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2,078 results for “soil data”
Air quality, soil moisture, green roof moisture and weather data from Meetjestad
<p>Soil moisture sensors were developed by citizen science collective Meet je Stad (Measure your City). Measure your City was started in 2015 by inhabitants of the City of Amersfoort, with the goal of measuring climate related indicators. To be able to do so, collaboration was sought with the City of Amersfoort (COA), the local Water Authority and the University of Applied Sciences of Amsterdam. For the first three years the initiative focused on measuring temperature and humidity. Importantly, citizens develop their own research questions, analyze the data together with professionals and discuss potential implications. By doing so, the collective uses citizen science to spread knowledge on both technology and climate change in the most grass-roots manner possible. Within the SCOREwater project, Measure your City was asked to expand measurements with soil moisture measurements and additional temperature and humidity sensors.</p> <p>An important note here is that Measure your City develops their own sensors, has developed their own data platform and uses its own gateways purchased from the Things Network. As a result, much effort is put into constructing sensors that are reliable, low-maintenance and accurate. The latter is important for the City of Amersfoort as well, which intends to not only work on shared knowledge and understanding, but also use the data for policy making. To do so the data has to be reliable. By deploying both these sensors and purchasing company-built sensors, we can compare the data to assess how reliable the Measure your City sensors are.</p> <p>The Measure your City can also be deployed on green roofs to measure soil moisture. Whereas the soil moisture sensor measures soil moisture on two depths (10 centimeter and 40 centimeter), the sensor on a roof only measures soil moisture on one depth. In addition to soil moisture, Measure your City also measures air temperature and relative humidity. Some sensors also measure air quality (particle matter).</p>
Soil moisture and climate data from SmartCityTrees sensors in Amersfoort
<p>Within the frame of the SCOREwater project, the City of Amersfoort commissioned <a href="https://hoefakker.com/boomspecialisten/smart-city-bodemvochtsensor/">Hoefakker</a> to install Teneo soil moisture and climate monitor sensors at several locations in the Schothorst neighbourhood and the Central Railway area. These sensors have been branded as "SmartCityTrees" by Hoefakker. The sensors measure soil moisture, temperature and humidity. Schothorst and the Central Railway area differ in groundwater levels. In Schothorst the groundwater levels are higher (average height: 0.7 meter to 1.0 meter below ground level) than in the Central Railway area (average height: lower than 1.6 meter below ground level). The lowest soil moisture sensors are placed on 1.2 meter below ground level. As a result, in the Schothorst area the sensors are located close to or in the groundwater during winter. In the Central Railway area they are located far above the groundwater level. This makes both areas interesting to include. What all soil moisture sensors have in common is that they are all located nearby trees and in public spaces. Locations differ in terms of: being in the sun or in the shade, being in a green setting (unpaved, such as parks) or being in a paved setting, and being near surface water or not. Because of the differences between the locations the sensors have been installed in, data from the sensors can be used to investigate questions such as:</p> <ul> <li>What is the influence of the type of surface on soil moisture levels?</li> <li>Does the nearby presence of surface water affect soil moisture?</li> <li>What is the influence of heat on soil moisture?</li> <li>What is the relation between groundwater levels fluctuance and soil moisture?</li> <li>Are adjustments on in public spaces (on street level) helpful to improve the soil situation for a more climate adaptive city?</li> </ul> <p>The soil moisture dataset contains soil moisture VWC (volumetric water content, the ratio of water volume to soil volume). This is a percentage represented as a number between 0 and 1. 0.73 for example is 73%.</p> <p>The climate dataset contains temperature in degrees Celsius and the relative humidity. Relative humidity is a percentage represented as a number between 0 and 1 as well.</p> <p>Time period: from 2021-01-01 to 2022-12-31.</p>
Soil and meteorological data, and finite element simulation framework for heat transfer through shrubs in winter near Lautaret pass, French Alps
<p>The data allow the calculation using finite element modeling of heat transfer through shrub branches and snow between the atmosphere and the soil. The shrubs are green alders (Alnus viridis). The site where they are found is called Alnus-Nivus (45.034750°N, 6.413630°E, 2034 m asl) near Col du Lautaret, French Alps. The soil data consist in temperature and volumetric liquid water content at 5 and 15 cm depths. One spot is near the alder collar (ALNUS), the other spot is 6 m away, under grass (GRASS).</p> <p>The meteorological data were obtained from the FR-Clt station, 750 m away (45.041278°N, 6.410611°E, 2046 m asl). See (Gupta et al., 2023) for details. Only the data relevant for heat transfer simulations are given.</p> <p>The simulation framework gives the alder mesh used in the heat transfer simulations. Typical simulations use a wood thermal conductivity of 1 W m<sup>-1</sup> K<sup>-1</sup> and a snow thermal conductivity of 0.1 W m<sup>-1</sup> K<sup>-1</sup>. Based on observations, the snow height at Alnus-Nivus is likely to be at least twice the value at FR-Clt. Forcing uses the snow surface temperature, derived from upwelling longwave radiation using an emissivity of 1. The data allow testing thermal bridging through shrub branches. These data are used in a publication in preparation: Domine, Fourteau, Choler, Exploration of Thermal Bridging Through Shrub Branches in Alpine Snow.</p> <p>Reference</p> <p>Gupta, A., Reverdy, A., Cohard, J. M., Hector, B., Descloitres, M., Vandervaere, J. P., Coulaud, C., Biron, R., Liger, L., Maxwell, R., Valay, J. G., and Voisin, D.: Impact of distributed meteorological forcing on simulated snow cover and hydrological fluxes over a mid-elevation alpine micro-scale catchment, Hydrol. Earth Syst. Sci., 27, 191-212, 2023.</p>
Near-surface, soil, and air temperature data acquired across multiple locations in the foothills of the Tehachapi mountains at Tejon Ranch, 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 in the foothills of the Tehachapi mountains at Tejon Ranch (Lat 34.983, Long -118.716, elevation 750-930 m, www.tejonranch.com). Temperature sensors were located at 23 sites across the Tehachapi foothills. 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 N-S. 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.
Near-surface, soil, and air temperature data acquired across multiple locations in the Tehachapi mountains at Tejon Ranch, 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 in the Tehachapi mountains at Tejon Ranch (Lat 34.967, Long -118.583, elevation 1600-1700 m, www.tejonranch.com). Temperature sensors were located at 23 sites across the Tehachapi foothills. 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 N-S. 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.
A scrubbed subset of near-surface, soil, and air temperature data acquired across multiple locations on the San Joaquin Experimental Range, California, 2012-2017
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.
A scrubbed subset of near-surface, soil, and air temperature data acquired across multiple locations on 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.
A scrubbed subset of near-surface, soil, and air temperature data acquired across multiple locations in the foothills of the Tehachapi mountains at Tejon Ranch, 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 in the foothills of the Tehachapi mountains at Tejon Ranch (Lat 34.983, Long -118.716, elevation 750-930 m, www.tejonranch.com). Temperature sensors were located at 23 sites across the Tehachapi foothills. 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 N-S. 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.
A scrubbed subset of near-surface, soil, and air temperature data acquired across multiple locations in the Tehachapi mountains at Tejon Ranch, 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 in the Tehachapi mountains at Tejon Ranch (Lat 34.967, Long -118.583, elevation 1600-1700 m, www.tejonranch.com). Temperature sensors were located at 23 sites across the Tehachapi foothills. 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 N-S. 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.
Seedling emergence and biomass data of nine dryland plant species characterizing the impact of soil residual auxin herbicide across two soil types and water pulse events on greenhouse growth; Las Cruces, New Mexico, Spring 2021.
Synthetic-auxin herbicides are often used to control woody plants and aid in grassland restoration. Seed-based restoration is common alongside herbicide applications and there may be unintended effects of these herbicides on dryland plant species at the seed and seedling stages. Additionally, abiotic conditions at the time of herbicide application may influence herbicide-soil-plant interactions. We conducted a greenhouse study to examine the effects of a common shrub-control herbicide mix and its interaction with soil type and a post-herbicide water pulse on common desert plant seeds and seedlings. In this greenhouse study, we found that a subset of species responded negatively to soil residual herbicide activity of a mixture of aminopyralid, clopyralid, and triclopyr at the seed and seedling stages. Species sensitive to soil herbicide residues were primarily shrub and forb species that are often the target species of herbicide applications for woody plant control, such as Prosopis glandulosa (honey mesquite) and Larrea tridentata (creosote bush). However, two shrub species (Atriplex canescens [four-wing saltbush] and Yucca elata [soaptree yucca]) and one perennial grass species (Digitaria californica [Arizona cottontop]), which are used in dryland restoration projects, were found to be particularly sensitive to soil residual herbicide activity. Thus, if using these herbicides to control woody plants and restore herbaceous vegetation via active seeding or relying on the in situ seed bank, considerations should be given to what species are used in the seed mix, what species are already present in the soil seed bank, and other details of the circumstances of herbicide application.
The Jefferson Project 2021 hydrologic, water quality, and soil quality data from 12 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, hydrology, and water quality. More information about The Jefferson Project is available at https://jeffersonproject.rpi.edu/ In 2021, The Jefferson Project had twelve 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_English, TS_Sunset, TS_Sucker, TS_ShelvingRock, TS_East, and TS_West. The stations have a sensor payload that may include some or all of the following sensors: YSI EXO2 Multi-parameter sonde, Campbell Scientific CS451 pressure transducer, SonTek-IQ+ multi-beam acoustic flow meter, Sontek-SL Doppler current meter, YSI 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 are transferred in near real-time to off-site databases for monitoring and review by Jefferson Project researchers. The data provided here are level 4 data which underwent data correction and downsampling to an hourly frequency.
Understory percent cover, plant traits, canopy LAI, PAR, temperature, and soil moisture data at multiple time points for sites in the burn chronosequence and Indian Point forest at the University of Michigan Biological Station, Pellston, MI (2022-2023)
Community ecology has sought to understand the mechanisms by which plant communities are assembled through time and space. One prominent way to address how communities are assembled is by quantifying functional traits. While there is a tremendous body of literature on functional traits, debate persists about how to account for variation in measured traits. For example, intraspecific trait variation (ITV) can be equal to or greater than interspecific trait variation and ITV has also been found to vary greatly across years. Therefore, there is a need to account for variability in functional trait measures among and within species and through time to improve our understanding of community assembly. Chronosequences are a powerful tool to address temporal changes in community dynamics, however, the inclusion of understory plants in forest chronosequence studies is still relatively uncommon. Previous chronosequence studies have been primarily performed in grasslands or in a limited subset of forest types, so further work is needed in understory plant traits across other ecosystems and climates to improve trait-based understanding of understory plant communities through time. Additionally, because plant traits change as ecosystems age, community interactions are likely to change with ecosystem age. Interactions of particular interest are herbivory, arthropod predation, and the influence of plant traits on arthropod diversity.
Soil moisture, soil temperature, air temperature, stream water temperature, stream stage and discharge data from Soil Moisture Station 01, Highlands Biological Station, Highlands, NC, USA, 2022-2025
Measurements of soil moisture, soil temperature, air temperature, stream temperatue, and stream stage/discharge were collected as part of a long-term monitoring project at the Highlands Biological Station, Western Carolina University, Highlands, North Carolina. The sensor station is located in an acidic cove forest (high elevation subtype) dominated by an understory of Rhododendron maximum and an overstory of Betula alleghanensis and formerly Tsuga canadensis, the latter of which has mostly succombed to the Hemlock Woolly Adelgid.
Daily Summary of Soil moisture, soil temperature, air temperature, stream water temperature, stream stage and discharge data from Soil Moisture Station 01, Highlands Biological Station, Highlands, NC
Measurements of soil moisture, soil temperature, air temperature, stream temperatue, and stream stage/discharge were collected as part of a long-term monitoring project at the Highlands Biological Station, Western Carolina University, Highlands, North Carolina. The sensor station is located in an acidic cove forest (high elevation subtype) dominated by an understory of Rhododendron maximum and an overstory of Betula alleghanensis and formerly Tsuga canadensis, the latter of which has mostly succombed to the Hemlock Woolly Adelgid.
Soil moisture, soil temperature, air temperature, stream water temperature, stream stage and discharge data from Soil Moisture Station 02, Highlands Biological Station, Highlands, NC, 2021-2025
Measurements of soil moisture, soil temperature, air temperature, stream temperatue, and stream stage/discharge were collected as part of a long-term monitoring project at the Highlands Biological Station, Western Carolina University, Highlands, North Carolina. The sensor station is located in a remnant old-growth Canada Hemlock Forest (typic subtype) community dominated by an understory of Rhododendron maximum and an overstory of Tsuga canadensis, the majority of which are still alive and have been treated with systemic insecticides to protect against infestations of the Hemlock Woolly Adelgid. Other trees include Betula alleghanensis, Acer rubrum, and Quercus rubra. The pressure transducer is located in the thalweg of Coker Creek, a second order stream that flows into Lindenwood Lake.
Daily Summary of Soil moisture, soil temperature, air temperature, stream water temperature, stream stage and discharge data from Soil Moisture Station 02, Highlands Biological Station, Highlands, NC, 2021-2025
Measurements of soil moisture, soil temperature, air temperature, stream temperatue, and stream stage/discharge were collected as part of a long-term monitoring project at the Highlands Biological Station, Western Carolina University, Highlands, North Carolina. The sensor station is located in a remnant old-growth Canada Hemlock Forest (typic subtype) community dominated by an understory of Rhododendron maximum and an overstory of Tsuga canadensis, the majority of which are still alive and have been treated with systemic insecticides to protect against infestations of the Hemlock Woolly Adelgid. Other trees include Betula alleghanensis, Acer rubrum, and Quercus rubra. The pressure transducer is located in the thalweg of Coker Creek, a second order stream that flows into Lindenwood Lake.
Soil moisture, soil temperature, air temperature, stream water temperature, stream stage and discharge data from Soil Moisture Station 03, Highlands Biological Station, Highlands, NC, 2021-2025
Measurements of soil moisture, soil temperature, air temperature, stream temperatue, and stream stage/discharge were collected as part of a long-term monitoring project at the Highlands Biological Station, Western Carolina University, Highlands, North Carolina. The sensor station is located in an acidic cove forest (high elevation subtype) dominated by an understory of Rhododendron maximum and an overstory of Liriodendron tulipifera, Betula alleghanensis, and Tsuga canadensis, the latter of which has several trees that have succombed to the Hemlock Woolly Adelgid, though living trees have been treated with a systemic insecticide. The pressure transducer is located in a second order stream known as Station Branch.
Daily Summary of Soil moisture, soil temperature, air temperature, stream water temperature, stream stage and discharge data from Soil Moisture Station 03, Highlands Biological Station, Highlands, NC, 2021-2025
Measurements of soil moisture, soil temperature, air temperature, stream temperatue, and stream stage/discharge were collected as part of a long-term monitoring project at the Highlands Biological Station, Western Carolina University, Highlands, North Carolina. The sensor station is located in an acidic cove forest (high elevation subtype) dominated by an understory of Rhododendron maximum and an overstory of Liriodendron tulipifera, Betula alleghanensis, and Tsuga canadensis, the latter of which has several trees that have succombed to the Hemlock Woolly Adelgid, though living trees have been treated with a systemic insecticide. The pressure transducer is located in a second order stream known as Station Branch.
The Jefferson Project 2022 hydrologic, water quality, and soil quality data from 11 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, hydrology, and water quality. More information about The Jefferson Project is available at https://jeffersonproject.rpi.edu/ In 2022, The Jefferson Project had eleven 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_English, TS_Sunset, TS_ShelvingRock, TS_East, and TS_West. The stations have a sensor payload that may include some or all of the following sensors: YSI EXO2 Multi-parameter sonde, Campbell Scientific CS451 pressure transducer, SonTek-IQ+ multi-beam acoustic flow meter, Sontek-SL Doppler current meter, YSI 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 are transferred in near real-time to off-site databases for monitoring and review by Jefferson Project researchers. The data provided here are level 4 data which underwent data correction and downsampling to an hourly frequency.
Gross methane production and consumption estimated for intact soil cores from agricultural plots including environmental covariates and example raw isotope pool dilution data
This study was performed to determine how different soil moistures, soil sources, and agricultural practices affected the gross CH4 fluxes (i.e., rates of methanogenesis) of soils. We extracted intact soil cores from two agricultural sites in the USA in row crop plots under conventional, no-till, and organic management. We then took them to the lab, manipulated their moisture levels, incubated them at room temperature for 22 weeks, and measured gas fluxes at weeks 6 and 21. We developed and utilized a new form of CH4 isotope pool dilution (IPD) to estimate gross CH4 production and consumption fluxes. This new method can measure IPD in a bag headspace that loses volume over time due to sampling. We fit the IPD model to the data and extracted gross CH4 production (P) and consumption (K) constants. These along with calculated fluxes and covariates measured (e.g., moisture, inorganic N) are reported in the main data table.
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Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.