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.
395
datasets available to search
ShareScore release 0.7.1
Dataset results
395 results for “carbon to nitrogen”
Climate Change Across Seasons Experiment (CCASE) at the Hubbard Brook Experimental Forest; concentrations of foliar metabolites: polyamines, amino acids, chlorophyll, carotenoids, soluble proteins, soluble elements, sugars, and total nitrogen and carbon in red maple (Acer rubrum) trees.
Foliage was collected in 2015 and 2017 from red maple trees at the Climate Change Across Seasons Experiment (CCASE) as part of the Hubbard Brook Ecosystem Study (HBES). Analyses of foliar metabolites include polyamines, amino acids, chlorophylls, carotenoids, soluble proteins, soluble inorganic elements, sugars, and total nitrogen and carbon. There are six (11 x 14m) plots in total in this study; two control (plots 1 and 2), two warmed 5 degrees (°) Celsius (C) above ambient throughout the growing season (plots 3 and 4), and two warmed 5 °C in the growing season, with snow removal during the winter to induce soil freezing and then warmed with buried heating cables to create a subsequent thaw (plots 5 and 6). Each soil freeze/thaw cycle includes 72 hours of soil freezing followed by 72 hours of thaw. Four kilometers (km) of heating cable are buried in the soil to warm these four plots. Together, these treatments led to warmer growing season soil temperatures and an increased frequency of soil freeze-thaw cycles (FTCs) in winter. Our goal was to determine how these changes in soil temperature affect foliar nitrogen (N) and carbon metabolism of red maple trees. These data were gathered as a collaborative effort at the Hubbard Brook Experimental Forest, which is operated and maintained by the USDA Forest Service, Northern Research Station.
Quantitative Pit Soil Carbon and Nitrogen on Watershed 5 at the Hubbard Brook Expermental Forest, 1983-1998
We sampled soils prior to the whole-tree harvest of watershed 5 at Hubbard Brook Experimental Forest in 1983, and again in 1986, 1991, and 1998, using the quantitative soil pit method. Here we report soil mass, C and N concentrations, and loss-on-ignition for each horizon in each of the 239 soil pits excavated over the four sampling years. These data were gathered as part of the Hubbard Brook Ecosystem Study (HBES). The HBES is a collaborative effort at the Hubbard Brook Experimental Forest, which is operated and maintained by the USDA Forest Service, Northern Research Station.
Soil carbon, soil nitrogen, and geometry of 30 playas and their catchment areas at the Jornada Basin LTER site in 2012
This data package contains soil carbon and nitrogen data at a range of soil depths from 30 ephemerally-flooded desert wetlands, or playas, in the Jornada Basin of southern New Mexico, USA. We conducted this study to assess how catchment biophysical variables control soil organic carbon and nitrogen in playas and how playas function differently than upland ecosystems. We chose 30 playas from across this Chihuahuan Desert Basin and collected 36 soil samples from four depths and nine locations. Soil cores samples were taken along two perpendicular transect lines to account for a topographic gradient from the edge of the playa to the center of the playa. At each of the nine locations, one sample was collected at four depths (0–10 cm, 10–30 cm, 30–60 cm, 60–100 cm). We measured soil organic carbon and total nitrogen concentrations in these soils using elemental combustion analysis. Using bulk density measurements for each depth range (m), we converted each soil measurement (g/g) to calculate concentrations of organic carbon and nitrogen per unit area (g/m^2) within the depth-ranges sampled. Data on the geometry of the playas and their associated catchments is also provided. This study is complete. For further information, refer to: McKenna, Owen P., and Osvaldo E. Sala. "Biophysical controls over concentration and depth distribution of soil organic carbon and nitrogen in desert playas." Journal of Geophysical Research: Biogeosciences 121, no. 12 (2016): 3019-3029. https://doi.org/10.1002/2016JG003545
Soil Total Carbon and Total Nitrogen on the Main Cropping System Experiment at the Kellogg Biological Station, Hickory Corners, MI (1989 to 2001)
Dataset Abstract Soil carbon and nitrogen are presented as % elemental carbon and nitrogen (g C or N / 100 g soil) for the sampling depth of the specific sampling date unless indicated otherwise. Samples were taken with either a 2.5 cm diameter soil corer (sampling by soil depth) or a 10 cm diameter Giddings probe (sampling by soil profile). See Baseline Soil Sampling protocol for general sampling information. For specific sampling details for a particular date, see Soil Sampling Field Log. Soil samples are sieved to 4mm and composited by plot. Soil % elemental carbon and nitrogen values are determined by sample combustion and subsequent TCD gas chromatography, using a Carlo Erba automated CHN analyzer as described in the sampling protocol. original data source http://lter.kbs.msu.edu/datasets/27
Soil Carbon and Nitrogen Deep Core Surveys at the Kellogg Biological Station, Hickory Corners, MI (2001 to 2013)
Dataset Abstract An LTER project goal is to periodically collect and analyze deep soil cores for the main site treatments and successional and forest sites. Soil is sampled to a depth of one meter, and analyzed for horizon depths, texture, moisture, and carbon and nitrogen content. original data source http://lter.kbs.msu.edu/datasets/47
Spatial Variation of Soil Carbon, Nitrogen and Phosphorus in the Luquillo Experimental Forest (LEF) (LEF_SOIL_CNP)
Hongqing Wang, a Ph.D graduate student of SUNY-ESF, with the help of many others, took soil samples in 119 locations over the entire Luquillo Experimental Forest (LEF) during the summer of 1998 and 1999. Soil organic carbon, total nitrogen and acid-extractable phosphorus were measured in the laboratory of SUNY-ESF; soil moisture and bulk density were measured at the laboratory of the El Verde Station of UPR. The geodetic coordinates (Lat., Lon.) and elevation of each sampling location were determined using a Global Positioning System (GPS Pathfinder Basic Receivers, Trimble Navigation Ltd.) in the field. Meanwhile, slope angle, aspect and topographic features (Ridge, slope I (<35 deg.), slope II (>=35 deg.), valleys) were also measured and observed in the field. Support for this work was provided by grants BSR-8811902, DEB-9411973, DEB-9705814 , DEB-0080538, DEB-0218039 , DEB-0620910 , DEB-1239764, DEB-1546686, and DEB-1831952 from the National Science Foundation to the University of Puerto Rico as part of the Luquillo Long-Term Ecological Research Program. Additional support provided by the University of Puerto Rico and the International Institute of Tropical Forestry, USDA Forest Service.
McMurdo Dry Valleys Lake Bonney Autonomous Lake Profiler and Samplers (ALPS): Particulate Organic Carbon and Nitrogen Concentrations
Knowledge of the McMurdo Dry Valley (MDV) lakes is limited by winter access, a period which is most relevant in understanding the habitability of other icy worlds and critical to understanding the overall function of these lakes. Owing to the lack of winter access, data that normally require human presence are incomplete. Our goal was to conduct the first year-round investigation of the biogeophysics of these unique lakes. An important part of the McMurdo Long Term Ecological Research (LTER) is evaluating carbon and nitrogen budgets in perennial ice-covered lakes. This data set addresses this core area of research and quantifies the particulate carbon and nitrogen found at specific depths in McMurdo Dry Valley lakes.
Temporal Dynamics of Soil Carbon and Nitrogen Resources Within a Grassland-Creosote Ecotone at the Sevilleta National Wildlife Refuge, New Mexico (1992-1994)
Plant communities across large portions of the southwestern United States have shifted from grassland to desert shrubland. Studies have demonstrated that soil nutrient resources become spatially more heterogeneous and are redistributed into islands of fertility with this shift in vegetation. This research addressed the additional question of whether soil resources become more temporally heterogeneous along a grassland-shrubland ecotome. Within adjacent grassland and creosotebush sites, soil profiles were described at 3 pits and samples collected for description of nutrient resources within the profile. Relative cover of plant species and bare soil were determined within each site by line transects. The top 20-cm of bare soil or soil beneath the canopy of grasses/creosotebush were collected 17 times during 1992-1994. Soil samples were analyzed for soil moisture, extractable ammonium and nitrate, nitrogen mineralization potential, microbial biomass carbon, total organic carbon, microbial respiration, dehydrogenase activity, ratio of microbial C to total C (C[mic]-to-C[org]), and microbial respiration to biomass carbon (metabolic quotient). The major differences in the structure of soils between sites were the apparent loss of a 3 to 5-cm depth of sandy surface soil at the creosotebush site and an associated increase in calcium carbonate content at a more shallow depth. Soils under plants at both sites had greater total and available nutrient resources with higher concentrations under creosotebush than under grasses. Greatest temporal variation in available soil resources was shown in soils under creosotebush. When expressed on an area basis, greater temporal variation in the total amount of available soil resources was shown in the grassland site, primarily due to greater plant cover (45% in grassland vs. 8% in creosote).
SGS-LTER Earthwatch Project - Nitrogen and Carbon in Native, Abandoned and Cultivated Fields in eastern Colorado, USA 1991
This data package was produced by researchers working on the Shortgrass Steppe Long Term Ecological Research (SGS-LTER) Project, administered at Colorado State University. Long-term datasets and background information (proposals, reports, photographs, etc.) on the SGS-LTER project are contained in a comprehensive project collection within the Digital Collections of Colorado (http://digitool.library.colostate.edu/R/?func=collections&collection_id=3429). The data table and associated metadata document, which is generated in Ecological Metadata Language, may be available through other repositories serving the ecological research community and represent components of the larger SGS-LTER project collection. Our objective in this study was to evaluate effects of land use on in situ net N mineralization in shortgrass steppe by comparing native and abandoned fields and cultivated fields, and by comparing soil under and between plants within native and abandoned fields. We also compared mineralization patterns between in situ and laboratory incubations to evaluate the role of environmental restrictions in determining N supply across management treatments and microsites. Additional information and referenced materials can be found: http://hdl.handle.net/10217/82140
SGS-LTER CO2 Elevation Study: Leaf carbon isotope, nitrogen, carbon and Ci/Ca means from the SGS Open Top Chamber experiment on the Central Plains Experimental Range, Nunn, Colorado, USA 1997 - 2001
This data package was produced by researchers working on the Shortgrass Steppe Long Term Ecological Research (SGS-LTER) Project, administered at Colorado State University. Long-term datasets and background information (proposals, reports, photographs, etc.) on the SGS-LTER project are contained in a comprehensive project collection within the Digital Collections of Colorado (http://digitool.library.colostate.edu/R/?func=collections&collection_id=3429). The data table and associated metadata document, which is generated in Ecological Metadata Language, may be available through other repositories serving the ecological research community and represent components of the larger SGS-LTER project collection. Additional information and referenced materials can be found: http://hdl.handle.net/10217/82454. Carbon isotopes of elevated and ambient OTC plants were measured for use in isotope labeling and plant water-use-efficiency measures. Leaf N and C are associated parameters were also measured. This research was conducted at the Central Plains Experimental Range, near Nunn, CO; lat.40degrees 40 minutes N; long. 104 degrees 45 minutes W in the shortgrass steppe region of NE Colorado, USA and as a collaboration between SGS-LTER and USDA-ARS researchers.
Shoot height and average carbon:nitrogen ratio for Spartina alterniflora in intertidal marshes on Hog Island, Parramore Island, Quinby inlet, and Phillips Creek of the Virginia Coast Reserve 1988-1989
Shoot height and average carbon:nitrogen ratio for Spartina alterniflora in intertidal marshes on Hog Island (Cattleshed Creek and Hodges Narrows), Parramore Island (Cresent Island: South Parramore), Quinby Inlet (Chimney Pole Marsh), and Phillips Creek (Phillips Creek) of the Virginia Coast Reserve 1988-1989.
Data from: Leaching losses of dissolved organic carbon and nitrogen from agricultural soils in the upper US Midwest
<p>Leaching losses of dissolved organic carbon (DOC) and nitrogen (DON) from agricultural systems are important to water quality and carbon and nutrient balances but are rarely reported; the few available studies suggest linkages to litter production (DOC) and nitrogen fertilization (DON). In this study we examine the leaching of DOC, DON, NO<sub>3</sub><sup>-</sup>, and NH<sub>4</sub><sup>+</sup> from no-till corn (maize) and perennial bioenergy crops (switchgrass, miscanthus, native grasses, restored prairie, and poplar) grown between 2009 and 2016 in a replicated field experiment in the upper Midwest U.S. Leaching was estimated from concentrations in soil water and modeled drainage (percolation) rates. DOC leaching rates (kg ha<sup>-1 </sup>yr<sup>-1</sup>) and volume-weighted mean concentrations (mg L<sup>-1</sup>) among cropping systems averaged 15.4 and 4.6, respectively; N fertilization had no effect and poplar lost the most DOC (21.8 and 6.9, respectively). DON leaching rates (kg ha<sup>-1 </sup>yr<sup>-1</sup>) and volume-weighted mean concentrations (mg L<sup>-1</sup>) under corn (the most heavily N-fertilized crop) averaged 4.5 and 1.0, respectively, which was higher than perennial grasses (mean: 1.5 and 0.5, respectively) and poplar (1.6 and 0.5, respectively). NO<sub>3</sub><sup>-</sup> comprised the majority of total N leaching in all systems (59-92%). Average NO<sub>3</sub><sup>-</sup> leaching (kg N ha<sup>-1</sup> yr<sup>-1</sup>) under corn (35.3) was higher than perennial grasses (5.9) and poplar (7.2). NH<sub>4</sub><sup>+</sup> concentrations in soil water from all cropping systems were relatively low (<0.07 mg N L<sup>-1</sup>). Perennial crops leached more NO<sub>3</sub><sup>-</sup> in the first few years after planting, and markedly less after. Among the fertilized crops, the leached N represented 14-38% of the added N over the study period; poplar lost the greatest proportion (38%) and corn was intermediate (23%). Requiring only one third or less of the N fertilization compared to corn, perennial bioenergy crops can substantially reduce N leaching and consequent movement into aquifers and surface waters.</p>
Quality control for modern bone collagen stable carbon and nitrogen isotope measurements
<p><strong>(1)</strong> Isotopic analyses of collagen, the main protein preserved in sub fossil bone and tooth, has long provided a powerful tool for the reconstruction of ancient diets and environments. Although isotopic studies of contemporary ecosystems have typically focused on more accessible tissues (e.g., muscle, hair), there is growing interest in the potential for analyses of collagen because it is often available in hard tissue archives (e.g., scales, skin, bone, tooth), allowing for enhanced long-term retrospective studies. The quality of measurements of the stable carbon and nitrogen isotopic compositions of ancient samples are subject to robust and well-established criteria for detection of contaminants and digenesis. Among these quality control (QC) criteria, the most widely utilized is the atomic C:N ratio (C:N<sub>Atomic</sub>), which for ancient samples has an acceptable range between 2.9 and 3.6. While this QC criterion was developed for ancient materials, it has increasingly being applied to collagen from modern tissues.</p> <p><strong>(2)</strong> Here we use a large survey of published collagen amino acid compositions (n<em> </em>= 436) from 193 vertebrate species as well as recent experimental isotopic evidence from 413 modern collagen extracts to demonstrate that the C:N<sub>Atomic</sub> range used for ancient samples is not suitable for assessing collagen quality of modern and archived historical samples.</p> <p><strong>(3) </strong>For modern tissues, collagen C:N<sub>Atomic</sub> falling outside 3.00–3.30 for fish and 3.00–3.28 for mammals and birds can produce systematically skewed isotopic compositions and may lead to significant interpretative errors. These findings are followed by a review of protocols for improving C:N<sub>Atomic</sub> criteria for modern collagen extracts.</p> <p><strong>(4)</strong> Given the tremendous conservation and environmental policy-informing potential that retrospective isotopic analyses of collagen from contemporary and archived vertebrate tissues have for addressing pressing questions about long-term environmental conditions and species behaviours, it is critical that QC criteria tailored to modern tissues are established.</p>
Data from: Accounting for disturbance history in models: using remote sensing to constrain carbon and nitrogen pool spin‐up
Disturbances such as wildfire, insect outbreaks, and forest clearing, play an important role in regulating carbon, nitrogen, and hydrologic fluxes in terrestrial watersheds. Evaluating how watersheds respond to disturbance requires understanding mechanisms that interact over multiple spatial and temporal scales. Simulation modeling is a powerful tool for bridging these scales; however, model projections are limited by uncertainties in the initial state of plant carbon and nitrogen stores. Watershed models typically use one of two methods to initialize these stores: spin-up to steady state, or remote sensing with allometric relationships. Spin-up involves running a model until vegetation reaches equilibrium based on climate; this approach assumes that vegetation across the watershed has reached maturity and is of uniform age, which fails to account for landscape heterogeneity and non-steady state conditions. By contrast, remote sensing, can provide data for initializing such conditions. However, methods for assimilating remote sensing into model simulations can also be problematic. They often rely on empirical allometric relationships between a single vegetation variable and modeled carbon and nitrogen stores. Because allometric relationships are species- and region-specific, they do not account for the effects of local resource limitation, which can influence carbon allocation (to leaves, stems, roots, etc.). To address this problem, we developed a new initialization approach using the catchment-scale ecohydrologic model RHESSys. The new approach merges the mechanistic stability of spin-up with the spatial fidelity of remote sensing. It uses remote sensing to define spatially explicit targets for one, or several vegetation state variables, such as leaf area index, across a watershed. The model then simulates the growth of carbon and nitrogen stores until the defined targets are met for all locations. We evaluated this approach in a mixed pine-dominated watershed in central Idaho, and a chaparral-dominated watershed in southern California. In the pine-dominated watershed, model estimates of carbon, nitrogen, and water fluxes varied among methods, while the target-driven method increased correspondence between observed and modeled streamflow. In the chaparral watershed, where vegetation was more homogeneously aged, there were no major differences among methods. Thus, in heterogeneous, disturbance-prone watersheds, the target-driven approach shows potential for improving biogeochemical projections.
Data for mycorrhizal C/N ratio determines plant-derived carbon and nitrogen allocation to symbiosis
<p><span><span>Nutrient cycling in temperate forests is driven by carbon allocation of trees to soil via ectomycorrhizas (EM). The sink activities of different fungal taxa for host resources are unknown. Aboveground dual </span><span>labeling of young beech<span> with <sup>15</sup>N and <sup>13</sup>C was used to trace resource transport to ectomycorrhizal root tips. Isotope enrichment in EM correlated with that in the corresponding EM-attached lateral root, supporting that EM drive taxon-specific N- and C-fluxes. The enrichments with <sup>13</sup>C and <sup>15</sup>N in EM increased with decreasing C/N ratio of the symbiotic association. Abundances of EM species were positively correlated with <sup>13</sup>C enrichment, demonstrating higher fitness of stronger than of less C-demanding symbioses. Overall, our results imply that differences among the resource traits of EM species regulate the supply of the symbioses with host-derived C and N.</span></span></span></p> <p><span><span><span>Here we provide the data sets containing information on the identities of fungal species colonizing roots tips of European beech and for N, C, 15N and 13C contents in bark, coarse roots, fine roots, very fine lateral roots, ectomycorrhizal species and rhizosphere soil and for biomass of the different compartments. The data were collected 5 and 20 days after labelling.</span></span></span></p>
Bulk Carbon and Amino Acid nitrogen isotope data from Baltic cod (Gadus morhua) and European flounder (Platichthys flesus) muscle tissue samples from the western and central Baltic Sea
<p><span>Eutrophication, increased temperatures and stratification can lead <span>to massive, filamentous, N<sub>2</sub>-fixing cyanobacterial (FNC) blooms in coastal ecosystems with largely unresolved consequences for the mass and energy supply in pelagic and benthic food webs. Mesozooplankton adapt to not top-down controlled FNC blooms by switching diets from phytoplankton to microzooplankton, resulting in a directly quantifiable increase in its trophic position (TP) from 2.0 (herbivore) to as high as 3.0 (carnivore). If this process in mesozooplankton, we call trophic lengthening, was transferred up to higher trophic levels of a food web, a large loss of energy could result in massive declines of fish biomass. </span></span><span>We used compound-specific nitrogen stable isotope data of amino acids (CSIA) to estimate and compare </span><span>the nitrogen (N) sources and TPs of cod and flounder (mesopredators) from areas</span><span> </span><span>with influence of FNC blooms (central Baltic Sea) and without it (western Baltic Sea)</span><span>. We tested if FNC-caused </span><span>trophic lengthening in mesozooplankton is carried over to fish.</span><span> The TP of cod from the western Baltic, feeding mainly on decapods, was equal to the global mean value (4.1, secondary carnivore). Only cod from the central Baltic, mainly feeding on zooplanktivorous pelagics, had a higher TP (4.8, near-tertiary carnivore), indicating a strong carry-over effect of </span><span>FNC-</span><span>caused trophic lengthening from mesozooplankton. In contrast, the TP of molluscivorous flounder (3.2 ± 0.2 in both areas), associated with the benthic food web, was unaffected by trophic lengthening. This suggests that FNC blooms cause a large loss of energy in zooplanktivorous but not in molluscivorous mesopredators. If FNC blooms continue to detour energy at the base of the pelagic food web, the TP of cod will not return to global mean values and the fish stock not recover. Monitoring the TP of key species can identify fundamental changes in ecosystems and provide useful information for resource management.</span></p>
Engineering Machine Learning features to predict adsorption of carbon dioxide and nitrogen in metal-organic frameworks
<p>This repository contains CIF files for metal-organic frameworks and Grand canonical Monte Carlo (GCMC) simulation results for the article <em>Engineering Machine Learning features to predict adsorption of carbon dioxide and nitrogen in metal-organic frameworks</em> by Zijun Deng and Lev Sarkisov.</p>
Carbon footprint of synthetic nitrogen under staple crops: A first cradle-to-grave analysis
<p>More than half of the world's population is nourished by crops fertilized with synthetic nitrogen (N). However, N fertilization is a major source of anthropogenic emissions, augmenting the carbon footprint (CF). To date, no global quantification of the CF induced by N fertilization of the main grain crops has been performed, and quantifications at the national scale have neglected the CO<sub>2</sub> assimilated by plants. A first Cradle-Grave life cycle assessment was performed to quantify the CF of the N fertilizers' production, transportation, and application to the field and the uses of the produced biomass in livestock feed, human food, and biofuel production. We quantified direct and indirect inventories emitted or sequestered by the N fertilization of grain crops (wheat, maize, and rice). Grain food produced with N fertilization had a net CF of 7.4 Gt CO<sub>2</sub>eq. in 2019 after excluding the assimilated C in plant biomass, which accounted for a quarter of the total CF. The Cradle (fertilizer production and transportation), Gate (fertilizer application, and soil and plant systems), and Grave (feed, food, biofuel, and losses) stages contributed to the CF by 2, 11, and 87%, respectively. Although Asia was the top grain producer, North America contributed 38% of the CF due to the greatest CF of the Grave stage (2.5 Gt CO<sub>2</sub>eq.). The CF of grain crops will increase to 21.2 Gt CO<sub>2</sub>eq. in 2100, driven by the rise in N fertilization to meet the growing food demand without actions to stop the decline in N use efficiency. To meet the targets of climate change, we introduced an ambitious mitigation strategy, including the improvement of N agronomic efficiency (6% average target for the three crops) and manufacturing technology, reducing food losses, and global conversion to healthy diets, whereby the CF can be reduced to 5.6 Gt CO<sub>2</sub>eq. in 2100.</p>
Data for: Nitrogen dynamics and carbon sequestration in soil following application of digestates from one- and two-step anaerobic digestion
<p>Data set for article <span>Nitrogen dynamics and carbon sequestration in soil following application of digestates from one- and two-step anaerobic digestion (https://doi.org/10.1016/j.scitotenv.2022.158177).</span></p>
SUPPLEMENTARY TABLES: Defining the Sphagnum core microbiome across the North American continent reveals a central role for diazotrophic-methanotrophs in the nitrogen and carbon cycles of boreal peatland ecosystems
<p>Peat mosses of the genus <em>Sphagnum</em> are ecosystem engineers that frequently predominate over photosynthetic production in boreal peatlands. <em>Sphagnum</em> spp. host diverse microbial communities capable of nitrogen-fixation (diazotrophy) and methane oxidation (methanotrophy), thereby potentially supporting plant growth under severely nutrient-limited conditions. Moreover, diazotrophic-methanotrophs represent a possible "missing link" between the carbon and nitrogen cycles, but the functional contributions of the <em>Sphagnum</em>-associated microbiome remain in question<em>.</em> A combination of metagenomics, metatranscriptomics, and dual-isotope incorporation assays was applied to investigate <em>Sphagnum</em> microbiome community composition across the North American continent and provide empirical evidence for diazotrophic-methanotrophy in <em>Sphagnum</em>-dominated ecosystems. Remarkably consistent prokaryotic communities were detected in over 250 <em>Sphagnum</em> SSU rRNA libraries from peatlands across the US (5 states, 17 bog/fen sites, 18 <em>Sphagnum</em> species), with twelve genera of the core microbiome comprising 60% of the relative microbial abundance. Additionally, nitrogenase (<em>nifH</em>) and SSU rRNA gene amplicon analysis revealed that nitrogen-fixing populations made up nearly 15% of the prokaryotic communities, predominated by <em>Nostocales</em> cyanobacteria and <em>Rhizobiales</em> methanotrophs. While cyanobacteria comprised the vast majority (>95%) of diazotrophs detected in amplicon and metagenome analyses, obligate methanotrophs of the genus <em>Methyloferula</em> (order <em>Rhizobiales</em>) accounted for one-quarter of transcribed <em>nifH</em> genes. Furthermore, in dual-isotope tracer experiments, members of the <em>Rhizobiales</em> showed substantial incorporation of <sup>13</sup>C-CH<sub>4</sub> and <sup>15</sup>N-N<sub>2</sub> isotopes into their rRNA. Our study characterizes the core <em>Sphagnum</em> microbiome across large spatial scales and indicates that diazotrophic methanotrophs, here defined as obligate methanotrophs of the rare biosphere (<em>Methyloferula</em> spp. of the <em>Rhizobiales</em>) that also carry out diazotrophy, play a keystone role in coupling of the carbon and nitrogen cycles in nutrient-poor peatlands.</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.