BUSCADOR RECOLECTA

[EN] Contains five compressed folders (.zip): one with shapefiles (.shp; requires a specific Geographic Information System GIS software) and four data tables in plain text (.csv). One PDF file explains the dataset details., [ES] Contiene cinco carpetas comprimidas (.zip): uno con shapefiles (.shp; requiere software específico para Sistemas de Información Geográfica, SIG) y cuatro tablas de datos en texto plano (.csv). Un archivo PDF explica el contenido del conjunto de datos., [EN] Geospatial information on the water balance components over the Pyrenees under climate change, covering the period 1981-2100. The data is based on the application of two hydrological models (SWAT and SASER), forced with the climate projections in the PIRAGUA_atmos_climate dataset. It includes information on the following variables: temperature, precipitation, snowfall, snowmelt, potential evapotranspiration, actual evapotranspiration, soil water storage, snowpack, aquifer recharge, and runoff generation. The temporal resolution is monthly, and the spatial aggregation is at the level of hydrographic sub-basins. The dataset was generated within the project EFA210/16 PIRAGUA Project ("Evaluation and prospective of the water resources of the Pyrenees in a context of climate change, and adaptation measures with impact on the territory")., [ES] Información geoespacial sobre componentes del balance hídrico sobre los Pirineos en condiciones de cambio climático, para el periodo 1981-2100. Los datos se basan en la aplicación de dos modelos hidrológicos (SWAT y SASER), forzados con las proyecciones climáticas del conjunto de datos PIRAGUA_atmos_climate. Incluye información sobre las siguientes variables: temperatura, precipitación, innivación, fusión nival, evapotranspiración potencial, evapotranspiración real, almacenamiendo de agua en el suelo, paquete de nieve, recarga de acuífero, y generación de escorrentía. La resolución temporal es mensual, y la agregación espacial es a nivel de sub-cuencas hidrográficas. El conjunto de datos fue generado en el contexto del proyecto EFA210/16 PIRAGUA ("Evaluación y prospectiva de los recursos hídricos de los Pirineos en un contexto de cambio climático, y medidas de adaptación con impacto en el territorio")., [FR] Information géospatiale sur les composantes du bilan hydrique des Pyrénées dans des conditions de changement climatique, pour la période 1981-2100. Les données sont basées sur l'application de deux modèles hydrologiques (SWAT et SASER), forcés avec les projections climatiques du jeu de données PIRAGUAatmosclimate. Il comprend des informations sur les variables suivantes : température, précipitations, chutes de neige, fonte des neiges, évapotranspiration potentielle, évapotranspiration réelle, stockage de l'eau dans le sol, manteau neigeux, recharge de l'aquifère et génération de ruissellement. La résolution temporelle est mensuelle, et l'agrégation spatiale se fait au niveau des sous-bassins hydrographiques. Le jeu de données a été généré dans le cadre du projet EFA210/16 PIRAGUA ("Evaluation et prospective des ressources en eau des Pyrénées dans un contexte de changement climatique, et mesures d'adaptation ayant un impact sur le territoire")., This dataset was developed within the project EFA210/16 PIRAGUA (“Evaluación y prospectiva de los recursos hídricos de los Pirineos en un contexto de cambio climático, y medidas de adaptación con impacto en el territorio / Evaluation et prospective des ressources en eau des Pyrénées dans un contexte de changement climatique, et mesures d’adaptation avec un impact sur le territoire”), co-funded by the European Regional Development Fund (ERDF) through the Interreg V-A Spain France Andorra program (POCTEFA 2014-2020) (65%) and the project’s partners: CSIC, UPV/EHU, UB, OE, IGME, CNRS, BRGM, INRAE and OBSA (35%)., Files in the data set: - PIRAGUA_hydro_climate_s-mode: Average values of the main water cycle components computed at different time horizons during the 21st century (short, medium and long term), together with the corresponding reference values (average over period 1981-2010), and absolute and relative change with respect to the reference period, at the sub-basin (water bodies catchments) spatial scale, for six different GCM/RCMs and two hydrological models. - PIRAGUA_hydro_climate_t-mode: Annual time series of the main water cycle components at the annual or monthly temporal scale, at the Pyrenees, basin or sub-basin spatial scales, for six different GCM/RCMs and two hydrological models. - GIS: shapefiles of the different spatial aggregation scales: Pyrenees, basins, sub-basins, and stream reaches. The id field in each shapefile allows matching the spatial units with the data files., Data fields (columns): Common fields: - month: month, one of ('annual', 1:12). - mod_hydro: one of ('SWAT', 'SASER'). - model: GCM/RCM model, one of ('bcc-csm1-1', 'CNRM-CM5', 'inmcm4', 'MIROC-ESM', 'MPI-ESM-MR', 'MRI-CGCM3'), or 'median' for the median of the six GCM/RCM (only in s-mode), or one of ('q10', 'q50', 'q90') for 10, 50 (median) and 90 quantiles (only in t-mode). - scenario: emissions scenario, one ov ('HISTORICAL', 'RCP45', 'RCP85'). - variable: one of ('PRECIP', 'SNOFALL', 'SNOMELT', 'TMPAV', 'ET', 'PET', 'ETPET', 'SW', 'SWE', 'DARCHG', 'WYLD', 'SNOWYLD', 'CONTRIB_CMS', 'CONTRIB_HM3'). See variable explanation below. - value: data value corresponding to the horizon / scenario / mod_hydro. - delta.absolute: change between value and value.hist in absolute units. - delta.relative: change between value and value.hist in relative units. - units: one of ('mm', 'ºC', 'mm/mm', 'm3/s', 'Mm3'). Only in in s-mode file: - id: identifier of the spatial unit (sub-basins) that matches the ids on file subbasins.shp. - horizon: always '1981-2010'. - support: spatial support, one of ('Pyrenees', 'AD', 'ES', 'FR', [basin names]). - area: area of the sub-basin, in km^2. - value.hist: reference value during the historical period (1981-2010). Only in in t-mode file: - year: year. - monthabb: month abbreviation. - date: date, in year-month-day format., Variables: - PRECIP: precipitacion, sum of liquid and solid over time period (mm). - SNOFALL: snowfall (solid precipitation), total over time period (mm). - SNOMELT: snowmelt, total over time period (mm). - TMP_AV: daily mean temperature, average over time period (ºC). - TMP_MX: daily maximum temperature, average over time period (ºC). - TMP_MN: daily minimum temperature, average over time period (ºC). - ET: real evapotranspiration, total over time period (mm). - PET: potential evapotranspiration, total over time period (mm). - ET_PET: ratio of real over potential evapotranspiration (mm/mm). - SW: soil water, mean storage over time period (mm). - SWE: snow water equivalent, mean over time period (mm). - DA_RCHG: deep aquifer recharge, total over time period (mm). - WYLD: water yield, total over time period (mm). - SNO_WYLD: contribution of snowmelt to total water yield (mm/mm). - CONTRIB_CMS: mean discharge at the sub-basins' outlet (m^3 / s). - CONTRIB_HM3: mean contribution at the sub-basins' outlet (Mm^3)., Transformation to other units: - mm to mm/day: value_mm_day = valuemm / ndays_in_month_year. - mm to hm3: value_hm3 = value_mm * 1000000 * area_in_km2 * 1.0e-09. - mm to m3/s: value_m3_s = value_mm_day * 1000000 * area_in_km2 * 1.2e-08., Shapefiles in the GIS directory: - pyrenees.shp: polygon shapefile with the limits of the study area. - basins.shp: polygon shapefile with the limits of the river basins, corresponding to field id in the s-mode data file. - subbasins.shp: polygon shapefile with the limits of the river basins, corresponding to field id in the s-mode data file. - reaches.shp: line shapefile with the river reaches, corresponding to field id in the s-mode data file., No

[Methods] Acoustic telemetry.--[Usage Notes] There is one file per species and year of tagging. Each file is an R object. Opening it with R, the estimated centers of activity for each group of fish will be shown; these centers of activity are then used for subsequent analyses. An excel file is also provided containing the biological characteristics of the tagged animals., The effectiveness of Marine Protected Areas (MPAs) depends on the mobility of the populations that are the target of protection, with sedentary species likely to spend more time under protection even within small MPAs. However, little is understood about how individual variation in mobility may influence the risk of crossing an MPA border, as well as the fitness costs associated with being exposed to spillover fisheries. Here we investigated the repeatability of spatial behaviour, its role in determining the probability of being at risk (i.e. exposed to the fishery) and the fitness consequences for the individuals. We acoustically tracked the movements and fate of 282 individuals of three fish species during 8 years in a southern Norwegian fjord. We found that for individuals with a home range centroid inside the MPA, the probability of being at risk outside the MPA increased rapidly with reduced distance from the home range centroid to MPA borders, particularly for individuals having larger and more dispersed home ranges. We also detected that the seasonal expansions of the home range are associated with increased time at risk. Last, we show that individuals spending more time at risk were also more likely to be harvested by the fishery operating outside the MPA. Our study provides clear links between individual fish behaviour, fisheries-induced selection, and the effectiveness of protected areas. These links highlight the importance of intraspecific trait variation for understanding the spatial dynamics of populations and emphasize the need to consider individual behaviour when designing and implementing MPAs., cleanCOAS_ballan2013.rds.-- cleanCOAS_ballan2015.rds.-- cleanCOAS_ballan2016.rds.-- cleanCOAS_ballan2017.rds.-- cleanCOAS_ballan2018.rds.-- cleanCOAS_cod2011.rds.-- cleanCOAS_cod2012.rds.-- cleanCOAS_cod2013.rds.-- cleanCOAS_cod2014.rds.-- cleanCOAS_cod2015.rds.-- cleanCOAS_cod2016.rds.-- cleanCOAS_cod2017.rds.-- cleanCOAS_cod2018.rds.-- cleanCOAS_pollack2015.rds.-- cleanCOAS_pollack2016.rds.-- cleanCOAS_pollack2017.rds.-- cleanCOAS_pollack2018.rds.-- fish_data.csv, Peer reviewed

Related identifiers: Part of 10.3897/jor.27.21064, Figure 5 Relationship between number of Mioscirtus wagneri per square meter (ABUNDANCE) and A. Cover (%) of Suaeda vera (SEEPWEED), and B. Livestock droppings per square meter (DROPPINGS). Open circles may correspond to one or more overlapping data points., Peer reviewed

The provided data are the raw or primary data used to create the figures and tables in the article: Valorization of different landrace and commercial sorghum (Sorghum bicolor (L.) Moench) straw varieties by anaerobic digestion.-- 2 Excel files, To reduce the impact on the environment and enhance the sustainability of resources, it is necessary to promote and strengthen the use of landrace cultivars that advocate regenerative agriculture. In this study, the growth and development as well as the anaerobic digestion (AD) of six different landrace cultivars, two commercial hybrids cultivars and a public genotype of Sorghum bicolor have been evaluated. The landrace cultivars, in general, presented greater heights, biomass yields and compactness shoots as well as similar or an improvement in grain production compare to the commercial varieties. The AD of the different sorghum straws was performed in batch mode at mesophilic temperature (35°C). The landrace cultivar Zahina (ZH) obtained the highest final methane yield (413 ± 79 NL CH4 kg−1 VS, volatile solids) but the landrace cultivars Zahina gigante (ZHG) and Trigomillo (TG) were the ones that obtained the highest methane per biomass production (13.7 and 12.7 NL CH4 shoot unit−1, respectively). By contrast, the commercial varieties were the ones that obtained the lowest methane yields. Two mathematical models, first-order kinetics and the Transference Function model, were used to fit the experimental data with the aim of describing and simulating the anaerobic biodegradation of these S. bicolor straw varieties and obtaining the kinetic constants. Both models allowed for adequately fitting the experimental results of methane production with time. In particular, the fastest biomethanization occurred using the commercial variety PR88Y20 (PR88) (specific rate constant k = 0.148 ± 0.008 days−1), while the slowest one was obtained from Panizo (PAN) variety (k = 0.064 ± 0.005 days−1). In addition, the highest values of the maximum methane production rate, Rm, were attained for the varieties ZH and PR88, which were 87.1% and 71.3% higher than that achieved for the PAN variety, which exhibited the lowest value., Regional government of Andalucía, Junta de Andalucía, Consejería de Transformación Económica, Industria, Conocimiento y Universidades. Grant Number: Project FEDER UPO-1380782, 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 October 2021 to Jun 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 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 February 2021 to October 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

EN] It contains one netCDF file per climate model, scenario (RCP45, RCP85 or HISTORICAL) and variable, for the following variables: Potential Evaporation (Hargreaves), Liquid Precipitation, Solid Precipitation, Total Precipitation, Relative Humidity (max, mean and min), Temperature (max, mean and min), Net Downward Solar Radiation, Net Downward Infrared Radiation and Wind Speed. [ES] Contiene un fichero netCDF por modelo climático, escenario (RCP45, RCP85 o HISTORICAL) y variable, para las siguientes variables: Evaporación potencial (Hargreaves), Precipitación Líquida, Precipitación Sólida, Precipitación Total, Humedad relativa (max., med. y min.), Temperatura (máx, med. y min.), Radiación solar neta descendiente, Radiación infrarroja neta descendiente y Velocidad del viento., [EN] PIRAGUA_atmos_climate is a gridded dataset of climate scenarios for the Pyrenees region. The database is based on the CLIMPY Project downscaled climate scenarios. A subset of 6 CMIP5 GCMs were chosen for assessing future water resources in Spain based on CEDEX/MAPAMA (2017). The CLIMPY scenarios included only Tx, Tn and Ptot, which is not enough to run a Land-Surface Model. Thus, an analogue resampling technique based on these three variables was used to extract analogues (and therefore all other required periods) from the PIRAGUA_atmos_analysis database. The analogy is here made on detrended daily standardized anomalies with respect to a local monthly baseline climatology. Monthly transient baseline trends are calculated and added to the resampled values. The dataset was generated within the project EFA210/16 PIRAGUA Project ("Evaluation and prospective of the water resources of the Pyrenees in a context of climate change, and adaptation measures with impact on the territory")., [ES] PIRAGUA_atmos_climate es una base de datos en malla de escenarios climáticos para los Pirineos. La base de datos se basa en los escenarios climáticos regionalizados de CLIMPY. Se eligió un subconjunto de 6 GCMs CMIP5 para evaluar los recursos hídricos futuros en España basándose en CEDEX/MAPAMA (2017). Los escenarios del CLIMPY incluían únicamente Tx, Tn y Ptot, lo que no es suficiente para ejecutar un LSM. Así, se utilizó una técnica de remuestreo de análogos basada en estas tres variables para extraer análogos de la base de datos PIRAGUA_atmos_analysis. La analogía se realiza sobre las anomalías estandarizadas diarias con respecto a una climatología local mensual de referencia. Se calcula una tendencia transitoria mensual de la línea de base y se añade a los valores remuestreados. El conjunto de datos fue generado en el contexto del proyecto EFA210/16 PIRAGUA ("Evaluación y prospectiva de los recursos hídricos de los Pirineos en un contexto de cambio climático, y medidas de adaptación con impacto en el territorio")., [FR] Base de données maillée des scénarios climatiques pour les Pyrénées, couvrant la période 1981-2100. La base de données est basée sur des scénarios climatiques régionalisés CLIMPY. Un sous-ensemble de 6 MCG CMIP5 a été choisi pour évaluer les futures ressources en eau en Espagne sur la base de CEDEX/MAPAMA (2017). Les scénarios CLIMPY incluaient uniquement Tx, Tn et Ptot, ce qui n'est pas suffisant pour exécuter un LSM. Ainsi, une technique de rééchantillonnage d'analogues basée sur ces trois variables a été utilisée pour extraire des analogues de la base de données PIRAGUA_atmos_analysis. L'analogie est faite sur les anomalies journalières normalisées par rapport à une climatologie locale mensuelle de référence. Une tendance mensuelle de référence transitoire est calculée et ajoutée aux valeurs rééchantillonnées. Le jeu de données a été généré dans le cadre du projet EFA210/16 PIRAGUA ("Evaluation et prospective des ressources en eau des Pyrénées dans un contexte de changement climatique, et mesures d'adaptation ayant un impact sur le territoire")., This dataset was developed within the project EFA210/16 PIRAGUA (“Evaluación y prospectiva de los recursos hídricos de los Pirineos en un contexto de cambio climático, y medidas de adaptación con impacto en el territorio / Evaluation et prospective des ressources en eau des Pyrénées dans un contexte de changement climatique, et mesures d’adaptation avec un impact sur le territoire”), co-funded by the European Regional Development Fund (ERDF) through the Interreg V-A Spain France Andorra program (POCTEFA 2014-2020) (65%) and the project’s partners: CSIC, UPV/EHU, UB, OE, IGME, CNRS, BRGM, INRAE and OBSA (35%)., No

English: This Collection of Botanical Iconography of the 18th century is the most relevant of the Flora of Colombia, and one of the best in the world, both from a scientific and artistic point of view. These are the original drawings made by the artists of the Expedition of the Royal Botanic Expedition of the New Kingdom of Granada, under the direction of José Celestino Mutis. During thirty years, the expeditionaries collected specimens in the territories of Colombia and Ecuador, which were illustrated by the artists. As a result this collection has reached our days, and has been admired by scientists like Carlos Linnaeus and Alexander von Humboldt. Since 2002, it has been recognized by the UNESCO as Memory of the World Register for Latin America and the Caribbean (MOWLAC).The data set includes information belonging to 5,796 records from a total of 7,167, including the scientific name, as well as subsequent identifications and revisions made by the specialists of the "Flora of the New Kingdom of Granada". This work is divided in various volumes in publishing process since 1952 thanks to an agreement between the Spanish and Colombian governments. Español: Esta colección de iconografía botánica del siglo XVIII es la más relevante para la flora de Colombia, pero también una de las mejores del mundo, tanto desde el punto de vista científico como artístico. Se trata de los dibujos originales realizados por los artistas de la Real Expedición Botánica del Nuevo Reino de Granada, bajo la dirección de José Celestino Mutis. Durante treinta años los expedicionarios recolectaron especímenes en los territorios de Colombia y Ecuador, que fueron ilustrados por los artistas. El resultado fue esta colección, ya en su momento admirada por científicos de la talla de Carlos Linneo y Alexander von Humboldt. Desde el año 2002, tiene el reconocimiento del Registro de Memoria del Mundo de la UNESCO para América Latina y el Caribe (MOWLAC). El conjunto de datos que se ofrece incluye información de 5.796 registros de un total de 7.167, incluyendo el nombre científico y las identificaciones y revisiones posteriores, realizadas por los especialistas de la “Flora del Nuevo Reino de Granada”, obra que se viene publicando desde 1952 gracias a un acuerdo entre los gobiernos de España y Colombia.

The Marine Biological Reference Collections (CBMR) are located at the Institute of Marine Sciences (ICM-CSIC) in Barcelona, Spain. The CBR are a Unit of Service where around 15000 referenced species are preserved, catalogued and maintained for their study. The most represented marine groups at the CBMR are fish, crustaceans, molluscs and echinoderms, but also other groups are present. The studies based on the CBMR specimens are focused on biodiversity, biogeography, taxonomy (type species), invasive and alien species, and genetic analysis. Several PhD theses have also been carried out in collaboration with the CBMR.The CBMR are a reference point for the marine biodiversity of the Mediterranean Sea, but in their facilities the CBMR also hold specimens from all the oceans (Atlantic, Pacific, Indian, Antarctic and Arctic). The Collections are constantly receiving new specimens and updating. The main sources of specimens are oceanographic surveys and different kind of sampling programs carried out by the research projects run by the ICM-CSIC. However, the CBMR have also received (in the past and currently) different collections donated by naturalists, researchers, other institutions, and particulars. The CBMR were created in 1981, in the earlier history of the ICM-CSIC, by Jaume Rucabado, Domingo Lloris and Concepción Allué. The Collections were later recognized and catalogued by the Spanish Ministry of Culture in 1990. In the last decade, the CBMR initiated a new stage where the information was digitized and the physical preservation of specimens updated to the new rules (such as change from formaldehyde to ethanol). The CBMR are now part of GBIF (Global Biodiversity Information Facility), thus making public and available all data collections and their metadata. We have also incorporated the use of Geographical Information Systems (GIS) to monitor and study the geographical distribution of our specimens and moreover, the CBMR started to act as repository of DNA voucher collections for genetic analyses.As a unit of service of the ICM-CSIC we think that education and outreach of marine science is of crucial importance for the society and for that reason the CBMR take active part in several outreach activities with schools, universities and general public. For more information or details you can visit our webpage (http://cbr.icm.csic.es/en/node) and send us an e-mail (cbr@icm.csic.es). We will be happy to help you.

The monitoring of biometric parameters (total body length, cephalothorax length, cephalothorax width and weight) of red-swamp crayfish (Procambarus clarkii) in Doñana wetlands was initiated in 2004 as part of the Monitoring Program of Natural Resources and Processes. The aim was to obtain a temporal and continuous series of data in the biometry of the species to analyze the evolution in these variables. Data were recorded annually between 2004-2022 by more than 2 members of the monitoring team which performed samplings in different locations twice per year in winter-spring and summer seasons when the study sites are flooded., The aim of this project is to provide information about the evolution of the conservation status of Doñana. To do that, it has been designed a monitoring program of the dynamic of natural processes and the distribution and abundance of species and communities. This monitoring is generating time series of data which is being used to analyzed long-term trends.