BUSCADOR RECOLECTA

Level-3 daily merged Copernicus-GlobColour multi-sensor Remote Sensing Reflectance (Rrs(λ)) from the Copernicus Marine Environmental Monitoring Service (CMEMS) is used as data source. The aCDOM(443) was estimated using the gsmA parametrizations for the southern Beaufort Sea (Matsuoka et al., 2013) with some modifications; while DOC was retrieved using an empirical aCDOM(443)-DOC relationship developed by Juhls et al. (2022), valid across the fluvial-marine transition zone of the Mackenzie River–Beaufort Sea region, Level-4 daily maps of aCDOM(443) and DOC for the Mackenzie River-Beaufort Sea region (122-142ºW and 68-73ºN) are distributed in the regular latitude–longitude grid at a spatial resolution of 4 km. The data is available from 1st January 2002 to 31st October 2023. Additionally, 8-day means, and monthly mean data are also provided. The dataset consists of four variables: (i) Chromophoric Dissolved Organic Matter at 443 nm (aCDOM(443) [m-1]) (ii) Dissolved Organic Carbon (DOC [µM]) (iii) water type mask (coastal/oceanic) (iv) model relative error for Rrs(443) (∆Rrs(443) [%]) (v) aCDOM(443) uncertainty (σaCDOM [m-1]) (vi) DOC uncertainty (σDOC [µM]), YYYYMMDD_aCDOM443_DOC_l4_4km_P1D.nc (This dataset contains daily Level-4 aCDOM and DOC product from satellite observations for the Mackenzie River-Beaufort Sea region) YYYYMMDD_YYYYMMDD_aCDOM443_DOC_l4_4km_P8D.nc (This dataset contains daily Level-4 aCDOM and DOC product from satellite observations for the Mackenzie River-Beaufort Sea region) YYYYMMDD_YYYYMMDD_aCDOM443_DOC_l4_4km_P1M.nc (This dataset contains monthly Level-4 aCDOM and DOC product from satellite observations for the Mackenzie River-Beaufort Sea region), In the regime-shifting Arctic, organic carbon export from river watersheds is expected to increase due to changes in hydrological regimes and permafrost thawing. Given the impact these changes have on the biogeochemical cycles of coastal and shelf areas, robust monitoring of major Arctic rivers is needed. During ice-free season, ocean color remote sensing has shown to be an effective monitoring tool for remote, under-sampled areas with limited access such as the Beaufort Sea region. It offers synoptic spatio-temporal coverage, filling in the gaps among the scarce in situ data and improving our knowledge of land-to-ocean transport pathways and coastal ocean dynamics near riverine zones. Remote sensing of Chromophoric Dissolved Organic Matter (CDOM) and Dissolved Organic Carbon (DOC) has proven to be a valuable approach for assessing variations in terrestrial carbon export. However, seasonal fluctuations and diverse vegetation and soil conditions of each river watershed make it difficult to establish a single retrieval method for the entire Arctic. This complexity has led to a development of several regional algorithms, yet accessible long-term series remain a challenge. We present the first long-term satellite-derived dataset quantifying the absorption coefficient of CDOM at 443 nm and DOC concentrations in the Mackenzie River–Beaufort Sea region (122–142ºW and 68–73ºN) from 1st January 1998 to 31st October 2023. We employed a modified version of the GIOP (Generalized Inherent Optical Properties) algorithm to retrieve CDOM(443) for the southern Beaufort Sea; DOC was then derived using a region-specific relationship between aCDOM(443) and DOC. The product has been validated using in situ observations from several field campaigns conducted in the area. We provide a consistent dataset that can be used to assess DOM spatial and temporal variability, trends, and export to the coastal seas, This work has been carried out as part of the ARCTIC-MON project (Advances in monitoring sea ice thickness and snow depth, ocean dynamics, and freshwater content in the Arctic using remote sensing data), funded through the Consejo Superior de Investigaciones Científicas (CSIC) (grant no. PID2021-125324OB-I00), With the institutional support of the ‘Severo Ochoa Centre of Excellence’ accreditation (CEX2019-000928-S), Level-4 daily maps of aCDOM(443) and DOC for the Mackenzie River-Beaufort Sea region (122-142ºW and 68-73ºN) are distributed in the regular latitude–longitude grid at a spatial resolution of 4 km. The data is available from 1st January 2002 to 31st October 2023. Additionally, 8-day means, and monthly mean data are also provided. The dataset consists of four variables: (i) Chromophoric Dissolved Organic Matter at 443 nm (aCDOM(443) [m-1]) (ii) Dissolved Organic Carbon (DOC [µM]) (iii) water type mask (coastal/oceanic) (iv) model relative error for Rrs(443) (∆Rrs(443) [%]) (v) aCDOM(443) uncertainty (σaCDOM [m-1]) (vi) DOC uncertainty (σDOC [µM]), Peer reviewed

S1 Appendix. PRISMA figure depicting the flow of documents obtained for each of the steps in the literature review in the database SCOPUS., S1 Data. Excel spreadsheet including, in separate sheets, all numerical values used for Figs 1, 2, 3, 4 and S1., S1 Fig. Regional distribution of autochthonous Leishmania infantum infections in humans and/or animals in European countries reported in the scientific literature and by the ministries of health of some countries, between 2009 and 2020., S1 Table. Number and cumulative incidence per 100,000 population of cutaneous and visceral leishmaniasis in European countries between 2005 and 2020 as reported in the WHO-GHOD., S2 Table. Geographical references of reported autochthonous symptomatic and asymptomatic infections by Leishmania infantum in animals and/or humans in European countries, between 2009 and 2020., Peer reviewed

Here you can find the SPSS data used for the manuscript titled "The role of implicit theories about climate change malleability in the prediction of pro-environmental behavioral intentions" accepted on 2022, June, in The Environment, Development and Sustainability. In this research, we analyze how the sense of responsibility toward climate change and implicit theories about climate change (ITCC) interact to condition individual pro-environmental intention in a pretest–posttest experiment., Peer reviewed

Monitoring compliance with environmental laws is essential to overcoming possible implementation shortfalls jeopardizing their effectiveness. Besides improving our ecological understanding of wildlife, remote tracking technologies also allow us to take advantage of such ecological knowledge to use wildlife as sentinels of compliance with law. We illustrate this sentinel potential of wildlife using GPS-tracking of large scavengers with complementary functional traits (i.e., 21 griffon vultures and 13 wolves) to assess compliance with EU sanitary regulations allowing livestock carcass disposal in the field. Wildlife sentinels allowed the systematic evaluation of 489 livestock carcasses left in the field, which revealed an important mismatch between on-paper and in-reality implementation of these regulations. While <45 % of the carcasses were placed in authorized areas, compliance with all the criteria required by the regulations on livestock carcass disposal (e.g., from carcass characteristics such as species, age, or production system to its location far away from water, buildings, or roads) ranged from 0 to 4.2%, with no major differences between regions with uneven implementation. Major gaps in compliance pointed towards insufficient and over-bureaucratized designation of Scavenger Feeding Zones (SFZs), where livestock carcass disposal is authorized. The indiscriminate nature of distance criteria from carcasses to watercourses, buildings, and infrastructure further affected compliance. Synthesis and applications: GPS-tagged scavengers allow the on-ground monitoring of carcasses, the addressing of potential risks for wildlife, livestock, and human health, the quantitative assessment of compliance with the law and would improve estimates of carcass availability, substantially contributing to more effective legislation enforcement. Our results show the huge potential of GPS-tagged wildlife as sentinels for monitoring compliance to enhance the environmental rule of law., Ministry of Economy, Industry and Competitiveness. Fundación BBVA. Gobierno del Principado de Asturias. Ministerio de Ciencia e Innovación. Fundación Biodiversidad. Ministério do Ambiente e da Ação Climática, Peer reviewed

Peer reviewed

Tabla Suplementaria 1. Detalles de las organizaciones contactadas y la información proporcionada., Peer reviewed

Table S1. Formulation of four margarines (M1–M4) containing olive pomace oil (OPO) and cooling rate used for each one. Table S2. Fatty acid (FA) profile corresponding to olive pomace oil (OPO), palm stearin (PS), a puff pastry (PP) commercial butter (CB), a PP commercial fatty preparation (CFP) and two margarines containing OPO (M1 and M3). Figure S1. Stress sweeps carried out at 1 Hz and at 20 °C of a puff pastry (PP) commercial butter (CB), a PP commercial fatty preparation (CFP) and four margarines (M1–M4) containing olive pomace oil (OPO). Shear stress (σ) ranged between 20 and 2000 Pa. G′, elastic modulus; G″, viscous modulus. Figure S2. Frequency sweeps carried out at 1 Hz and at 20 °C to determine the mechanical spectra of a puff pastry (PP) commercial butter (CB), a PP commercial fatty preparation (CFP) and four margarines (M1–M4) containing olive pomace oil (OPO). G′, elastic modulus; G″, viscous modulus. Figure S3. Force–distance curves from a penetration test at 20 °C of a puff pastry (PP) commercial butter (CB), a PP commercial fatty preparation (CFP) and four margarines (M1–M4) containing olive pomace oil (OPO). Figure S4. Force–time curves from a texture analysis profile (TPA) test of a puff pastry (PP) made with a commercial butter (PP-CB), a PP made with a commercial fatty preparation (PP-CFP) and PP prepared with four margarines (PP-M1/PP-M4) containing olive pomace oil (OPO). Figure S5. Force–distance curves from a cutting test of a puff pastry (PP) made with a commercial butter (PP-CB), a PP made with a commercial fatty preparation (PP-CFP) and PP prepared with four margarines (PP-M1/PP-M4) containing olive pomace oil (OPO)., Peer reviewed

1H NMR and 13C NMR spectra of perlolyrine (Table S1 and Figure S1) and HPLC and HPLC-MS chromatograms (Figures S2–S5)., Peer reviewed

Table S1: Nutritional composition of the red berries mixture, Table S2: Nutritional composition of cacao powder, Table S3: Demographics and characteristics of the participants at enrollment in each group, Table S4: Blood pressure and heart rate values in each group and by visit, Table S5: p-value from the comparison between diets at the baseline., Peer reviewed

[EN] Three files in .csv format ('Infogeo_Spain10.csv', 'MOTEDAScentury_TMAX_1916-2015.csv' and 'MOTEDAScentury_TMIN_1916-2015.csv'). The first one contains the metadata of the grid points, the first column is the ID (Point), the second is the latitude (lon), the third is the latitude (lat) and the fourth is the elevation of the point with respect to the sea level (alt.). In the second and third file the climatic information is collected, in both, the first column is the ID (Point), in the second column the year to which the data refer (Year), the following 12 columns show the monthly temperatures (maximum and minimum daily respectively) from January to December (Jan to Dec), in the next 4 columns the seasonal averages (Win to Aut) and in the last one the annual average (Ann); all of them expressed in 1/10 Celsius degrees. [ES] Tres archivos en formato .csv ('Infogeo_Spain10.csv', 'MOTEDAScentury_TMAX_1916-2015.csv' y 'MOTEDAScentury_TMIN_1916-2015.csv'). El primero de ellos contiene los metadatos de los puntos del grid, la primera columna es el ID (Point), la segunda es la latitud (lon), la tercera es la latitud (lat) y la cuarta es la elevación del punto respecto al nivel del mar (alt.). En el segundo y tercer archivo queda recogida la información climática, en ambos, la primera columna queda recogido el ID (Point), en la segunda el año al que van referidos los datos (Year), las 12 columnas siguientes se muestran las temperaturas mensuales (máximas y mínimas diarias respectivamente) de enero a diciembre (Jan a Dec), en las 4 columnas siguientes se muestran los promedios estacionales (Win a Aut) y en la última el promedio anual (Ann); expresadas todas ellas en 1/10 grados Celsius., [EN] A monthly temperature (mean daily maximum and minimum) gridded data set over mainland Spain between December 1915 and December 2015. The dataset combines ground observations from the National Climate Data Bank (NCDB) of the Spanish national climate and weather service (AEMET) and new data rescued from meteorological yearbooks published prior to 1951 that was never incorporated into the NCDB. The yearbooks data represented a significant improvement of the dataset, as it almost doubled the number of weather stations available during the first decades of the 20th century. The final dataset contains records from 5,259 stations. The station data were interpolated on a 0.1° × 0.1° regular grid using the angular distance weighting (ADW) method., [ES] Conjunto de datos en rejilla de temperatura mensual (promedio de los valores máximos y mínimos diarios) en la España peninsular entre diciembre de 1915 y diciembre de 2015. El conjunto de datos utilizado combina observaciones del Banco Nacional de Datos de AEMET y nuevos datos rescatados de los anuarios climáticos publicados con anterioridad a 1951, y que casi duplican la información existente sobre la primera mitad del siglo 20. El conjunto final contiene información de un total de 5.259 observatorios. Las observaciones se interpolaron a una rejilla regular de 0.1° × 0.1° mediante mediante el método de ponderación inversa a la distancia angular (ADW)., Project CGL2017-83866-C3-3-R (CLICES: Climate of the last Century in the Spanish mainland), funded by the Spanish Ministry of Science., Infofile, grid., No