23 research outputs found

    Evolución de la cubierta forestal de la cuenca del Duero: análisis multitemporal mediante teledetección

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    Se presenta un estudio de la evolución de la cubierta forestal en cuatro sub-cuencas de la cuenca del Duero mediante el uso de imágenes Landsat desde mediados de los años 70 hasta la actualidad. El estudio se basa en el análisis multitemporal en las cuencas del Esla, el Carrión, el Tormes y el Alto Duero, todas ellas representativas de las diferentes vertientes hidrográficas. A diferencia de lo que se observa en la mayoría de los estudios realizados sobre la evolución de la superficie de bosque, que utilizan como punto de partida la foto aérea de 1956 y que, como máximo, aportan mapas de la distribución de los usos/coberturas de suelo en dos o tres fechas durante la década de los 90 o en la actualidad, en este trabajo se han utilizado todas las imágenes disponibles (entre 10 y 13 por cuenca). De esta forma se consiguió una serie homogénea en el tiempo y con un número de mapas suficiente para realizar un análisis de tendencias y determinar de manera rigurosa la existencia o no de una evolución clara. En una fase preliminar se empleó cartografía base del Mapa de Cultivos y Aprovechamientos y del Mapa Forestal de España, mapas de los Inventarios Forestales Nacionales y ortofotos aéreas como datos auxiliares para definir las clases de cubierta, seleccionar las zonas de entrenamiento y validar los resultados. Para la caracterización espectral de las distintas clases se utilizaron para cada escena y fecha el NDVI (Normalized Difference Vegetation Index) y las reflectividades de superficie de las bandas visible, infrarrojo cercano e infrarrojo de onda corta, tras los procesos de calibración y corrección geométrica, radiométrica y atmosférica. El método elegido para la discriminación de cubiertas boscosas ha sido el de clasificación supervisada por máxima probabilidad y el posterior refinado de resultados mediante filtrado y criterios condicionales. Finalmente, los resultados se evaluaron mediante matrices de confusión generadas a partir del Mapa Forestal de España (2002-2004), y también se compararon las superficies obtenidas por el proceso de clasificación con las de la cartografía base de los IFN y del programa CORINE. Los resultados muestran que, a diferencia de lo que ha ocurrido en las principales zonas forestales de España, en la cuenca del Duero la superficie de bosque no ha aumentado en los últimos 40 años. Dicha cubierta muestra una tendencia claramente negativa en tres de las cuencas estudiadas.Este trabajo ha sido posible gracias a la financiación del Proyecto SA212A11-2 de la Junta de Castilla y León. Los autores también agradecen al United States Geological Survey (USGS) y a la Agencia Europea del Espacio (ESA) las imágenes Landsat

    SIGPAC y series multitemporales LANSAT 15 TM como estrategia híbrida de clasificación de usos de suelo para aplicaciones hidrológicas

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    El objetivo de este trabajo consiste en la obtención de un mapa de usos y coberturas de suelo para su integración en un modelo hidrológico de balance de agua a lo largo de 2009. Los resultados de dicha aplicación (evapotranspiración, humedad de suelo, necesidades de riego) se obtienen a escala de parcela, con escala temporal diaria y contemplando los usos y coberturas más frecuentes en la zona. La herramienta diseñada para aplicar el modelo (HidroMORE, Modelo Hidrológico de Estimación de Recarga y Evapotranspiración) proporciona los resultados en forma de mapa imagen. Con este fin, se presenta una alternativa híbrida de clasificación consistente en la combinación de la base de datos vectorial del Sistema de Información Geográfica de Parcelas Agrícolas (SIGPAC), junto con una serie multitemporal de imágenes Landsat 5 TM (Thematic Mapper) del año 2009. El primero aporta la definición parcelaria, mientras que la segunda provee la información suficiente para resolver clases poco definidas en el SIGPAC, especialmente la categoría ‘tierra arable’. Se utilizaron metodologías de teledetección como la clasificación, la segmentación multitemporal y el NDVI (Normalized Difference Vegetation Index), junto con herramientas SIG. El método propuesto supuso una mejora global de la precisión respecto a un método de clasificación supervisada convencional del 20% para la zona de estudio en 2009, y con un coste operacional muy bajo.The aim of this work consists on retrieving a land use-land cover map in order to integrate it in a water balance model along 2009. The results of this application, i.e., evapotranspiration, soil moisture, irrigation rates, are obtained at field scale, in a daily basis, and over the most representative agricultural uses. The model is implemented in a computerized tool, HidroMORE, which provides image maps of the results. A hybrid alternative of classification is presented for such hydrological application. It consisted in a combination of the vectorial database from the Spanish Geographic Information System for Agricultural Plots (SIGPAC) and a Landsat 5 TM multitemporal series of images for the year of study. The SIGPAC affords the spatial shape of the plots, whereas the images allow the segmentation of some ambiguous categories, i.e., ‘agricultural plots’. Remote sensing techniques (classification, segmentation, and NDVI, Normalized Difference Vegetation Index) were used, as well as GIS tools. The proposed method improved by 20% the global accuracy comparing to a typical supervised classification in the study area along 2009, while the computational cost is low

    Assessment of Root Zone Soil Moisture Estimations from SMAP, SMOS and MODIS Observations

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    [EN]In this study, six satellite-based root zone soil moisture (RZSM) estimates from March 2015 to December 2016 were evaluated both temporally and spatially. The first two were the Soil Moisture Active Passive (SMAP) and the Soil Moisture and Ocean Salinity (SMOS) L4 RZSM products. The other four were obtained through the Soil Water Index (SWI) approach, which embedded surface soil moisture (SSM). The SMOS-Barcelona Expert Center (BEC) L4 SSM product and the apparent thermal inertia (ATI)-derived SSM from the Moderate Resolution Imaging Spectroradiometer (MODIS) data were used as SSM datasets. In the temporal analysis, the RZSM estimates were compared to in situ RZSM from 14 stations of the Soil Moisture Measurements Station Network of the University of Salamanca (REMEDHUS). Regarding the spatial assessment, the resulting RZSM maps of the Iberian Peninsula were compared between them. All RZSM values followed the temporal evolution of the ground-based measurements well, although SMOS and MODIS showed underestimation while SMAP displayed overestimation. The good results obtained from MODIS ATI are notable, notwithstanding they were not estimated through microwave radiometry. A very high agreement was found in terms of spatial patterns for the whole Iberian Peninsula except for the extreme north area, which is dominated by high mountains and dense forests

    Amaranth’s response to two planting distances and population density

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    El objetivo de este estudio fue evaluar el comportamiento de tres genotipos de amaranto, Amaranthus sp.; con la fina­lidad­de utilizarlos en cosecha mecánica. Estos fueron­ sembrados en la Facultad de Agronomía, Universidad Nacional La Pampa en surcos separados a 0,25 y 0,50 m y densidades de 100 x 10 3 , 200 x 10 3 y 400 x 10 3 plantas ha-1. Se midió la altura de las plantas y la radiación fotosinté- ticamente activa a los 30 días después de la siembra (DDS) en la antesis y madurez­fisiológica, así como, el índice de cosecha (IC) y rendimiento de semilla. Estadísti­camente el diseño fue de bloques al azar con 4 réplicas x 3 genotipos x 3 densidades x 2 distancias. No hubo diferencias significativas (P= 0,01) en el IC y rendimiento­en grano (kg ha-1) en los tres genotipos, entre distancias en surcos y densidades­. La inter­cepción solar (IS) a los 30 DDS (51,2%) solo difirió significa­tivamente (P= 0,01) en A. cruentus var. Don Guiem, para la distancia de 0,25 m y 100.000 plantas ha -1 . Las plantas en la madurez no presentaron diferencias para los distintos tratamientos. Las densidades a campo oscilaron entre 50-90 x 10 3 , 90-150 x 10 3 y 150-270 x 10 3 plantas ha -1 , explicando la falta de significancia entre tratamientos.Field studies were conducted to evaluate the behavior of amaranths, Amaranthus sp.; with the purpose of being able to use them in the mechanical crop. Three amaranths were sowed in the Facultad de Agronomía, Universidad Nacional La Pampa in furrows separated to 0,25 and 0,50 m and densities of 100 x 103 ; 200 x 103 and 400 x 103 plants ha-1. The height of plants, photosyntetically active radiation (30 days of the sowing, anthesis and physiological maturity),), harvest index of crop and seed yield were measured. Experimental design was totally randomized blocks: 4 replications x 3 genotypes x 3 densities x 2 distances. There were no significant differences(P= 0,01) in the harvest index of crop and grain yield (expressed in kg ha-1), in the 3 genotypes between distances in furrows and densities. The solar interception at 30 days of the sowing (51,2%), only difered significantly (P= 0,01) in A. cruentus var. Don Guiem for the distance of 0,25 m and 100.000 plants ha-1. At maturity there were not significant different treatments. The densities in the field ranged between 50-90 x 103 , 90-150 x 103 and 150-270 x 103 plants ha-1 which would explain the lack ofsignificance between treatments.Fil: Repollo, Rodolfo. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Centro de Recursos Naturales Renovables de la Zona Semiarida. Universidad Nacional del Sur. Centro de Recursos Naturales Renovables de la Zona Semiarida; Argentina. Universidad Nacional de La Pampa; ArgentinaFil: Martín de Troiani, Rosa. Universidad Nacional de la Pampa. Facultad de Agronomía; ArgentinaFil: Nollemeyer, Elke. Universidad Nacional de la Pampa. Facultad de Agronomía; ArgentinaFil: Sánchez, Teresa. Universidad Nacional de la Pampa. Facultad de Agronomía; ArgentinaFil: Reinaudi, Nilda. Universidad Nacional de la Pampa. Facultad de Agronomía; Argentin

    Assessment of SMADI and SWDI agricultural drought indices using remotely sensed root zone soil moisture

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    [EN]The increasing frequency of drought events has expanded the research interest in drought monitoring. In this regard, remote sensing is a useful tool to globally mapping the agricultural drought. While this type of drought is directly linked to the availability of root zone soil moisture (RZSM) for plants growth, current satellite soil moisture observations only characterize the water content of the surface soil layer (0–5 cm). In this study, two soil moisture-based agricultural drought indices were obtained at a weekly rate from June 2010 to December 2016, using RZSM estimations at 1 km from the Soil Moisture and Ocean Salinity (SMOS) satellite, instead of surface soil moisture (SSM). The RZSM was estimated by applying the Soil Water Index (SWI) model to the SMOS SSM. The Soil Moisture Agricultural Drought Index (SMADI) and the Soil Water Deficit Index (SWDI) were assessed over the Castilla y León region (Spain) at 1 km spatial resolution. They were compared with the Atmospheric Water Deficit (AWD) and the Crop Moisture Index (CMI), both computed at different weather stations distributed over the study area. The level of agreement was analyzed through statistical correlation. Results showed that the use of RZSM does not influence the characterization of drought, both for SMADI and SWDI

    Cuaderno de prácticas de la asignatura de 1º del Grado en Ingeniería Agrícola de la Facultad de Ciencias Agrarias y Ambientales

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    [ES]Cuaderno de prácticas de Cartografía y Topografía con el programa Civil 3D de Autocad. Realización de explanaciones y movimientos de obra de proyectos de ingeniería agrícola

    Autologous t-cell activation fosters ABT-199 resistance in chronic lymphocytic leukemia: Rationale for a combined therapy with SYK inhibitors and anti-CD20 monoclonal antibodies

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    Fil: Elías, Esteban Enrique. Consejo Nacional de Investigaciones Científicas y Técnicas. Instituto de Medicina Experimental. Academia Nacional de Medicina de Buenos Aires. Instituto de Medicina Experimental; Argentina. Academia Nacional de Medicina de Buenos Aires; ArgentinaFil: Almejún, María Belén. Universidad de Buenos Aires; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Instituto de Medicina Experimental. Academia Nacional de Medicina de Buenos Aires. Instituto de Medicina Experimental; ArgentinaFil: Colado, Ana. Academia Nacional de Medicina de Buenos Aires; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Instituto de Medicina Experimental. Academia Nacional de Medicina de Buenos Aires. Instituto de Medicina Experimental; ArgentinaFil: Cordini, Gregorio. Academia Nacional de Medicina de Buenos Aires; ArgentinaFil: Vergara Rubio, Maricef. Academia Nacional de Medicina de Buenos Aires; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Instituto de Medicina Experimental. Academia Nacional de Medicina de Buenos Aires. Instituto de Medicina Experimental; ArgentinaFil: Podaza, Enrique Arturo. Consejo Nacional de Investigaciones Científicas y Técnicas. Instituto de Medicina Experimental. Academia Nacional de Medicina de Buenos Aires. Instituto de Medicina Experimental; Argentina. Universidad de Buenos Aires. Facultad de Medicina. Hospital de Clínicas General San Martín; ArgentinaFil: Risnik, Denise Mariel. Consejo Nacional de Investigaciones Científicas y Técnicas. Instituto de Medicina Experimental. Academia Nacional de Medicina de Buenos Aires. Instituto de Medicina Experimental; Argentina. Academia Nacional de Medicina de Buenos Aires; ArgentinaFil: Cabrejo, María. Academia Nacional de Medicina de Buenos Aires; ArgentinaFil: Fernández Grecco, Horacio. Academia Nacional de Medicina de Buenos Aires; ArgentinaFil: Bezares, Raimundo Fernando. Universidad de Buenos Aires; ArgentinaFil: Custidiano, María Del Rosario. Sanatorio Municipal Dr. Julio Méndez; ArgentinaFil: Sánchez Ávalos, Julio César Américo. Sanatorio Municipal Dr. Julio Méndez; ArgentinaFil: Vicente, Ángeles. Gobierno de la Ciudad de Buenos Aires. Hospital General de Agudos "Dr. Teodoro Álvarez"; ArgentinaFil: Garate, Gonzalo Martín. Instituto Alexander Fleming; ArgentinaFil: Borge, Mercedes. Instituto Alexander Fleming; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Instituto de Medicina Experimental. Academia Nacional de Medicina de Buenos Aires. Instituto de Medicina Experimental; ArgentinaFil: Giordano, Mirta Nilda. Consejo Nacional de Investigaciones Científicas y Técnicas. Instituto de Medicina Experimental. Academia Nacional de Medicina de Buenos Aires. Instituto de Medicina Experimental; Argentina. Hospital Alemán; ArgentinaFil: Gamberale, Romina. Consejo Nacional de Investigaciones Científicas y Técnicas. Instituto de Medicina Experimental. Academia Nacional de Medicina de Buenos Aires. Instituto de Medicina Experimental; Argentina. Hospital Aleman; Argentin

    Detailed stratified GWAS analysis for severe COVID-19 in four European populations

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    Given the highly variable clinical phenotype of Coronavirus disease 2019 (COVID-19), a deeper analysis of the host genetic contribution to severe COVID-19 is important to improve our understanding of underlying disease mechanisms. Here, we describe an extended genome-wide association meta-analysis of a well-characterized cohort of 3255 COVID-19 patients with respiratory failure and 12 488 population controls from Italy, Spain, Norway and Germany/Austria, including stratified analyses based on age, sex and disease severity, as well as targeted analyses of chromosome Y haplotypes, the human leukocyte antigen region and the SARS-CoV-2 peptidome. By inversion imputation, we traced a reported association at 17q21.31 to a ~0.9-Mb inversion polymorphism that creates two highly differentiated haplotypes and characterized the potential effects of the inversion in detail. Our data, together with the 5th release of summary statistics from the COVID-19 Host Genetics Initiative including non-Caucasian individuals, also identified a new locus at 19q13.33, including NAPSA, a gene which is expressed primarily in alveolar cells responsible for gas exchange in the lung.S.E.H. and C.A.S. partially supported genotyping through a philanthropic donation. A.F. and D.E. were supported by a grant from the German Federal Ministry of Education and COVID-19 grant Research (BMBF; ID:01KI20197); A.F., D.E. and F.D. were supported by the Deutsche Forschungsgemeinschaft Cluster of Excellence ‘Precision Medicine in Chronic Inflammation’ (EXC2167). D.E. was supported by the German Federal Ministry of Education and Research (BMBF) within the framework of the Computational Life Sciences funding concept (CompLS grant 031L0165). D.E., K.B. and S.B. acknowledge the Novo Nordisk Foundation (NNF14CC0001 and NNF17OC0027594). T.L.L., A.T. and O.Ö. were funded by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation), project numbers 279645989; 433116033; 437857095. M.W. and H.E. are supported by the German Research Foundation (DFG) through the Research Training Group 1743, ‘Genes, Environment and Inflammation’. L.V. received funding from: Ricerca Finalizzata Ministero della Salute (RF-2016-02364358), Italian Ministry of Health ‘CV PREVITAL’—strategie di prevenzione primaria cardiovascolare primaria nella popolazione italiana; The European Union (EU) Programme Horizon 2020 (under grant agreement No. 777377) for the project LITMUS- and for the project ‘REVEAL’; Fondazione IRCCS Ca’ Granda ‘Ricerca corrente’, Fondazione Sviluppo Ca’ Granda ‘Liver-BIBLE’ (PR-0391), Fondazione IRCCS Ca’ Granda ‘5permille’ ‘COVID-19 Biobank’ (RC100017A). A.B. was supported by a grant from Fondazione Cariplo to Fondazione Tettamanti: ‘Bio-banking of Covid-19 patient samples to support national and international research (Covid-Bank). This research was partly funded by an MIUR grant to the Department of Medical Sciences, under the program ‘Dipartimenti di Eccellenza 2018–2022’. This study makes use of data generated by the GCAT-Genomes for Life. Cohort study of the Genomes of Catalonia, Fundació IGTP (The Institute for Health Science Research Germans Trias i Pujol) IGTP is part of the CERCA Program/Generalitat de Catalunya. GCAT is supported by Acción de Dinamización del ISCIII-MINECO and the Ministry of Health of the Generalitat of Catalunya (ADE 10/00026); the Agència de Gestió d’Ajuts Universitaris i de Recerca (AGAUR) (2017-SGR 529). M.M. received research funding from grant PI19/00335 Acción Estratégica en Salud, integrated in the Spanish National RDI Plan and financed by ISCIII-Subdirección General de Evaluación and the Fondo Europeo de Desarrollo Regional (European Regional Development Fund (FEDER)-Una manera de hacer Europa’). B.C. is supported by national grants PI18/01512. X.F. is supported by the VEIS project (001-P-001647) (co-funded by the European Regional Development Fund (ERDF), ‘A way to build Europe’). Additional data included in this study were obtained in part by the COVICAT Study Group (Cohort Covid de Catalunya) supported by IsGlobal and IGTP, European Institute of Innovation & Technology (EIT), a body of the European Union, COVID-19 Rapid Response activity 73A and SR20-01024 La Caixa Foundation. A.J. and S.M. were supported by the Spanish Ministry of Economy and Competitiveness (grant numbers: PSE-010000-2006-6 and IPT-010000-2010-36). A.J. was also supported by national grant PI17/00019 from the Acción Estratégica en Salud (ISCIII) and the European Regional Development Fund (FEDER). The Basque Biobank, a hospital-related platform that also involves all Osakidetza health centres, the Basque government’s Department of Health and Onkologikoa, is operated by the Basque Foundation for Health Innovation and Research-BIOEF. M.C. received Grants BFU2016-77244-R and PID2019-107836RB-I00 funded by the Agencia Estatal de Investigación (AEI, Spain) and the European Regional Development Fund (FEDER, EU). M.R.G., J.A.H., R.G.D. and D.M.M. are supported by the ‘Spanish Ministry of Economy, Innovation and Competition, the Instituto de Salud Carlos III’ (PI19/01404, PI16/01842, PI19/00589, PI17/00535 and GLD19/00100) and by the Andalussian government (Proyectos Estratégicos-Fondos Feder PE-0451-2018, COVID-Premed, COVID GWAs). The position held by Itziar de Rojas Salarich is funded by grant FI20/00215, PFIS Contratos Predoctorales de Formación en Investigación en Salud. Enrique Calderón’s team is supported by CIBER of Epidemiology and Public Health (CIBERESP), ‘Instituto de Salud Carlos III’. J.C.H. reports grants from Research Council of Norway grant no 312780 during the conduct of the study. E.S. reports grants from Research Council of Norway grant no. 312769. The BioMaterialBank Nord is supported by the German Center for Lung Research (DZL), Airway Research Center North (ARCN). The BioMaterialBank Nord is member of popgen 2.0 network (P2N). P.K. Bergisch Gladbach, Germany and the Cologne Excellence Cluster on Cellular Stress Responses in Aging-Associated Diseases, University of Cologne, Cologne, Germany. He is supported by the German Federal Ministry of Education and Research (BMBF). O.A.C. is supported by the German Federal Ministry of Research and Education and is funded by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) under Germany’s Excellence Strategy—CECAD, EXC 2030–390661388. The COMRI cohort is funded by Technical University of Munich, Munich, Germany. This work was supported by grants of the Rolf M. Schwiete Stiftung, the Saarland University, BMBF and The States of Saarland and Lower Saxony. K.U.L. is supported by the German Research Foundation (DFG, LU-1944/3-1). Genotyping for the BoSCO study is funded by the Institute of Human Genetics, University Hospital Bonn. F.H. was supported by the Bavarian State Ministry for Science and Arts. Part of the genotyping was supported by a grant to A.R. from the German Federal Ministry of Education and Research (BMBF, grant: 01ED1619A, European Alzheimer DNA BioBank, EADB) within the context of the EU Joint Programme—Neurodegenerative Disease Research (JPND). Additional funding was derived from the German Research Foundation (DFG) grant: RA 1971/6-1 to A.R. P.R. is supported by the DFG (CCGA Sequencing Centre and DFG ExC2167 PMI and by SH state funds for COVID19 research). F.T. is supported by the Clinician Scientist Program of the Deutsche Forschungsgemeinschaft Cluster of Excellence ‘Precision Medicine in Chronic Inflammation’ (EXC2167). C.L. and J.H. are supported by the German Center for Infection Research (DZIF). T.B., M.M.B., O.W. und A.H. are supported by the Stiftung Universitätsmedizin Essen. M.A.-H. was supported by Juan de la Cierva Incorporacion program, grant IJC2018-035131-I funded by MCIN/AEI/10.13039/501100011033. E.C.S. is supported by the Deutsche Forschungsgemeinschaft (DFG; SCHU 2419/2-1).Peer reviewe
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