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123 results for “carbon cycle”
Dataset for "Structural complexity and benthic metabolism: resolving the links between carbon cycling and biodiversity in restored seagrass meadows"
<p>This dataset accompanies the article "Structural complexity and benthic metabolism: resolving the links between carbon cycling and biodiversity in restored seagrass meadows" accepted for publication in Biogeosciences (https://doi.org/10.5194/bg-2023-173). The dataset includes benthic fluxes and biodiversity data in from bare sediments, restored <em>Zostera marina</em> and a natural <em>Z. marina</em> meadow collected in Gåsö, Sweden (58.2325, 11.3984) between July 05 - July 20, 2022. </p>
Data and code for "Carbon cycle instability for high-CO2 exoplanets: implications for habitability"
<p>Data supporting "Carbon cycle instability for high-CO2 exoplanets: implications for habitability," Graham and Pierrehumbert, 2024, <em>Astrophysical Journal </em>(under review at time of upload)</p> <ul> <li>Global climate model (GCM) simulation output necessary to reproduce figures in paper. Netcdf (.nc) format. <ul> <li>For simulations receiving instellation of 1250 W m-2, the format is atmos_monthly_[co2 mixing ratio]ppmv_S1250.nc</li> <li>For other simulations, the format is: atmos_monthly_[co2 partial pressure]bar_S[675, 750, 800, or 1000].nc</li> </ul> </li> <li>Continental configuration land mask used in GCM simulations. Netcdf (.nc) format. <ul> <li>land.nc</li> </ul> </li> <li>Python scripts to<br> <ul> <li>post-process climate simulation data to calculate global weathering rates according to WHAK or MAC weathering <ul> <li>isca_weathering_calc.py</li> </ul> </li> <li>reproduce all model-based figures <ul> <li>figures 1-8: isca_plot_maker.py</li> <li>figure 9: isca_weathering_calc.py</li> </ul> </li> </ul> </li> </ul>
Data set for the study "Assessing the lifetime of anthropogenic CO2 and its sensitivity to different carbon cycle processes"
<p>This repository contains the data necessary to reproduce the results of the paper: <br>"Assessing the lifetime of anthropogenic CO<sub>2</sub> and its sensitivity to different carbon cycle processes" <br><a href="https://doi.org/10.5194/bg-22-2767-2025" target="_blank" rel="noopener">https://doi.org/10.5194/bg-22-2767-2025</a></p> <h3><strong>Data organization:</strong></h3> <p>The Zenodo upload is organized as the following inside of <code>results.zip</code>:</p> <ul> <li>Data analysis and figure generation are given by "*.pynb" and "*.m" files<br><br></li> <li>Data files as NetCDF output are organized with the following structure inside of <code>data</code>:<br><br> <ul> <li><strong>Experiment</strong>: <code>REF</code>, <code>noLAND</code>, <code>noWEATH</code>, <code>ECS2</code>, <code>ECS4</code>, <code>intCH4</code>, <code>PATH1</code>, <code>PATH2</code>, and <code>PULSE</code><br><br> <ul> <li><strong>Emissions scenario</strong>: <code>0_gtc</code>, <code>500_gtc</code>, <code>1000_gtc</code>, <code>2000_gtc</code>, <code>3000_gtc</code>, <code>4000_gtc</code>, and <code>5000_gtc</code><br><br> <ul> <li><strong>Component</strong>: atmosphere (<code>atm</code>), land (<code>lnd</code>), ocean (<code>ocn</code>), biogeochemistry (<code>bgc</code>), and the carbon cycle (<code>co2</code>)<br> <ul> <li>Note: for <code>intCH4</code>, there is another file concerning methane (<code>ch4</code>)</li> <li>Note: surface ocean pH and surface ocean DIC were not part of the standard output in the original CLIMBER-X model. Instead, these variables were calculated during post-processing using 2D spatial data. Since the 2D data was only output every 1 kyr, the first millennium of data was missing. To address this, we re-ran the experiments with surface ocean pH and DIC included in the output for the first 1 kyr. This is why there are additional individual files for pH, DIC, and the Revelle factor (see "fig5_7_8_9.ipynb" for further details).<br><br></li> </ul> </li> <li><strong>File type</strong>: for each component, files are divided into timeseries (<code>*_ts.nc</code>) or 2D data with a 1 kyr output frequency (<code>*.nc</code>)<br> <ul> <li>Note: due to size constraints of the Zenodo repository, only some 2D spatial data presented in the publication (for the <code>REF</code> experiment) is available. However, this is not an exhaustive dataset. For inquiries regarding additional data, please contact the corresponding author to explore potential availability.</li> </ul> </li> </ul> </li> </ul> </li> </ul> </li> </ul>
Dataset from "The Land-to-Ocean Loops of the Global Carbon Cycle" article
<p>Dataset of Tables S1, S2 and S3 from the paper entitled "The Land-to-Ocean Loops of the Global Carbon Cycle".</p>
Data and code for "Relationships between aboveground plant traits and carbon cycling in tundra plant communities"
<p><strong>Paper</strong></p> <p>See the preprint for more detailed description of the performend analyses <a href="https://doi.org/10.1101/865899">here.</a></p> <p><strong>Description of subdirectories</strong></p> <p>The structure of this repository loosely follows that recommended by <a href="https://doi.org/10.1371/journal.pcbi.1005510">Wilson et al. 2017</a>.</p> <p><em>docs</em></p> <p>Contains data documentation and metadata.</p> <p><em>data</em></p> <p>Holds raw, unedited data</p> <p><em>src</em></p> <p>Contains analysis scripts. The src/new_analyses.R script generates all the figures for this project. The other scripts prepare the data for analysis, and must be run before src/new_analyses.R</p> <p><em>results</em></p> <p>Contains all analysis results, cleaned, analysis-ready data, figures, etc. Some of the figures (such as measurement schematics) have been generated by hand, and are thus not linked to any scripts.</p>
Limited legacy effects of extreme multi-year drought on carbon and nitrogen cycling in a mesic grassland
<p>The intensification of drought throughout the US Great Plains has the potential to have large impacts on grassland functioning, as has been shown with dramatic losses of plant productivity annually. Yet, we have a poor understanding of how grassland functioning responds after drought ends. This study examined how belowground nutrient cycling responds after drought and whether legacy effects persist post-drought. We assessed the two-year recovery of nutrient cycling processes following a four-year experimental drought in a mesic grassland by comparing two different growing season drought treatments - chronic (each rainfall event reduced by 66%) and intense (all rain eliminated until 45% of annual rainfall was achieved) – to the control (ambient precipitation) treatment. At the beginning of the first growing season post-drought, we found that in situ soil CO<sub>2</sub> efflux and laboratory-based soil microbial respiration were reduced by 42% and 22% respectively in the intense drought treatment compared to the control, but both measures had recovered by mid-season (July) and remained similar to the control treatment in the second post-drought year. We also found that extractable soil ammonium and total inorganic N were elevated throughout the growing season in the first year after drought in the intense treatment. However, these differences in inorganic N pools did not persist during the growing season of the second year post-drought. The remaining measures of C and N cycling in both drought treatments showed no post-drought treatment effects. Thus, although we observed short-term legacy effects following the intense drought, C and N cycling returned to levels comparable to non-droughted grassland within a single growing season regardless of whether the drought was intense or chronic in nature. Overall, these results suggest that key aspects of C and N cycling in mesic tallgrass prairie do not exhibit persistent legacies from four years of experimentally-induced drought.</p>
Large uptake of atmospheric OCS observed at a moist old growth forest: Controls and implications for carbon cycle applications
<p>This repository contains all data for the manuscript by Rastogi et al., titled "<strong>Large uptake of atmospheric OCS observed at a moist old growth forest: Controls and implications for carbon cycle applications</strong>". This manuscript has been accepted for publication in the Journal of Geophysical Research: Biogeosciences</p> <p> </p>
Carbon-latitude analysis of the ocean carbon cycle computed from NEMO-Medusa
<p>NetCDF files containing carbon-latitude stream functions computed from the coupled physical-biogeochemical model NEMO-Medusa. The stream functions have been computed for the last years of a historical run and the first years of the RCP 8.5 scenario run (2000-2009). The dataset includes a climatology of the most important tracers, the computed meridional carbon transports in the ocean, and volume distribution in the carbon-latitude space.</p>
Dataset for "Fire in lichen-rich subarctic tundra changes carbon and nitrogen cycling between ecosystem compartments but has minor effects on stocks"
<p>Data that support the findings of the study "Fire disturbance promotes biodiversity of plants, lichens and birds in the Siberian subarctic tundra".</p>
Supplementary material for "Including filter-feeding gelatinous macrozooplankton in a global marine biogeochemical model: model-data comparison and impact on the ocean carbon cycle"
<p>Supplementary material for "Including filter-feeding gelatinous macrozooplankton in a global marine biogeochemical model: model-data comparison and impact on the ocean carbon cycle". </p> <p>Clerc, C., Bopp, L., Benedetti, F., Vogt, M., and Aumont, O.: Including filter-feeding gelatinous macrozooplankton in a global marine biogeochemical model: model-data comparison and impact on the ocean carbon cycle, EGUsphere [preprint], https://doi.org/10.5194/egusphere-2022-1282, 2022.</p> <p>Three directories can be downloaded:</p> <p><strong>DataOBS</strong> : AtlantECO [WP2] – Traditional microscopy dataset – Thaliacea (Salpida+Doliolida+Pyromosomatida) abundance and biomass concentration data, presented in Clerc et al. (2022). </p> <p><strong>FigPaper </strong>: Source code and .nc files for the figures presented in Clerc et al. (2022) (https://doi.org/10.5194/egusphere-2022-1282). </p> <p><strong>MY_SRC_PISCES_NEMO_3.6 :</strong> Additional fortran routines for the compilation of PISCES-FFGM, the model developed for Clerc et al. (2022), from NEMO-3.6 (https://www.nemo-ocean.eu)</p>
MAGICC7 SSP carbon cycle output using AR6 tuning
<p>Output from the MAGICC7 carbon cycle model under the SSP scenarios with the configuration used in IPCC AR6. For further details on MAGICC and expectations re use of data and the model, please see https://magicc.org/download/magicc7.</p>
Towards alternative solutions for flaring : life cycle assessment and carbon substance flow analysis of associated gas conversion into C3 chemicals
<p>Supplementary material and used data for the publication.</p>
Data for "Coupled carbon and nitrogen cycling regulates the cnidarian-algal symbiosis"
<p>Raw data associated with the publication "Coupled carbon and nitrogen cycling regulates the cnidarian-algal symbiosis". Data associated with individual figures and corresponding analyses are uploaded as separate tabs in the Excel file. Radecker_etal_NanoSIMS.zip contains the individual NanoSIMS images (names according to treatment). Radecker_etal_Chlorophyll_Fluorescence_Images.zip contains exemplary photographs of chlorophyll fluorescence of Aiptasia (names according to treatment).</p> <p> </p> <p> </p>
Limited legacy effects of extreme multi-year drought on carbon and nitrogen cycling in a mesic grassland
Open the record for dataset details and reuse information.
Shifts in plant composition mediate grazing effects on carbon cycling in grasslands
<p> </p> <p>Carbon cycling in grasslands can be impacted by livestock grazing, partially as an indirect result of herbivory-induced compositional shifts in the plant community. However, the underlying mechanisms of how these shifts impact carbon cycling are not well documented.</p> <p>We conducted a long-term grazing experiment with four sheep stocking rates in the semi-arid grasslands of Inner Mongolia, China, to examine grazing effects on the ratio of C<sub>3</sub> to C<sub>4</sub> species (C<sub>3</sub>:C<sub>4</sub>), shoot biomass, root biomass, root:shoot, soil respiration, soil C, soil N, and soil C:N between 2014 and 2018. We explored the responses of these carbon metrics to C<sub>3</sub>:C<sub>4</sub> under different grazing treatments and the mechanisms driving grazing-induced carbon loss using structural equation models.</p> <p>Livestock grazing directly shifted plant community composition (i.e., increasing C<sub>3</sub>:C<sub>4</sub>) and reduced vegetation carbon (i.e., shoot biomass), whereas grazing effects on belowground carbon were mediated by the interactions of the soil profile (i.e., depth-dependence) and year-to-year variation (e.g., rainfall regulation). Grazing-induced increases in C<sub>3</sub>:C<sub>4 </sub>suppressed soil carbon loss by inhibiting the rate of soil respiration. Furthermore, grazing intensity indirectly altered these relationships. Specifically, C<sub>3</sub>:C<sub>4 </sub>was<sub> </sub>positively related to shoot biomass and negatively associated with root:shoot, soil C, and soil N, whereas these relationships were only significant in no-grazed plots. Meanwhile, soil respiration was negatively associated with C<sub>3</sub>:C<sub>4</sub>, soil C, soil N, and soil C:N, but a positive relationship with shoot biomass; these relationships were significant only in grazed-plots.</p> <p><a> <i>Synthesis and applications.</i></a> Our findings emphasize the functional linkages between community characteristics and ecosystem processes, i.e. shifts in plant community composition play a key role in regulating grassland carbon cycling. These results provide a useful field-observed resource for model development and could improve the guidelines for livestock management and policies regarding climate <a>mitigation.</a></p> <p> </p>
Precipitation regime controls bryosphere carbon cycling similarly across contrasting ecosystems
<p>In arctic and boreal ecosystems, ground bryophytes play an important role in regulating carbon (C) exchange between vast belowground C stores and the atmosphere. Climate is changing particularly fast in these high-latitude regions, but it is unclear how altered precipitation regimes will affect C dynamics in the bryosphere (i.e., the ground moss layer including senesced moss, litter, and associated biota) and the closely associated upper humus layer, and how these effects will vary across contrasting environmental conditions. Here, we set up a greenhouse experiment in which mesocosms were assembled containing samples of the bryosphere, dominated by the feather moss <i>Hylocomium splendens</i>, and the upper humus layer, that were collected from across a boreal forest chronosequence in northern Sweden which varies strongly in nutrient availability, productivity, and soil biota. We tested the effect of variation in precipitation volume and frequency on CO<sub>2</sub> exchange and dissolved organic carbon (DOC) export, and on moss growth. As expected, reduced precipitation volume and frequency lowered net CO<sub>2</sub> efflux, DOC export, and moss growth. However, by regulating moisture, the lower bryosphere and humus layers often mediated how precipitation volume and frequency interacted to drive C dynamics. For example, less frequent precipitation reduced moss growth only when precipitation volume was low. When volume was high, high moisture content of the humus layer helped avoid moss desiccation. Variation in precipitation regime affected C cycling consistently in samples collected across the chronosequence, despite large environmental variation along the sequence. This suggests that the bryosphere exerts a strong buffering effect on environmental variation at the forest floor, which leads to similar responses of C cycling to external perturbations across highly contrasting ecosystems. As such, our study indicates that projected increases in droughts and ground evapotranspiration in high-latitude regions resulting from climate change will consistently reduce C losses from moss-dominated ecosystems.</p>
A before/after intervention study to determine impact on life cycle carbon footprint of converting from single-use to reusable sharps containers in 40 United Kingdom NHS Trusts
<p>The purpose of this study was t<span>o compare Global Warming Potential (GWP) of hospitals converting from single-use to reusable sharps containers (SSC, RSC). Does conversion to RSC result in GWP reduction? </span><span>Using BS PAS 2050:2011 principles, a retrospective, before/after intervention quantitative model together with a purpose-designed, attributional "cradle-to-grave" life cycle tool, were used to determine the annual GHG emissions of the two sharps containment systems. Functional unit was total fill-line litres (FLL) of sharps containers needed to dispose of sharps for one-year period in 40 trusts. Scope 1, 2 and 3 emissions were included. Results were workload-normalised using NHS national hospital patient-workload indicators. A sensitivity analysis examined areas of data variability.</span></p> <p><span><b>Setting</b>. Acute-care hospital trusts in United Kingdom.</span></p> <p><span><b>Participants</b>. 40 NHS hospital Trusts using RSC.</span></p> <p><span><b>Intervention</b>. <span>Conversion from SSC to RSC. SSC and RSC usage details in </span><span>17 base-line trusts immediately prior to 2018 were applied to the RSC usage details of the 40 trusts using RSC in 2019</span><span>.</span></span></p> <p><span><span>The comparison of GWP </span>calculated in carbon dioxide equivalents (CO<sub>2</sub>e)<span> generated in the manufacture, transport, service and disposal of</span> 12 months, hospital-wide usage of both containment systems in the 40 trusts. </span><span>The 40 trusts converting to RSC reduced their combined annual GWP by 3267.4 tonnes CO<sub>2</sub>e (-83.9%); eliminated incineration of 900.8 tonnes of plastic; eliminated disposal/recycling of 132.5 tonnes of cardboard; and reduced container exchanges by 61.1%. GHG as kg CO<sub>2</sub>e/1000 FLL were 313.0 and 50.7 for SSC and RSC systems respectively. A sensitivity analysis showed substantial GHG reductions within unit processes could be achieved, however their impact on relevant final GWP comparison varied <5% from base comparison.</span> Adopting RSC is an example of a sustainable purchasing decision that can assist trusts meet NHS GHG reduction targets and can reduce GWP permanently with minimal staff behaviour-change.</p>
Enabling Long-term Cycling Stability of Na3V2(PO4)3/C vs. Hard Carbon Full-cells
<p>Battery cycling data to research paper: </p><p>https://doi.org/10.26434/chemrxiv-2023-jf6mq </p><p>for questions on the data files, please contact pirmin[dot]stueble[at]kit.edu or anna[dot]smith[at]kit.edu</p>
CCycDB (an integrative knowledgebase to fingerprint microbial carbon cycling processes)
<p>CCycDB - version 2.0 (Please see<strong> </strong><a href="https://ccycdb.github.io/"><strong>https://ccycdb.github.io/</strong></a> for more details)</p><p><strong>CCycDB</strong> is a knowledge-based functional gene database for accurate metagenomic profiling of carbon cycling microbial communities. CCycDB contains 4,676 gene families within 6 categories. These gene families are further categorized into 45 sub-categories within sub-category I and 188 sub-categories within sub-category II with a total of 10,991,724 targeted sequences. A series of validations demonstrated that CCycDB outperformed large public orthology databases in terms of coverage, specificity, and accuracy, and can be used to accurately profile carbon cycling microbial communities in real metagenomic datasets.</p>
Authigenic carbonate burial within the Late Devonian Western Canada Sedimentary Basin and its impact on the global carbon cycle
<p>The complete dataset for the research project entitled <i>Authigenic carbonate burial within the Late Devonian Western Canada Sedimentary Basin and its impact on the global carbon cycle</i>. Within this zip file includes an excel file compiling a list of rock samples and their corresponding stable carbon and oxygen isotope compositions as well as their inorganic carbon content. Rock samples are grouped according to formation name, depositional environment and stratigraphic height. Along with the excel data compilation are two supplementary figures meant to accompany the publication of this research. Figure S1 illustrates coulometry-measured inorganic carbon content of shale samples plotted with respect to their respective IRMS beam area. Figure S2 illustrates a rolling window analysis of the covariability between the d13C and d18O composition of each sample grouped according to their respective core and field sections. A window size of 20 samples was used.</p>
ScienceDex guides
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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.