Find research datasets worth reusing

openCustomJan 2020View details →

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.

openCC (other)Apr 2022View details →

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

openCC0Jan 2023View details →

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.

openCC (other)Nov 2023View details →

Patterns in soil and physical properties of the Bisley Watersheds 1 and 2 (Big Dig 1988, Big Dig 1990)

(1) Exchangeable cation concentrations were measured using different soil extracting procedures (fresh soil and air-dried and ground soil) to establish a range of nutrient availability in the soil, and to determine the relationship between different, but commonly used laboratory protocols.(2) Soils extracted using fresh soils generally yielded significantly lower exchangeable Ca , Mg, and K concentrations than soils which were dried and ground prior to extraction. Soil nutrients generally decreased with depth in the soil.(3) Several soil properties varied predictably across the landscape and could be viewed in the context of a simple catena model. In the surface soils, exchangeable base cation concentrations and pH decreased along a gradient from ridge tops to riparian valleys, while soil organic matter, exchangeable Fe and acidity increased along this gradient. On the ridges, N,P, and K were positively correlated with soil organic matter; on slopes, N and P were positively correlated with organic matter, and Ca, Kg, and pH were negatively correlated with exchangeable Fe. (4) Soil nutrient availability in the upper catena appears to be primarily controlled by biotic processes, particularly the accumulation of organic matter. Periodic flooding and impeded drainage in the lower catena resulted in a more heterogeneous environment. Drying and grinding the soil prior to extraction had a greater impact on exchangeable cations from the upper catena than in the valley positions, probably due to greater soil organic matter content. See Silver, W.L., F.N. Scatena, A.H. Johnson, T.G. Siccama, and M.J. Sanchez. 1994. Nutrient availability in a montane wet tropical forest in Puerto Rico: spatial patterns and methodological considerations. Plant and Soil 164:129-145. 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 Univ

openCC (other)Oct 2025View details →

Integrated measurements of soil micro-invertebrate abundance and associated physicochemical properties from the McMurdo Dry Valleys, Antarctica (1993–2022)

This data package compiles three decades (1993–2022) of soil micro-invertebrate abundance data and associated physicochemical measurements collected as part of the McMurdo Dry Valleys Long Term Ecological Research (MCM LTER) project in Antarctica. Variables include soil micro-invertebrate counts and species richness, along with associated soil physicochemical properties, including gravimetric moisture content, pH, electrical conductivity, soil organic carbon, ammonium, and nitrate. Data originate from both long-term core monitoring efforts and targeted opportunistic sampling campaigns across multiple valleys, including Arena, Beacon, Pearse, Taylor, Victoria, and Wright Valleys. Sampling locations span a range of geomorphic and ecological settings, providing broad spatial and temporal coverage of soil conditions across the Dry Valleys ecosystem. Data were curated to represent the most comprehensive and spatially diverse records available while minimizing sampling bias across years and study types. These integrated measurements provide a valuable resource for understanding the drivers of soil micro-invertebrate abundance and habitat suitability and serve as a foundation for future analyses of long-term ecological change and species distribution modeling in polar desert soils.

opencc-by-4.0Jan 2022View details →

Model outputs from the study "A scalable framework for soil property mapping tested across a highly diverse tropical data-scarce region"

Model outputs from the study "A scalable framework for soil property mapping tested across a highly diverse tropical data-scarce region". The study is published as open access and can be found at the following link: <a href="https://www.sciencedirect.com/science/article/pii/S2950289625000326">https://www.sciencedirect.com/science/article/pii/S2950289625000326</a>   The file "SWAT_USERSOIL.csv" was included to facilitate the assimilation of the soil mapping data into the Soil & Water Assessment Tool (SWAT, https://swat.tamu.edu/) for hydrological modeling.    Regarding the raster files, please note: a) All values in these datasets have been multiplied by 10,000 to optimize file sizes. b) Files are named using the variable acronym, followed by the corresponding soil layer. For outputs derived from pedotransfer functions (PTFs), the PTF reference is appended after the variable acronym. c) Available data decrease with increasing soil layer number. This occurs because not all locations (grid cells) have the same soil depth or number of soil layers.   If you have any questions about the dataset or its use, please don't hesitate to contact us.

opencc-by-4.0Aug 2024View details →

Soil Properties Summarized by Lots in Ouro Preto D'Oeste, Rondônia - Brazil (2019 surveyed lots V2)

Soil properties data, summarized (weighted average by area with the given property on the lots surveyed on 2019 - V2) over small properties lots in Ouro Preto d'Oeste, Rondônia - Brazil:     AWHC:Available Water Holding Capacity: Water content at “field capacity” minus Water content at wilting point.  Water content is % by weight.  (50% = 50% of the weight of a lump of soil is water). (%)     PBS: Percent Base Saturation (%)     CLAY: Clay content (%)

opencc-by-4.0Oct 2024View details →

Soil properties in agricultural systems affect microbial genomic traits

Code and supplementary table

opencc-by-4.0Jul 2021View details →

Soil microarthropods, ground-dwelling arthropods and soil properties in mown and grazed grasslands in the Veluwe region

In order to find out which factors limit the restoration of soil life and their ecosystem services under grasslands on sandy soils, we studied 40 grasslands of which 20 had agricultural and 20 nature land use, all after an agricultural history.   Site selection Within the Veluwe region (The Netherlands), we selected 40 grasslands: 20 agricultural grasslands and 20 nature grasslands which were managed as new nature reserves since last tillage. Within each of these two land-use types, two types of grassland management were selected: mowing and grazing. Within each of the four combinations of land use and management we selected ten grasslands over a broad age range since last tillage. All grasslands were located on sandy soils (Typic Haploquod and Plaggeptic Haploquod; Soil Survey Staff 1999) with a deep water table to rule out dispersal of soil fauna during waterlogging (Siepel 1996; Jabbour & Barbercheck 2008).   Vegetation and insect surveys Within each grassland a 5×5 meter monitoring plot was laid-out for plant cover surveys, insect and soil-microarthropod sampling and soil analyses. The vegetation surveys were carried out in 2019 at the end of May and in early June, using the Braun-Blanquet method (Braun-Blanquet 1932). In June 2019 soil-surface dwelling insects were sampled with a pitfall trap (Wiggers et al. 2015). Three pitfall traps (8 cm diameter, ca. 20 cm deep) were placed in each plot. Traps were half filled with a solution of water and glycol (3:1) and 3 % Extran soap. A plexiglass cover 20 cm above the trap prevented rainfall diluting the liquid. Traps were removed and emptied after seven days.  Insects were identified and grouped at the order level, however, predator groups (carabid and staphylinid beetles, ants and spiders) were identified to the species level in order to group those by their feeding guild.             Before analyzing the pitfall trap catches we first removed certain groups from the counts because pitfall traps are not well-suited to catch them systematically: Acari, Collembola, Psocoptera, Thysanoptera, Trichoptera, Lepidoptera, Siphonaptera, Diptera, Symphyta, Apocrita, and Parasitica. The remaining 62.0% of the caught individuals were surface-dwelling animals, and their totals (of three pitfall traps per site) were analyzed with negative-binomial generalized linear models. We also analyzed the subset of predators (73.6% of the surface dwellers).   Soil chemical and pesticide sampling and analysis On 8, 9 and 16 October 2019, a bulk soil sample of 50 soil cores (0 - 10 cm) was collected from each 5×5 meter monitoring plot. After homogenization a sub-sample was analyzed for soil chemical analysis. Prior to chemical analysis, samples were oven-dried at 40 °C. Soil acidity of the oven-dried samples was measured in 1 M KCl (pH-KCl). Soil Organic Matter (SOM) was determined by loss-on-ignition (Ball 1964). Ammonium-lactate-extractable P (PAL) was determined according to the standard method (Bronswijk et al. 2003). Total potassium (K) in solution was determined using flame photometry after extraction of soil with HCl (0.1 M) and oxalic acid (0.5 M) in a 1:10 M:V ratio and filtration (Bronswijk et al. 2003).  Clay (<2 μm diameter) content was determined through density fractionation (NEN 5753, 2018). Another soil sub-sample was sent to Eurofins Zeeuws-Vlaanderen for pesticide/residue analysis. Samples were freeze-dried and homogenized prior to analysis. Homogenized samples were extracted with acetone, petroleum ether and dichloro-methane using an optimized mini-Luke method. In total 664 pesticides and pesticide residues were analyzed with gas chromatography (Agilent) and liquid chromatography (LC-chromatograph (Agilent) and MSMS (Sciex)). Glyphosate, its residue AMPA and gluphosinate were analyzed using single residue analysis. The detection limit (LOD) was 0,1 mg per kg sample.   Soil microarthropods sampling and determination Grasslands were sampled for microarthropods on 8, 9 and 16 October 2019, taking three cores per monitoring plot of 5×5 m. Cores were 5 cm Ø and 5 cm deep mineral soil plus upper litter. Cores were taken in the middle of the monitoring plots, 1 m apart from each other. Cores were extracted on a Tullgren funnel for 7 days. During that period temperature was increased from 35 to 45 0C. Ethanol 70% was used as conservation fluid and microarthropods obtained were put into lactic acid 30% for clarification and identification (Siepel & van de Bund 1988). Identification for the main groups is according to Weigmann (2006) for Oribatida, Karg (1993) for Gamasina and Karg (1989) for Uropodina. Nomenclature is according to Siepel et al. (2009) (Oribatida), Siepel et al. (2016) (Astigmatina) and Siepel et al. (2018) (Mesostigmata).   Litter decomposition To determine the potential decomposition of soil organic matter on each grassland the Tea Bag Index (TBI) was used (Keuskamp et al. 2013). In each grassland four green tea and four rooibos tea bags were buried at 8 cm deep in May 2019 in the 5×5 meter monitoring plots. After 90 days tea bags were collected and stored at 4 ⁰C prior to drying at 70 ⁰C for 48 hours. After drying, remaining sand and (fine) plant roots were carefully removed and the teabags were weighted to determine weight loss. The decomposition rate (k) and the litter stabilization factor (S) of the tea was calculated using the Tea Bag Index (Keuskamp et al. 2013).   Data files siteData.csv site: grassland ID landuse: agricultural or nature land use treat: mowing or grazing management yearsManaged: number of years since last tillage fertilization: kg available nitrogen applied per hectare nGrazingDaysPerHa: livestock days per hectare per year N: mg nitrogen per 100 g  PAl: mg P205 per 100 g organicMatter: soil organic matter percentage clay: soil clay percentage nPlantSpecies: number of plant species nForbSpecies: number of forb species nMitesSpringtails: total number of individuals of mites and springtails in three core samples nMitesSpringtailsSpecies: number of mite and springtail species in three core samples shannonMitesSpringtails: Shannon diversity index for microarthropods (mites and springtails) nHerboFungivorousGrazerMitesSpringtails: total number of individuals of mites and springtails that are (herbo-)fungivorous grazers, in three core samples nInsectsSpidersPitfall: number of ground-dwelling insect and spider individuals in pitfall traps nPredatorInsectsSpidersPitfall: number of ground-dwelling insect and spider individuals that are predators, in pitfall traps decompositionRate: decomposition rate based on the Tea Bag Index litterStabilisationFactor: litter stabilization factor based on the Tea Bag Index nPesticides: number of detected pesticides avicidesTotalConcentration: microgram antraquinon per kg dry soil fungicidesTotalConcentration: total microgram of fungicides per kg dry soil insecticidesTotalConcentration: total microgram of insecticides per kg dry soil herbicidesTotalConcentration: total microgram of herbicides per kg dry soil pesticidesTotalConcentration: total microgram of pesticides (avicides+fungicides+herbicides+insecticides) per kg dry soil nPredatorCarabids: number of predator carabid beetles in pitfall traps nPredatorStaphylinids: number of predator staphylinid beetles in pitfall traps distanceToNearestHighway: shortest distance (in meters) to the nearest highway (A-road) distanceToNearestNroad: shortest distance (in meters) to the nearest national road (N-road)   mitesSpringtails.csv core: core ID, consisting of the site ID (number) and core-within-site ID (letter) species: soil mite or springtail taxon encountered in a soil core guild: feeding guild of the soil mite or springtail taxon:             b: bacterivorous             fb: fungivorous browser             fg: fungivorous grazer             gp: general predator             hb: herbivorous browser             hfg: (herbo-)fungivorous grazer             hg: herbivorous grazer             o: omnivore             ohf: opportunistic herbo-fungivore droughtSens: drought strategy of soil mite and springtail taxa             1: drought avoiders             2: drought sensitive             3: drought mesotolerant             4: drought tolerant microart: number of individuals of a taxon found in a soil core   insecticideData.csv fungicideData.csv herbicideData.csv site: grassland ID other variables: microgram of a certain pesticide per kg dry soil

opencc-by-4.0Mar 2023View details →

General soil properties of wheat fields along 9 Pedoclimatic regions in Europe

This data set contains general soil characteristics from wheat fields sampled (0-25 cm) in conventional and organic farms from 9 European pedoclimatic regions (Mediterranean South, Mediterranean North, Lusitanean, Atlantic Central, Atlantic North, Continental, Pannonian, Nemoral and Boreal). This data set is part of the work performed in WP3 SoildiverAgro project, funded by the European Commission Horizon 2020 programme [grant agreement 817819].

opencc-by-4.0Jul 2023View details →

Spatial models of topsoil properties in Romania using digital soil mapping techniques

The database includes the selected spatial models of soil variables for the Romanian territory derived by digital soil mapping techniques, accepted for publication in: Cristian Valeriu Patriche, Bogdan Roșca, Radu Gabriel Pîrnău, Ionuț Vasiliniuc, Spatial modelling of topsoil properties in Romania using geostatistical methods and machine learning, PLOS ONE, 2023 The database includes the selected spatial models of soil variables for the Romanian territory derived by digital soil mapping techniques. The file names indicate the soil variable and the method used for interpolation (RK – regression - kriging, EML – ensemble machine learning, GWR_OK – Geographically Weighted Regression – Ordinary kriging). The raster data is classified and saved in tif format with a resolution of 100 x 100 m. The spatial reference is Stereographic projection 1970 (Pulkovo_1942_Adj_58_Stereo_70). The soil variables are classified as follows: <table> <tbody> <tr> <td> Variable </td> <td> Classes </td> </tr> <tr> <td> 1 </td> <td> 2 </td> <td> 3 </td> <td> 4 </td> <td> 5 </td> <td> 5 </td> <td> 7 </td> </tr> <tr> <td> pH </td> <td> ≤ 5 (strongly acid) </td> <td> 5.1 – 5.8 (moderately acid) </td> <td> 5.9 – 6.8 (weakly acid) </td> <td> 6.9 – 7.2 (neutral) </td> <td> 7.3 – 8.4 (weakly alkaline) </td> <td> 8.5 – 8.8 (moderately alkaline) </td> <td>   </td> </tr> <tr> <td> EC (mS m-1) </td> <td> ≤ 12.75 </td> <td> 12.76 – 16.49 </td> <td> 16.50 – 20.04 </td> <td> 20.05 – 24.18 </td> <td> 24.19 – 29.11 </td> <td> 29.12 – 35.23 </td> <td> ≤ 35.24 </td> </tr> <tr> <td> OC (g kg-1) </td> <td> < 7.5 (very low) </td> <td> 7.5 – 17.4 (low) </td> <td> 17.4 – 37.8 (moderate) </td> <td> 37.8 – 61.0 (high) </td> <td> > 61 (very high) </td> <td>   </td> <td>   </td> </tr> <tr> <td> CaCO3 (g kg-1) </td> <td> 0 (no carbonates) </td> <td> 1 – 10 (low) </td> <td> 11 – 40 (medium 1) </td> <td> 41 – 80 (medium 2) </td> <td> 81 – 107 (medium 3) </td> <td>   </td> <td>   </td> </tr> <tr> <td> P (mg kg-1) </td> <td> < 4 (extremely low) </td> <td> 4 – 8 (very low) </td> <td> 8 – 18 (low) </td> <td> 18 – 36 (medium) </td> <td> 36 – 72 (high) </td> <td> > 72 (very high) </td> <td>   </td> </tr> <tr> <td> N (g kg-1) </td> <td> ≤ 1 (very low) </td> <td> 1.1 – 1.4 (low) </td> <td> 1.5 – 2.0 (medium 1) </td> <td> 2.1 – 2.7 (medium 2) </td> <td> 2.8 – 6.0 (high) </td> <td> > 6 (very high) </td> <td>   </td> </tr> <tr> <td> K (mg kg-1) </td> <td> ≤ 40 * (extremely low) </td> <td> 41 – 65 * (very low) </td> <td> 66 – 130 (low) </td> <td> 131 – 200 (medium) </td> <td> 201 – 300 (high) </td> <td> > 300  (very high) </td> <td>   </td> </tr> <tr> <td> Clay (%) </td> <td> ≤ 25  (low 1) </td> <td> 26 – 32 (low 2) </td> <td> 33 – 40 (medium 1) </td> <td> 41 – 45 (medium 2) </td> <td> ≥ 46  (high) </td> <td>   </td> <td>   </td> </tr> <tr> <td> Silt (%) </td> <td> < 25 (medium 1) </td> <td> 25 – 32 (medium 2) </td> <td> 33 – 40 (high 1) </td> <td> 41 – 50 (high 2) </td> <td> > 50 (high 3) </td> <td>   </td> <td>   </td> </tr> <tr> <td> Sand (%) </td> <td> < 15 (low 1) </td> <td> 15 – 25 (low 2) </td> <td> 26 – 35 (low 3) </td> <td> 36 – 56 (medium) </td> <td> > 56 (high) </td> <td>   </td> <td>   </td> </tr> </tbody> </table>   * classes not present on the Romanian territory

openCC (other)Jun 2023View details →

UCSB SONGS Mitigation Monitoring: Wetland Process Study – Soil Properties

These data describe physical and chemical properties of soil samples collected as part of the San Onofre Nuclear Generating Station (SONGS) Mitigation Monitoring Program. Data collection began in 2019 at the San Dieguito Wetland in San Diego County, CA. Additional locations at Tijuana Estuary in San Diego County, CA, Carpinteria Salt Marsh is Santa Barbara County, CA, and Mugu Lagoon in Ventura County, CA were added in 2021. Sampling occurred sporadically at various locations in each wetland. All soil samples were characterized for organic matter content and particle size. Additional properties were characterized for select soil samples.

openSep 2016View details →

The relationship between early succession rates and soil properties in the Andrews Experimental Forest, 1999-2000

This study represents only one portion of a much larger study involving a wide range of disciplines and several H.J. Andrews Forest researchers. This dataset represents all the soils data collected up through the summer of 1999. In addition, Steve Acker conducted surveys of vegetation and measuring tree growth using cores. Mark Harmon has conducted a survey of coarse woody debris. Future studies could include hydrology and species diversity. When we compared the soil characteristics between slow and expected recovery sites, the only variables showing significant differences were soil moisture, litter depth and substrate induced respiration (SIR) rates at low glucose concentrations. The litter depth was slightly less, soil moisture lower, and SIR rates higher in the slow sites. When we compared soils in adjacent uncut forests, we found that field respiration rates were lower in forests adjacent to slow recovery sites than to normal sites suggesting that these sites may have inherently lower productivities. We concluded that slow recovery after clear-cutting is most likely related to physical site characteristics; i.e. steepness of slope and aspect. There did not appear to be any difference in soil depth.

openCustomDec 2013View details →

Chemical and microbiological properties of soils in the Andrews Experimental Forest (1994 REU Study)

To conduct a comprehensive study of soil chemical and microbiological properties at the HJA during the week of July 11,1994.

openOpenDec 2015View details →

Soil properties and nutrient concentrations by depth from the Anaktuvuk River Fire site in 2011

Below ground soil bulk density, carbon and nitrogen was measured at various depth increments in mineral and organic soil layers at three sites at and around the Anaktuvuk River Burn: severely burned, moderately burned and unburned. This data corresponds with the aboveground biomass and root biomass data files: 2011ARF_AbvgroundBiomassCN, 2011ARF_RootBiomassCN_byDepth, 2011ARF_RootBiomassCN_byQuad, 2011ARF_RootBiomassCN_byQuad.

openOpenFeb 1998View details →

Soil physical and chemical properties based on genetic horizon from 4 replicate pits placed around the replicate LTER control plots sampled in 1988 and 1989.

Dataset contains the following soil properties for each genetic horizon - site, Soil pit, upper and lower boundary (cm), Mg meq/100gm, Ca meq/100gm, K meq/100gm, CEC meq/100gm, pH, %C, %sand, %silt, %clay, Total %N, Total %P, % organic matter, Mn meq/100gm, Available-P ppm, %CO3, bulk density gm/cm3, Volume wt gm/m2.

openOpenMar 2009View details →

Patterns of and controls over nitrogen inputs by green alder (Alnus viridis spp. fruticosa) to a secondary successional chronosequence in interior Alaska II - Soil Physical and Chemical Properties

In September of 1999 we collected soil cores to identify stage, replicate stand, canopy, and soil horizon patterns of soil physical (color, bulk density, pH) and chemical (N, C, P) parameters.

openCustomJan 2020View details →

February- March 2010 RTK survey of salt marsh plant ground elevations, plant characteristics and soil properties to support analysis of a LIDAR-derived DEM.

Real time kinematic (RTK) GPS survey of ground elevations for six plant species (Spartina alterniflora, Juncus roemerianus, Batis maritima, Distichlis spicata, Salicornia virginica and Borrichia frutescens) and two non-vegetated cover classes (salt pan and intertidal mud) was carried out from February to March 2010 to assess the accuracy of a LIDAR-derived digital elevation model. In total, 369 ground control points (GCP) were collected for the Duplin River (Sapelo Island) and Blackbeard Creek (Blackbeard Island) salt marshes with associated plant and soil charactistics (soil salinity and water content, soil organic matter, soil redox potential). Data were collected to examine the relationships between marsh soil elevation, plant habitat distribution and soil properties and to support the analysis of a a LIDAR-derived digital elevation model (DEM) and RTK data collect in 2009.

openCC (other)Dec 2023View details →

Hubbard Brook Experimental Forest: Soil Acid-Base Properties and Microbial Activity, Watershed 1 and West of Watershed 6 (2015-2016)

In summer 2015 and spring 2016, researchers collected soils from the CaSiO3-enriched watershed at Hubbard Brook (W1) and from a nearby site west of the reference watershed at Hubbard Brook (W6). These soils were sampled throughout the hardwood zone of each watershed, and the sampling scheme explicitly examined pit-and-mound microtopographic gradients. These soils were analyzed for acid-base properties, net and gross N cycling rates, microbial biomass, and C cycling rates. 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 US Forest Service, Northern Research Station.