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.
74
datasets available to search
ShareScore release 0.7.1
Dataset results
74 results for “microbial biomass”
Data from: Plant diversity improves resistance of plant biomass and soil microbial communities to drought
Open the record for dataset details and reuse information.
The vertical distribution of soil microbial biomass carbon: A global dataset
<p>Soil microbial biomass carbon (SMBC) is important in regulating soil organic carbon (SOC) dynamics along soil profiles by mediating the decomposition and formation of SOC. The dataset is about the vertical distributions of SOC, SMBC, and soil microbial quotient (SMQ = SMBC/SOC) and their relations to environmental factors across five continents. Data are collected from literature, with a total of 289 soil profiles and 1040 observations in different soil layers compiled. The associated environment data were also collectd including climate, ecosystem types, and edaphic factors. More specifically, we develop this dataset by compiling data from 59 papers published in the Web of Sciene and the China National Knowledge Infrastructure from the year of 1970 to 2019. All the data included in this dataset meet two creteria: 1) there are at least three soil layers along a soil profile, and 2) soil MBC is measured using the fumigation extraction method. The data were obtained from tables and texts from literature directly, and the data in figures were extracted using GetData Graph digitizer software version 2.25. When climate and soil properties are not available from publications, we obtainted the data from the World Weather Information Service (https://worldweather.wmo.int/en/home.html) and SoilGrids at a spatial resolution of 250 meters (version 0.5.3, https://soilgrids.org).</p> <p>The units of all the variables are converted to the standard international units or commonly used ones and the values are converted correspondingly. For example, the value of soil organic matter (SOM) is converted to SOC using the equation (SOC = SOM × 0.58). Soil depth is calculated as the arithmetic mean value of the upper and lower boundaries for a given soil layer.</p> <p>This dataset can be used in predicting global SOC change along soil profiles using the multi-layer soil C models. It can also be used to analyse how soil microbial biomass changes with plant roots as well as the composition, structure, and functions of soil microbial communities along soil profiles at large spatial scales. This dataset offers opportunities to improve our prediction of SOC dynamics under global changes and to advance our understanding of the environmental controls.</p>
Data from: Soil microbial species loss affects plant biomass and survival of an introduced bacterial strain, but not inducible plant defences
- Background and Aims: Plant growth-promoting rhizobacteria (PGPR) strains can influence plant-insect interactions. However, little is known about the effect of changes in the soil bacterial community in general and especially the loss of rare soil microbes on these interactions. Here, the influence of rare soil microbe-reduction on induced systemic resistance (ISR) in a wild ecotype of Arabidopsis thaliana against the aphid Myzus persicae was investigated. - Methods: To create a gradient of microbial abundances, soil was inoculated with a serial dilution of a microbial community and responses of Arabidopsis plants that originated from the same site as the soil microbes were tested. Plant biomass, transcription of genes involved in plant defences, and insect performance were measured. In addition, the effects of the PGPR strain Pseudomonas fluorescens SS101 on plant and insect performance were tested under influence of the various soil dilution treatments. - Key Results: Plant biomass showed a hump-shaped relationship with soil microbial community dilution, independent of aphid or Pseudomonas treatments. Both aphid infestation and inoculation with Pseudomonas reduced plant biomass, and led to downregulation of PR1 (salicylic acid-responsive gene) and CYP79B3 (involved in synthesis of glucosinolates). Aphid performance and gene transcription were unaffected by soil dilution. - Conclusions: Neither the loss of rare microbial species, as caused by soil dilution, nor Pseudomonas, affect the resistance of A. thaliana against M. persicae. However, both Pseudomonas survival and plant biomass respond to rare species loss. Thus, loss of rare soil microbial species can have a significant impact on both above- and belowground organisms.
Squeegee: de novo identification of reagent and laboratory induced microbial contaminants in low biomass microbiomes
<p> </p> <p>Computational analysis of host-associated microbiomes has opened the door to numerous discoveries relevant to human health and disease. However, contaminant sequences in metagenomic samples can potentially impact the interpretation of findings reported in microbiome studies, especially in low biomass environments. Our hypothesis is that contamination from DNA extraction kits or sampling lab environments will leave taxonomic "bread crumbs” across multiple distinct sample types, allowing for the detection of microbial contaminants when negative controls are unavailable. To test this hypothesis we implemented Squeegee, a de novo contamination detection tool. We tested Squeegee on simulated and real low biomass metagenomic datasets. On the low biomass samples, we compared Squeegee predictions to experimental negative control data and show that Squeegee accurately recovers known contaminants. We also analyzed 749 metagenomic datasets from the Human Microbiome Project and identified likely previously unreported kit contamination. Collectively, our results highlight that Squeegee can identify microbial contaminants with high precision.</p>
Squeegee: de novo identification of reagent and laboratory induced microbial contaminants in low biomass microbiomes, simulation dataset 0.5% spike-in contaminant sequences
<p>Computational analysis of host-associated microbiomes has opened the door to numerous discoveries relevant to human health and disease. However, contaminant sequences in metagenomic samples can potentially impact the interpretation of findings reported in microbiome studies, especially in low biomass environments. Our hypothesis is that contamination from DNA extraction kits or sampling lab environments will leave taxonomic "bread crumbs” across multiple distinct sample types, allowing for the detection of microbial contaminants when negative controls are unavailable. To test this hypothesis we implemented Squeegee, a de novo contamination detection tool. We tested Squeegee on simulated and real low biomass metagenomic datasets. On the low biomass samples, we compared Squeegee predictions to experimental negative control data and show that Squeegee accurately recovers known contaminants. We also analyzed 749 metagenomic datasets from the Human Microbiome Project and identified likely previously unreported kit contamination. Collectively, our results highlight that Squeegee can identify microbial contaminants with high precision.</p> <p> </p> <p>Simulation Dataset 0.5% contaminant spike-in. </p>
Data from: Soil microbial species loss affects plant biomass and survival of an introduced bacterial strain, but not inducible plant defences
Open the record for dataset details and reuse information.
Soil microbial biomass and enzyme kinetics for the assessment of temporal diversification in agroecosystems
Open the record for dataset details and reuse information.
A Compilation of Global Soil Microbial Biomass Carbon, Nitrogen, and Phosphorus Data
This data set provides the concentrations of soil microbial biomass carbon (C), nitrogen (N) and phosphorus (P), soil organic carbon, total nitrogen, and total phosphorus at biome and global scales. The data were compiled from a comprehensive survey of publications from the late 1970s to 2012 and include 3,422 data points from 315 papers. These data are from soil samples collected primarily at 0-15 cm depth with some from 0-30 cm. In addition, data were compiled for soil microbial biomass concentrations from soil profile samples to depths of 100 cm. Sampling site latitude and longitude were available for the majority of the samples that enabled assembling additional soil properties, site characteristics, vegetation distributions, biomes, and long-term climate data from several global sources of soil, land-cover, and climate data. These site attributes are included with the microbial biomass data. This data set contains two *.csv files of the soil microbial biomass C, N, P data. The first provides all compiled results emphasizing the full spatial extent of the data, while the second is a subset that provides only data from a series of profile samples emphasizing the vertical distribution of microbial biomass concentrations.There is a companion file, also in .csv format, of the references for the surveyed publications. A reference_number relates the data to the respective publication.The concentrations of soil microbial biomass, in combination with other soil databases, were used to estimate the global storage of soil microbial biomass C and N in 0-30 cm and 0-100 cm soil profiles. These storage estimates were combined with a spatial map of 12 major biomes (boreal forest, temperate coniferous forest, temperate broadleaf forest, tropical and subtropical forests, mixed forest, grassland, shrub, tundra, desert, natural wetland, cropland, and pasture) at 0.05-degree by 0.5-degree spatial resolution. The biome map and six estimates of C and N storage and C:N ration in soil microbial biomass are provided in a single netCDF format file.
LBA-ECO ND-07 Microbial Biomass in Cerrado Soils, Brasilia, Brazil
This data set reports the microbial biomass in soil samples collected from the Cerrado, a woodlands-savannah area, in Brasilia, Brazil. Microbial biomass was determined as the total concentration of phospholipid fatty acids (PLFAs). Soil samples (0-5 cm) were collected from June, 2000 to June, 2001 in two native areas of Cerrado that were subjected to a range of fire regimes. Two plots were protected from fire since 1973, another two plots were subjected to prescribed fires every two years since 1992, and a fifth plot was in a 20 year-old active pasture (Brachiaria brizantha). The analyses were conducted to determine the effects of fire regimes and changes in vegetation cover on the microbial communities of Cerrada soils. There is one comma-separated ASCII data file with this data set.
Annual Removal of Aboveground Plant Biomass Alters Soil Microbial Responses to Warming
GEO Series GSE86527. Fungi; Viruses; Bacteria; Archaea. 24 samples. Type: Genome variation profiling by array.
Data from: Contrasting effects of ammonium and nitrate additions on the biomass of soil microbial communities and enzyme activities in subtropical China
The nitrate to ammonium ratios in nitrogen (N) compounds in wet atmospheric deposits have increased over the recent past, which is a cause for some concern as the individual effects of nitrate and ammonium deposition on the biomass of different soil microbial communities and enzyme activities are still poorly defined. We established a field experiment and applied ammonium (NH4Cl) and nitrate (NaNO3) at monthly intervals over a period of 4 years. We collected soil samples from the ammonium and nitrate treatments and control plots in three different seasons, namely spring, summer, and fall, to evaluate the how the biomass of different soil microbial communities and enzyme activities responded to the ammonium (NH4Cl) and nitrate (NaNO3) applications. Our results showed that the total contents of phospholipid fatty acids (PLFAs) decreased by 24 and 11 % in the ammonium and nitrate treatments, respectively. The inhibitory effects of ammonium on Gram-positive bacteria (G+) and bacteria, fungi, actinomycetes, and arbuscular mycorrhizal fungi (AMF) PLFA contents ranged from 14 to 40 % across the three seasons. We also observed that the absolute activities of C, N, and P hydrolyses and oxidases were inhibited by ammonium and nitrate, but that nitrate had stronger inhibitory effects on the activities of acid phosphatase (AP) than ammonium. The activities of N-acquisition specific enzymes (enzyme activities normalized by total PLFA contents) were about 21 and 43 % lower in the ammonium and nitrate treatments than in the control, respectively. However, the activities of P-acquisition specific enzymes were about 19 % higher in the ammonium treatment than in the control. Using redundancy analysis (RDA), we found that the measured C, N, and P hydrolysis and polyphenol oxidase (PPO) activities were positively correlated with the soil pH and ammonium contents, but were negatively correlated with the nitrate contents. The PLFA biomarker contents were positively correlated with soil pH, soil organic carbon (SOC), and total N contents, but were negatively correlated with the ammonium contents. The soil enzyme activities varied seasonally, and were highest in March and lowest in October. In contrast, the contents of the microbial PLFA biomarkers were higher in October than in March and June. Ammonium may inhibit the contents of PLFA biomarkers more strongly than nitrate because of acidification. This study has provided useful information about the effects of ammonium and nitrate on soil microbial communities and enzyme activities.
Global patterns and drivers of soil microbial biomass C, N, and P in terrestrial ecosystems
<p>Soil microbes<strong> </strong>play key roles in driving and regulating nutrient cycling in terrestrial ecosystems. However, a lack of global-scale information regarding the distribution of soil microbial biomass C (SMB C), N (SMB N), and P (SMB P) in terrestrial ecosystems has limited our ability to incorporate the broad-scale soil microbial nutritional properties and the associated processes into biogeochemical models. Here, we synthesized a global dataset including 3,801 observations for SMB C, 3,154 observations of SMB N, and 2,429 observations of SMB P in the top 0–30 cm soil depth. Based on this comprehensive global dataset, we generated quantitative and spatially explicit maps of SMB C, N, and P across terrestrial ecosystems using a random forest approach. In general, the global mean values of SMB C, N, and P concentrations were 693.0 mg kg<sup>-1</sup>, 89.5 mg kg<sup>-1</sup>, and 35.5 mg kg<sup>-1</sup>, respectively. These mean values belie a significantly spatial heterogeneity of these concentrations across biomes and a clear latitudinal trend (wherein SMB C, N, and P increase in cold and high latitude environments along with the large soil organic carbon, SOC). SOC was the most important factor regulating SMB C, N, and P at a global scale. At the global scale, the storage of SMB C, N, and P was estimated to be 23.13 Pg C, 3.93 Pg N, and 2.16 Pg P in the top 0–30 cm soil surface, respectively. Our global maps of SMB C, N, and P presented here can be used to constraint Earth system models, and provide the first step forward to predict the roles of soil microbial nutrients in terrestrial nutrient cycling.</p>
Data from: Contrasting effects of ammonium and nitrate additions on the biomass of soil microbial communities and enzyme activities in subtropical China
Open the record for dataset details and reuse information.
Global patterns and drivers of soil microbial biomass C, N, and P in terrestrial ecosystems
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.