranean Neogene basins, e.g., Valencia Trough and Alboran Basin, also comprising the acoustic basement for the rest of the Western Mediterranean region. SedDARE-IB database has been built thanks to a Portuguese-Spanish collaboration promoting open data exchange among institutions and research groups., This research has been partly supported by the project funded by the Spanish Government GeoCAM (PID2022-139943NB-I00) and GEOADRIA (PID2022-139943NB-I00). The onshore Iberia data sets were compiled under the umbrella of the ALGECO2 project (IGME-CSIC). The Lower Tagus Basin and Alentejo datasets were prepared by JC under the scope of an academic thesis and updated during projects (SISMOD/LISMOT and NEFITAG), financed by the Portuguese Foundation for Science and Technology. AMGG received a grant (FJC2021-047434-I) funded by MICIU/AEI /10.13039/501100011033 and by “European Union NextGenerationEU/PRTR”., SedDARE-IB_Readme.txt; TA_Basement_IAM_Part1_WGS84.xyz; TA_Basement_IAM_Part2_WGS84.xyz; TA_Basement_ISE_Off_Portugal_WGS84.xyz; TA_Basement_Peniche_Basin_WGS84.xyz; Top_Basement_N_LusitaniaB_WGS84.xyz; TA_Basement_Lines_Off_Lisbon_WGS84.xyz; Top_Basement_Lines_Off_SPortugal_WGS84.xyz; Top_Basement_Alentejo_and_Algarve_WGS84.xyz; Top_Basement_Lower_Tagus_Basin_WGS84.xyz; Top_Paleozoic_Basement_Onshore_IB_Basins_ETRS89.xyz; Top_Basement_WestMed_Basins_WGS84.xyz ; TA_Base_Cenozoic_IAM_Part1_WGS84.xyz; TA_Base_Cenozoic_IAM_Part2_WGS84.xyz; TA_Base_Cenozoic_ISE_Off_Portugal_WGS84.xyz; TA_Base_Cenozoic_Peniche_WGS84.xyz; Base_Cenozoic_N_LusitaniaB_WGS84.xyz; TA_Base_Cenozoic_Lines_Off_Lisbon_WGS84.xyz; Base_Cenozoic_Lines_Off_SPortugal_WGS84.xyz; Base_Cenozoic_Alentejo_Algarve_basins_Part1_WGS84.xyz; Base_Cenozoic_Alentejo_Algarve_basins_Part2_WGS84.xyz; Base_Cenozoic_Lower_Tagus_Basin_WGS84.xyz; Base_Cenozoic_Ebro_Basin_ETRS89.xyz; Base_Cenozoic_Duero_Basin_ETRS89.xyz; Base_Cenozoic_Tajo_Basin_ETRS89.xyz; Base_Cenozoic_Guadalquivir_Basin_ETRS89.xyz; Base_Cenozoic_Mallorca_Island_ETRS89.xyz; Base_Cenozoic_Valencia_Trough_WGS84.xyz; Base_Cenozoic_Alboran_Basin_WGS84.xyz; Algarve_PaleogeneUnc_TopUpperK_cokriginig_WGS84.xyz, Peer reviewed