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.
167
datasets available to search
ShareScore release 0.9.0
Dataset results
167 results for “greenhouse gas”
Idiosyncratic phenology of greenhouse gas emissions in a Mediterranean reservoir
Open the record for dataset details and reuse information.
Data from: Pollution-tolerant invertebrates enhance greenhouse gas flux in urban wetlands
Open the record for dataset details and reuse information.
Data for meta-analysis of the soil greenhouse gas emissions
Open the record for dataset details and reuse information.
Carbon sequestration of a forested wetland receiving nutrient inputs - soil, tree and greenhouse gas data
Open the record for dataset details and reuse information.
Data for: Wetland productivity determines trade-off between biodiversity and greenhouse gas production
Open the record for dataset details and reuse information.
Hot spots and hot moments of greenhouse gas emissions in agricultural peatlands
Open the record for dataset details and reuse information.
Uncertainties in greenhouse gas emission factors: A comprehensive analysis of switchgrass-based biofuel production
Open the record for dataset details and reuse information.
Disentangling the effects of methanogen community and environment on peatland greenhouse gas production by a reciprocal transplant experiment
Open the record for dataset details and reuse information.
Data from: Compound- and context-dependent effects of antibiotics on greenhouse gas emissions from livestock
Open the record for dataset details and reuse information.
The interplay between climate warming driven by greenhouse gas emissions and the ecotoxicological effects of microplastics: Insights from a meta-analysis
Open the record for dataset details and reuse information.
Laboratory mesocosm data measuring the impact of bioturbation frequency on greenhouse gas emissions from reservoir sediments
Inland aquatic systems are major global contributors to the atmospheric carbon budget through greenhouse gas (GHG) emissions, although the amount and form of carbon released varies widely across and within systems. Bioturbation of aquatic sediments can impact biogeochemical conditions and physically release sediment-bound bubbles containing GHGs, but variation in the frequency of such disturbance may modify the rate and composition of resulting GHG emissions. We hypothesized that an intermediate bioturbation frequency would result in the greatest methane (CH4) releases due to mechanical release of trapped bubbles, while frequent disturbance would result in greater diffusive carbon dioxide (CO2) releases relative to CH4, due to increased aeration of the sediment. We tested this bioturbation frequency hypothesis using laboratory mesocosms containing homogenized reservoir sediment. We used mechanical disturbance to simulate bioturbation at 3, 7, 14, or 21-day intervals; a control treatment was undisturbed for the duration of the experiment. We measured GHG emission (ebullition and diffusion) rates. An intermediate frequency of disturbance (7 days) produced the highest total GHG emission rate, while the most frequent disturbance interval (3 days) and least frequent interval (0 days) reduced overall GHG emissions relative to weekly disturbance by 24% and 15%, respectively. These patterns were primarily driven by differences in CH4 ebullition. Contrary to our hypothesis, there was no relationship between disturbance frequency and diffusive CO2 emissions. For all disturbance treatments, the majority of ebullition occurred during disturbance events, suggesting mechanical release of entrapped bubbles is an important emission mechanism. The frequency of disturbance has variable effects on GHG emissions and may explain conflicting results in prior studies of bioturbation. Our study provides insight into bioturbation as a driver of within-system variation in GHG emissions and h
Growth, gas exchange and hydraulic conductivity of greenhouse grown willows under pre-drought conditions: Investigating patterns of habitat specialization in fifteen co-occurring willow and poplar species.
Thirteen willow (Salix) species occur in southeastern Minnesota and often co-occur within the same wetlands. This high local diversity is challenging to explain since closely related species are often functionally similar and density-dependent interactions such as competition and susceptibility to pests and pathogens should limit their co-occurrence. However, if willow species are partitioning resources, or if they are phylogenetically structured so that closely related species rarely co-occur, then the impact of these density-dependent processes could be reduced. In this study, I examined the role of niche partitioning in maintaining local willow diversity by documenting species distributions in plots across a water availability gradient and comparing species physiology in the field and greenhouse. By taking a phylogenetic approach, I also investigated whether willow communities exhibit phylogenetic community structure and whether there is evidence for environmental filtering.
Data from: Reported U.S. Wild Game Consumption and Greenhouse Gas Emissions Savings
<p>These two tables present raw data utilized to calculated greenhouse gas savings associated with hunting within the US. Appendix I shows the estimated numbers of "big game" animals legally harvested in each state and the mean yield from each species. Appendix II shows total number of migratory waterfowl harvested in the US and the mean yield for each species. Both of these tables refer to the paper "Reported US Wild Game Consumption and Greenhouse Gas Emissions Savings" published in Human Dimensions of Wildlife.</p>
Energy consumption and greenhouse gas emissions data of activated carbon production using different biomass
<p>This dataset includes the energy consumption and Greenhouse Gas emissions data of activated carbon production using 73 different types of woody biomass.</p> <p>Understanding the environmental implications of activated carbon (AC) produced from diverse biomass feedstocks is critical for biomass screening and process optimization for sustainability. Many studies have developed Life Cycle Assessment (LCA) for biomass-derived AC. However, most of them either focused on individual biomass species with differing process conditions or compared multiple biomass feedstocks without investigating the impacts of feedstocks and process variations. Developing LCA for AC from diverse biomass is time-consuming and challenging due to the lack of process data (e.g., energy and mass balance).</p> <p>This study addresses these knowledge gaps by developing a modeling framework that integrates artificial neural network (ANN), a machine learning approach, and kinetic-based process simulation. The integrated framework is able to generate Life Cycle Inventory data of AC produced from 73 different types of woody biomass with 250 characterization data samples. The results show large variations in energy consumption and GHG emissions across different biomass species (43.4–277 MJ/kg AC and 3.96–22.0 kg CO<sub>2</sub>-eq/kg AC). The sensitivity analysis indicates that biomass composition (e.g., hydrogen and oxygen content) and process operational conditions (e.g., activation temperature) have large impacts on energy consumption and GHG emissions associated with AC production.</p>
Data from: Canopy soil greenhouse gas dynamics in response to indirect fertilization across an elevation gradient of tropical montane forests
Canopy soils can significantly contribute to aboveground labile biomass, especially in tropical montane forests. Whether they also contribute to the exchange of greenhouse gases is unknown. To examine the importance of canopy soils to tropical forest-soil greenhouse gas exchange, we quantified gas fluxes from canopy soil cores along an elevation gradient with 4 yr of nutrient addition to the forest floor. Canopy soil contributed 5–12 percent of combined (canopy + forest floor) soil CO2 emissions but CH4 and N2O fluxes were low. At 2000 m, phosphorus decreased CO2 emissions (>40%) and nitrogen slightly increased CH4 uptake and N2O emissions. Our results show that canopy soils may contribute significantly to combined soil greenhouse gas fluxes in montane regions with high accumulations of canopy soil. We also show that changes in fluxes could occur with chronic nutrient deposition.
Data from: Technical note: rapid image-based field methods improve the quantification of termite mound structures and greenhouse-gas fluxes
Termite mounds (TMs) mediate biogeochemical processes with global relevance, such as turnover of the important greenhouse gas methane (CH4). However, the complex internal and external morphology of TMs impede an accurate quantitative description. Here we present two novel field methods, photogrammetry (PG) and cross-section image analysis, to quantify TM external and internal mound structure of 29 TMs of three termite species. Photogrammetry was used to measure epigeal volume (VE), surface area (AE) and mound basal area (AB) by reconstructing 3D models from digital photographs, and compared against a water-displacement method and the conventional approach of approximating TMs by simple geometric shapes. To describe TM internal structure, we introduce TM macro- and micro-porosity (θM and θµ), the volume fractions of macroscopic chambers, and microscopic pores in the wall material, respectively. Macro-porosity was estimated using image analysis of single TM cross-sections, and compared against full x-ray tomography (CT) scans of 17 TMs. For these TMs we present complete pore fractions to assess species-specific differences in internal structure. The PG method yielded VE nearly identical to a water-displacement method, while approximation of TMs by simple geometric shapes led to errors of 4–200 %. Likewise, using PG substantially improved the accuracy of CH4 emission estimates by 10–50 %. Comprehensive CT scanning revealed that investigated TMs have species-specific ranges of θM and θµ, but similar total porosity. Image analysis of single TM cross-sections produced good estimates of θM for species with thick walls and evenly distributed chambers. The new image-based methods allow rapid and accurate quantitative characterisation of TMs to answer ecological, physiological and biogeochemical questions. The PG method should be applied when measuring greenhouse-gas emissions from TMs to avoid large errors from inadequate shape approximations.
Data from: Using greenhouse gas fluxes to define soil functional types
Aim: Soils provide key ecosystem services and directly control ecosystem functions; thus, there is a need to define the reference state of soil functionality. Most common functional classifications are vegetation-centered, such as plant functional types (PFTs), and neglect soil characteristics and processes. We propose Soil Functional Types (SFTs) as a conceptual approach to represent and describe the functionality of soils based on characteristics of their greenhouse gas (GHG) flux dynamics. Methods: We used automated measurements of CO2, CH4 and N2O soil fluxes in a forested area to define SFTs as surface areas with similar GHG dynamics. We performed mixed effects models, and independent cluster analyses of our environmental variables and SFT classifications. Results Unique groupings based on SFTs, but not environmental variables, supported the hypothesis that SFTs provide additional insights on the spatial variability of soil functionality beyond information represented by commonly measured soil parameters (e.g., soil moisture, soil temperature, litter biomass). Conclusions: This approach could complement vegetation-based functional classifications to better represent the broad range of ecosystem functions. A global application of the proposed SFT framework will only be possible if there is a community-wide effort to share data and create a global database of GHG emissions from soils.
Dataset on laboratory soil greenhouse gas fluxes and soil microbial parameters as affected by soil management strategies in SOMMIT long term experiments
<p>We present a database containing over 50 soil-microbial parameters from eight long-term European experiments where specific soil management strategies are compared. Intact topsoil cores (7 cm diameter, 7 cm height) were collected from LTE participating in the tasks WP3.2 and WP3.3. from the SOMMIT experiment, and incubated under standard conditions in the laboratory. The soil management strategies considered at the eight LTEs ("ACBB Estrées-Mons, France", "Rutzendorf_17, Austria", , "Foggia, Italy", "ULBF-Ljubljana, Slovenia", "Toholampi, Finland", "Senés, Spain", "La Poveda, Spain" and "Grabow 1, Poland") included crop residue management, addition of different types of compost and sludge and biochar addition. All LTEs are referenced according to the LTE Index from https://doi.org/10.5281/zenodo.7598122 . The soil cores were subjected to i) a pre-equilibration phase of five days ("pre.inc"), followed by ii) a drying phase ("DR") of ten days and finally a iii) rewetting (five days, "RW"). A subset of the cores were kept under iv) constantly moist conditions for comparison purposes ("moist"). By the end of the "pre.inc" phase, soil microbial biomass, soil microbial community (phospholipidic fatty acids), enzymatic activities and soil nutrient data were collected. After the "pre.inc" phase, soil fluxes of N2O and CO2 were monitored with an automated system at subdaily temporal resolution. In addition, soil nutrients and microbial biomass data were estimated during at the end of the "DR", "RW" and "moist" phases. This dataset contributes to a better understanding of the linkages between soil conditions, soil microbes and soil greenhouse gas fluxes as affected by different soil management strategies across European agro-ecosystems. This product is part of the EJP SOIL internal project SOMMIT, and serves as deliverable WP3.4</p>
Field data of soil greenhouse gas fluxes from SOMMIT long-term experiments
<p>This is a database of field data of soil greenhouse gas fluxes and ancillary data from long-term experiments (LTEs) that participated in the task 1 of the work package 3 from SOMMIT. As of November 2024 (V 1.0) six LTEs have contributed with data: "ACBB Estrées-Mons, France", "Rutzendorf_17, Austria", "Maintainance of organic orchards, Italy", "Fagna, Italy", "ULBF-Ljubljana, Slovenia" and "Grabow 2, Poland". All LTEs are referenced according to the LTE Index from <a href="https://doi.org/10.5281/zenodo.7598122" target="_blank" rel="noopener">https://doi.org/10.5281/zenodo.7598122</a>. The data includes soil greenhouse gas fluxes (N2O, CO2 and CH4) under different management practices, as well as ancillary data that might be useful to explain the observed fluxes. The database includes metadata on how soil greenhouse flux data and ancillary data were collected. Individual soil gas flux estimates are also expressed in CO2 equivalents [mg CO2-eq m-2 h-1], thereby providing a dataset on the contribution of soil CO2, N2O and CH4 fluxes to the soil global warming potential. This product is part of the EJP SOIL internal project SOMMIT, and serves as deliverables WP3.2 and WP3.3.</p>
Reduction of iron-organic carbon associations shifts net greenhouse gas release after initial permafrost thaw
<p>This dataset contains data associated with the manuscript "Reduction of iron-organic carbon associations shifts net greenhouse gas release after initial permafrost thaw". doi: <a title="Persistent link using digital object identifier" href="https://doi.org/10.1016/j.soilbio.2025.109735" target="_blank" rel="noreferrer noopener"><span><span>https://doi.org/10.1016/j.soilbio.2025.109735</span></span></a></p>
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.