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7,355 results for “soils”

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edi52/100

NEON soil inorganic nitrogen measurements 2017-2020, derived data and code for Earth's Future manuscript

Nitrogen (N) is a key limiting nutrient in terrestrial ecosystems, but there remain critical gaps in our ability to predict and model controls on soil N cycling. This may be in part due to lack of standardized sampling across broad spatial-temporal scales. In a paper submitted for publication in Earth's future, we introduce a continentally distributed, publicly available dataset collected by the National Ecological Observatory Network (NEON) that can help fill these gaps. To overcome methodological challenges and generate a standardized dataset, we produced a derived data version of soil inorganic N pools and net N transformation rate tables, which accounts for nitrite contamination in blanks. This derived dataset is then used to evaluate sources of variation within the NEON sampling design with mixed effects models, and we also compare measured net N mineralization to simulated fluxes from the Community Earth System Model 2 (CESM2).

openCC0Feb 2023View details →
edi52/100

Near-surface, soil, and air temperature data acquired across multiple locations on the San Joaquin Experimental Range, California, 2011-2017

These temperature records were collected as part of a larger study relating microclimates to tree seedling survival in southern California mountains. These temperature records are for studies at the San Joaquin Experimental Range (Lat 37.083, Long -119.716, elevation 210-520 m, www.fs.fed.us/psw/ef/san_joaquin/). Temperature sensors were located at 23 sites across the landscape. Sites were selected to sample topographic variation in surface and air temperatures within a narrow range of elevations on northeast to southwest-facing slopes, ridges, and valleys. To characterize surface temperature variation within a site, 21 sensors were arranged in an identical pattern around and in six, 5x5 m experimental gardens. An additional 18 sensors were placed along three transects over the landscape running E-W. They were placed strategically to sample topographic inflection points (hill tops and valley bottoms) as well as north and south facing slopes. Temperatures were recorded on a 10 or 20-minute interval, depending on the sensor, using HOBO (Onset, www.onsetcomp.com) devices.

openCC (other)Feb 2018View details →
edi52/100

Near-surface, soil, and air temperature data acquired across multiple locations in the Teakettle Experimental Forest, California, 2011-2017

These temperature records were collected as part of a larger study relating microclimates to tree seedling survival in southern California mountains. These temperature records are for studies at the Teakettle Experimental Forest (Lat 36.967, Long -119.017, elevation 2000-2800 m, www.fs.fed.us/psw/ef/teakettle/). Temperature sensors were located at 44 sites across the landscape. Sites were selected to sample topographic variation in surface and air temperatures within a narrow range of elevations on northeast to southwest-facing slopes, ridges and valleys. To characterize surface temperature variation within select sites, 21 sensors were arranged in an identical pattern around and in six, 5x5 m experimental gardens (see garden schematic for details). An additional 33 sites were located across the site by way of a stratified sampling scheme which targeted low, medium, and high elevation areas, low, medium, and high radiation areas, and cold air pooling areas. In June 2012, in order to concentrate sensors in a smaller study area (ease of access and to make this more similar to other sites, 22 sites were "retired," and 7 new sites were installed, for a total of 18 during the remainder of the study. Temperatures were recorded on a 10 or 20-minute interval, depending on the sensor. using HOBO (Onset, www.onsetcomp.com) devices.

openCC (other)Apr 2018View details →
edi52/100

New Hampshire Soil Sensor Network: Soil CO2 Fluxes

The goal of the New Hampshire Soil Sensor Network is to examine spatial and temporal changes in soil properties and processes as the climate changes. Data collected can also calibrate and validate models that examine how ecosystems may respond to changing climate and land use. To determine how soil processes are affected by climate change and land management, this soil sensor network measures snow depth, air temperature, soil temperature, soil volumetric water content, and soil electrical conductivity, as well as soil CO2 fluxes. This data package includes air temperature, soil temperature at 5 cm, and soil volumetric water content at 5 cm, and soil CO2 flux at the time of sampling, as well as gap-filled soil CO2 fluxes using non-linear least squares regression. Data were collected at the following sites: BRT = Bartlett Experimental Forest, Bartlett, NH; BDF = Burley-Demmerit Farm, Lee, NH; DCF = Dowst Cate Forest, Deerfield, NH; HUB = Hubbard Brook Experimental Forest, Woodstock, NH; SBM = Saddleback Mountain, Deerfield, NH; THF = Thompson Farm, Durham, NH; and Trout Pond Brook, Strafford, NH.

openCC (other)Jul 2025View details →
edi52/100

Root Biomass, Fine Root Production, Soil Mass, and Soil pH in Limed and Control Plots at the Woods Lake Watershed, Adirondack Park, NY, USA, 2021-2022

In 1989, 6.89 Mg/ha of pelletized lime (CaCO3) was applied by helicopter to two subcatchments at the Woods Lake Watershed in Adirondack Park, New York, USA to ameliorate ecosystem acidification. Two unlimed (control) subcatchments were paired with limed subcatchments. In the same year, 99 permanent plots (20 m x 20 m) were established. Between 2008 and 2010, tree inventory and soil physicochemical measurements were made in five plots in each of the four subcatchments (20 plots total). This dataset contains soil physicochemical properties (dry mass, depth, and pH); root biomass (<1 mm, 1-2 mm, and >2 mm diameter); and annual fine root production (<1 mm and 1-2 mm) measurements made between 2021 and 2022 in 19 of these same plots (5 plots per control subcatchment and 4 or 5 plots per limed subcatchment). Data include measurements for all properties for Oe, Oa, and 0-10 cm mineral soil samples collected from 5 locations within each plot.

openCC (other)Jan 2025View details →
edi52/100

Field Evidence of Carbon and Nitrogen Stabilization through Mineral Associated Organic Matter Formation in Coastal Wetland Soils from Apalachicola, Florida, collected in June, 2022.

This data set was used to observe the role of Mineral Associated Organic Matter Formation (MAOM) on biogeochemical soil properties in three coastal wetlands in Apalachicola, Florida. One wetland was restored using beneficial dredged sediment, increasing the soil's inorganic matter content. Soil samples were collected in June 2022 from this wetland and two nearby reference wetlands: one with high organic matter and the other with higher inorganic matter content. The samples were analyzed at the University of Central Florida for biogeochemical properties to determine which properties were most related to MAOM pools.

openCC (other)Feb 2025View details →
edi52/100

Soil respiration rates, biogeochemical pools, and mineral-associated organic matter from high organic matter and high mineral content coastal wetland soils in Apalachicola, Florida, 2022

This data set was used to observe how the application of dredged sediment would impact soil respirations rates, biogeochemical pools, mineral associated organic matter of coastal wetland soils from Apalachicola, Florida. To achieve this, a combination of intact core and bottle incubations were used, comparing a high organic matter coastal wetland soil to a high mineral content wetland soil which were collected in June, 2022. All laboratory analysis was conducted at the University of Central Florida in Orlando, Florida.

openCC (other)Mar 2025View details →
edi52/100

Geochemical Characterizations for Identifying Fugitive Dust Deposition and Enrichment of Surface and Subsurface Subalpine Soils from Phosphorus Mining, Eastern Ashley National Forest, Utah, 2022-2023.

Phosphorus is a non-renewable resource essential for all life. Anthropogenic alterations to the phosphorus cycle have led to widespread phosphorus pollution, and the unsustainable management of P has led to the threat of global depletion of phosphorus resources. Thus, accounting for the natural and anthropogenic flow paths of phosphorus is essential for its conservation and pollution reduction. One such source of human alteration to the phosphorus-cycle is phosphate rock mining. Mining, however, has many adverse environmental effects, including widespread fugitive dust emissions. Dust collection in the Ashley National Forest of northeastern Utah, proximate to a surface phosphorus mine, has shown phosphorus concentrations in dust more than four times that of other regional samples. Elevated phosphorus in dust near active surface mining suggests that mining emissions may alter the natural phosphorus loading of the soils in the National Forest through dust deposition; however, no research has been done to identify the abundance and range of mine-attributable phosphorus enrichment in the soils surrounding phosphate mining activities. The combined geospatial and geochemical approach of this study shows that surface soil phosphorus concentrations were found to be enriched above naturally occurring levels up to 6.5 km from mining activity (enrichment factor > 1.5), with the most significant enrichment occurring within the first 3 km (enrichment factor > 2). On average, surface phosphorus concentrations were significantly enriched by 25% within 6.5 km of phosphorus mining activity. Observed phosphorus enrichment was positively correlated with the presence of fluorapatite in the soil, which is the primary phosphorus-mineral extracted from the nearby mine. Further, bioavailable phosphorus concentrations were also higher for the soils that were enriched in phosphorus. This study shows that fugitive emissions associated with the surface mining of phosphate rock are a significan

openCC (other)Mar 2025View details →
edi52/100

Deep-soil carbon changes at 62 European beech stands in the Vienna Woods, Austria, 1984-2022

This dataset comprises repeated soil, vegetation, and site measurements from long-term forest monitoring in the Vienna Woods (Wienerwald), Austria, part of the UNESCO Biosphere Reserve “Wienerwald” (48.1°–48.3° N, 15.8°–16.3° E). The study focuses on pure, naturally regenerated European beech (Fagus sylvatica) stands, initially sampled in 1984 and resampled in 2012 and 2022 . Elevations range from ~180 to 800 m a.s.l., with mean annual temperatures of 8–9 °C and precipitation of 600–900 mm. Soil samples were collected from three mineral soil depths (0–5 cm, 30–40 cm, and 80–90 cm) following consistent protocols across sampling years. Variables include total, organic, and inorganic carbon, total nitrogen and sulfur, exchangeable base cations (Ca, Mg, K), pH, total Fe and Mn, fine soil mass, bulk density, rock content, soil texture, and root biomass. Stocks were calculated. Leaf nutrient concentrations (C, N, S, P, Ca, Mg, K) were determined in all sampling years. Dendrochronological measurements were conducted to determine growth trends since stand establishment, and stand-level characteristics (tree density, DBH, aboveground biomass, crown vitality, slope, aspect) were recorded. Site-level climate data (mean annual temperature, annual precipitation) from 1961 to present and atmospheric deposition data for N and S (1990, 2012, 2022) were integrated from national and European gridded datasets. The dataset supports long-term assessments of soil carbon and nutrient dynamics, forest productivity, and environmental change impacts in old-growth beech forests. Data collection is complete for the 1984, 2012, and 2022 campaigns; no ongoing sampling is planned.

openCC (other)Aug 2025View details →
edi52/100

Environmental Data for Soil, Leaf, and Root samples Boston Street Trees and Massachusetts Rural and Urban Forests in Summer 2021

This dataset provides detailed environmental and tree-level data and metadata for over 850 samples collected from 91 trees across an urban-to-rural gradient in Massachusetts. The dataset captures key variables characterizing urban environmental gradients, including soil moisture, pH, temperature, and nitrogen availability. Tree-level attributes include species identification, diameter at breast height (DBH), and growth rate based on previous tree census data. Geographic coordinates and site-specific context (urban forest, rural forest, street tree, forest edge, forest interior) are included to enable spatial analyses. The microbial sequence data associated with this environmental metadata can be found in the NCBI SRA under BioProject accession number PRJNA1297772.

openCC0Aug 2025View details →
edi52/100

Soil organic carbon and nutrient dynamics in response to anaerobic digestate application to farm fields, Eastern Iowa, 2011-2023

This dataset documents a long-term, field-scale study of anaerobic digestate application on commercial croplands in eastern Iowa, USA. It includes detailed records of digestate composition, application rates, and timing, as well as soil test results collected over a 12-year period (2011–2023) from 14 agricultural fields. The dataset supports analysis of soil organic carbon (SOC), nutrient dynamics, and isotopic composition in response to digestate inputs. It contains 421 georeferenced soil samples, digestate nutrient profiles, field management histories, and spatial boundaries. The data were collected as part of a collaborative effort between researchers at Iowa State University and Sievers Family Farms to evaluate the agronomic and environmental implications of integrating anaerobic digestion into row crop and livestock systems.

openCC (other)Aug 2025View details →
edi52/100

Red Oak Root and Soil Environmental Gradient Study, Midwest U.S., 2022-2023.

Fine root trait and soils data for Quercus rubra L. (northern red oak) sampled along a Midwestern latitudinal gradient. Fourteen sites spanning 5-14 degrees C were sampled. Each sample represents 2 6 cm deep x 5 cm wide soil cores obtained from near the base of a Q. rubra individuals, with 6 sampled plots per site. Plots were located approximately 40 m apart along a linear transect to be at a cluster of Q. rubra individuals. All 14 sites were visited twice in the growing season of 2022: between June 1st and June 21st, and between July 5th and July 21st. Root traits sampled include average diameter, root tissue density, specific root length, branching intensity, and specific respiration rate. A 1 mm diameter limit cut-off was used. These traits were measured in the field (respiration rates) or from output from RhizoVision Explorer image analysis. Traits are associated with the smaller fine root sample used for respiration measurement in the field (~2 g dry weight). Fine root biomass was also obtained by removing all remaining fine roots in the core, drying, and weighing, and then was multiplied by weight-normalized respiration rates to obtain estimates of fine root ecosystem respiration. This data package is complete, but will be associated with data from 4 sites revisited in 2023 to obtain repeat fine root trait measurements and fungal community community metrics.

openCC (other)Oct 2025View details →
edi52/100

Soil nitrogen availability and acidity: effects on aboveground production and belowground carbon allocation in mid- and late-successional mixed temperate forests (2009-2021)

In 2011, an experimental nitrogen x pH manipulation study was initiated in mid- and late-successional mixed temperate forests in central New York, USA to disentangle the often-confounded roles of nitrogen (N) and soil pH in driving various ecosystem processes. This data package contains forest productivity (wood, litterfall, and aboveground net primary production), total belowground carbon flux (TBCF), and leaf litterfall and fine root chemistry (C and N concentration) data collected from all experimental plots. It also includes plot-level, species-weighted estimates of measured and modeled photosynthesis (Anet) for the late-successional stands. Wood production, litterfall production, and litterfall chemistry data were collected between 2009 and 2019. Aboveground net primary production data are reported for a pre-treatment interval (2009-2011) and the interval including years 6-9 of experimental treatment (2016-2019). All other properties were measured between years 9 and 11 of the experiment (2019-2021).

openCC (other)Jan 2026View details →
edi52/100

Microbial and soil moisture impacts of compost amendments and rainfall pulses in a degraded dryland soil, Arizona, 2021-2023

Compost, an organic soil amendment, has been proposed to increase soil carbon storage and water-holding capacity in drylands, and this management strategy may be particularly impactful in degraded drylands with low soil organic content. Compost additions and rainfall variability may interact to affect soil moisture, which is an important catalyst for soil microbial activity. This dataset is from a study that investigated how variable compost application amounts and simulated rainfall pulses affect soil moisture, microbial activity, and carbon content in a laboratory incubation study. Soils were amended with different amounts of compost (0, 0.35, and 0.70 g cm -2) and water pulses (5, 10, and 15 mm) in a full-factorial design. Each treatment received the same cumulative amount of water throughout the incubation, but pulses occurred at different frequencies (every 5, 10, and 15 days). Soil moisture content and microbial respiration were measured daily. Soil carbon content was measured at the end of the experiment.

openCC (other)Nov 2025View details →
edi52/100

Landscape Ecosystem Classification Soils and Vegetation Plots Data at the University of Michigan Biological Station, Pellston, Michigan from 1987 to 2015 remeasurements

Landscape ecosystems are a means of understanding the spatial patterns of and the functional interrelationships in forest ecosystems. Landscape ecosystem research is a multifactor, holistic approach to identifying, classifying, describing, and mapping terrain ecosystems. Abiotic and biotic factors are integrated in the field to distinguish repeating units similar in ecological structure and function. Landscape ecosystems are identified by simultaneous integration of physiographic, soil, and vegetation information. The more stable components--physiography and soil--largely determine local climate, and water and nutrient relations, and thus the interrelationships of physiography and soil form the foundation of a landscape ecosystem classification. Vegetation is seen as a phytometer that integrates the many abiotic factors and their interactions, and therefore reflects differences in ecosystem structure and function. When the three main ecosystem factors are analyzed simultaneously, one can perceive interrelationships that result in ecologically meaningful differences among segments of the ecosphere. Landscape ecosystems are spatial; they are volumetric, multi-dimensional segments of earth, whose components include soil, water, atmosphere, solar radiation, and biota. These segments can be identified, classified, described, and mapped at various scales. From the years of 1988 to 2001, various graduate students of Burton V. Barnes completed their masters thesis and dissertations in this pursuit. The attached data set is a culmination of these individual work. Each plot has measurements at various scales within the 10 by 30 meet plot. A stratified random design was used to locate plot locations. The random design was stratified by major and minor landforms in the region. All trees within the plot where identified and dbh was measured. All individual shrubs where identified and abundance was counted within the entire plot. Soils pits locations for each plot where selected

openCC (other)Apr 2025View details →
edi52/100

The Biomass and Plant Functional Traits of Leymus chinensis Affected by Genotypic Diversity and Soil Nitrogen Addition through a Two-year Experiment, Tianjin, China, 2021-2023

In order to investigate the effects of soil nitrogen addition on the genotypic diversity of Leymus chinensis, 12 genotypes of Leymus chinensis were used as plant material and a two-factor experimental design was carried out in this study. Factor one was genotypic diversity of L. chinensis, including three levels: mono-genotype (G1), three genotypes (G3), and six genotypes (G6). Factor two was the soil nitrogen addition level, which included four levels: no nitrogen addition (N0), 2.5 g N/(m²·a) nitrogen application (N2.5), 5 g N/(m²·a) nitrogen application (N5), and 10 g N/(m²·a) nitrogen application (N10). Each treatment had 12 combinations as replicates, and 12 genotypes of L. chinensis were used. The frequency of each genotype was standardized across all treatment levels of genotypic diversity × soil nitrogen addition. The experiment commenced in September 2021 and soil nitrogen was applied every 2 months. Plants were cultivated in the experimental field at Nankai University, but were moved to a greenhouse for overwintering from November to February each year. During the experiment, there were no stresses or disturbances such as shading, drought, or insect feeding; weeds were regularly removed.

openCC (other)Jan 2026View details →
edi52/100

Nitrogen Cycling and Environmental Data in Riparian Soils across Biomes

This dataset compiles soil nitrogen cycle data from riparian soils, sourced from peer-reviewed studies published between 1980 and 2023. The selection process was based on three inclusion criteria: (1) studies measuring in-situ net nitrification rates in the top soil layer using the incubating bag technique, (2) studies reporting net nitrification rates from laboratory incubations without altering the initial nitrogen pool, and (3) studies providing field data on soil nitrogen concentrations, moisture, and temperature. The final dataset (D1) includes data from 174 riparian sites across four continents, with the majority of sites (86%) located in North America and Europe, while only 13 were located in the Southern hemisphere. For each site, we gathered data on net nitrification rates and key soil physicochemical properties, including bulk density, depth, moisture (expressed as water-filled pore space, WFPS), temperature, and ammonium and nitrate concentrations. The dataset includes 734 observations from 99 field sites and 120 observations from 45 laboratory-incubated sites. All publications from which data were used are list in dataset 2 (D2). This comprehensive dataset offers valuable insights into nitrogen dynamics in riparian soils, supporting further research into soil nitrogen cycling across diverse biomes and environmental conditions.

openCC (other)Feb 2026View details →
edi52/100

Marcell Experimental Forest weekly soil temperature, 1989 - ongoing

This data publication contains soil temperature measured at eight depths weekly (1989 - ongoing) at the Marcell Experimental Forest (MEF) in Balsam Township, Itasca County, Minnesota. The data came from five peatland / upland forest watersheds instrumented for long-term hydrological and biogeochemical research. The Marcell Experimental Forest in Itasca County, Minnesota is operated and maintained by the USDA Forest Service, Northern Research Station, and was formally established in 1962 to study the ecology and hydrology of peatlands.

openCC (other)Mar 2025View details →
edi52/100

Soil and root-associated fungal response to nitrogen and phosphorus addition from grasslands worldwide: 2011-2012.

Ecosystems across the globe receive elevated inputs of nutrients, but the consequences of this for soil fungal guilds that mediate key ecosystem functions remain unclear. We found that nitrogen and phosphorus addition to 25 grasslands distributed across four continents promoted the relative abundance of fungal pathogens, suppressed mutualists, but did not affect saprotrophs. Structural equation models suggested that responses were often indirect and primarily mediated by nutrient-induced shifts in plant communities. Nutrient addition also reduced co-occurrences within and among fungal guilds, which could have important consequences for belowground interactions. Focusing only on plots that received no nutrient addition, soil properties influenced pathogen abundance globally, whereas plant community characteristics influenced mutualists, and climate influenced saprotrophs. These guild-level responses enhance our ability to predict soil functional responses to anthropogenic eutrophication and the associated longer-term responses of plant communities to this important global change factor.

openCC (other)Apr 2021View details →
edi52/100

2017 hydrologic, water quality, and soil quality data from The Jefferson Projects 8 Tributary Stations within the Lake George basin, NY, USA.

The Jefferson Project at Lake George – a partnership between Rensselaer Polytechnic Institute, IBM Research, and Lake George Association – combines Internet of Things technology and powerful analytics with science to create a new model for environmental monitoring and prediction. The project is building a computing platform that captures and analyzes data from a network of sensors tracking water quality and movement. These sensor data are combined with other monitoring and experimental data to create a thorough understanding of the factors that drive the lake’s food web and overall water quality. More information about The Jefferson Project is available at https://jeffersonproject.rpi.edu/ In 2017, The Jefferson Project had eight tributary monitoring stations around the lake collecting data on water quality, soil quality and hydrology. These stations are TS_Finkle, TS_Hague, TS_Indian, TS_NorthwestBay, TS_Outlet, TS_PoleHill, TS_ShelvingRock and TS_West. The stations have a sensor payload that may include some or all of the following sensors: EXO2 Multi-parameter sonde, CS451 pressure transducer, SonTek-IQ+ multi-beam acoustic flow meter with five 3.0 MHz transducers, Argonaut-SL Doppler current meter, WaterLOG® H-3123 submersible pressure transducer, and Stevens HydraProbe soil moisture sensor. The sensors collect data at high-frequency (~1 sample per minute) and the data is transferred in near real-time to off-site databases for monitoring and review by Jefferson Project researchers. Data provided is level 4 data which underwent data correction and down sampling to an hourly frequency.

openCC (other)Apr 2023View details →

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Allen Brain Atlas

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allen-brain-atlas
neuroscienceopenDocumentation, web resources, and API references are available online.
Last verified 2026-04-30Open record

Annotated Behaviour and Observability Dataset (ABODe)

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abode-home-cage
behavioral-neuroscienceopenThe DataShare record exposes download links for annotations, documentation, license text, and the zipped per-snippet data directory.
Last verified 2026-04-30Open record

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.

dandi-nwb
electrophysiologyopenPublished Dandiset metadata and archive endpoints are available through the production DANDI API.
Last verified 2026-04-30Open record

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.

ibl
behavioral-neuroscienceopenPublic sessions can be searched and loaded from the IBL public data server through ONE.
Last verified 2026-04-29Open record

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.

openneuro
neuroscienceopenPublished datasets are available on demand over the internet.
Last verified 2026-04-29Open record