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141 results for “isotopic composition”
Carbon and nitrogen content and stable isotope compositions from biota samples from lagoon sites along the Alaska Beaufort Sea coast, 2018-ongoing
Stable isotopic composition can be used to differentiate between predominantly marine and terrestrial food sources in nearshore marine food webs. The Beaufort Lagoon Ecosystems LTER (BLE LTER) Core Program employs spatial and temporal sampling regimes to track shifts in diet, both seasonally (ice cover, ice break-up, and open water), and spatially among lagoons along the Alaskan Beaufort Sea coast. Ice coring, net tows, ponar grabs, and trawls are employed to collect organisms associated with the sea-ice interface, the water column, and the benthos respectively. Tissues are analyzed for stable isotopic composition as well as organic carbon and nitrogen content.
Carbon and nitrogen content and stable isotope compositions from particulate organic matter samples from lagoon, river, and open ocean sites along the Alaska Beaufort Sea coast, 2018-ongoing
Multiple water types (river, lagoon, ocean) from the North Slope of Alaska and nearshore Beaufort Sea are sampled seasonally by the Beaufort Lagoon Ecosystems LTER (BLE LTER) Core Program to investigate biogeochemical linkages between terrestrial, lagoon, and open ocean ecosystems. Water samples are collected during full ice cover (April), ice break-up (mid-June to early July), and open water (late July and August) periods, and analyzed for particulate organic carbon (POC) and particulate organic nitrogen (PON) content and stable isotopic composition.
Carbon and nitrogen content and stable isotope composition from sediment organic matter from lagoon sites along the Alaska Beaufort Sea coast, 2018-ongoing
Multiple sediment samples from lagoons along the nearshore Beaufort Sea are sampled seasonally by the Beaufort Lagoon Ecosystems LTER (BLE LTER) Core Program to investigate biogeochemical linkages between terrestrial, lagoon, and open ocean ecosystems. Sediment samples are collected during full ice cover (April), ice break-up (mid-June to early July), and open water (late July and August) periods, and analyzed for carbon and nitrogen content and stable isotopic composition.
Isotopic Composition of Net Ecosystem CO2 Exchange at Harvard Forest EMS Tower since 2011
This archive features long-term measurements of the eddy and storage fluxes of 16O12C16O, 16O13C16O, and 18O12C16O at the Harvard Forest EMS flux tower. Provided are the individual isotopologue fluxes, the total CO2 flux, the δ13C and δ18O isofluxes, and various ancillary flux and environmental data. The data are described in Wehr et al (2013), Long-term eddy covariance measurements of the isotopic composition of the ecosystem–atmosphere exchange of CO2 in a temperate forest, Agricultural and Forest Meteorology 181, 69–84. They are also analyzed in Wehr and Saleska (2015), An improved isotopic method for partitioning net ecosystem–atmosphere CO2 exchange, Agricultural and Forest Meteorology 214-215, 515–531, as well as in Wehr et al 2016, Seasonality of Temperate Forest Photosynthesis and Daytime Respiration, Nature (in press). The eddy (iso)fluxes were measured by eddy covariance (EC), with a 30- or 35-minute integration period on a 40- or 45-minute duty cycle (the precise duty cycle was changed during the record to accommodate various synergistic measurement campaigns). The storage fluxes were measured as the increase in storage below 29 m during the EC integration period, based on vertical integrations over 7 air sampling heights on the tower (0.2, 1.0, 7.5, 12.7, 18.1, 24.1, 29.0 m, prior to July 3, 2012), or over 6 air sampling heights on the tower (0.2, 1.0, 7.5, 12.7, 18.1, 29.0 m, after July 3, 2012). Some periods are missing at regular intervals because the system was being used for other measurements, not reported here. Corrected and uncorrected versions of the eddy (iso)fluxes are provided; the corrections account for high-frequency signal attenuation, and were made by comparing w-CO2 and w-T cospectra. The precise method is novel and complex and is described, along with all further details of the measurements, in Wehr et al (2013), Long-term eddy covariance measurements of the isotopic composition of the ecosystem–atmosphere exchange of CO2 in a temperat
Seawater chromium concentrations and isotope compositions in the Southern Ocean during the austral summer of 2016/2017, on board the Antarctic Circumnavigation Expedition (ACE).
<p><strong>Dataset abstract</strong></p> <p>Dissolved seawater chromium (Cr) concentrations and stable isotope compositions measured on samples collected with a trace metal clean rosette system in the Southern Ocean. Stations TM 7 to TM 12 reflect a north-south transect from Hobart, Tasmania to Mertz Glacier in Antarctica. Stations TM 14 and TM 15 neighbour the Balleny Islands. Stations TM 18 and TM 20 are located in the Drake Passage. Water samples were collected down to a depth of 1000 metres. The water was filtered in a class 100 clean container aboard the ship through pre-rinsed Supor Acropak capsule filters (0.2 um). Subsequently the samples were acidified and stored at a pH < 2 for several months prior to analysis. Reported values therefore represent bulk seawater chromium (Cr III and Cr VI). The data was obtained using the double-spike technique.</p> <p><strong>Dataset contents</strong></p> <ul> <li>ace_chromium_isotope_concentration.csv, data file, comma-separated values</li> <li>data_file_header.txt, metadata, text format</li> <li>README.txt, metadata, text format</li> </ul> <p><strong>Dataset license</strong></p> <p>This chromium concentration and isotope composition dataset is made available under the Creative Commons Attribution 4.0 International License (CC BY 4.0) whose full text can be found at <a href="https://creativecommons.org/licenses/by/4.0/">https://creativecommons.org/licenses/by/4.0/</a></p>
Particulate organic carbon and particulate organic nitrogen concentrations and stable isotope composition of seawater sampled during the Antarctic Circumnavigation Expedition (ACE) during the Austral Summer of 2016/2017.
<p><strong>Dataset abstract</strong></p> <p>This dataset contains particulate organic carbon and particulate organic nitrogen concentrations and stable isotope composition (delta 13C and delta 15N) sampled during the Antarctic Circumnavigation Expedition (ACE) Leg 1-3. Water samples were collected from the underway seawater supply every 3 hours, filtered onto pre-combusted glass fibre filters, acidified to remove inorganic compounds and analysed for both elements on the same filter using an elemental analyser. These samples provide an estimate of the organic carbon and organic nitrogen concentration and carbon and nitrogen stable isotope composition of living and detrital particles > 0.7 micrometres in size.</p> <p><strong>Dataset contents</strong></p> <ul> <li>README.txt, metatdata, text</li> <li>data_file_header.txt, metadata, text</li> <li>ace_uw_poc_pon_blanks_20200512CURRSGCMR.csv, data file, comma-separated values</li> <li>ace_uw_poc_pon_20200512CURRSGCMR.csv, data file, comma-separated values</li> </ul>
Seawater dissolved chromium concentration, redox speciation, and stable isotope composition in the North Pacific Ocean
<p>Dissolved seawater chromium concentrations, redox speciation, and stable isotope composition were measured on samples collected in the North Pacific Ocean. Samples were collected over diel cycles (2 for stations 1-5, 1 for station 6) on board the RV Kilo Moana cruise KM1713 from Seward Alaska to Honolulu Hawai’i. Sampling stations spanned the subarctic North Pacific (stations 1 & 2), the dynamic subarctic-subtropical convergence zone (stations 3 and 4) and the subtropical North Pacific (stations 5 and 6). Chromium was enriched from filtered samples by Mg(OH)<sub>2</sub> co-precipitation and analyzed by MC-ICP-MS using either isotope dilution (Cr redox speciation) or double spike methodology.</p>
SIC01 Isotopic composition of select archived soil cores from Konza Prairie
The concentration and isotopic composition of soil carbon and nitrogen were measured from select archived soil cores originally collected for the NSC01 dataset using an isotope ratio mass spectrometer coupled with an elemental analyzer. These soil cores were collected from the lowlands (25 cm depth) of four experimental watersheds in 1982, 1987, 2002, 2010, and 2015. The four experimental watersheds are 001d, n01b, 020b, and n20b.
iNRACM: Incorporating 15N into the Regional Atmospheric Chemistry Mechanism (RACM) for assessing the role photochemistry plays in controlling the isotopic composition of NOx, NOy, and atmospheric nitrate
<p><sup>15</sup>N compounds and reactions were incorporated into Regional Atmospheric Chemistry Mechanism (RACM), based on recent experimental or calculated values of isotope fractionation factors (α), to simulate δ<sup>15</sup>N values in NO<sub>y</sub> compounds.</p>
Processed model output of the climate simulation in the study: The effects of diachronous surface uplift of the European Alps on regional climate and the isotopic composition of precipitation (δ18Op) [Boateng et al.]
<p><strong>The geodynamic evolution of the Alps suggests that the Alps did not rise monotonically due to the different post-collisional processes such as slab break-off. However, understanding such subsurface dynamics would require adequate knowledge about its surface uplift history. Stable isotope paleoaltimetry methods are widely used to infer past surface elevation using geologic archives. However, its accurate interpretation relies on attributing the extracted isotopic signal from proxies to surface uplift despite other influences such as climate. To resolve this issue, topographic sensitivity experiments across the Alps are used to investigate the impacts of the diachronous surface uplift on regional climate and δ18Op. The Atmospheric General Circulation Model ECHAM5 with water isotope tracking capabilities (ECHAM5-wiso) is used to simulate the climate with varied topographic scenarios. We present the processed (long-term means) model output of the relevant climate variables (i.e δ18Op, near-surface temperature, precipitation amount, near-surface meridional and zonal winds, mean sea level pressure, and elevation) in response to the changes in topography. The file names are representative of the topographic scenarios used for the simulations. For example, the file “W2E1.nc” is the model output produced by a topographic scenario in which the topography across the west-central Alps was set to 200% of its modern height, and the Eastern Alps were kept at 100%. The “CTL.nc” file contains model output from the control simulation that uses present-day topography. The datasets for instance can be used to select far-field sampling points for the δ-δ paleoaltimetry method that are not significantly affected by the topographic changes.</strong></p>
Atmospheric clumped O2 isotope composition simulation data and analysis scripts from EMAC/aMC models
<p>This publication contains source code, data and analysis scripts/results of the simulations presented in the following manuscript:</p> <blockquote> <p>Laskar, A.H., G.A. Adnew, S.S. Gromov, R. Peethambaran, B. Steil, J. Lelieveld, T. Blunier and T. Röckmann (2022). "Large variations in atmospheric oxidants and temperature during the Holocene" (in review)</p> </blockquote> <p> </p> <p><strong>EMAC simulations analysis</strong></p> <p>The analysis contains integrals of species burdens and other atmospheric physicochemical parameters obtained with the clumped isotopes of oxygen (CIO)-enabled ECHAM/MESSy Atmospheric Chemistry model (EMAC, see <a href="https://www.messy-interface.org">MESSy consortium website</a> for more information) model in various climate states. Simulations were performed in 2021–2022 at the <a href="https://www.dkrz.de">German Climate Computing Centre</a> (DKRZ) with the support of the <a href="https://www.palmod.de">PalMod project</a>.</p> <p>Analysis data is stored in human/machine-readable file <code>D36-EMAC-analysis.dat</code>, please refer to its header for variables description, etc.</p> <p>Additional (to those presented in the manuscript) analysis plots from EMAC data analysis are available in <code>D36-EMAC-analysis.vsz</code> (see the hardcopy in <code>D36-EMAC-analysis.pdf</code>) prepared using the <a href="https://veusz.github.io">Veusz</a> software.</p> <p> </p> <p><strong>2BM/MC (two-box Monte-Carlo) model code, simulation data and analysis</strong></p> <p>2BM/MC code/simulation setup is implemented within the advanced Monte-Carlo framework (aMC) and is available in the <a href="https://gitlab.com/sergey.gromov/amc/-/tree/vpCIO">respective repository</a>. A copy of the source code used to perform simulations is provided here (see <code>aMC-vpCIO.tar.gz</code> archive).</p> <p>2BM/MC output is stored in the <a href="https://www.unidata.ucar.edu/software/netcdf/">netCDF format</a> (ver. 4) and can be read in by any compatible software. The output contains probe statistics (reference <em>probed</em> distributions of the variables) in <code>vpCIO-probe_stat-*.nc</code> and resulting statistics (distributions <em>matching</em> given criteria, i.e. changes to the Δ36 signature vs. PD conditions) in <code>vpCIO-delta-*.nc</code> files, respectively.</p> <p>We use <a href="https://ferret.pmel.noaa.gov">NOAA Ferret</a> software to derive additional statistics of the third parameter (viz. average STE (<em>S</em>) changes) over the obtained 2D frequency histograms of other parameters (viz. changes to equilibration rate (<em>Req)</em> and temperature (<em>Teq</em>)). The scripts exemplifying this calculation are presented in <code>D36-vpCIO-analysis__proc*</code> files, which output results/overview plots in <code>vpCIO-delta-*__proc.nc</code> and <code>vpCIO-delta-*.gif</code> files.</p> <p>The analysis of the 2BM/MC simulation is available in <code>D36-vpCIO-analysis.vsz</code> script (see the hardcopy in <code>D36-vpCIO-analysis.pdf</code>) prepared using the <a href="https://veusz.github.io">Veusz</a> software. Note that some plots require the abovementioned third-parameter statistics as input.</p> <p><strong>Performing simulations with 2BM/MC</strong></p> <p>In order to perform simulations (e.g. with altered parameters), please follow the <a href="https://gitlab.com/sergey.gromov/amc/-/tree/vpCIO#integrating-your-code-building-executing">respective guide</a> for and build the <code>aMC-vpCIO</code> model. A typical sequence of shell commands to build and run 2BM/MC (which is referred to as <code>vpCIO</code> generic model within the <code>aMC</code>) is:</p> <pre><code># clone the distribution and check-out `vpCIO` branch or particular commit referenced in the repository history [user@pc]/~> git clone https://gitlab.com/sergey.gromov/amc.git [user@pc]/~> cd amc [user@pc]/~/amc> git checkout vpCIO # or unpack the source code available in this publication: [user@pc]/~> tar -xvf `aMC-vpCIO.tar.gz` [user@pc]/~> cd amc # build the aMC/vpCIO model executable # (note that you need at least a GCC or Intel compiler suite and respective netCDF v.4 library Fortran interface available in your environment): [user@pc]/~/amc> make vpCIO # adjust model setup (see the `vpCIO/amc.nml` namelist) ... # perform simulation [user@pc]/~/amc> cd vpCIO [user@pc]/~/amc/vpCIO> ./xamc # calculate additional statistics/produce overview with NOAA Ferret: [user@pc]/~/amc/vpCIO> ferret -gif -script D36-vpCIO-analysis__proc.jnl MH [user@pc]/~/amc/vpCIO> ./D36-vpCIO-analysis__proc</code></pre> <p>Note that output files contain the build timestamp and repository commit hash for the code used in the simulation, e.g.:</p> <pre><code>[user@pc]/~/amc/vpCIO> ncdump -h ./vpCIO-delta-dMH.nc | grep 'build' :build = "vpCIO@https://gitlab.com/sergey.gromov/amc__aMC_v1.9-110-g2566229@2022-12-09T16:43:12+01:00__built@2022-12-09T16:48:03+01:00__<user>@<email.com>" ;</code></pre> <p> </p> <p>Please contact Sergey Gromov ( sergey.gromov (at) mpic.de ) for additional information and access to the original experiment data.</p> <p> </p>
Surface sediment Nd isotope compositions from the Ross Sea, Antarctica
<p>The dataset contains seafloor surface sediment neodymium isotope compositions for several sites in the Ross Sea, Antarctica. The sediments were supplied by Helen Bostock from NIWA, Wellington, New Zealand, plus two samples from International Ocean Discovery Program (IODP) Expedition 374.</p>
Data for Water deficit and potassium affect carbon isotope composition in cassava bulk leaf material and extracted carbohydrates
<p>This repository contains data and scripts to reproduce results that are presented in the manuscript: Van Laere, J., Merckx, R., Hood-Nowotny, R., Dercon, G. (2023) Water deficit and potassium affect carbon isotope composition in cassava bulk leaf material and extracted carbohydrates. <em>Front. Plant Sci</em>. 14:1222558 doi: 10.3389/fpls.2023.1222558</p>
Organic and inorganic carbon concentration and stable isotope composition in poorly drained agricultural soils in Iowa, USA
We measured soil organic carbon (SOC) and inorganic carbon (carbonate) in samples collected along topographic gradients in agricultural fields in Iowa, USA, in 2018. We also measured stable isotopes of SOC, soil nitrogen, and carbon in respired CO2 to provide additional context for organic matter dynamics. Additional physical, chemical, and hydrologic variables were measured on these samples and in the field sites to understand mechanisms underlying patterns in soil organic and inorganic carbon.
Respiration, isotope composition, and carbon source partitioning from incubations of soil amended with litter and isotope-labeled lignin
We incubated 10 forest soils (collected from sites across North America, including the Luquillo LTER/CZO) in the laboratory for over two years to quantify the decomposition of carbon derived from added litter and lignin, as well as from extant soil organic matter. Each soil was subjected to two substrate addition treatments: a) litter derived from a C4 grass precipitated with 13C-enriched lignin, or the same C4 grass litter was precipitated with natural-abundance lignin. The concentrations and delta13C composition of carbon dioxide produced from each soil were measured periodically over time and partitioned into sources (soil organic matter, litter, and added lignin) using isotope mixing models. The methods and results are described in detail by a manuscript in Ecology (Hall et al., 2020).
Total tree ring widths, earlywood ring widths, latewood ring widths, and stable carbon isotope composition of tree rings from 1979-2003 for 18 trees (3 trees/site for 6 sites) located in the 2004 burn along the Steese Highway.
This dataset contains annual raw ring width measurements, earlywood width, latewood width, and annual stable carbon isotope composition from 1979-2003 for 18 trees. A total of 6 sites were sampled. Ring widths were measured using WinDendro (resolution 0.001 mm) on two radii per stem disk collected 1.3 m along stem. Data is the average of the two radii measurments in each year for each tree. Accuracy of ring width dates were checked by crossdating using COFECHA. We manually separated annual rings from the outer twenty-five years
Major and trace bulk sample and micro-XRF geochemistry, carbon and oxygen stable isotope compositions of magmatic and sedimentary rocks from Hovedøya Island, Oslo fjord, Norway.
<p>This data set reports on the methodologies and results of geochemical analysis carried out on samples of magmatic rock, calcite and sedimentary rocks of Hovedoya Island, Oslo fjord, Norway, in the framework of the publication by Poppe et al. (2020; <em>Geochemistry, Geophysics, Geosystems</em>; <a href="https://doi.org/10.1029/2019GC008685">https://doi.org/10.1029/2019GC008685</a>). The major and trace element bulk sample geochemical analysis was carried at the Laboratoire G-Time, Université Libre de Bruxelles, Brussels (V. Debaille), the micro-XRF mapping and line scanning, was carried out at the laboratory of the Analytical and Environmental Geo-Chemistry (AMGC) group at the Vrije Universiteit Brussel (VUB), Brussels (N.J. de Winter, S. Poppe) and the stable isotope composition analysis was carried out as well at the AMGC laboratory (S. Poppe, S. Goderis), supervised by P. Claeys and M. Kervyn, in collaboration with P. Boulvias. Data sheets are provided in .csv or .xlsx format and compressed folders containing .TIF images of µXRF elemental maps are attached. This data set also contains the complete data sets obtained for the construction of calibration curves for µXRF line scan analysis of rock samples of magmatic composition at the AMGC laboratory at VUB.</p>
Figure 5 in Variations in trophic niches of generalist predators with plant community composition as indicated by stable isotopes and fatty acids
Figure 5. Principal components analysis of the relative abundance (mol %, logit- transformed) of individual NLFAs of Trochosa ruricola using body size (small, large), flooding index (FI), plant species richness (SR), plant functional group richness (FG), presence of grasses (Gr), legumes (Leg), small herbs (SH) and tall herbs (TH) as supplementary variables.
Figure 4 in Variations in trophic niches of generalist predators with plant community composition as indicated by stable isotopes and fatty acids
Figure 4. Variations in δ15N signatures of Trochosa ruricola as affected by flooding index (P = 0.04, R2 = 0.12) and body size (small, large; P <0.01).
Figure 1 in Variations in trophic niches of generalist predators with plant community composition as indicated by stable isotopes and fatty acids
Figure 1. Variations in δ15N and δ13C signatures of Harpalus rufipes (black) and Trochosa ruricola (pink) across the study site of the Jena Experiment.
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