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238
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ShareScore release 0.7.1
Dataset results
238 results for “carbon flux”
Data from: Rainfall pulse response of carbon fluxes in a temperate grass ecosystem in the semiarid Loess Plateau
Rainfall pulses can significantly influence carbon cycling in water limited ecosystems. The magnitude of carbon flux component responses to precipitation may vary depending on precipitation amount and antecedent soil moisture, associated with nonlinear responses of plants and soil microbes. The present study was carried out in a temperate grass ecosystem during 2013–2015 in the semiarid Loess Plateau of China, to examine the response of carbon fluxes to precipitation using the "threshold-delay" model. The unique contribution of environmental variables, such as precipitation amount and antecedent soil moisture before rainfall (SWC_antecedent) to carbon fluxes in response to rainfall were also investigated. The lower threshold of effective rainfall was 6.6 mm for gross ecosystem production (GEP), 8.5 mm for net ecosystem production (NEP) and 4.5 mm for ecosystem respiration (RE); and the upper threshold of effective rainfall was 21.4 mm for GEP and NEP, and 16.8 mm for RE. Rainfall amount was positively affected the relative rainfall responses of GEP, NEP and RE. However, SWC_antecedent at 20 cm soil depth offset the response of GEP to rainfall pulses, and SWC_antecedent at 5 cm depth offset the response of NEP and RE to rainfall pulses, with corresponding partial slopes of linear regressions of −0.50, −0.40 and −0.52. These results indicated that NEP was more sensitive to rainfall pulses and RE was more sensitive to SWC_antecedent. These results demonstrate the importance of rainfall events of < 10 mm, and that the negative effect of SWC_antecedent should also be considered when estimating ecosystem carbon fluxes in this semiarid region.
Carbon concentration and flux data of the Yangtze River main stream
<p><span lang="EN-US">Data and statistical analysis of carbon concentration, flux, budget, and environmental factors in the main stream of the Yangtze River, including relevant data from manuscripts and text S2-4.</span></p> <p><span lang="EN-US">The data have already been part of (Wang, M., et al., 2025. Determining carbon fate and budgets throughout the Yangtze mainstream’s transportation processes. Fundamental Researc (https://doi.org/10.1016/j.fmre.2025.08.012)).</span></p>
Global ocean carbon uptake enhanced by rainfall : CO2 flux datasets
<p>1) NETCDF files containing the annual mean maps of the CO2 flux diagnostics considering the different effects of rain over the period 2008-2018 (Parc et al. 2024)</p> <ul> <li>map_statflux_REF.nc : Diagnostic reference flux taking into the ocean skin effect and formation of diurnal warm layers (Bellenger et al. 2017)</li> </ul> <p>- Diagnostics based on the ERA5 reanalysis rain dataset (Hersbach et al. 2020) : </p> <ul> <li>map_statflux_KR_rERA5.nc : Diagnostic flux integrating the impact of rain-induced turbulence (Harrison et al. 2012) to the reference flux</li> <li>map_statflux_DIL_DS1_rERA5.nc : Diagnostic flux integrating the impact of rain-induced dilution using Bellenger et al. (2017) parametrization to the reference flux</li> <li>map_statflux_DIL_DS2_rERA5.nc : Diagnostic flux integrating the impact of rain-induced dilution using Supply et al. (2020) parametrization to the reference flux</li> <li>map_statflux_INT_DS1_rERA5.nc : Diagnostic flux integrating the combined effect of rain-induced turbulence (Harrison et al. 2012) and dilution using Bellenger et al. (2017) parametrization to the reference flux</li> <li>map_statflux_INT_DS2_rERA5.nc : Diagnostic flux integrating the combined effect of rain-induced turbulence (Harrison et al. 2012) and dilution using Supply et al. (2020) parametrization to the reference flux</li> <li>map_statflux_WD_rERA5.nc : Additional diagnostic CO2 flux due to wet deposition (Komori et al. 2007)</li> </ul> <p>- Diagnostics based on the IMERG satellite-based rain dataset (Huffman et al. 2023) : </p> <ul> <li>map_statflux_KR_rIMERG.nc : Diagnostic flux integrating the impact of rain-induced turbulence (Harrison et al. 2012) to the reference flux</li> <li>map_statflux_DIL_DS1_rIMERG.nc : Diagnostic flux integrating the impact of rain-induced dilution using Bellenger et al. (2017) parametrization to the reference flux</li> <li>map_statflux_DIL_DS2_rIMERG.nc : Diagnostic flux integrating the impact of rain-induced dilution using Supply et al. (2020) parametrization to the reference flux</li> <li>map_statflux_INT_DS1_rIMERG.nc : Diagnostic flux integrating the combined effect of rain-induced turbulence (Harrison et al. 2012) and dilution using Bellenger et al. (2017) parametrization to the reference flux</li> <li>map_statflux_INT_DS2_rIMERG.nc : Diagnostic flux integrating the combined effect of rain-induced turbulence (Harrison et al. 2012) and dilution using Supply et al. (2020) parametrization to the reference flux</li> <li>map_statflux_WD_rIMERG.nc : Additional diagnostic CO2 flux due to wet deposition (Komori et al. 2007)</li> </ul> <p>All these files contain three variables : </p> <ul> <li>MFLUX : Annual mean of diagnostic flux (gC/m2/yr)</li> <li>SFLUX : Standard deviation of diagnostic flux</li> <li>WEIGHT : Number of data time steps used for the statistics</li> </ul> <p>2) Excel file containing the monthly means of the global ocean CO2 sink (PgC/y) corresponding to all the different diagnostics previously described (Parc et al. 2024) : GlobalOceanSink_2008-2018_rain_monthly_diagnostics.xlsx</p> <p>References : </p> <ul> <li><em>Bellenger, H. et al. Extension of the prognostic model of sea surface temperature to rain‐induced cool and fresh lenses. J. Geophys. Res. Oceans 122, 484–507 (2017).</em></li> <li><em>Hersbach, H. et al. The ERA5 global reanalysis. Q. J. R. Meteorol. Soc. 146, 1999–2049 (2020).</em></li> <li><em>Harrison, E. L. et al. Nonlinear interaction between rain- and wind-induced air-water gas exchange. J. Geophys. Res. Oceans 117, (2012).</em></li> <li><em>Supply, A., Boutin, J., Reverdin, G., Vergely, J.-L. & Bellenger, H. Variability of Satellite Sea Surface Salinity Under Rainfall. in Satellite Precipitation Measurement (eds. Levizzani, V. et al.) vol. 69 1155–1176 (Springer International Publishing, Cham, 2020).</em></li> <li><em>Komori, S., Takagaki, N., Saiki, R., Suzuki, N. & Tanno, K. The Effect of Raindrops on Interfacial Turbulence and Air-Water Gas Transfer. in Transport at the Air-Sea Interface (eds. Garbe, C. S., Handler, R. A. & Jähne, B.) 169–179 (Springer Berlin Heidelberg, Berlin, Heidelberg, 2007). doi:10.1007/978-3-540-36906-6_12.</em></li> <li><em>Huffman, G., Stocker, E. F., Bolvin, D. T., Nelkin, E. J. & Tan, J. GPM IMERG Final Precipitation L3 Half Hourly 0.1 degree x 0.1 degree V07. NASA Goddard Earth Sciences Data and Information Services Center https://doi.org/10.5067/GPM/IMERG/3B-HH/07 (2023).</em></li> </ul>
Dataset: Methane and carbon dioxide fluxes in an intermediate marsh in Barataria Bay, LA (v.0.10)
<p>Methane and carbon dioxide fluxes were measured in August 2019 in an Intermediate salinity marsh in Barataria Bay, Louisiana. The flux chamber method was used to measure methane (CH<sub>4</sub>) and carbon dioxide (CO<sub>2</sub>) under light and dark conditions in an Intermediate salinity marsh in Barataria Bay, LA. Fluxes were measured in plots with the following treatments: Control and high nutrients. Treatments included: Control; Sediment deposition- 0 (control) and 5 cm (45 kg river silt); Nutrient- Low nutrients: 645.2 g of CaNO<sub>3</sub> and 11.11g of P<sub>2</sub>O<sub>5</sub> High nutrients: 6451.6 g of CaNO<sub>3</sub> and 111.1 g of P<sub>2</sub>O<sub>5</sub>; and Low nutrients + Sediment and High nutrients + Sediment Measurements included methane flux (calculated from concentration regressions over time), carbon dioxide flux (calculated from concentration regressions over time), air temperature inside and outside of chambers, PAR inside and outside of chambers, salinity and water table depth.</p>
Global control of carbon flux in Bifidobacterium breve UCC2003
GEO Series GSE108949. Bifidobacterium breve UCC2003. 4 samples. Type: Expression profiling by array.
Dataset for "Soil fluxes of carbonyl sulfide (COS), carbon monoxide, and carbon dioxide in a boreal forest in southern Finland"
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Data from: Rainfall pulse response of carbon fluxes in a temperate grass ecosystem in the semiarid Loess Plateau
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Data from: Temperature mediated responses of carbon fluxes to precipitation variabilities in an alpine meadow ecosystem on the Tibetan Plateau
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Dataset: Methane and carbon dioxide fluxes in an intermediate marsh in Barataria Bay, LA (v.0.10)
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Absence of KpsM (Slr0977) impairs the secretion of extracellular polymeric substances (EPS) and impacts carbon fluxes in Synechocystis sp. PCC 6803
GEO Series GSE165073. Synechocystis sp. PCC 6803. 6 samples. Type: Expression profiling by high throughput sequencing.
Tumor reliance on cytosolic versus mitochondrial one-carbon flux depends on folate availability
GEO Series GSE153023. Homo sapiens. 6 samples. Type: Expression profiling by high throughput sequencing.
PahT regulates carbon fluxes in Novosphingobium sp. HR1a and influence its survival in soil and rhizosphere.
GEO Series GSE163593. Novosphingobium sp. HR1a. 12 samples. Type: Expression profiling by high throughput sequencing.
Du feu à l'eau: source and flux of dissolved black carbon from the Congo River
<p>DBC, DOC, and discharge data used in the manuscript.</p>
Flux melting of the subducting carbonated sediments: An experimental study
<p>Chemical compositions of the run products</p>
Role of Transcriptional Regulation in Controlling Fluxes in Central Carbon Metabolism of Saccharomyces cerevisiae
GEO Series GSE8895. Saccharomyces cerevisiae. 12 samples. Type: Expression profiling by array.
Energy, water and carbon fluxes over burned forests in Eastern Amazon
<p>Dataset of to energy, water and carbon fluxes over burned forests in Eastern Amazon.</p>
Agrivoltaics system impacts on winter wheat carbon fluxes and growth in a temperate climate
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Wind Energetic Particle Acceleration Composition Transport (EPACT) SupraThermal Energetic Particle Telescope (STEP) Differential, Directional Carbon, Nitrogen, and Oxygen Fluxes, 10 min Data
The EPACT Instrument on Wind STEP - SupraThermal Energetic Particle Telescope measures Ion Fluxes of Protons (H) in 0.12.5 MeV Energy Range and He-Fe Nuclei in the ~0.032 MeV/nucleon Energy Ranges in two identical Telescopes, each with a Geometrical Factor of 0.4 cm^2 sr and a rectangular Field of View with an Angular Acceptance of 44° in Azimuth and 17° in Polar Angle.
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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.