Resultados de investigación

[Description of methods used for collection/generation of data] Raw data about damages produced by wildlife in Spain was requested to the different Administrations involved by different means (by mail, by official letter, by transparency portal) between January 2022 and December 2023, [Methods for processing the data] Obtained data from the different Administrations was processed and standardized individually and presented in a single dataset., Human population and anthropogenic pressures on Earth´s ecosystems are growing in unprecedented numbers, promoting an increase of animal-human interactions that may have negative effects for both wildlife and humans. Among all types of animal-human interactions, animal-caused damages to human properties and activities (i.e. livestock depredation, crop riding, etc.) are especially relevant, frequently leading to the emergence of human-wildlife conflicts that may additionally jeopardize conservation efforts. In this context, gathering accurate information about damages caused by animals is essential to minimize these conflicts. In Spain, most information about animal-caused damages to human properties and activities is gathered by different regional Administrations (i.e. Comunidades Autónomas), implying that data are generally scattered, fragmented and highly heterogeneous, hindering the implementation of effective and adaptive management strategies aiming at reducing these conflicts. Here we present a unique dataset in which we gathered all the information available about individual damages produced by animals to human activities and properties. Data were collected from different Administrations and subsequently standardized and unified in a single database. This dataset is a valuable resource not only because it will allow a deep characterization of the casuistry of animal-caused damages to human properties and activities in Spain but also because we believe that it provides a good example of which variables must be collected by the different Administrations responsible of collecting these data., This work was funded by the Spanish Ministry of Science and Innovation through the SUMHAL project (LIFEWATCH2019-09-CSIC-13). A.G.-R. was additionally funded by the EU-NextGenerationEU funds through the 2021–2023 Margarita Salas call for the requalification of the Spanish university system, convened by the Universidad de León., Peer reviewed

This dataset corresponds to the model made from the EGS project of Basel (2006, Switzerland). The model is solving coupled hydromechanical problem for 2D fault network on a surface of 1 km2, located at 4630-meters depth coinciding with the injection depth in the crystalline basement at Basel. A set of faults are embedded in a rock matrix, with the fault network derived from the induced seismicity that was monitored in the range of 3750 and 4750 meters deep. The maximum principal stress S_Hmax is aligned with y-axis (S_Hmax=160 MPa, S_hmin=84 MPa, S_v=115 MPa). The hydrostatic pressure is set at 45 MPa following a hydrostatic profile and the temperature at the depth of the reservoir is set at 190°C. Stimulation parameters are inputs as wellhead pressure based on the injection strategy from Häring et al. (2008), injection fluid is water. - “ .gid” is the Code_Bright file with the model of Basel. The file “_gen.dat” contains the input data of the model (including material properties, initial and boundary conditions and the time intervals). The file “_gri.dat” includes the information on the mesh. The “root.dat” includes the name of the model. To run simulations, execute the Code_Bright executable “Cb_2020_21.exe” in a folder that contains the three input files and the executable, where X and Y denote the used version of the executable. • V13_C_NW_longbleed.gid corresponds to the model in which the bleed-off of the well is imposed. • V13_C_NW_shutin.gid corresponds to the model in which the injection well is shut-in., Horizon 2020 Research and Innovation Program through the ‎Starting Grant ‎GEoREST under Grant agreement No. 801809, - V13_c_NW_longbleed.gid - V13_c_NW_shutin.gid - Readme.docx, Peer reviewed

Supplemental material is available online only. Supplemental file 3 Tables S1-S3; Figures S1-S3. Download spectrum.00823-23-s0001.docx, DOCX file, 1.1 MB Supplemental file 1 Data Set S1. Download spectrum.00823-23-s0002.xlsx, XLSX file, 0.2 MB Supplemental file 2 Data Set S2. Download spectrum.00823-23-s0003.xlsx, XLSX file, 0.1 MB, Peer reviewed

Documento en Word - 6 páginas, 5 figuras, Peer reviewed

The data is a compilation of information from previous studies and during the study published in “ Seasonal and isotopic precipitation patterns in the Andes of NW Argentina., [Description of methods used for collection/generation of data] In the study area, we employed a DAVIS-type weather station located south of the lagoon at coordinates 22° 28' 24.00"S and 65° 59' 35.00" W, with an elevation of 3,675 m a.s.l. (Figure 1). This weather station records hourly air temperature (⁰C), precipitation (mm), relative humidity (%), wind speed (m/s), solar radiation (W/m2), and other meteorological parameters. The management of this meteorological information falls under the Biodiversity Information System of the National Parks Administration (https://sib.gob.ar/#!/area-protegida/monumento-natural-laguna-de-los-pozuelos). Additionally, we considered essential climate data, including: (1) The daily mean (non-interpolated) Outgoing Longwave Radiation (OLR) Climate Data Record (CDR), which measures the amount of terrestrial radiation released into space and, by extension, the amount of cloud cover and water vapor intercepting that radiation in the atmosphere. The data has a resolution of 2.5° × 2.5°, with units in W/m2 (“NOAA Daily (non-interpolated) Outgoing Longwave Radiation (OLR),” 2023); and (2) the Convective Precipitation Rate (CPR) from NCEP-DOE AMIP-II Reanalysis (R-2). The NCEP-DOE Reanalysis 2 project utilizes a state-of-the-art analysis/forecast system for data assimilation from 1979 through the near present. The data has a resolution of 2.5° × 2.5°, with units in Kg/m2/s (Kanamitsu et al., 2002). The average of the monthly CPR values for each month in which rain was collected was calculated using ARCGIS software. Specifically, the monthly CPR values were averaged for February in the years 2020, 2021, 2022, and 2023. OLR and CPR data were provided by the NOAA PSL in Boulder, Colorado, USA, and can be accessed on their website at https://psl.noaa.gov., This study reports precipitation samples covering a 3-year period (January 2020 to April 2023) with extensive monitoring of meteorological parameters in the local atmosphere, satellite imagery and HYSPLIT backward trajectory models humid air masses causing the sampled reception in the Los Pozuelos basin in NW Argentina., Peer reviewed

Multimedia component 1., Peer reviewed

Products obtained from the publication "Climate and human stressors on global penguin hotspots: current assessments for future conservation". It contains the hotspots produced for the diferent penguin species and the layers of the diferent threats, With the institutional support of the ‘Severo Ochoa Centre of Excellence’ accreditation (CEX2019-000928-S), Peer reviewed

4 pages. -- Supplementary Figure 1: Schematics of the scattering set up employed in the HRBS experiments. -- Supplementary Figure 2: Check of the possible angular dependence of the Brillouin peak. -- Supplementary Figure 3: Raw specific heat data before statistical averaging, using two different cryostats., Peer reviewed

13 pages. -- Supplementary Figs. 1–7, experimental methods and theoretical methods., Peer reviewed

No