Resultados totales (Incluyendo duplicados): 34354
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Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/260833
Dataset. 2022

DATASET FOR THE PAPER “OUJJA, M., PALOMAR, T., MARTÍNEZ-WEINBAUM, M., MARTÍNEZ-RAMÍREZ S., CASTILLEJO, M. 2021. CHARACTERIZATION OF MEDIEVAL-LIKE GLASS ALTERATION LAYERS BY LASER SPECTROSCOPY AND NONLINEAR OPTICAL MICROSCOPY. EUR. PHYS. J. PLUS 136, 859"

  • Oujja, M.
  • Palomar, T.
  • Martínez-Weinbaum, Marina
  • Martínez-Ramírez, S.
  • Castillejo, Marta
The study was undertaken in six medieval-like model glass samples UG (unaltered glass), MAK, MAR, MTA, MTB and MTN subjected to various environmental and atmospheric conditions in order to generate alteration layers of different characteristics. A potash-lime silicate glass, with composition similar to that of medieval glasses, was melted at 1400 °C during two hours, poured in a brass mould of rectangular cross section and annealed at 650 °C. The resulting glass ingot was cut in slices of around 10×10×2 mm3 and then polished using emery paper and an aqueous suspension of cerium oxide to obtain optical quality surfaces. Alteration of the glass slices was conducted by exposure to five different laboratory corrosion tests: SO2 corrosion for MAK sample, synthetic river water degradation for MAR, and degradation due to acid, basic and neutral medium for MTA, MTB and MTN, respectively. This dataset consists of images of the samples; Laser-induced Breakdown Spectrocopy (LIBS) spectra; Laser-induced Fluorescence (LIF) spectra; Optical Microscopy (OM); FT-Raman spectroscopy and Multi-Photon Excitation Fluorescence (MPEF) signals obtained with a Nonlinear optical microscopy (NLOM). This information allows characterizing the composition of both body glass and determining the thickness of the degradation layer. Images are presented in JPG. All spectra are presented in cvs format, in a single page. Descriptions of the samples and the experimental conditions in which the spectra were taken and the name of the column values are included at the top of each page. For LIBS, 1 file per sample of elemental composition of the medieval-like glass are included. Each file is composed of 2 columns (wavelength and intensity). For LIF, 1 file per sample of the analysis of fluorescent species of each medieval-like glass are included. Each file is composed of 2 columns (wavelength and intensity). For NLOM, 2 files per sample. In the first one: “MPEF Safe limits”, each file is composed for 10 columns: 2 are for depth (µm) and 8 are for MPEF signal divided in two groups relating to the the power in the sample surface. In the second group of files: “MPEF profiles”, each file is composed for 4 columns: 1 is for depth (µm), 1 is the normalized MPEF intensity, 1 is the Lorentzian fit of depth (µm) and the last one Lorentzian fit. (The thicknesses of the degradation layers of the medieval-like glasses is calculated by the FWHM values of the fits after refractive index corrections). For FT-Raman, 1 file per sample of the analysis of the structure of the medieval-like glass through their vibrational modes is included. Each file is composed of 2 columns (Raman shift and intensity in arbitrary units). This dataset is subject to a Creative Commons Attribution 4.0 International (CC BY 4.0) License., This is the experimental dataset used in the paper Eur. Phys. Plus, 136:859 (2021) (http://hdl.handle.net/10261/248668). Historical glass-based objects undergo, since the time of their manufacture, different degradation phenomena that are related to their composition and to the environment to which they were exposed. Three-dimensional (3D) structural and chemical characterization of the degradation layers is important to select the most adequate conservation strategies for glass objects. Optical microscopy (OM) is the most frequently used non-destructive method to examine the surface of historical glasses; however, the 3D structural assessment of alteration layers requires applying the destructive modality of this technique to conduct a cross-sectional study. In this work, a different approach for structural and compositional characterization of alteration layers on model medieval-like glasses is presented, based on the combination of the laser spectroscopies of laser-induced breakdown spectroscopy (LIBS), laser-induced fluorescence (LIF) and FT-Raman, and the emerging, cutting edge technique of nonlinear optical microscopy (NLOM) in the modality of multiphoton excitation fluorescence (MPEF). The results obtained through this multi-analytical photonic approach were compared with those retrieved by examination of the surface and cross sections of the samples by OM and scanning electron microscopy–energy-dispersive X-ray spectroscopy (SEM–EDS). While the combination of LIBS, LIF and FT-Raman served to assess the composition of the various alteration layers, the use of MPEF microscopy allowed the non-destructive determination of the thicknesses of these layers, showing for both thickness and composition a good agreement with the OM and SEM–EDS results. Thus, the proposed approach, which avoids sample preparation, illustrates the capability of non-destructive, or micro-destructive in the case of LIBS, laser spectroscopies and microscopies for the in situ study of glass objects of historic or/and artistic value, This research has been funded by the Spanish State Research Agency (AEI) through projects PID2019-104124RB-I00/AEI/1013039/501100011033, the CSIC General Foundation (ComFuturo Programme), by project TOP Heritage-CM (S2018/NMT-4372) from Community of Madrid, by the H2020 European project IPERION HS (Integrated Platform for the European Research Infrastructure ON Heritage Science, GA 871034). Support by CSIC Interdisciplinary Platform “Open Heritage: Research and Society” (PTI-PAIS) is acknowledged. M.O. thanks CSIC for a contract. The authors also thank M.A. Villegas and M. García Heras (Institute of History, CSIC) for fruitful discussions on historical glasses., There are 4 files which correspond to each technic employed for the analysis of the six different samples. The file title “LIBS” contains: LIBS_UG; LIBS_MAK; LIBS_MAR; LIBS_MTA; LIBS_MTB; LIBS_MTN. The file for “LIF” contains: LIF_UG; LIF_MAK; LIF_MAR; LIF_MTA; LIF_MTB; LIF_MTN. The file for “FT-RAMAN” contains: FT-RAMAN_UG; FT-RAMAN_MAK; FT-RAMAN_MAR; FT-RAMAN_MTA; FT-RAMAN_MTB; FT-RAMAN_MTN. For the “MPEF” there are two files inside. One title “MPEF safe limits” which contains the documents: MPEF_MAK_SL; MPEF_MAR_SL; MPEF_MTA_SL; MPEF_MTB_SL; MPEF_MTN_SL. And the other called “MPEF profiles” which contains: MPEF_MAK_PROFILE; MPEF_MAR_PROFILE; MPEF _MTA_PROFILE; MPEF _MTB_PROFILE; MPEF _MTN_PROFILE., Peer reviewed

DOI: http://hdl.handle.net/10261/260833
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/260833
HANDLE: http://hdl.handle.net/10261/260833
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/260833
PMID: http://hdl.handle.net/10261/260833
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/260833
Ver en: http://hdl.handle.net/10261/260833
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Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/260864
Dataset. 2022

COMPLETE DATA OF THE DNA SEQUENCES USED FOR THE STUDY OF THE RHYACOPHILA FASCIATA GROUP (INSECTA, TRICHOPTERA, RHYACOPHILIDAE) IN EUROPE

  • Valladolid, María
  • Arauzo, Mercedes
  • Dorda, Beatriz A.
  • París, Mercedes
  • Fraile, Isabel
The table lists all the DNA sequences (COI mit) studied to date, of specimens belonging to the Rhyacophila fasciata Group and published in different articles. Due to the progressive increase of sequences obtained in successive publications, they have been compiled in this table for consultation by researchers interested in this material. The document will be updated with new sequences as the following studies are published., The table includes the following information: species and specimen number, sex, locality of collection, latitudinal and longitudinal geographical coordinates, altitude, accession numbers to GenBank, voucher number from Tissues and DNA Collection, voucher number of Entomological Collection, both from Museo Nacional de Ciencias Naturales, Consejo Superior de Investigaciones Científicas (MNCN-CSIC), accession number and/or collection in other Collections, and legit (Leg.) of specimens., No

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DOI: http://hdl.handle.net/10261/260864
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/260864
HANDLE: http://hdl.handle.net/10261/260864
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/260864
PMID: http://hdl.handle.net/10261/260864
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/260864
Ver en: http://hdl.handle.net/10261/260864
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oai:digital.csic.es:10261/260864

Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/260924
Dataset. 2021

DATOS PARA LA INVESTIGACIÓN DE LA ICONOGRAFÍA DEL ARCO PARA LA ENTRADA DEL VIRREY DE LAS AMARILLAS EN PUEBLA (1755), A PARTIR DEL LIENZO ATRIBUIDO A ATRIBUIDO A JOSÉ JOAQUÍN MAGÓN [DATASET]

  • Farré Vidal, Judith
Data for the investigation (images and transcription of the epigrams of the arch for the entrance of the viceroy of Las Amarillas in Puebla (1755), from the canvas attributed to José Joaquín Magón., This paper studies the entrance in Puebla of the Marquis de las Amarillas (1755) as viceroy of New Spain. The iconographic program of the arch for the entrance to the Cathedral of Puebla was carried out by the Magisterial Canon and preacher Andrés de Arce y Miranda. Since the printed explanatory program is not preserved, it is here analyzed from the painting deposited in the Guillermo Tovar de Teresa Collection of The Soumaya Museum-Carlos Slim Foundation of Mexico City, and also studied, as a new contribution, in correlation to the sermon «Keeping a Kingdom in Peace» that Arce himself preached in the Cathedral on October 29 as a tribute and welcome to the viceroy., Peer reviewed

DOI: http://hdl.handle.net/10261/260924
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/260924
HANDLE: http://hdl.handle.net/10261/260924
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/260924
PMID: http://hdl.handle.net/10261/260924
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/260924
Ver en: http://hdl.handle.net/10261/260924
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oai:digital.csic.es:10261/260924

Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/261228
Dataset. 2022

DATASET SUPPORTING THE PAPER "ATOMIC-SCALE SPIN SENSING WITH A SINGLE MOLECULE AT THE APEX OF A SCANNING TUNNELING MICROSCOPE. DOI: 10.1126/SCIENCE.AAX8222"

  • Verlhac, Benjamin
  • Bachellier, Nicolas
  • Garnier, L.
  • Ormaza, Maider
  • Abufager, Paula
  • Robles, Roberto
  • Bocquet, Marie-Laure
  • Ternes, Markus
  • Lorente, Nicolás
  • Limot, Laurent
List of files: Co_bilayer_spin_density.vesta: VESTA file (https://jp-minerals.org/vesta/en/). Corresponds to figure 4a. CHG: spin density of a Co bilayer on Co111 (VASP format). Corresponds to figure 4a. CONTCAR: structure of a Co bilayer on Co111 (VASP format). Corresponds to figure 4a. delta_Eex.agr: grace file (https://plasma-gate.weizmann.ac.il/Grace/). Corresponds to figure 4b. delta_Eex.dat: raw format. Corresponds to figure 4b. Methods for the generation of data: Results from density functional calculations generated with the VASP code., Dataset corresponding to figure 4 of the paper "Atomic-scale spin sensing with a single molecule at the apex of a scanning tunneling microscope" Science 366: 623-627 (2019), DOI: 10.1126/science.aax8222 (http://hdl.handle.net/10261/203083)., Ministerio de Ciencia, Innovación y Universidades: RTI2018-097895-B-C44 European Commission: 766864 MeMo Deutsche Forschungsgemeinschaft: TE 833/2-1 Agence Nationale de la Recherche: ANR-13-BS10-0016 Agence Nationale de la Recherche: ANR-15-CE09-0017 Agence Nationale de la Recherche: ANR-11-LABX-0058 NIE Agence Nationale de la Recherche: ANR-10-LABX-0026 CSC, Peer reviewed

DOI: http://hdl.handle.net/10261/261228
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/261228
HANDLE: http://hdl.handle.net/10261/261228
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/261228
PMID: http://hdl.handle.net/10261/261228
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/261228
Ver en: http://hdl.handle.net/10261/261228
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Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/261482
Dataset. 2022

MICROSATELLITE GENOTYPES FOR RED COLOBUS MONKEYS FROM KIBALE NATIONAL PARK AND FOREST FRAGMENTS AROUND IT [DATASET]

  • Ruiz-López, María José
  • Hitchcock, Arleigh Jane
  • Simons, Noah D.
  • McCarter, Jenneca
  • Chapmane, Colin A.
  • Sarkar, Dipto
  • Omeja, Patrick
  • Goldberg, Tony L.
  • Ting, Nelson
Between 2010 and 2013 we collected red colobus samples from eight sites in or near Kibale National Park. We sampled three sites within Kibale (Kanyawara, Sebitoli, and Mainaro) and five fragments (Isunga, Kamakune, Byara, Lake Nkuruba, and Lake Kasenda). Of the collected samples, some were blood samples from Kanyawara and the rest were fecal samples across the other localities. Fecal samples were collected along transects except for Kanyawara where samples were collected during behavioral surveys from habituated, known individuals. All samples were genotyped at 15 microsatellite loci selected from the human genome and that have been used in previous studies of colobus monkeys Alleles were scored using GeneMapper® Software 5 (Applied Biosystems, Foster City, CA, USA). Heterozyogous genotypes were confirmed in at least two separate reactions and homozygous genotypes were confirmed in at least three separate reactions. Blood samples were genotyped twice, and fecal samples were genotyped from 3 to 6 times (see above). We assigned a consensus genotype per sample across runs and then calculated the error rate per locus, including both false allele and allelic drop out, using the program GIMLET (Valière, 2002)., Date of data collection: Samples collected in 2013, Genotyped between 2013 and 2015.-- Number of variables: 15 micro satellite markers., NIH: TW009237, NSF BCS-1540459., RCMicrosatellitegenotypesKibale, Peer reviewed

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DOI: http://hdl.handle.net/10261/261482
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/261482
HANDLE: http://hdl.handle.net/10261/261482
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/261482
PMID: http://hdl.handle.net/10261/261482
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/261482
Ver en: http://hdl.handle.net/10261/261482
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oai:digital.csic.es:10261/261482

Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/261555
Dataset. 2022

REPOSITORY FILE FOOD2021

FOOD SUPPLEMENTATION OF PARENTS BEFORE HATCHING OF THE YOUNG PROLONGS THE NESTLING PERIOD IN PIED FLYCATCHERS FICEDULA HYPOLEUCA [DATASET]

  • Moreno Klemming, Juan
Dataset of the scientific article “Food supplementation of parents before hatching of the young prolongs the nestling period in Pied Flycatchers Ficedula hypoleuca"., Grants PID2019-106032GB-I00 funded by MCIN/AEI/10.13039/501100011033., Peer reviewed

DOI: http://hdl.handle.net/10261/261555
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/261555
HANDLE: http://hdl.handle.net/10261/261555
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/261555
PMID: http://hdl.handle.net/10261/261555
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/261555
Ver en: http://hdl.handle.net/10261/261555
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oai:digital.csic.es:10261/261555

Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/261845
Dataset. 2022

[DATASET] NUMERICAL MODELS FOR THE SIMULATION OF POTENTIAL CO2 LEAKAGE THROUGH SHALY CAPROCKS OVER GEOLOGICAL ‎TIME SCALES

  • Vilarrasa, Víctor
This dataset contains the input files for numerical assessment of the risk of CO2 leakage from gigatonne-scale geologic carbon storage sites over geological time scales. Numerical models are one-dimensional and evaluate vertical transport of CO2 through a multilayered sedimentary basin comprising a sequence of aquifers and caprocks. The caprocks are assumed to be of either high or low sealing capacity, corresponding respectively to best-case and worst-case scenarios for CO2 migration. Accordingly, the dataset has two folders, each containing data for a leakage assessment scenario: - “Best_case_scenario.gid” in which the considered caprocks have low intrinsic permeability k=1·10-20 m2, high capillary entry pressure p0=2.5 MPa, and high powerlaw exponent n=6 for relative permeabilities - and - “Worst_case_scenario.gid” in which the caprocks have high permeability k=1·10-16 m2, low capillary entry pressure p0=0.1 MPa and low powerlaw exponent n=3 for relative permeabilities. In each folder, there is a file with the name of the folder ended as “_gen.dat” which contains the input data of the model, including material properties, initial and boundary conditions and the time intervals. There is also a file ended as “_gri.dat” that includes the information on the mesh. The file “root.dat” includes the name of the model. To run the simulation, execute the Code_Bright executable “Cb_v9_3.exe” in a folder that contains the three input files and the executable., This dataset contains the input files for numerical assessment of the risk of CO2 leakage from gigatonne-scale geologic carbon storage sites over geological time scales. Numerical models are one-dimensional and evaluate vertical transport of CO2 through a multilayered sedimentary basin comprising a sequence of aquifers and caprocks., Peer reviewed

Proyecto: //
DOI: http://hdl.handle.net/10261/261845
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/261845
HANDLE: http://hdl.handle.net/10261/261845
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/261845
PMID: http://hdl.handle.net/10261/261845
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/261845
Ver en: http://hdl.handle.net/10261/261845
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oai:digital.csic.es:10261/261845

Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/261849
Dataset. 2022

[DATASET] LIPIDOMICS AND METABOLOMICS DATASETS FOR "ADVERSE EFFECTS OF ARSENIC UPTAKE IN RICE METABOLOME AND LIPIDOME REVEALED BY UNTARGETED LIQUID CHROMATOGRAPHY COUPLED TO MASS SPECTROMETRY (LC-MS) AND REGIONS OF INTEREST MULTIVARIATE CURVE RESOLUTION"

  • Jaumot, Joaquim
  • Pérez-Cova, Miriam
  • Tauler, Romà
Files description Raw files for lipidomics and metabolics studies on the impact of arsenic exposure on rice growth. File details on the worksheets lipids_files.xlsx and metabolomics_files.xlsx Files have been organized as follows: Lipidomics 1) Control samples: lip_controls.rar 2) Watering low As exposure: lip_water_1.rar 3) Watering high As exposure: lip_water_1000.rar 4) Soil low As exposure: lip_soil_5.rar 5) Soil high As exposure: lip_soil_50.rar 6) QC samples: lip_qcs.rar Metabolomics (positive ionization mode) 1) Control samples: met_pos_controls.rar 2) Watering low As exposure: met_pos_water_1.rar 3) Watering high As exposure: met_pos_water_1000.rar 4) Soil low As exposure: met_pos_soil_5.rar 5) Soil high As exposure: met_pos_soil_50.rar 6) QC samples: met_pos_qcs.rar Metabolomics (negative ionization mode) 1) Control samples: met_neg_controls.rar 2) Watering low As exposure: met_neg_water_1.rar 3) Watering high As exposure: met_neg_water_1000.rar 4) Soil low As exposure: met_neg_soil_5.rar 5) Soil high As exposure: met_neg_soil_50.rar 6) QC samples: met_neg_qcs.rar, Arsenic Exposure Arsenic was supplied through two main routes: watering with contaminated water or soil containing arsenic. In addition, this new study includes metabolomic as well as lipidomic analysis, in order to have a more global overview of arsenic exposure. For the watering treatment, during the first 11 days, rice was irrigated with Milli-Q water. From that day until harvesting, plants were watered with 1 and 1000 μM of As (V) for the two concentration levels of exposure, and with Milli-Q water for control samples. The lowest concentration was established at 1 μM as it is the limit of the acceptable arsenic concentration in water by European legislation. The upper concentration was set at 1000 μM, a threshold established to ensure that the experiment was performed under sub-lethal arsenic concentration for the plant, based on previous studies. For the soil treatment, two containers were prepared with 1 kg of soil two days before planting. Soil from the container was exposed to two arsenic concentration levels (5 and 50 mg L-1). Once sowing, rice was irrigated the whole growth period with a solution containing 0.001 μM of As (V). The lowest arsenic limit in this treatment was set at 5 mg L-1 as a maximum value of common arsenic leaches without toxic characteristics, although background soil content of arsenic varies between one and 40 ppm according to the US food and drug administration (FDA) report. The highest arsenic limit was established to 50 mg L-1, as a considerably high arsenic content in the soil, slightly above the maximum frequently encountered levels. Lipidomic Analysis The lipidomic analysis was performed using a Waters Acquity UPLC system (Waters Corporation, MA, USA), connected to a Waters LCT Premier orthogonal accelerated time of flight mass spectrometer (Waters), operated in both positive and negative electrospray (ESI) ionization modes. Full scan spectra were acquired from 50 to 1500 Da. The chromatographic column employed was a Kinetex C8 (100 x 2.1 mm, 1.7 μm) (Phenomenex) under the following conditions (already used in [47]): temperature at 30˚C, injection volume at 10 μL, and flow rate at 0.3 mL min-1. Mobile phases selected were (A) MeOH 1mM ammonium formate, and (B) H2O 2mM ammonium formate, both at 0.2% formic acid. The gradient started at 80% A, increased to 90% A in 3 min, from 3 to 6 min remained at 90% A, changed to 99 % A until minute 15, remained constant 1 min, and returned to initial conditions until minute 20. Metabolomic analysis The metabolomic analysis was performed using a Waters Acquity UPLC system connected to a Q-Exactive (Thermo Fisher Scientific, Hemel Hempstead, UK) equipped with a quadrupole-Orbitrap mass analyzer. Electrospray (ESI) was used as an ionization source in both positive and negative ion modes. Full scan mass range was set from m/z 90 to 1000, and all ion fragmentation (AIF) was performed with normalized collision energy (NCE) of 35 eV. The column employed was an HILIC TSK gel amide-80 column (250 x 2.0 mm i.d., 5 μm) provided by Tosoh Bioscience (Tokyo, Japan), under the following experimental conditions (already employed in [45]): flow rate at 0.15 mL min-1, at room temperature, and 5 μL injection volume. Mobile phases were (A) AcN, and (B) 5 mM ammonium acetate, adjusted at pH 5.5 with acetic acid. The gradient employed was: starting conditions at 25% B, then increased until 30% B in 8 min; a 60% B was reached at 10 min, held for 2 min more and then back to 25% B until minute 14 min; lastly, a re-equilibration step was added and from 14 to 20 min at 25% B., This research was funded by the Spanish Ministry of Science and Innovation (MCI, Grant CTQ2017-82598-P) and Severo Ochoa Project CEX2018-000794-S (funded by MCIN/AEI/ 10.13039/501100011033), and supported from the Catalan Agency for Management of University and Research Grants (AGAUR, Grant 2017SGR753). MPC was funded by a predoctoral FPU 16/02640 scholarship from the Spanish Ministry of Education and Vocational Training (MEFP)., Peer reviewed

DOI: http://hdl.handle.net/10261/261849
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/261849
HANDLE: http://hdl.handle.net/10261/261849
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/261849
PMID: http://hdl.handle.net/10261/261849
Digital.CSIC. Repositorio Institucional del CSIC
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Ver en: http://hdl.handle.net/10261/261849
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oai:digital.csic.es:10261/261849

Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/262244
Dataset. 2021

THERMAL ACCLIMATION AND ADAPTATION IN MARINE PROTOZOOPLANKTON AND MIXOPLANKTON [DATASET]

  • Calbet, Albert
  • Saiz, Enric
It is a contribution of the Marine Zooplankton Ecology Group (2017 SGR 87), Proper thermal adaptation is key to understanding how species respond to temperature. However, this is seldom considered in protozooplankton and mixoplankton experiments. In this work, we studied how two heterotrophic dinoflagellates (Gyrodinium dominans and Oxyrrhis marina), one heterotrophic ciliate (Strombidium arenicola), and one mixotrophic dinoflagellate (Karlodinium armiger) responded to warming, comparing strains adapted at 16, 19 and 22 °C and those adapted at 16 °C and exposed for 3 days at 19 and 22 °C (acclimated treatments). Neither CNP contents nor the corresponding elemental ratios showed straightforward changes with temperature, except for a modest increase in P contents with temperature in some grazers. In general, the performance of both acclimated and adapted grazers increased from 16 to 19 °C and then dropped at 22 °C, with a few exceptions. Therefore, our organisms followed the “hotter is better” hypothesis from 16 to 19 °C; above 19 °C, however, the results were variable. Despite the disparity in the responses between species and physiological rates, in general, it seems that 19 °C-adapted organisms performed better than acclimated-only organisms. However, at 22 °C, most species were at the limit of their metabolisms and were unable to fully adapt. Nevertheless, adaptation to higher temperatures conferred some advantages prior to sudden increases in temperature (up to 25 °C) that simulated a heatwave episode. In summary, adaptation to temperature seems to confer a selective advantage to protistan grazers within a narrow range (i.e., ca. 3 °C). Adaptation to much higher temperatures (i.e., 6 °C) does not confer any clear physiological advantage (with few exceptions; e.g., the mixotroph K. armiger), at least within the time frame of our experiments, This research was funded by Grant CTM2017-84288-R by Fondo Europeo de Desarrollo Regional (FEDER)/ Ministerio de Ciencia, Innovación y Universidades—Agencia Estatal de Investigación (AEI), and by Grant PID2020-118645RB-I00 by Ministerio de Ciencia e innovación (MCIN)/AEI/ 10.13039/501100011033 and by “ERDF A way of making Europe”. With the institutional support of the ‘Severo Ochoa Centre of Excellence’ accreditation (CEX2019-000928-S), Para 4 especies: Volumen (µm3/depredador), Tasa crecimiento (µ 1/d), Tasa de ingestion (cells/ind/d), Eficiencia bruta de crecimiento (GGE, %), Peer reviewed

DOI: http://hdl.handle.net/10261/262244
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/262244
HANDLE: http://hdl.handle.net/10261/262244
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/262244
PMID: http://hdl.handle.net/10261/262244
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/262244
Ver en: http://hdl.handle.net/10261/262244
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/262244

Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/263004
Dataset. 2022

MEDITERRANEAN SEAGRASS METABOLIC RATES

  • Hendriks, Iris E.
  • Escolano-Moltó, Anna
  • Vaquer-Sunyer, Raquel
  • Wesselmann, Marlene
  • Flecha, Susana
  • Marbà, Núria
[Geographic location of data collection] Mediterranean basin, seagrass meadows of Posidonia oceanica and Cymodocea nodosa in coastal regions, max. depth 17m., [File List] datacompilation_med_seagrass_metabolic_rates_hendriks.csv, readme.txt., [Relationship between files, if important] readme provides background information for csv datafile., [Additional related data collected that was not included in the current data package] dissolved nutrients for author data (available upon request)., [Description of methods used for collection/generation of data] Data on metabolic rates was extracted from the literature, through a literature search (March 2020) on SCOPUS and the Web of Science using the keywords “Posidonia”, OR “Cymodocea”, OR “Seagrass”, AND “Productivity”, OR “Metabolism” and manually screened for data on metabolism in the Mediterranean basin. This database was extended with unpublished data from the authors and data from dedicated sampling campaigns in 2016 in Mallorca (Western Mediterranean) and 2017 in the Eastern basin (Crete and Cyprus). We compiled data from multiparametric sensors, and data using the benthic chambers methodology with a temporal cover from 1982 to 2019., [Methods for processing the data] For benthic chambers, reported metabolic rates were extracted from the literature. For measurements with multiparametric sensors we used time series of dissolved oxygen (DO, in mg/L), salinity and temperature (C) measured in P. oceanica and/or C. nodosa meadows. With the time series of dissolved oxygen (DO), temperature (°C) and salinity we calculated the metabolic rates of the seagrass habitats using a modification of the model of Coloso et al., (2008) implemented in MATLAB (version 7.5. the Mathworks Inc.) explained in detail in Vaquer-Sunyer et al., (2012). Wind speed was estimated at each station for the same interval as oxygen measurements to predict k660 (air-sea gas transfer velocity for oxygen at 20º C and salinity 35) based on Kihm et al., (2010) and Cole et al., (1998). Schmidt number equations for seawater according to Wanninkhof (1992) were used for the k calculation from k660. As the cubic model equals the model proposed by Wanninkhof et al., (1999) for short-term winds this parameterization by Kihm et al., (2010) is used. Meteorological data (windspeed) for the deployment period was obtained from the Agencia Estatal de Meteorología (AEMET) for the stations in Mallorca, from the Cyprus Department of Meteorology for Cyprus sampling sites and from the Hellenic National Meteorological Service for the locations in Crete.--, [Standards and calibration information] Sensors were calibrated before each deployment; oxygen sensors (Hach LDOTM) were calibrated using the water saturated air method calibration. For validation of salinity, specific conductance calibrations were performed with 50.000uS/cm buffers. For depth measurements, pressure readings were corrected for specific conductance., [Environmental/experimental conditions] Coastal seagrass meadows with max. 17m depth., [Describe any quality-assurance procedures performed on the data] Negative respiration rates (oxygen production) at night for sensor deployments, were discarded as this was interpreted as an indication for the influence of lateral advection and passing of different water masses. Therefore, we trimmed the dataset to contain only measurements where this influence was not detected. Respiration rates were notated as oxygen consumption (positive values, literature reports differ in notation)., [People involved with sample collection, processing, analysis and/or submission, please specify using CREDIT roles https://casrai.org/credit/: Conceptual idea IEH and NM. Data collection in the field MW, SF, RVS, IEH, NM. Literature compilation IEH and AEM. Data curation AEM and IEH., [Data-specific information] 1. Number of variables: 21. 2. Number of cases/rows: 151. 3. Variable List: Reference, Journal, Methodology, Year, Month, Season, Site, Region, Latitude, Longitude, Species, Temperature_C, Salinity, Depth, NCP, NCP_SD, CR, CR_SD, GPP, GPP_SD, Wind_m_s. 4. Missing data codes: Empty cell. 5. Specialized formats or other abbreviations used: C (degree Celcius), SD (Standard Deviation), m_s (Meter per second). Depth in meter. Latitude and Longitude in Decimal Degrees (DD)., The data is a compilation of information on metabolic rates of Mediterranean seagrasses obtained by two different methodologies (benthic incubations and multiparametric sensors) from published literature and data from the authors., The Spanish Ministry of Economy and Competitiveness (Project MEDSHIFT, CGL2015-71809-P). Project RTI2018-095441-B-C21 (SUMAECO) from the Spanish Ministry of Science, Universities and Innovation. SF was supported by a “Margalida Comas” postdoctoral scholarship, funded by the Balearic Islands Government. Also funding was received from “projectes de recerca La Caixa en àrees estratègiques” (2018) through a grant to IEH at the University of the Balearic islands., datacompilation_med_seagrass_metabolic_rates_hendriks.csv, readme.txt, Peer reviewed

DOI: http://hdl.handle.net/10261/263004
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/263004
HANDLE: http://hdl.handle.net/10261/263004
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/263004
PMID: http://hdl.handle.net/10261/263004
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/263004
Ver en: http://hdl.handle.net/10261/263004
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/263004

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