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3,206 results for “property (T)”
Research data for Investigation of coatings and metallic materials for icephobic properties, dataset
<p>This dataset is used in deliverable 3.5, 'Investigation of coatings and metallic materials for icephobic properties', where you can get more information.</p> <p>The Dataset includes:</p> <table> <tbody> <tr> <td>Coating Data</td> </tr> <tr> <td>Metalic materials data</td> </tr> <tr> <td>Coating Freezing spike</td> </tr> <tr> <td>Coating Atmospheric freezing</td> </tr> <tr> <td>Coating contact angle</td> </tr> <tr> <td>Coating Ice adhesion</td> </tr> <tr> <td>Submerged freeze depression</td> </tr> <tr> <td>Metalic materials droplet freezing</td> </tr> <tr> <td>Metalic materials Droplet contact angle</td> </tr> <tr> <td>Coating freeze depression brine test</td> </tr> <tr> <td>Coating freeze depression CFT</td> </tr> <tr> <td>Metalic amorphous materials freeze depression</td> </tr> <tr> <td>Metalic pure materials freeze depression</td> </tr> </tbody> </table>
Solar Wind properties measured with instruments on the Advanced Composition Explorer (ACE)
<p>Combined ACE/SWEPAM, ACE/Mag, and ACE/SWICS data set<br> ACE/MAG and ACE/SWEPAM data are taken from the ACE Science center (https://izw1.caltech.edu/ACE/ASC/) and binned to the 12-minute time resolution of SWICS.<br> The SWICS data is based on the PHA data and analyzed as described in Berger (2008).<br> This data set is used in the following two publications:<br> Teichmann, S. Heidrich-Meisner, V, Berger, L, Wimmer-Schweingruber, R.F. (2023, submitted), "Influence of solar wind parameters on unsupervised solar wind classification with k-means" source code available: 10.5281/zenodo.7695074<br> Hecht, M, Heidrich-Meisner, V, Berger, L, Wimmer-Schweingruber, R.F. 2023 (in preparation) "Scope and limitations of ad-hoc neural network reconstructions of solar wind parameters", source code available: 10.5281/zenodo.7681047.</p> <p>Contact: Verena Heidrich-Meisner, CAU Kiel heidrich@physik.uni-kiel.de</p> <p>We thank the science teams of ACE/SWEPAM, ACE/MAG as well as<br> ACE/SWICS for developing, maintaining and calibrating the instruments and for providing the respective level 2 and level 1 data products.<br> This work was supported by the Deutsches Zentrum für Luft- und Raumfahrt (DLR) as SOHO/CELIAS 50 OC 2104.</p> <p>Data products description:<br> year: year of observation (int)<br> time: day of year in current year as float<br> yeartime: time in years as float (UTC)<br> vsw: solar wind proton speed in km/s, measured by ACE/SWEPAM (level 2 from ACE Science Center) and rebinned to 12 minute time resolution<br> dsw: solar wind proton density in cm^{-3}, measured by ACE/SWEPAM (level 2 from ACE Science Center)and rebinned to 12 minute time resolution<br> tsw: solar wind proton temperature in K, measured by ACE/SWEPAM (level 2 from ACE Science Center) and rebinned to 12 minute time resolution<br> B: magnetic feld strength in nT, measured by ACE/MAG (level 2 from ACE Science Center)<br> colage: proton-proton collisional age computed as 6.4* 1e8 * dsw /(vsw* tsw**(3/2)) in K^{3/2} s^2 cm^3 km^{-1}<br> dO7_6: ratio of the O7+ to O6+ charge state densities, measured by ACE/SWICS, derived directly from PHA (pulse height analysis) data<br> eO7_6: estimate of the relative error of dO7_6 based on the counting statistics<br> ldO7_6: decadic logarithm of dO7_6<br> elO7_6: estimate of the relative error of the decadic logarithm dO7_6 based on the counting statistics<br> mcsFe: mean charge state of Fe, based on SWICS PHA of Fe8+, Fe9+, Fe10+, Fe11+, and Fe12+ in units of the elementary charge e. At least 10 counts distributed over Fe8+, Fe9+, Fe10+, Fe11+ and Fe12+ are required<br> emcsFe: estimate of the relative error of dO7_the mean Fe charge state in e (assumes 10% relative error for each Fe charge state)<br> cor_hole: coronal hole wind category in the categorization of Xu&Borovsky (2015) The ejecta category is disregarded, see for example Heidrich-Meisner (2020). Entries are 0 or 1, 1 of the data point is assigned to this type.<br> sec_rev: sector reversal plasma wind category in the categorization of Xu&Borovsky (2015) The ejecta category is disregarded, see for example Heidrich-Meisner (2020). Entries are 0 or 1, 1 of the data point is assigned to this type.<br> stream_belt: streamer belt wind category in the categorization of Xu&Borovsky (2015) The ejecta category is disregarded, see for example Heidrich-Meisner (2020). Entries are 0 or 1, 1 of the data point is assigned to this type.<br> ICME: interplanatery coronal mass ejections time periods (with a six hour safety margin before and after each ICME) from the Jian (2006,2011) and Richardson & Cane (2014, 2018) ICME lists. Entries are 0 or 1, 1 of the data point is assigned to this type.<br> totalCountsFe: number of counts in ACE/SWICS distributed over Fe8+-Fe12+<br> The data set is restricted to data points where valid data points are available for all listed data products. Only for the mean charge state of Fe invalid data points are indicated with nan (not a number)</p> <p>References:<br> Berger, L. 2008, PhD thesis, Kiel, Christian-Albrechts-Universität, Diss., 2008<br> Gloeckler, G., Cain, J., Ipavich, F., et al. 1998, in The Advanced Composition Explorer Mission (Springer), 497–539<br> McComas, D., Bame, S., Barker, P., et al. 1998b, in The Advanced Composition Explorer Mission (Springer), 563–612<br> Smith, C. W., L’Heureux, J., Ness, N. F., et al. 1998, in The Advanced Composition Explorer Mission (Springer), 613–632</p> <p>Xu, F. & Borovsky, J. E. 2015, Journal of Geophysical Research: Space Physics, 120, 70<br> Heidrich-Meisner, V., Berger, L., & Wimmer-Schweingruber, R. F. 2020, Astronomy & Astrophysics, 636, A103<br> Jian, L., Russell, C., & Luhmann, J. 2011, Solar Physics, 274, 321<br> Jian, L., Russell, C., Luhmann, J., & Skoug, R. 2006, Solar Physics, 239, 393<br> Richardson, I. G. 2004, Space Science Reviews, 111, 267<br> Richardson, I. G. 2018, Living reviews in solar physics, 15, 1</p> <p>Teichmann, S. Heidrich-Meisner, V, Berger, L, Wimmer-Schweingruber, R.F. (2023), "Influence of solar wind parameters on unsupervised solar wind classification with k-means" source code available: 10.5281/zenodo.7695074<br> Hecht, M, Heidrich-Meisner, V, Berger, L, Wimmer-Schweingruber, R.F. 2023 (in preparation) "Scope and limitations of ad-hoc neural network reconstructions of solar wind parameters", source code available: 10.5281/zenodo.7681047.</p> <p>year/1 time/day of year yeartime/UTC vsw/km/s dsw/cm^{-3} tsw/K B/nT colage/(K^{3/2} s^2 cm^3 km^{-1}) dO7_6/1 eO7_6/1 ldO7_6/1 elO7_6/1 mcsFe/e emcsFe/e cor_hole/bool sec_rev/bool stream_belt/bool ICME/bool totalCountsFe/1</p>
Fatigue properties of wind turbine rotor blade hybrid epoxy adhesives
<p>This dataset includes the tensile data at two different strain rates and tensile-tensile fatigue data of epoxy adhesives used in wind turbine rotor blades. SPABOND™ 820HTA (non-toughened) and SPABOND™ 840HTA (toughened) epoxy adhesives are combined at different weight proportions to develop the hybrid adhesives. The hybrid and ASTM D638-22 tensile specimen geometry (Type I and Type II) effects on fatigue performance are determined through instrumented experiments. </p>
Molecular and functional properties of human Plasmodium falciparum CSP C-terminus antibodies
<p>AIRR Community-compliant information comprising all antibodies described in EMBO Mol Med 15:e17454 [DOI:10.15252/emmm.202317454].</p>
MASCDB, a database of images, descriptors and microphysical properties of individual snowflakes in free fall
<p><strong>Dataset overview</strong></p> <p>This dataset provides data and images of snowflakes in free fall collected with a <a href="https://amt.copernicus.org/articles/5/2625/2012/">Multi-Angle Snowflake Camera (MASC)</a> The dataset includes, for each recorded snowflakes:</p> <ol> <li>A triplet of gray-scale images corresponding to the three cameras of the MASC</li> <li>A large quantity of geometrical, textural descriptors and the pre-compiled output of published retrieval algorithms as well as basic environmental information at the location and time of each measurement.</li> </ol> <p>The pre-computed descriptors and retrievals are available either individually for each camera view or, some of them, available as descriptors of the triplet as a whole. A non exhaustive list of precomputed quantities includes for example:</p> <ul> <li>Textural and geometrical descriptors as in <a href="https://amt.copernicus.org/articles/10/1335/2017/"><em>Praz et al 2017</em></a></li> <li>Hydrometeor classification, riming degree estimation, melting identification, as in <a href="https://amt.copernicus.org/articles/10/1335/2017/"><em>Praz et al 2017</em></a></li> <li>Blowing snow identification, as in <a href="https://tc.copernicus.org/articles/14/367/2020/"><em>Schaer et al 2020 </em></a></li> <li>Mass, volume, gyration estimation<em>, as in <a href="https://amt.copernicus.org/preprints/amt-2021-176/">Leinonen et al 2021</a></em></li> </ul> <p><strong>Data format and structure</strong></p> <p>The dataset is divided into four <em>.parquet</em> file (for scalar descriptors) and a <em>Zarr</em> database (for the images). A detailed description of the data content and of the data records is available <a href="https://pymascdb.readthedocs.io/en/latest/data.html#data">here</a>.</p> <p><strong>Supporting code</strong></p> <p>A python-based API is available to manipulate, display and organize the data of our dataset. It can be found on <a href="https://github.com/ltelab/pymascdb">GitHub</a>. See also the code documentation on <a href="https://pymascdb.readthedocs.io/en/latest/index.html">ReadTheDocs</a>.</p> <p><strong>Download notes</strong></p> <ul> <li>All files available here for download should be stored in the same folder, if the python-based API is used</li> <li><em>MASCdb.zarr.zip</em> must be unzipped after download</li> </ul> <p><strong>Field campaigns</strong></p> <p>A list of campaigns included in the dataset, with a minimal description is given in the following table</p> <table> <tbody> <tr> <td><strong>Campaign_name</strong></td> <td><strong>Information</strong></td> <td> <p><strong>Shielded / Not shielded</strong></p> <p><em>DFIR = Double Fence Intercomparison Reference</em></p> </td> </tr> <tr> <td> <p><em>APRES3-2016 & APRES3-2017</em></p> </td> <td>Installed in Antarctica in the context of the APRES3 project. See for example <a href="https://essd.copernicus.org/articles/10/1605/2018/essd-10-1605-2018.html">Genthon et al, 2018</a> or <a href="https://tc.copernicus.org/articles/11/1797/2017/">Grazioli et al 2017</a></td> <td>Not shielded</td> </tr> <tr> <td><em>Davos-2015</em></td> <td>Installed in the Swiss Alps within the context of <a href="https://public.wmo.int/en/resources/meteoworld/spice-%E2%80%93-improving-snowfall-measurements">SPICE</a> (Solid Precipitation InterComparison Experiment)</td> <td>Shielded (DFIR)</td> </tr> <tr> <td><em>Davos-2019</em></td> <td>Installed in the Swiss Alps within the context of <a href="https://www.envidat.ch/group/about/raclets-field-campaign">RACLETS</a> (<em>Role of Aerosols and CLouds Enhanced by Topography on Snow</em>)</td> <td>Not shielded</td> </tr> <tr> <td><em>ICEGENESIS-2021</em></td> <td>Installed in the Swiss Jura in a MeteoSwiss ground measurement site, within the context of ICE-GENESIS. See for example <a href="https://doi.org/10.1175/BAMS-D-21-0184.1">Billault-Roux et al, 2023</a></td> <td>Not shielded</td> </tr> <tr> <td><em>ICEPOP-2018</em></td> <td>Installed in Korea, in the context of ICEPOP. See for example <a href="https://doi.org/10.5194/essd-13-417-2021">Gehring et al 2021</a>.</td> <td>Shielded (DFIR)</td> </tr> <tr> <td><em>Jura-2019 & Jura-2023</em></td> <td>Installed in the Swiss Jura within a MeteoSwiss measurement site</td> <td>Not shielded</td> </tr> <tr> <td><em>Norway-2016</em></td> <td>Installed in Norway during the High-Latitude Measurement of Snowfall (HiLaMS). See for example <a href="https://doi.org/10.1175/BAMS-D-21-0007.1">Cooper et al, 2022</a>.</td> <td>Not shielded</td> </tr> <tr> <td><em>PLATO-2019</em></td> <td>Installed in the "Davis" Antarctic base during the <a href="https://www.osti.gov/biblio/1524773">PLATO</a> field campaign</td> <td>Not shielded</td> </tr> <tr> <td><em>POPE-2020</em></td> <td>Installed in the "Princess Elizabeth Antarctica" base during the POPE campaign. See for example <a href="https://essd.copernicus.org/articles/15/1115/2023/essd-15-1115-2023.html">Ferrone et al, 2023</a>.</td> <td>Not shielded</td> </tr> <tr> <td><em>Remoray-2022</em></td> <td>Installed in the French Jura.</td> <td>Not shielded</td> </tr> <tr> <td><em>Valais-2016</em></td> <td>Installed in the Swiss Alps in a ski resort.</td> <td>Not shielded</td> </tr> <tr> <td>ISLAS-2022</td> <td>Installed in Norway during the <a href="https://www.uib.no/en/rg/meten/150202/islas2022-field-campaign">ISLAS campaign</a></td> <td>Not shielded</td> </tr> <tr> <td>Norway-2023</td> <td>Installed in Norway during the MC2-ICEPACKS campaign</td> <td>Not shielded</td> </tr> </tbody> </table> <p> </p> <p><strong>Version</strong></p> <p>1.1 - Two new campaigns ("ISLAS-2022", "Norway-2023") added.</p> <p>1.0 - Two new campaigns ("Jura-2023", "Norway-2016") added. Added references and list of campaigns.</p> <p>0.3 - a new campaign is added to the dataset ("Remoray-2022")</p> <p>0.2 - rename of variables. Variable precision (digits) standardized</p> <p>0.1 - first upload</p>
Dataset of reported synthetic conditions for ZIF-8 since 2006 and final characteristics and properties of the particles obtained
<p>This is a dataset generated by mining available literature between 2006 and August 2021. Initial literature search was done using Scopus database, employing a combination of keywords such: "ZIF-8", "Zeolitic+ZIF-8", "Framework+ZIF-8", "Zeolitic+MOF".</p> <p>First, removal of duplicates and review articles was done and the remaining documents were chosen by title+abstract analysis. The dataset contains a total of 254 entries, i.e., 254 individual reported synthesis.</p> <p>Throughout this dataset, the following parameters can be found:</p> <p>-About synthesis conditions: Zinc source and the amount employed for the synthesis in mmol (milli-moles); 2-methylimidazole in mmol (HmIm); solvent and quantity employed (in mmol). Modulator and quantity employed (in mmol). Please note that quantities in milli-moles were calculated by hand in most of the cases, since reported data was expressed in different units. Reaction temperature (in °C), reaction time (min) and stirring condition (YES-NO-Initial-time). Finally, reports were classified as "systematic" (or not) based on wether the scope of the work was to explore different synthetic conditions.</p> <p>-About ZIF-8 characteristics: information is mainly focusing on structure-related characteristic, namely the particle morphology (classified as Faceted, poor-faceted, quasispherical, aggregated) and the particle´s size. Reported sizes where classified by the different techniques employed. Finally, Surface area determined by BET formalism was also included.</p>
Dataset exploring the use of quasi-harmonic approximation to understand the thermal properties of Bi2Se3
<p>This data set contains input and output files for DFT calculations on Bi<sub>2</sub>Se<sub>3</sub> for a number of different fixed unit cells with calculations performed using VASP and Phonopy. At each fixed volume, optimisations and phonon calculations have been performed. These have been used to understand the thermal properties of the material using the quasi-harmonic approximation. </p>
Source Data for "Transport properties and doping evolution of the Fermi surface in cuprates"
<p>Source data for the publication "Transport properties and doping evolution of the Fermi surface in cuprates", in Scientific Reports (https://doi.org/10.1038/s41598-023-39813-z) and on arxiv (https://doi.org/10.48550/arXiv.2303.05254).</p> <p>This dataset is organized in the following way:</p> <p>For every figure of the manuscript there is a separate folder, which includes the figure itself, as well as one or more additional folders for the individual panels. In those, there are one or more .csv files with the data. Some of the .csv files have two header lines, for example when the temperature and <span class="math-tex">\(n_{\mathrm{H}}\)</span> are recorded for multiple doping levels.</p> <p>Additional comments:</p> <ul> <li>Figure 1 <ul> <li>The generic phase boundaries are not included.</li> <li>The precision of values of <span class="math-tex">\(n_{\mathrm{loc}}\)</span>is increased for presentation purposes</li> </ul> </li> <li>experimental doping values are typically rounded to 2 decimal points, doping errors to 3 decimal points</li> <li>estimated <span class="math-tex">\(n_{\mathrm{eff}}\)</span> are rounded to 5 decimal points</li> <li>experimental <span class="math-tex">\(n_{\mathrm{H}}\)</span> from the literature are rounded to 3 decimal points</li> <li>otherwise, if it exists, experimental values are typically rounded to the error</li> <li>temperature is always given in Kelvin</li> <li><span class="math-tex">\(C_2\)</span>is given in <span class="math-tex">\([\mathrm{TK}^{-2}]\)</span> (i.e. Tesla Kelvin^-2)</li> <li>the unit for <span class="math-tex">\(n_{\mathrm{eff}}\)</span>, <span class="math-tex">\(n_{\mathrm{loc}}\)</span>, <span class="math-tex">\(n_{\mathrm{H}}\)</span> is [per CuO2 unit cell]</li> <li>the unit for the resistivity in figure 4 is described in the methods section of the article</li> </ul>
Effect of Restoration on Physical and Chemical Peat Properties in Previously Drained Boreal Peatlands, latitude 57-63, Sweden, 2021
The major objective behind peatland restoration is to improve ecosystem services, such as increased biodiversity, increased carbon sequestration, increased groundwater storage, and improved surface water quality. However, a century or more of drained conditions has drastically changed the soil properties in relation to natural wetlands and this is likely to profoundly influence the potential for various biogeochemical peat processes. Thus, peatland restoration may result in undesired impacts and potential environmental threats. Two such undesired effects are increased methane production and increased mercury methylation. In this study, we investigated how nine boreal peatlands across a latitudinal gradient in Sweden have been affected by rewetting after up to a century of drained conditions. Each peatland was sampled for three 50 cm deep peat cores that were analyzed for carbon, nitrogen, δ13C, δ15N, bulk density, and organic matter proportion. Adjacent to each restored peatland, we sampled a corresponding pristine (natural) peatland to facilitate a comparison of how the peat properties have been affected by drainage and subsequent rewetting of the peatlands. Groundwater depth was monitored at all peatland locations to confirm restored conditions at the rewetted peatlands. The results indicate that a long period of drained conditions and subsequent rewetting have changed the peat properties, with differences shown in C/N ratio, dry bulk density, and organic matter content. Rewetting will thus not regenerate a pristine environment. Instead, it creates new conditions to which various biogeochemical processes will respond and these do not necessarily represent conditions prior to disturbance. Our study will provide background information to understand the biogeochemical dynamics in peatlands after restoration, especially since the study covers a large span of nutrient conditions and catchment settings. This understanding will be fundamental for the development of strat
Limnological data from nearly 400 lakes across the Americas and New Zealand with a focus on vertical profiles of temperature, UV radiation, and optical properties
Two and a half decades of limnological data have been collected from nearly 400 lakes, encompassing a wide range of systems and a broad range of geography. This data set comprises one of the largest and most complete sets of measurements of underwater ultraviolet (UV) transparency available in the world. The data include a suite of 36 variables, with a focus on the optical characteristics. Lakes range from pristine natural lakes to manmade reservoirs. The systems represented in this data set are largely located in North America, from the northeastern United States to Alaska, and alpine and subalpine lakes in the Rocky Mountains of the United States and Canada. Lakes included range from iconic Lake Tahoe, and Castle Lake in northern California, to lakes in the South American Patagonian region, as well as New Zealand. Data were most often collected during the summer, and in some lakes span multiple years (with year-round data since 2006 in Lake Tahoe). The data here are contained in four files, including LakeData.csv, SiteInformation.csv, Methods.csv, and Variables.csv. The main data are in LakeData.csv. SiteInformation.csv, Methods.csv, and Variables.csv support the main data file with descriptions of the sampling sites, methods by which samples were processed, and descriptions of the variables that were measured, respectively. This data set complements the site-intensive limnological data that we published in EDI on 30+ years of data from 3 lakes in the Poconos Mountains region of Pennsylvania, USA. This complementary data set can be accessed at https://portal.edirepository.org/nis/mapbrowse?scope=edi&identifier=186
Soil moisture and soil properties in Watershed 1 of the HJ Andrews Experimental Forest, 2016–2020
Soil water content was measured at 0–30 cm and 0–60 cm depth at 54 sites within a 10-ha north-facing forested slope of Watershed 1 on 14 dates from August 2016–October 2017. Soil properties were measured at 13 soil moisture sites during the summer of 2017. Soil properties include bulk density, percent sand, percent clay, percent silt, gravimetric rock content, volumetric water content at field capacity, volumetric water content at turgor loss point, and saturated hydraulic conductivity at 15 and 45 cm depth. Total soil depth and resistance to penetration were also measured at 38 sites using a dynamic cone penetrometer. Volumetric water content (VWC) and soil water potential were recorded every 30 min at 9 locations in Watershed 1. VWC sensors were installed at 5, 50, and 100 cm and soil water potential were installed at 50 cm at each location.
Soil hydraulic and thermal properties determined in surface organic and mineral soils in the region near Toolik Lake on the North Slope of Alaska, 2016-2019
Soil cores of 5 cm diameter down to frozen soil were taken from a subset of sample sites for laboratory analysis. Determinations of hydraulic conductivity, thermal conductivity, porosity, and bulk density were made for each core. For a further subset of sites we developed soil moisture retention curves.
Baltimore Ecosystem Study: Physical, chemical and biological properties of forest and home lawn soils
Abstract: One-meter soil cores were taken to evaluate soil texture, bulk density, carbon and nitrogen pools, microbial biomass carbon and nitrogen content, microbial respiration, potential net nitrogen mineralization, potential net nitrification and inorganic nitrogen pools in 32 residential home lawns that differed by previous land use and age, but had similar soil types. These were compared to soils from 8 forested reference sites. Purpose: Soil cores were obtained from residential and forest sites in the Baltimore, MD USA metropolitan area. The residential sites were mostly within the Gwynns Falls Watershed (-76.012008W, -77.314183E, 39.724847N, 38.708367S and approximately 17 km2) Lawns on residential sites were dominated by a variety of cool season turfgrasses. Forest soil cores were taken from permanent forest plots of the Baltimore Ecosystem Study (BES) LTER (Groffman et al. 2006). These remnant forests are over 100 years old with soils that were comparable in type and texture to those underlying the residential study sites. Soils from all sites were from the Manor series (coarse-loamy, micaceous, mesic Typic Dystrudepts), which are well-drained upland soils with loamy textures and bedrock at 5 to 10 feet below the soil surface. To aid the site selection process we used neighborhoods in the Baltimore City metropolitan area that have been mapped using HERCULES, a high resolution land cover classification system designed to assist in the study of human-ecological systems (Cadenasso et al. 2007). Using HERCULES and additional data sources, we identified residential sites that were similar except for single factors that we hypothesized to be important predictors of ecosystem dynamics. These factors included land use history (agriculture and forest, n = 10 and n = 22), housing density (low and medium/high, n = 9 and n = 23), and housing age (4 to 58 yrs old, n = 32). Housing age was acquired from the Maryland Property View database. Prior land use was determined b
Eight Mile Lake Research Watershed, Carbon in Permafrost Experimental Heating Research (CiPEHR): physical and chemical properties of soils, 2009-2017
The Carbon in Permafrost Experimental Heating Research (CiPEHR) project addresses the following questions: 1) Does ecosystem warming cause a net release of C from the ecosystem to the atmosphere?, 2) Does the decomposition of old C, that comprises the bulk of the soil C pool, influence ecosystem C loss?, and 3) How do winter and summer warming alone, and in combination, affect ecosystem C exchange? We are answering these questions using a combination of field and laboratory experiments to measure ecosystem carbon balance and radiocarbon isotope ratios at a warming experiment located in an upland tundra field site near Healy, Alaska in the foothills of the Alaska Range. This data set includes measurements of moisture, bulk density, ash, carbon, and nitrogen concentrations, and carbon and nitrogen stable isotope composition (δ13C and δ15N) at depth increments in soil cores collected in 2009, 2010, 2011, 2013 and 2017 from warming and control treatment plots.
Field survey and long-term measurements of biological, geomorphic, and hydrologic properties across ecosystem states in a non-tidal, salinizing peat marsh in Everglades National Park, Florida, USA, June 2018 - ongoing
This dataset package details a field survey and long-term measurements of biological, geomorphic, and hydrologic properties across ecosystem states found within a salinizing, non-tidal peat marsh in the coastal Everglades. There are four datasets included: FCE1250_Lamb_AltStableState_HydroGeo includes point measurements of soil surface elevation, bedrock elevation, soil depth, water depth, and porewater salinity across ecosystem states: emergent marsh (sawgrass dominated), submerged marsh (submerged aquatic vegetation), and unvegetated open water. The survey was conducted between November 2019 to January 2020. FCE1250_Lamb_AltStableState_Bio contains plot-scale (1 m^2) biological measurements from emergent marsh (sawgrass). Biological measurements (total sawgrass, average individual sawgrass biomass, and total sawgrass aboveground biomass), are inherently plot-level but geomorphic and hydrologic measurements were averaged (n = 3) for each plot. Standard deviations are provided. FCE1250_Lamb_AltStableState_Bio_LongTerm contains biological plot-scale (1 m^2) measurements at a bi-monthly timestep from Nov 2019 - July 2022 from a subset of plots (n = 9) included in the FCE_1250_Lamb_AltStableState_Bio dataset. Each bi-monthly measurement is the average value across all 9 nine plots. Standard deviations are also included. FCE_1250_Lamb_AltStableState_SETMH contains long-term measurements of soil surface elevation change and vertical accretion from surface elevation change and marker horizon plots from June 2018 - May 2023. Average and standard errors across all plots are included as well as measurements from each plot. Also included is the cumulative number of dry days based on the average soil surface elevation for all plots. Data collection for all datasets is complete, except for FCE_1250_Lamb_AltStableState_SETMH. SET-MH measurements are still ongoing.
Experimental manipulation of predatory crab species identity (Panopeus obesus vs. Eurytium limosum) and size-structure and assessment of effects on invertebrate densities, sediment properties and plant biomass.
Predatory mud crabs (Panopeus obesus and Eurytium limosum) are two of the main resident infaunal predators in southeastern US salt marshes. Little is known, however, about their effects on important prey species, or their influences on sediment or plant properties. These influences are likely to be dependent on the identity of species and the size-stucture of the population. We therefore manipulated the species identity (Panopeus or Eurtium) and size-structure. The size-structure treatrment had four levels: small [9 individuals, each 18-22mm carapace diameter], medium [6 ind. 24 -28mm], large [3 ind. 32-36mm], mixed (3 small, 2 medium, 1 large, all within same cage). The numbers of crabs in each size-structure treatment were chosen to capture natural size-abundance relationships. The treatments were maintained in experimental cages (70 x 70 x 100 cm, length, width, height) in the mid-Spartina zone at Dean Creek, Sapelo Island, GA. We maintained the treatments over 4 months (July - October 2010), before assessing impacts on prey densitities (mud fiddler crabs, ribbed mussels and marsh periwinkles), and ecosystem properties (aboveground plant biomass, sediment redox potential, sediment water content).
Geographic coordinates, soil properties, plant species composition and vegetation survey data in the study on tidal marshes of the Ogeechee, Altamaha and Satilla estuaries in Georgia, USA
We examined patterns of habitat function (plant species richness), productivity (plant aboveground biomass and total C), and nutrient stocks (N and P in aboveground plant biomass and soil) in tidal marshes of the Satilla, Altamaha, and Ogeechee Estuaries in Georgia, USA. We worked at two sites within each salinity zone (fresh, brackish, and saline) in each estuary, sampling a transect from the creekbank to the marsh platform. Site-scale and plot-scale species richness decreased from fresh to saline sites. Standing crop biomass and total carbon stocks were greatest at brackish sites, followed by freshwater then saline sites.
Soil properties in the MELNHE study at Hubbard Brook Experimental Forest, Bartlett Experimental Forest and Jeffers Brook, central NH USA, 2009 - present
The Multiple Element Limitation in Northern Hardwood Ecosystems (MELNHE) project studies N, P, and Ca acquisition and limitation of forest productivity through a series of nutrient manipulations in northern hardwood forests. We are monitoring resin N and P availability, N mineralization, and soil enzyme activities. This data set includes soil water content, soil pH, organic horizon mass, soil organic matter, bicarbonate extractable P, extractable Ca, and soil texture data. Additional detail on the MELNHE project, including a datatable of site descriptions and a pdf file with the project description and diagram of plot configuration can be found in this data package: https://portal.edirepository.org/nis/mapbrowse?scope=knb-lter-hbr&identifier=344. This work is a contribution of the Hubbard Brook Ecosystem Study. Hubbard Brook is part of the LTER network, which is supported by the US National Science Foundation. The Hubbard Brook Experimental Forest is operated and maintained by the US Department of Agriculture, Forest Service, Northern Research Station. These data have been described and analyzed in the following publications: Shan S, Devens H, Fahey TJ, Yanai RD, Fisk MC. 2022. Fine root growth increases in response to nitrogen addition in phosphorus-limited northern hardwood forests. Ecosystems. https://doi.org/10.1007/s10021-021-00735-4 Goswami S, Fisk MC, Vadeboncoeur MA, Johnston M, Yanai RD, and Fahey TJ. 2018. Phosphorus limitation of aboveground production in northern hardwood forests. Ecology 99:438-449. https://doi.org/10.1002/ecy.2100 Ratliff TJ, Fisk MC. 2015. Phosphatase activity is related to N availability but not P availability across hardwood forests in the northeastern United States. Soil Biology and Biochemistry 94:61-69 https://doi.org/10.1016/j.soilbio.2015.11.009. Bae B, Fahey TJ, Yanai RD, Fisk MC. 2015. Soil nitrogen availability affects belowground carbon allocation and soil respiration in northern hardwood forests of New Hampshire. Ecosystem
AGW01 Long-term measurement of groundwater physical and chemical properties from wells on watersheds N04D and N01B at Konza Prairie
In 1988 and 1990, 31 wells were installed at 20 sites within watershed N04D at Konza Prairie Biological Station to allow long-term monitoring of groundwater physical and chemical properties. Subsequently, four additional wells were installed in N04D in 1997, and five wells were installed in an adjacent watershed, N01B, in 2020. Most of the wells are nested to include wells completed in alluvium/colluvium and two Permian limestone units, the Morrill Limestone and the Eiss Limestone. The wells are completed along transects perpendicular to the main drainage in each watershed. Every four to six weeks, water samples and water depth measurements have been collected at subsets of the wells in N04D since 1991 and in N01B since 2021. At the same time, stream samples are collected from the outlet in N04D and N01B when the stream is flowing, as well as two upstream locations in N04D. Moreover, since 2024, stream samples are also collected at the same time from the outlet of a third watershed, N02B, when the steam is flowing. Methodologies have evolved since 1991 as detailed in the method description, though the primary goal of assessing groundwater and surface water major ion composition, pH, temperature, and groundwater level has been constant since 1991.
RCS01 Recovery and relative influence of root, microbial, and structural properties of soil on physically sequestered carbon stocks in restored grassland at Konza Prairie
Managing soil to sequester C can help mitigate increasing CO2 in the atmosphere. To maximize this ecosystem service, more knowledge of factors influencing C sequestration is needed. The objectives of this study were to (i) quantify recovery of the roots, microbial biomass and composition, and soil structure across a chronosequence of grassland restorations and (ii) use a structural equation model to develop a data-based hypothesis on the relative influence of physical and biological soil properties on the soil C aggregate fraction diagnostic of sequestered C. We hypothesized measured variables would recover with restoration age. Belowground plant biomass and tissue quality (C/N ratio), soil microbial biomass C, phospholipid fatty acid (PLFA) concentrations, soil structure, and soil C stocks in the bulk soil and each aggregate fraction were quantified from a cultivated field, prairies restored for 1 to 35-yr (n = 6), and a never-cultivated (native) prairie. Root biomass, microbial biomass C, arbuscular mycorrhizal fungi (AMF) PLFA biomass across the chronosequence increase to resemble native prairie following 35 yr of restoration. Many aspects of soil structure (i.e., bulk density, proportional mass of aggre- gate fractions, and aggregate mean weighted diameter) and the distribution C among soil fractions, including C in the micro-within-macro aggregate fraction (sequestered C), also became representative of native prairie within 35 yr of restoration. Total soil C stock and physically protected C increased at a similar rate (23 and 27 g C m-2 yr-1) respectively, across the chronosequence. After 35 yr of restoration, 50% of the total C pool was physically protected. The structural equation modeling developed by these data hypothesizes that microbial biomass C and AMF biomass (microbial composition) have the strongest causal influence on physically protected C. This model needs to be tested using independent sites to achieve greater inference.
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Allen Brain Atlas
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Annotated Behaviour and Observability Dataset (ABODe)
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