Find research datasets worth reusing
Search datasets from major research repositories and use ShareScore to quickly assess how well each record supports discovery, access, and reuse.
151
datasets available to search
ShareScore release 0.7.1
Dataset results
151 results for “Soil Respiration”
Global Annual Soil Respiration Data (Raich and Schlesinger 1992)
This data set is a compilation of soil respiration rates (g C m-2 yr-1) from terrestrial and wetland ecosystems reported in the literature prior to 1992. These rates were measured in a variety of ecosystems to examine rates of microbial activity, nutrient turnover, carbon cycling, root dynamics, and a variety of other soil processes. In this summary, only those data based on most or all of one full year of measurements were used so that annual rates of soil respiration could be estimated. Data from soil cores were excluded because the sample coring modifies root respiration. Also included in the data set are biome type, vegetation type, locality, and geographic coordinates, based on information from the original paper. Mean annual temperature and precipitation were based on the original paper; where those data were not included, they were estimated from a gridded global climate database [0.5 degree resolution; Legates D.R. and C.J. Willmott. 1988. Global Air Temperature and Precipitation Data Archive. Department of Geography, University of Delaware, Newark, Delaware, USA).
BOREAS TE-05 Soil Respiration Data
The BOREAS group TE-05 collected measurements in the NSA and SSA on gas exchange, gas composition and tree growth. Soil respiration data collected in the BOREAS NSA and SSA to compare the soil respiration rates in different forest sites using a Li-Cor 6200 soil respiration chamber (model 6299).
Global Gridded 1-km Soil and Soil Heterotrophic Respiration Derived from SRDB v5
This dataset provides global gridded estimates of annual soil respiration (Rs) and soil heterotrophic respiration (Rh) and associated uncertainties at 1 km resolution. Mean soil respiration was estimated using a quantile regression forest model utilizing data from the global Soil Respiration Database Version 5 (SRDB-V5) and covariates of mean annual temperature, seasonal precipitation, and vegetative cover. The SRDB holds results of field studies of soil respiration from around the globe. A total of 4,115 records from 1,036 studies were selected from SRDB-V5. SRDB-V5 features more soil respiration data published in Russian and Chinese scientific literature for better global spatio-temporal coverage and improved global climate-space representation. These soil respiration records were combined with global meteorological, land cover, and topographic data and then evaluated with variable selection using random forests. The standard deviation and coefficient of variation of Rs are included and were also derived from the same model. Global heterotrophic respiration was calculated from Rs estimates. The data are produced in part from SRDB-V5 inputs that cover the period 1961-2016.
Global annual soil respiration from 2000 to 2014
<p>This dataset contains a product of annual global soil respiration from 2000 to 2014 at 1 km×1 km spatial resolution. A Matlab script (i.e., global_soil_respiration_calculation.m) for the calculation of global soil respiration is provided. More details on this dataset are presented in the manuscript titled "Spatial and temporal variations in global soil respiration and their relationships with climate and land cover".</p>
Data from: Modeling spatial patterns of soil respiration in maize fields from vegetation and soil property factors with the use of remote sensing and geographical information system
To examine the method for estimating the spatial patterns of soil respiration (Rs) in agricultural ecosystems using remote sensing and geographical information system (GIS), Rs rates were measured at 53 sites during the peak growing season of maize in three counties in North China. Through Pearson's correlation analysis, leaf area index (LAI), canopy chlorophyll content, aboveground biomass, soil organic carbon (SOC) content, and soil total nitrogen content were selected as the factors that affected spatial variability in Rs during the peak growing season of maize. The use of a structural equation modeling approach revealed that only LAI and SOC content directly affected Rs. Meanwhile, other factors indirectly affected Rs through LAI and SOC content. When three greenness vegetation indices were extracted from an optical image of an environmental and disaster mitigation satellite in China, enhanced vegetation index (EVI) showed the best correlation with LAI and was thus used as a proxy for LAI to estimate Rs at the regional scale. The spatial distribution of SOC content was obtained by extrapolating the SOC content at the plot scale based on the kriging interpolation method in GIS. When data were pooled for 38 plots, a first-order exponential analysis indicated that approximately 73% of the spatial variability in Rs during the peak growing season of maize can be explained by EVI and SOC content. Further test analysis based on independent data from 15 plots showed that the simple exponential model had acceptable accuracy in estimating the spatial patterns of Rs in maize fields on the basis of remotely sensed EVI and GIS-interpolated SOC content, with R2 of 0.69 and root-mean-square error of 0.51 µmol CO2 m−2 s−1. The conclusions from this study provide valuable information for estimates of Rs during the peak growing season of maize in three counties in North China.
Data from: Modeling spatial patterns of soil respiration in maize fields from vegetation and soil property factors with the use of remote sensing and geographical information system
Open the record for dataset details and reuse information.
Data from: Long-term antagonistic effect of increased precipitation and nitrogen addition on soil respiration in a semiarid steppe
Open the record for dataset details and reuse information.
Global annual soil respiration from 2000 to 2014
Open the record for dataset details and reuse information.
Soil respiration CO2 efflux data - Telok Kurau, Singapore
<p><em>To evaluate the ability of turfgrass systems to sequester carbon in tropical cities, we deployed a flux gradient system built by solid-state CO<sub>2</sub> sensors in a residential lawn of Singapore to measure continuously the production of carbon bellow-ground and soil respiration CO<sub>2</sub> efflux for a period of almost three years (Sep 2014 to Jul 2017). The data presented here include 30-min average data of soil temperature, soil moisture and soil CO2 concentration at 2, 8 and 16 cm of depth, along with the post-processed soil efflux and carbon production.</em></p>
datasets for yanzhang's manuscript, Temperature variation promotes the thermal adaptation of soil microbial respiration
<p>datasets for yanzhang's manuscript, Temperature variation promotes the thermal adaptation of soil microbial respiration</p>
Codes for 'Diurnal asymmetry in soil respiration generates overestimation of global soil carbon emissions'
Open the record for dataset details and reuse information.
ScienceDex guides
Understand access before you commit
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.