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57 results for “carbon (C)”
Total Particulate Carbon and Nitrogen Concentration from R/V Melville MV1015 in the S. Pacific from Arica, Chile to Easter Island, 2010 (C-MORE project)
<p>"The South East Pacific (SEP) is characterized by very high nutrient concentrations in the waters adjacent to the Chilean coast, but very low nutrient concentrations (oligotrophic) in the mid- South Pacific Subtropical Gyre (SPSG), near Easter Island. The steep gradient in nutrient concentrations across the region affects the level of marine production, the composition of the microbial community, and the operation of major biogeochemical cycles in ways that are not fully understood. Despite the remarkable diversity of trophic conditions, strong gradients and even some unique singularities, the SEP is still the most sparsely sampled oceanic region of the global ocean from hydrodynamic, biological and biogeochemical points of view. The SPSG is also the most oligotrophic of all sub-tropical gyres. Previous expeditions and remote sensing studies have described the nutrient and chlorophyll field, but there have been few simultaneous measurements of chemical properties with microbial community structure and function. This expedition is designed to investigate the impact of elemental nutrient (nitrogen, phosphorus, iron, silicon, carbon) ratios on marine productivity and microbial community composition. Samples for PC (particulate carbon) and PN (particulate nitrogen) were collected on a combusted 25mm glass fiber filter (GF/F) and stored in a -80 freezer until analysis. Samples were further analyzed using a Carlo Erba NA 1500 Elemental Analyzer." Time is in GMT. Note: it is questionable if the 500m sample collected on 2010-11-27 was really taken at 500m (see comment on data sheet). This “best guess” for depth was included in the data for CMAP visualization purposes.</p> <p>This description has been reproduced using the following source:<br> <br> http://dmoserv3.bco-dmo.org/jg/info/BCO-DMO/CMORE/bigrapa/PCPN%7Bdir=dmoserv3.bco-dmo.org:80/jg/dir,data=dmoserv3.bco-dmo.org:80/jg/serv/BCO-DMO/CMORE/bigrapa/PCPN.html1%7D?</p>
Decreasing landscape carbon storage in western US forests with 2˚C of warming
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Soil carbon, nitrogen, and phosphorus cycling microbial populations and their resistance to global change depend on C:N:P stoichiometry
<p><span>Maintaining the stability of ecosystem functions to global change calls for a better understanding the regulatory factors of functionally specialized microbial-groups and their population-response to disturbance. Here, we explored this issue by collecting soils from 54 managed ecosystems in China and building a predictive model of microcosm experiments. <span>S</span><span>oil carbon:nitrogen:phosphorus (C:N:P) stoichiometry</span> <span>(3</span><span>5</span><span>%~4</span><span>9</span><span>%)</span> imparted a greater individual effects on the abundances of microbial-groups associated with main carbon C, N, and P biogeochemical processes in comparison with geographical conditions <span>(7%~10%).</span> <span>Soil</span><span> total </span><span>C </span><span>and N </span><span>content</span><span>s were</span><span> significantly positively correlated with the abundances of </span><span>d</span><span>iazotrophs</span><span> (</span><i><span><span>nifH</span></span></i><span>), </span><span>n</span><span>itrifiers</span><span> (bacterial </span><i><span><span>amoA</span></span></i><span>), </span><span>n</span><span>itrate </span><span>r</span><span>educers</span><span> (</span><i><span><span>narG</span></span></i><span>) and d</span><span>enitrifiers</span><span> (</span><i><span><span>nirS</span></span></i><span>/</span><i><span><span>K</span></span></i><span> and </span><i><span><span>nosZ </span></span></i><span>genes).</span><span> Soil C:</span><span>N</span><span> ratio not only exhibited a negative relationship with the abundances of </span><span>P activators</span><span> (</span><i><span><span>phoD</span></span></i><span><span>,</span></span> <i><span><span>phoC</span></span></i><i> </i><span>and </span><i><span><span>pqqC</span></span></i><span> genes</span><span>)</span><span>, but also with </span><span>c</span><span>ellulolytic</span><span> decomposers</span><span> (</span><i><span><span>fungcbhIR</span></span></i><span> and </span><i><span><span>GH74</span></span></i> <span>genes)</span><span>. N</span><span>itrogen</span><span> cycling </span><span>genes, including bacterial </span><i><span><span>amoA</span></span></i><span>,</span><i><span><span> nirS</span></span></i><span>, </span><i><span><span>narG</span></span></i><span> and </span><i><span><span>norB</span></span></i><span>,</span> <span>exhibited</span><span> high</span><span>er</span><span> genetic resistance to </span><span>N deposition</span><span> compared with the </span><span>drying-wetting cycles</span><span> and </span><span>warming</span><span>. </span><span>Soil </span><span>total </span><span>C, N and P contents, and their ratios</span> <span>had</span><span> a </span><span>strong </span><span>direct effect on </span><span>the </span><span>genetic </span><span>resistance </span><span>of </span><span>microbial-groups</span><span>.</span><span> S</span><span>oil C:P ratio </span>was selected by random forest analyses as the main predictor of N cycling genetic resistance to <span>N deposition</span><span>. </span><span>Soil </span><span>total </span><span>C and N contents, and their ratios were </span>the main predictors of the <span>P cycling genetic resistance</span><span> to three global change drivers</span>. Overall, our work highlights the importance of soil stoichiometric balance for maintaining the ability of microbially-driven ecosystem functions to withstand global change.</span></p>
Data from: Soil carbon, nitrogen and phosphorus stoichiometry (C:N:P) in relation to conifer species productivity and nutrition across British Columbia perhumid rainforests
<p>Temperate rainforest soils of the Pacific Northwest are often carbon (C) rich and encompass a wide range in fertility reflecting varying nitrogen (N) and phosphorus (P) availability. Soil resource stoichiometry (C:N:P) may provide an effective measure of site nutrient status and help refine species-dependent patterns in forest productivity across edaphic gradients. We described the nature of soil organic matter for mineral soil and forest floor substrates across very wet (perhumid) rainforest sites of southwestern Vancouver Island (Canada), and employed soil element ratios as covariates in a long-term planting density trial to test their utility in defining basal area growth response of four conifer species. There were strong positive correlations in mineral soil C, N and organic P (P<sub>o</sub>) concentrations, and close alignment in C:N and C:P<sub>o</sub> both among and between substrates. Stand basal area after five decades was best reflected by soil C:N but included a significant species-soil interaction. The conifers with ectomycorrhizal fungi had diverging growth responses displaying either competitive (<i>Picea sitchensis</i>) or stress-tolerant (<i>Tsuga heterophylla</i>, <i>Pseudotsuga menziesii</i>) attributes, in contrast to a more generalist response by an arbuscular mycorrhizal tree (<i>Thuja plicata</i>). Despite the consistent patterns in organic matter quality we found no evidence via foliar nutrition for increased P availability with declining element ratios as we did for N. The often high C:P<sub>o</sub> ratios (as much as 3000) of these soils may reflect a stronger immobilization sink for P than N, which, along with ongoing sorption of PO<sub>4</sub><sup>-</sup>, could limit the utility of C:P<sub>o</sub> or N:P<sub>o</sub> to adequately reflect P supply. The dynamics and availability of soil P to trees, particularly as P<sub>o</sub>, deserves greater attention as many perhumid rainforests were co-limited by N and P, or, in some stands, possibly P alone. </p>
Supplementary Data: Trade-Offs in Land-Based Carbon Removal Measures under 1.5°C and 2°C Futures
<p>This compressed dataset includes the queried CVS files from 16 GCAM data bases generated for the study titled "<strong>Trade-Offs in Land-Based Carbon Removal Measures under 1.5°C and 2°C Futures</strong>".</p> <p>The data sets provided here came from the GCAM model output. Please find the model and code information at the GitHub repo: <a href="https://github.com/realxinzhao/paper-LandBasedCDR-GCAM">realxinzhao/paper-LandBasedCDR-GCAM</a>.</p> <p>In addition, the data were used for generating results used in the paper. See more information at <a href="https://github.com/realxinzhao/paper-LandBasedCDR-DisplayItems">realxinzhao/paper-LandBasedCDR-DisplayItems</a>.</p>
Soil acidification reduces soil fungal diversity, alters microbial carbon metabolism and enhances soil C persistence in an alkaline grassland
<p>This dataset was used to make tables and figures for the study entitled "Soil acidification reduces soil fungal diversity, alters microbial carbon metabolism and enhances soil C persistence in an alkaline grassland", which will be recently submitted to Global Change Biology in October 2023. It contains data of soil properties, plant and microbial communities under soil acidification in an alkaline grassland on the Loess Plateau. </p>
Soil carbon, nitrogen, and phosphorus cycling microbial populations and their resistance to global change depend on C:N:P stoichiometry
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Data from: Broad-scale patterns of soil carbon (C) pools and fluxes across semiarid ecosystems are linked to climate and soil texture
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Comprehensive result data for a pathway for the German energy sector compatible with a 1.5°C carbon budget
<p>This data set covers the results of an energy scenario for Germany within a 1.5°C carbon budget. It represents all relevant results from an energ system modelling excersise, coupling two complementary models.</p> <p>The data set consists of two excel files</p> <ul> <li>Comprehensive results of the energy balance based Energy System Model (ESM) for the heat, transport and power sectors for Germany, disaggregated by consumption sectors (residential, service & commerce, industry, transport)</li> <li>Comprehensive results of the linear optimization energy system model REMix for power, heat and sector coupling</li> </ul> <p>Methodology, models and scenario assumption are detailed in:</p> <p>Simon, S., Xiao, M., Harpprecht, C., Pregger, T., Gardian, H., & Sasanpour, S. (submitted). A pathway for the German energy sector compatible with a 1.5°C carbon budget. <em>Sustainability</em>.</p>
Fig. 2 Reefal facies. a-c in Microfacies Analysis And Depositional Environments Of The Tithonian-Valanginian Limestones From Dâmbovicioara Gorges (Cheile Dâmbovicioarei), Getic Carbonate Platform, Romania
Fig. 2 Reefal facies. a-c Coral-microbial boundstone; coral colonies are heavily encrusted by problematic microorganisms (a) or bordered by syndepositional, radiaxial-fibrous cements (b). d-h Bioclastic packstone (d, e, g-h) and bioclastic grainstone (f) internal sediment with dasycladalean algae [Steinmanniporella kapelensis (Sokač & Nikler)] (d), sponges (e), mollusks, corals, Crescentiella (f), microstalactitic (g) and microthrombolitic (h) microbial crusts.
Summertime productivity and carbon export potential in the Weddell Sea, with a focus on the waters adjacent to Larsen C Ice Shelf
<p>The data stored here are part of the manuscript entitled "Summertime productivity and carbon export potential in the Weddell Sea, with a focus on the waters adjacent to Larsen C Ice Shelf" published in European Geosciences Union: Biogeosciences. https://doi.org/10.5194/bg-2021-122</p> <p>The spreadsheet includes oceanographic data, namely CTD data, nutrient concentrations, phytoplankton nitrogen (N) and carbon (C) uptake rates, and phytoplankton by microscopy and flow cytometry. </p>
Supplementary material 6 from: Balestra V, Lana E, Carbone C, De Waele J, Manenti R, Galli L (2021) Don't forget the vertical dimension: assessment of distributional dynamics of cave-dwelling invertebrates in both ground and parietal microhabitats. Subterranean Biology 40: 43-63. https://doi.org/10.3897/subtbiol.40.71805
SIMPER Analysis
Supplementary material 4 from: Balestra V, Lana E, Carbone C, De Waele J, Manenti R, Galli L (2021) Don't forget the vertical dimension: assessment of distributional dynamics of cave-dwelling invertebrates in both ground and parietal microhabitats. Subterranean Biology 40: 43-63. https://doi.org/10.3897/subtbiol.40.71805
Richness and abundance of Baraccone Cave invertebrate fauna
Supplementary material 3 from: Balestra V, Lana E, Carbone C, De Waele J, Manenti R, Galli L (2021) Don't forget the vertical dimension: assessment of distributional dynamics of cave-dwelling invertebrates in both ground and parietal microhabitats. Subterranean Biology 40: 43-63. https://doi.org/10.3897/subtbiol.40.71805
Monthly temperature, relative humidity and light intensity in Baraccone Cave for each sampling area
Supplementary material 2 from: Balestra V, Lana E, Carbone C, De Waele J, Manenti R, Galli L (2021) Don't forget the vertical dimension: assessment of distributional dynamics of cave-dwelling invertebrates in both ground and parietal microhabitats. Subterranean Biology 40: 43-63. https://doi.org/10.3897/subtbiol.40.71805
Fauna observed in Baraccone Cave
Supplementary material 5 from: Balestra V, Lana E, Carbone C, De Waele J, Manenti R, Galli L (2021) Don't forget the vertical dimension: assessment of distributional dynamics of cave-dwelling invertebrates in both ground and parietal microhabitats. Subterranean Biology 40: 43-63. https://doi.org/10.3897/subtbiol.40.71805
Percentage of minerals found in each sampling area
Figure 5 from: Balestra V, Lana E, Carbone C, De Waele J, Manenti R, Galli L (2021) Don't forget the vertical dimension: assessment of distributional dynamics of cave-dwelling invertebrates in both ground and parietal microhabitats. Subterranean Biology 40: 43-63. https://doi.org/10.3897/subtbiol.40.71805
Figure 5 A trend of Equitability (Pielou's evenness), Dominance (1-Simpson index) and Shannon diversity (H) indices from March 2017 to March 2018 B rarefaction curve (in red). In blue the 95% confidence interval.
Supplementary material 1 from: Balestra V, Lana E, Carbone C, De Waele J, Manenti R, Galli L (2021) Don't forget the vertical dimension: assessment of distributional dynamics of cave-dwelling invertebrates in both ground and parietal microhabitats. Subterranean Biology 40: 43-63. https://doi.org/10.3897/subtbiol.40.71805
Information on the study area
Figure 3 from: Balestra V, Lana E, Carbone C, De Waele J, Manenti R, Galli L (2021) Don't forget the vertical dimension: assessment of distributional dynamics of cave-dwelling invertebrates in both ground and parietal microhabitats. Subterranean Biology 40: 43-63. https://doi.org/10.3897/subtbiol.40.71805
Figure 3 A one-Way ANOSIM test. Wall in eight sites (A-H, Group 1–8), Ground in seven sites (A-E and G-H, Group 9–15) B similarity between ground (from AG to HG) and wall (from AW to HW) faunal samples (UPGMA clustering based on Jaccard similarity index - bootstrap values are shown under each node) C SIMPER Analysis. Taxa responsible for the observed differences between faunal assemblages in different sampling areas in percentage.
Figure 2 from: Balestra V, Lana E, Carbone C, De Waele J, Manenti R, Galli L (2021) Don't forget the vertical dimension: assessment of distributional dynamics of cave-dwelling invertebrates in both ground and parietal microhabitats. Subterranean Biology 40: 43-63. https://doi.org/10.3897/subtbiol.40.71805
Figure 2 Canonical Correspondence Analysis. Hypogean fauna related to environmental factors and mineral substratum A classes of ground fauna B orders of ground fauna (Arachnida, Entognatha and Insecta) with a number of specimens exceeding 5% of each considered class total C classes of parietal fauna D orders of parietal fauna (Arachnida and Insecta) with a number of specimens exceeding 5% of each considered class total.
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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)
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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.