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32 results for “nutrient composition”
H2Ohio Wetland Monitoring Program Vegetation Community Composition, Biomass, and Nutrient Content across Ohio, USA (2021-2022)
This data package includes vegetation community composition, percent cover, biomass, and nutrient concentration data from wetland projects across Ohio, USA, monitored by the H2Ohio Wetland Monitoring Program. Monitoring began in July 2021 and is ongoing, with annual updates planned. While data collection varies by site, most wetlands are surveyed to characterize vegetation and estimate nutrient stocks through community composition assessments and biomass sampling. Sampling points are randomly generated within and up to 5 meters outside the approximated wetland boundary. Surveys are conducted at points where wetland species (FAC–OBL) are present using a 1×1 meter quadrat to record species composition and percent cover. At approximately half of these locations, a 0.25×0.25 meter quadrat is placed outside the northeast corner to collect vegetation samples for nutrient analysis. In these smaller quadrats, community composition and percent cover are recorded prior to sampling aboveground biomass and, at approximately one third of those sites, belowground biomass. Datasets collected by the H2Ohio Wetland Monitoring Program containing surface water and soil nutrient concentration from samples collected at Ohio wetlands during the 2021–2022 sampling period can be found in an accompanying data package (edi.2087) at https://doi.org/10.6073/pasta/297bd6d93b4fcc8416e4225834db380e.
Shrub influence on soil moisture, nutrients, temperature and species composition, 2019 - 2020.
Shrubification, the expansion and densification of shrubs, is occurring in arctic and alpine zones across the globe (Myers-Smith et al., 2011). This alteration is primarily driven by warming temperatures (Elmendorf et al., 2012b, 2012a), and can have major consequences for the existing vegetation (Anthelme et al., 2007; Pajunen et al., 2011; Venn et al., 2014) and for nutrient pools (Sturm et al., 2005; DeMarco et al., 2014) due to the abiotic and biotic effects of shrubs. Shrubs accumulate snow which insulates the ground during the winter and provides more moisture later in the season (Liston et al., 2002). During the summer, shrubs provide shade and wind protection. Additionally, shrubs can increase the soil nitrogen (N) pool through their high input of plant material into the soil (DeMarco et al., 2014). These small-scale climatic and soil alterations have important consequences for plant community dynamics in the arctic and alpine. References: Anthelme, F., Villaret, J.-C., and Brun, J.-J., 2007: Shrub encroachment in the Alps gives rise to the convergence of sub-alpine communities on a regional scale. Journal of Vegetation Science, 18(3):355–362. DeMarco, J., Mack, M. C., and Bret-Harte, M. S., 2014: Effects of arctic shrub expansion on biophysical vs . biogeochemical drivers of litter decomposition. Ecological Society of America, 95(7):1861–1875. Elmendorf, S. C., Henry, G. H. R., Hollister, R. D., Björk, R. G., Bjorkman, A. D., Callaghan, T. V., Collier, L. S., Cooper, E. J., Cornelissen, J. H. C., Day, T. A., Fosaa, A. M., Gould, W. A., Grétarsdóttir, J., Harte, J., Hermanutz, L., Hik, D. S., Hofgaard, A., Jarrad, F., Jónsdóttir, I. S., Keuper, F., Klanderud, K., Klein, J. A., Koh, S., Kudo, G., Lang, S. I., Loewen, V., May, J. L., Mercado, J., Michelsen, A., Molau, U., Myers-Smith, I. H., Oberbauer, S. F., Pieper, S., Post, E., Rixen, C., Robinson, C. H., Schmidt, N. M., Shaver, G. R., Stenström, A., Tolvanen, A., Totland, Ø., Troxler, T., Wahren, C. H
Linking temporal changes in species composition and biomass in a globally distributed grassland experiment: The Nutrient Network
Global change drivers, such as anthropogenic nutrient inputs, are increasing globally. Nutrient deposition simultaneously alters plant biodiversity, species composition, and ecosystem processes like aboveground biomass production. These changes are underpinned by species extinction, colonization, and shifting relative abundance. Here, we use the Price equation to quantify and link the contributions of species that are lost, gained, or that persist to change in aboveground biomass in 59 experimental grassland sites. Under ambient (control) conditions, compositional and biomass turnover was high, and losses (i.e., local extinctions) were balanced by gains (i.e. colonization). Under fertilization, the decline in species richness resulted from increased species loss and from decreases in species gained. Biomass increase under fertilization resulted mostly from species that persist, and to a lesser extent from species gained. Drivers of ecological change can interact relatively independently with diversity, composition, and ecosystem processes and functions such as aboveground biomass due to the individual contributions of species lost, gained, or persisting.
Data for: Top-down control and species composition non-linearly influence the short-term response of experimental food webs to a nutrient pulse perturbation
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Raw data of the microarthropods and decomposition from: Effects of microarthropod density on soil fungal community composition in nutrient-poor ecosystems
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Plant Species Composition percent cover:Nutrient Network: A cross-site investigation of bottom-up control over herbaceous plant community dynamics and ecosystem function.
This experiment is one implementation of a globally distributed experiment, known as the Nutrient Network. At Cedar Creek, as in over 70 other sites in grasslands around the world, the experiment aims to describe impacts of increased nutrients (nitrogen, phosphorus, potassium, sulfur and other metals) and decreased herbivory (removal of mammals by fencing). Two overarching questions are being explored with these manipulations: 1. To what extent are plant production and diversity co-limited by multiple nutrients in herbaceous-dominated communities? 2. Under what conditions do grazers or fertilization control plant biomass, diversity, and composition? By utilizing identical protocols at diverse grassland sites around the world, NutNet aims to uncover both the generalities in ecosystem functioning, and the contingencies or differences which can obscure those common mechanisms. In addition to the standard NutNet protocol, e247 includes an additional low Nitrogen gradient (1 gram Nitrogen per meter squared per year and 5 grams Nitrogen per meter squared per year in addition to the standard 10 grams Nitrogen per meter squared per year).
Food composition database for nutrient intake: selected vitamins and minerals in selected European countries
<p>Following a request from the European Commission for a review of European dietary reference values (DRVs), the EFSA’s Panel on Dietetic Products, Nutrition and Allergies (NDA) has prepared a number of Scientific Opinions on DRVs for micronutrients. The DATA Unit supported this activity by estimating the nutrient intake of a number of micronutrients in nine selected European countries and different age groups. In addition, the DATA Unit also provided information on average content of food sources of the respective nutrients per country based on the composition database, as well as main food group contributors to nutrient intakes and assessed the comparability of the provided data with pertinent published intake data.</p> <p>Intake estimates have been assessed using food consumption data from the EFSA Comprehensive Food Consumption Database (EFSA, 2011a) and the EFSA Nutrient composition database. Food composition data used to populate the Nutrient composition database were provided to EFSA through the EFSA procurement project ‘<em>Updated food composition database for nutrient intake’</em> (Roe at al., 2013). Data were provided following the EFSA specification for standard sample description for food and feed and were classified according to the FoodEx2 classification system of EFSA (EFSA, 2011b).</p> <p>The food composition data used in these assessments and here published cover the following vitamins and minerals: calcium (Ca); copper (Cu); cobalamin (vitamin B12); magnesium (Mg); niacin; phosphorus (P); potassium (K); riboflavin; thiamin; iron (Fe); selenium (Se); vitamin B6; vitamin K, zinc (Zn), and vitamin E<sup>1</sup>. The food composition dataset contains data from seven<sup>2</sup> countries: Finland, France, Germany, Italy, Netherlands, Sweden, and United Kingdom. This dataset version has been checked for outliers but is prior to data completion for missing foods and nutrient values.</p> <p><sup>1</sup> Vitamin E is defined as alpha-tocopherol (AT) only, however as most food composition databases in the EU contain values as alpha-tocopherol equivalents (TE), data on TE are also provided</p> <p><sup>2</sup> For the nutrient intake estimates of Ireland and Latvia present in the opinions of the EFSA Panel on Dietetic Products, Nutrition and Allergies (NDA), food composition data from UK and Germany were respectively used</p>
Data from: Nutrient composition and functional constituents of daylily from different producing areas based on widely targeted metabolomics
<p>Daylily is a functional food with high nutritional value in China. Datong (DT) in Shanxi Province is one of the four main production areas of daylily. Therefore, Linfen (LF), Lvliang (LL), and Yangquan (YQ) in Shanxi Province have also introduced daylily from DT. However, geographical and climatic conditions and producing patterns cause variations in the vegetable quality. In the present study, we determined the quality of daylilies from different producing areas and found that the nutrient composition of daylilies from different producing areas varied. The widely targeted metabolomics was performed, and the results showed that 1642 metabolites were found in daylily. The differential metabolites between DT and YQ, LL and LF were 557, 667, and 359, respectively. Notably, 9 metabolic pathways and 76 metabolite markers could be associated with daylily from different areas. This study provides a theoretical basis for the quality maintenance and health efficacy research of daylily.</p>
Data from: Phytoplankton functional composition determines limitation by nutrients and grazers across a lake productivity gradient
<p>Functional tradeoffs among ecologically important traits govern the diversity of communities and changes in species composition along environmental gradients. A tradeoff between predator defense and resource competitive ability has been invoked as a mechanism that may maintain diversity in lake phytoplankton. Tradeoffs may promote diversity in communities where grazing- and resource-limited taxa coexist, which determines the extent to which communities are resource- or consumer-controlled. In addition, changes in temperature may alter nutrient demands and grazing pressure, changing the balance between the two regulating factors. Our study aims to understand whether a tradeoff between grazer vulnerability and nutrient limitation promotes coexistence of phytoplankton functional groups in communities that differ in trophic status, and how this tradeoff may shift with warming. We conducted multifactorial experiments manipulating grazing, nutrients, and temperature in phytoplankton communities from three Dutch lakes varying in trophic status, and used a trait-based approach to classify functional groups based on grazing susceptibility. <span>We found no associations between susceptibility to grazing and response to nutrient additions in any of the communities or temperature regimes, indicating that</span> a competition-defense tradeoff is unlikely to <span>explain diversity within the tested communities. Instead, w</span>e observed a tendency towards both a higher grazing-resistance and weaker nutrient limitation <span>along with a shift in the functional composition of phytoplankton in communities across a gradient from low to high productivity.</span></p>
Data for: Ingredient and nutrient composition of brown bear diets
<p><span>The dietary nutrient profile has metabolic significance and possibly contributes to species' foraging behavior. The brown bear (<em>Ursus arctos</em>) was used as a model species for which dietary ingredient and nutrient concentrations as well as nutrient ratios were determined annually, seasonally and per reproductive class. Brown bears had a vertebrate- and ant-dominated diet in spring and early summer and a berry-dominated diet in fall, which translated into protein-rich and carbohydrate-rich diets, respectively. Fiber concentrations appeared constant over time and averaged at 25 % of dry matter intake. Dietary ingredient proportions differed between reproductive classes; however, these differences did not translate into a difference in dietary nutrient concentrations, suggesting that bears manage to maintain similar nutrient profiles with selection of different ingredients. In terms of nutrient ratios, the dietary protein to non-protein ratio, considered optimal at around 0.2 (on metabolizable energy basis), averaged around 0.2 in this study in fall and around 0.8 in spring and summer. We introduced the minimal non-fat to fat ratio necessary for efficient maintenance metabolism. This ratio varied across seasons but never fell beneath the theoretically estimated minimum to ensure metabolic efficiency. This population thus managed to ingest diets that never exerted a lack of glucogenic substrate, suggesting that metabolic efficiency may either be a driver of active diet selection or that natural resources available to bears did not constitute a constraint in this respect. Given the considerable proportion of fiber in the diet of brown bears, the relevance of this nutrient and its role in foraging behavior might be underestimated.</span></p>
Community assembly amplicon sequences, with pipeline to get asv table for "Spatial structure drives compositional convergence between nutrient environments in experimental microbial communities"
<p>Community assembly amplicon sequences, with pipeline to get asv table for "Spatial structure drives compositional convergence between nutrient environments in experimental microbial communities"</p> <p> </p> <p>compressed FASTA files for 16s amplicon sequences relating to two separate projects, "Spatial structure drives compositional convergence between nutrient environments in experimental microbial communities" and "Habitat filtering leads to phylogenetic clustering in synthetic microbial communities". DADA22 pipeline is included, which pools all samples for better accuracy. A Julia script bioinfo.jl is then used to select only the samples relevant to spatial structure project.</p> <p> </p> <p>All csv filenames are appended with "_q" indicating an increase in the stringency of quality filtering parameters (also increasing minimum hamming distance used in DADA2 algorithm to 5) to produce a taxa table with a sensible number of ASVs (given a known number of input strains) with each ASV uniquely aligning to an individual sequence from colony PCR of said input strains.</p> <p> </p>
Data from: Nutrient landscape of a cricket nymph: How dietary protein and carbohydrate shape intake, performance, and body composition in the two-spotted cricket, <em>Gryllus bimaculatus</em>
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Data from: Phytoplankton functional composition determines limitation by nutrients and grazers across a lake productivity gradient
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Data for: Ingredient and nutrient composition of brown bear diets
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Data from: Nutrient composition and functional constituents of daylily from different producing areas based on widely targeted metabolomics
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Data from: Long-term nutrient addition and grazing exclusion determine flower abundance, diversity and community composition in high-latitude grasslands
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Data from: Soil nutrients and dispersal limitation shape compositional variation in secondary tropical forests across multiple scales
1. Soil resource partitioning and dispersal limitation have been shown to shape the tree community structure of mature tropical forests, but are poorly studied in the context of forest succession. We examined the relative contributions of both ecological processes to the variation in the species composition of young tropical secondary forests at different spatial scales, and if the relative importance of these two ecological processes changed during succession. At the species level, we examined if the association between species abundances and soil fertility differed between early and late successional species and/or changed over the course of succession. 2. We used vegetation and soil data from 47 secondary forest sites with two plots each in a tropical agricultural landscape. A distance-based redundancy analysis and variation partition were employed to examine the relative importance of spatial distance (proxy for dispersal limitation) and heterogeneity in soil nutrients (proxy for soil nutrient partitioning) at the landscape scale, and a linear regression to test their effects at the local scale. We examined interspecific variation in species' responses to successional age and soil nutrients with a joint species distribution model. 3. Dispersal limitation and soil niche partitioning drove considerable variation in the composition of plant communities at local and landscape scales. The relative contribution of these two ecological processes changed with scale (local versus landscape), topography (lower slope versus upper slope plots). At the species level, significant abundance-soil fertility associations were mostly positive. Most species became less responsive to soil nutrients over the first few decades of tropical forest succession, probably because light became the main limiting resource in older forests. 4. Synthesis. Our key finding is that spatial heterogeneity in soil resources and spatial distance jointly drive compositional variation within and across early successional forests. Our results highlight that a network of forest fragments enhances the resilience of ecological processes and the potential of secondary forests to restore and preserve biodiversity in human-modified landscapes. To advance our understanding of ecological succession, we need to move beyond single-factor and local-scale studies and examine the effects of multiple variables on succession at multiple spatial scales.
Data from: CO2 alters community composition and response to nutrient enrichment of freshwater phytoplankton
Nutrients can limit the productivity of ecosystems and control the composition of the communities of organisms that inhabit them. Humans are causing atmospheric CO2 concentrations to reach levels higher than those of the past millions of years while at the same time propagating eutrophication through the addition of nutrients to lakes and rivers. We studied the effect of elevated CO2 concentrations, nutrient addition and their interaction in a series of freshwater mesocosm experiments using a factorial design. Our results highlight the important role of CO2 in shaping phytoplankton communities and their response to nutrient addition. We found that CO2 greatly magnified the increase in phytoplankton growth caused by the increased availability of nutrients. Elevated CO2 also caused changes in phytoplankton community composition. As predicted from physiology and laboratory experiments, the taxonomic group that was most limited by current day CO2 concentrations, chlorophytes, increased in relative frequency at elevated CO2. This predictable change in community composition with changes in CO2 is not altered by changes in the availability of other nutrients.
Composition of Functional Tooth Units and Nutrient Intake in Older Men
ClinicalTrials.gov study NCT03295435. IPD Sharing: YES. Countries: 1. Publications: 5.
Effect of Domperidone on the Nutrient Composition of Preterm Mother's Breast Milk
ClinicalTrials.gov study NCT00308334. IPD Sharing: Not stated. Countries: 1. Publications: 2.
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Allen Brain Atlas
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DANDI Archive for NWB datasets
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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.