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Initial Sample of HYPERNETS Hyperspectral Water Reflectance Measurements for Satellite Validation at the mouth of the Gironde Estuary, MAFR site (France)
<p>The HYPERNETS project (www.hypernets.eu) has the overall aim to ensure that high quality in situ measurements are available to support the (VNIR/SWIR) optical Copernicus products. Therefore, it established a new autonomous hyperspectral spectroradiometer (HYPSTAR® - www.hypstar.eu) dedicated to land and water surface reflectance validation with instrument pointing capabilities. In the prototype phase, the instrument is being deployed at 24 sites covering a range of water and land types and a range of climatic and logistic conditions. This dataset provides the first published data for the HYPERNETS site at the Gironde Estuary, MAGEST Network, in France (MAFR). It is a subset of the complete data record which consists of the best quality MAFR measurements which could be used for satellite validation. </p> <p>The provided NetCDF files are the L2A hypernets products with water leaving radiance and reflectances without NIR Similarity Correction (see Ruddick et al., 2006, DOI:<a href="http://dx.doi.org/10.2307/3841124">10.2307/3841124</a>). The reflectance in the L2A products is the Water Reflectance without NIR Similarity Correction (referred to as reflectance_nosc in the file) defined as:</p> <p><span class="math-tex"><em>ρ</em><em>w</em><em>n</em><em>o</em><em>s</em><em>c</em>=<em>π</em>(<em>L</em><em>u</em>−<em>ρ</em><em>F</em><em>L</em><em>d</em>)/<em>E</em><em>d</em></span></p> <p>where Lu is the upwelling radiance (at 40° zenith angle, and, 90° or 135° azimuth angle relative to the sun), Ld is the downwelling radiance (at 140° zenith angle, and, 90° or 135° azimuth angle relative to the sun). Ed is the (hemispherical) downwelling irradiance (i.e. including both direct solar and diffuse sky irradiance).</p> <p>These reflectances have dimensions of wavelength and series, where each series is a set of measurements for the computation of a water reflectance measurement. In addition to variables for wavelength and bandwidth, the files also contain variables that provide for each series the acquisition time, viewing and solar angles, and quality flags (typically no flags are set in the data provided in this dataset). These NetCDF files also contain further relevant metadata as attributes. See https://hypernets-processor.readthedocs.io/ for further info.</p> <p>The HYPSTAR®-SR (Standard Range) instruments deployed at each land HYPERNETS site consist of a VNIR sensor and autonomously collect data between 380-1000 nm at various viewing geometries and send it to a central server for quality control and processing. The VNIR sensor spans 1330 channels between 380 and 1000 nm with a FWHM of 3 nm. The hypernets_processor (Goyens et al. 2021, DOI: <a href="https://doi.org/10.1109/IGARSS47720.2021.9553738">10.1109/IGARSS47720.2021.9553738</a>; De Vis et al. in prep.) automatically processes all this data into various products, including the L2A surface reflectance product provided here. The current dataset is limited to the 400-900 nm range. Uncertainties are not yet included.</p> <p>To obtain this dataset, we start from the full MAFR data record and omit all the data that do not pass all of the quality checks performed as part of the hypernets_processor. In addition, an additional screening procedure was developed to supply the best quality data suitable for satellite validation:</p> <p>1. The coefficient of variation in water reflectance is below 10% in the 600-700 nm range</p>
Initial Sample of HYPERNETS Hyperspectral Surface Reflectance Measurements for Satellite Validation from the IFEVA site in Argentina
<p>The HYPERNETS project (www.hypernets.eu) has the overall aim to ensure that high quality in situ measurements are available to support the (VNIR/SWIR) optical Copernicus products. Therefore, it established a new autonomous hyperspectral spectroradiometer (HYPSTAR® - www.hypstar.eu) dedicated to land and water surface reflectance validation with instrument pointing capabilities. In the prototype phase, the instrument is being deployed at 24 sites covering a range of water and land types and a range of climatic and logistic conditions. This dataset provides the first published data for the HYPERNETS site at IFEVA in Buenos Aires Argentina (IFAR). It is a subset of the complete data record which consists of the best quality IFAR measurements which could be used for satellite validation. </p> <p>The provided NetCDF files are the L2A hypernets products with surface reflectances, their associated uncertainties and error-correlation information. The reflectance in the L2A products is the Hemispherical-directional Reflectance Factor (HDRF) defined as: HDRF = π L / E where L is the directional upwelling radiance (with field of view of 5 degrees) and E is the (hemispherical) downwelling irradiance (i.e. including both direct solar and diffuse sky irradiance). These reflectances have dimensions of wavelength and series, where each series is a set of measurements for a given geometry (combination of viewing zenith and azimuth angle). In addition to variables for wavelength and bandwidth, the files also contain variables that provide for each series the acquisition time, viewing and solar angles, number of valid scans used, and quality flags (typically no flags are set in the data provided in this dataset). These NetCDF files also contain further relevant metadata as attributes. See https://hypernets-processor.readthedocs.io/ for further info.</p> <p>The IFAR site is a temporary test site located in the Agronomy Faculty campus in Buenos Aires city, Argentina (34.592322°S, 58.479017°W). The venue is managed by the IFEVA (Agricultural Physiology and Ecology Research Institute) and characterized by natural pastures with different treatments distributed in 16 patches of 7mx7m. The HYPSTAR®-XR sensor has been deployed in June 2021 at the top of a 2.4 m high tripod that is pointing to one of the patches where the vegetation has no specific treatment (natural) and is cut regularly every year in February. Data is collected every 30 min between 14:00 and 18:00 hs UTC (11:00 to 15:00 local time).</p> <p>The HYPSTAR®-XR (eXtended Range) instruments deployed at each land HYPERNETS site consist of a VNIR and a SWIR sensor and autonomously collect data between 380-1700 nm at various viewing geometries and send it to a central server for quality control and processing. The VNIR sensor spans 1330 channels between 380 and 1000 nm with a FWHM of 3 nm and the SWIR sensor has 220 channels between 1000 and 1700 nm with a FWHM of 10 nm. The hypernets_processor (Goyens et al. 2021; De Vis et al. in prep.) automatically processes all this data into various products, including the L2A surface reflectance product provided here. All of the products have associated uncertainties (divided into random and systematic uncertainties, including error-correlation information) which were propagated using the CoMet toolkit (www.comet-toolkit.org). </p> <p>To obtain this dataset, we start from the full IFAR data record and omit all the data that do not pass all of the quality checks performed as part of the hypernets_processor. In addition, an additional screening procedure was developed to remove outliers and only supply the best quality data suitable for satellite validation. To remove the outliers, a sigma-clipping method is used. First reflectances are extracted in separate 2 hour windows throughout the day (to account for BRDF differences due to different solar position) for 4 different wavelengths (500, 900, 1100 and 1600 nm). Outliers in these reflectances are then identified by iteratively calculating the mean reflectance trend with time (by binning the data per maximum 30 data points), calculating the standard deviation from this trend, and masking any data that is more than 3 standard deviations away from the trend. This process is repeated on the unmasked data until the standard deviation does not vary by more than 5% between two iterations. The masks for the 4 different wavelengths are then combined (keeping only measurements for which none of the 4 wavelengths is an outlier). The reflectances and associated uncertainties for any masked series (i.e. a geometry that is masked either by the sigma-clipping procedure or from the masks of the hypernets_processor) are replaced by NaNs. Any sequence that has more than half of its series masked is removed entirely. </p>
Initial Sample of HYPERNETS Hyperspectral Water Reflectance Measurements for Satellite Validation at the measurement tower MOW1, M1BE site (Belgium)
<p>The HYPERNETS project (www.hypernets.eu) has the overall aim to ensure that high quality in situ measurements are available to support the (VNIR/SWIR) optical Copernicus products. Therefore, it established a new autonomous hyperspectral spectroradiometer (HYPSTAR® - www.hypstar.eu) dedicated to land and water surface reflectance validation with instrument pointing capabilities. In the prototype phase, the instrument is being deployed at 24 sites covering a range of water and land types and a range of climatic and logistic conditions. This dataset provides the first published data for the HYPERNETS site at the measurement pole near the <em>Zeebrugge</em> harbour 3.65km from land, often called MOW1, in Belgium (M1BE). It is a subset of the complete data record which consists of the best quality M1BE measurements which could be used for satellite validation. </p> <p>The provided NetCDF files are the L2A hypernets products with water leaving radiance and reflectances, with and without NIR Similarity Correction (see Ruddick et al., 2006, DOI:<a href="http://dx.doi.org/10.2307/3841124">10.2307/3841124</a>). The reflectance in the L2A products is the Water Reflectance without NIR Similarity Correction (referred to as reflectance_nosc in the file) defined as:</p> <p><span class="math-tex">\(\rho_wnosc=\pi (Lu-\rho_FLd)/E_d\)</span></p> <p>where Lu is the upwelling radiance (at 40° zenith angle, and, 90° or 135° azimuth angle relative to the sun), Ld is the downwelling radiance (at 140° zenith angle, and, 90° or 135° azimuth angle relative to the sun). Ed is the (hemispherical) downwelling irradiance (i.e. including both direct solar and diffuse sky irradiance).</p> <p>For the M1BE site, the reflectance corrected for the NIR Similarity correction (epsilon, see Ruddick et al., 2006) is also provided:</p> <p><span class="math-tex">\(\rho_w=\pi (Lu-\rho_FLd)/E_d-\epsilon\)</span></p> <p>These reflectances have dimensions of wavelength and series, where each series is a set of measurements for the computation of a water reflectance measurement. In addition to variables for wavelength and bandwidth, the files also contain variables that provide for each series the acquisition time, viewing and solar angles, and quality flags (typically no flags are set in the data provided in this dataset). These NetCDF files also contain further relevant metadata as attributes. See https://hypernets-processor.readthedocs.io/ for further info.</p> <p>The HYPSTAR®-SR (Standard Range) instruments deployed at each land HYPERNETS site consist of a VNIR sensor and autonomously collect data between 380-1000 nm at various viewing geometries and send it to a central server for quality control and processing. The VNIR sensor spans 1330 channels between 380 and 1000 nm with a FWHM of 3 nm. The hypernets_processor (Goyens et al. 2021, DOI: <a href="https://doi.org/10.1109/IGARSS47720.2021.9553738">10.1109/IGARSS47720.2021.9553738</a>; De Vis et al. in prep.) automatically processes all this data into various products, including the L2A surface reflectance product provided here. The current dataset is limited to the 400-900 nm range. Uncertainties are not yet included.</p> <p>To obtain this dataset, we start from the full M1BE data record and omit all the data that do not pass all of the quality checks performed as part of the hypernets_processor. In addition, an additional screening procedure was developed to supply the best quality data suitable for satellite validation:</p> <p>1. The coefficient of variation in water reflectance is below 10% in the 500-600 nm range</p> <p>2. The water reflectance at 500 nm is below 0.1</p> <p>The data consists of 73 spectra ranging from 20230226T1431 till 20230429T1502.</p> <p>Coordinates of the site are the following:</p> <p>site_latitude = 51.360548<br> site_longitude = 3.118246</p> <p>The site is owned by Afdeling Kust (https://www.agentschapmdk.be/nl).</p> <p> </p>
Initial Sample of HYPERNETS Hyperspectral Surface Reflectance Measurements for Satellite Validation from the Wytham Woods site in the United Kingdom
<p>The HYPERNETS project (www.hypernets.eu) has the overall aim to ensure that high quality in situ measurements are available to support the (VNIR/SWIR) optical Copernicus products. Therefore, it established a new autonomous hyperspectral spectroradiometer (HYPSTAR® - www.hypstar.eu) dedicated to land and water surface reflectance validation with instrument pointing capabilities. In the prototype phase, the instrument is being deployed at 24 sites covering a range of water and land types and a range of climatic and logistic conditions. This dataset provides the first published data for the Wytham Woods HYPERNETS site in the United Kingdom (WWUK). It is a subset of the complete data record which consists of the best quality WWUK measurements which could be used for satellite validation. </p> <p>The provided NetCDF files are the L2A hypernets products with surface reflectances, their associated uncertainties and error-correlation information. The reflectance in the L2A products is the Hemispherical-directional Reflectance Factor (HDRF) defined as: HDRF = π L / E where L is the directional upwelling radiance (with field of view of 5 degrees) and E is the (hemispherical) downwelling irradiance (i.e. including both direct solar and diffuse sky irradiance). These reflectances have dimensions of wavelength and series, where each series is a set of measurements for a given geometry (combination of viewing zenith and azimuth angle). In addition to variables for wavelength and bandwidth, the files also contain variables that provide for each series the acquisition time, viewing and solar angles, number of valid scans used, and quality flags (typically no flags are set in the data provided in this dataset). These NetCDF files also contain further relevant metadata as attributes. See https://hypernets-processor.readthedocs.io/ for further info.</p> <p>The WWUK site is a deciduous broadleaf forest comprised primarily of Oak, Hazel, Ash, Sycamore and Beech. It is located approximately 5 km North-West of Oxford, UK and has an extensive history of scientific research. The site follows the typical seasonal dynamics of a temperate forest with distinctive periods of leaf-off, green up and senescence across the growing season. The HYPERNETS site itself (51.777206 degrees N, 1.338494 W), is located at a height of 28 m upon a flux tower in the centre of the forest. The HYPSTAR®-XR sensor was installed in October 2021. Data are collected e very 30 minutes between 9am and 6pm local time between viewing zenith angles of 0 and 30 degrees.</p> <p>The HYPSTAR®-XR (eXtended Range) instruments deployed at each land HYPERNETS site consist of a VNIR and a SWIR sensor and autonomously collect data between 380-1700 nm at various viewing geometries and send it to a central server for quality control and processing. The VNIR sensor spans 1330 channels between 380 and 1000 nm with a FWHM of 3 nm and the SWIR sensor has 220 channels between 1000 and 1700 nm with a FWHM of 10 nm. The hypernets_processor (Goyens et al. 2021; De Vis et al. in prep.) automatically processes all this data into various products, including the L2A surface reflectance product provided here. All of the products have associated uncertainties (divided into random and systematic uncertainties, including error-correlation information) which were propagated using the CoMet toolkit (www.comet-toolkit.org). </p> <p>To obtain this dataset, we start from the full WWUK data record and omit all the data that do not pass all of the quality checks performed as part of the hypernets_processor. In addition, two additional screening procedures are developed to remove outliers and only supply the best quality data suitable for satellite validation. For Wytham wood, sequences are only supplied that match a typical vegetation spectrum. As such, data is only provided between April and October during the leaf-on period. Reflectances are then tested against three parameters to check that they are vegetation spectrum. Firstly, that there is a peak in the green portion of the visible wavebands (560 nm). Secondly, that a red edge is detected. Finally, the Normalized Difference Vegetation Index (NDVI) is calculated. Spectra with an NDVI of less than 0.42 are removed from the final data set.</p> <p>After the vegetation quality flag are applied, a sigma-clipping method is used to remove outliers. First reflectances are extracted in separate 2 hour windows throughout the day (to account for BRDF differences due to different solar position) for 4 different wavelengths (500, 900, 1100 and 1600 nm). Outliers in these reflectances are then identified by iteratively calculating the mean reflectance trend with time (by binning the data per maximum 30 data points), calculating the standard deviation from this trend, and masking any data that is more than 3 standard deviations away from the trend. This process is repeated on the unmasked data until the standard deviation does not vary by more than 5% between two iterations. The masks for the 4 different wavelengths are then combined (keeping only measurements for which none of the 4 wavelengths is an outlier). The reflectances and associated uncertainties for any masked series (i.e. a geometry that is masked either by the sigma-clipping procedure or from the masks of the hypernets_processor) are replaced by NaNs. Any sequence that has more than half of its series masked is removed entirely. </p>
Sound samples for the evaluation of source-level blending between violins
<p>The repository includes monophonically rendered sound files used in the source-level blending evaluation. The sound samples provided are recorded from a violin ensemble performance at Detmold Concert House as a part of an investigation on the influence of acoustic environment on the impression of blending [1]. DPA 4099 clip-on microphones were used to capture individual violins in the performance.</p> <p>Each sound sample consists of two violin signals that were rendered by downmixing to a monophonic format at 44.1kHz/16-bit depth. The impression of blending between the two violins in each sample was rated by a group of trained listeners, and the results are provided in the file, 'Sound sample_description'. Please refer to the publication for more details on the performance of the violin ensemble. Also, please cite the publication if these samples are used for scientific evaluations.</p> <p>In addition to the sound samples, three Matlab figures that demonstrate the cluster distribution of MFCC features extracted from sound samples (that are classified into blended and non-blended classes) transformed using Principal component Analysis (PCA), Linear Discriminant Analysis (LDA), and t-Stochastic Neighbourhood Embedding (t-SNE), are included for 3D visualization. This corresponds to Figure 9 in [2].</p> <p> </p> <p> [1] Jithin Thilakan and Malte Kob, “Evaluation of subjective impression of instrument blending in a string ensemble”, Fortschritte der Akustik - DAGA 2021 in Wien, pp. 524-527.</p> <p>[2] Jithin Thilakan, Balamurali BT, Jer-Ming Chen, Malte Kob, “Classification of the perceptual impression of source-level blending between violins in a joint performance”, currently under review at Acta Acustica.</p>
Water chemistry data from synoptic sampling of 235 Lake Michigan tributaries: 10-15 July, 2018
This dataset includes nutrient (total nitrogen and phosphorus, soluble reactive phosphorus, and dissolved inorganic nitrogen [nitrate+nitrite+ammonium]) and chloride concentrations for 235 tributaries of Lake Michigan collected during a synoptic sampling event from 10-15 July, 2018. The dataset also includes modeled discharge metrics for the 235 sampled watersheds, as well as spatial watershed characteristics.
Flume Erosion Testing of Unamended and Organic Matter Amended Soil Samples Using an Acoustic Doppler Profiler, 2021
This data accompanies a publication titled "Soil Amended with Organic Matter Increases Fluvial Erosion Resistance of Cohesive Streambank Soil". Briefly, fluvial erosion testing was conducted on soil samples using an indoor flume channel. Soil samples were previously collected from the riparian zone of a river near Virginia Tech's campus in Blacksburg, VA, USA. The soil was subsequently air-dried and stored until use. Prior to erosion testing, soil samples were amended with varying amounts of organic matter (0%, 1%, and 4% OM by mass), compacted to a bulk density of 0.95 KilogramsPerCubicCentiMeters in growth containers, and allowed to mature in a greenhouse setting for 50 days prior to flume erosion testing. An Acoustic Doppler Profiler (ADP) was used to measure soil erosion and collect three-dimensional velocity data during erosion tests; raw velocity and soil depth data for each sample tested were stored in MATLAB files. Follow testing, the soil remaining from each sample was collected, stored, and analyzed for aggregate stability, soil organic matter (SOM), and extracellular polymeric substances (EPS). Additionally, soil temperature, water temperature, and volumetric water content were also measured prior to or during erosion testing. Data collected from this study, and the accompanying ADP MATLAB files, are presented here.
Palmyra Atoll soil and/or wood density sampling locations used in the carbon storage analysis
This dataset provided soil and/or wood density sampling locations and values from Palmyra Atoll (2016 and 2019). Soil samples were extracted to measure organic carbon content associated with different vegetation communities in Palmyra. Wood samples were collected to measure basic wood density values for dominant woody vegetation types found in Palmyra to calculate aboveground carbon values.
Lignin, litter, and soil carbon decomposition from soil samples collected from 20 National Ecological Observatory Network (NEON) sites in 2019
These data support the findings of a manuscript by Huang et al. (2023) published in Nature Communications (doi pending). We used incubations of soil and stable isotope measurements to measure lignin, litter, and SOC decomposition over an 18-month lab incubation and assessed their relationships with geochemical, microbial, N-related and climatic factors across 156 mineral soils collected from 20 National Ecological Observatory Network (NEON) sites, which span broad biophysical gradients (climate, soil, and vegetation type) across North America. The soils were collected in 2019. Lignin decomposition and biogeochemical variables were also measured in an approximately 12-month field incubation.
Lake Tahoe Nutrients data for discrete water samples
Lake water nutrient data measured on discrete water samples from Lake Tahoe, CA/NV. There are two sampling stations Index (LTP, 39.0972 -120.155) and Mid-lake (MLTP, 39.1417 -120.0153). See methods for details
Lake Tahoe particle size distribution (PSD) data for discrete water samples
Particle size distribution data measured on discrete water samples from Lake Tahoe, CA/NV. There are two sampling stations Index (LTP, 39.0972 -120.155) and Mid-lake (MLTP, 39.1417 -120.0153). See methods for details
Lake Tahoe Chlorophyll a concentration for discrete water sample
Chlorophyll a concentrations for discrete water samples taken at Lake Tahoe, CA/NV. There are two sampling stations Index (LTP, 39.0972 -120.155) and Mid-lake (MLTP, 39.1417 -120.0153). See methods for details
Understory plant community data from repeated plot sampling (1978-2019) in old-growth northern hardwood forest, northern Michigan (Dukes RNA, Hiawatha National Forest)
This data-set includes long-term, permanent-plot-based data for understory plant communities in old-growth mixed northern hardwood-hemlock forest and forested peatland in the Upper Great Lakes region. Data for over 900 understory quadrats (all associated with long-term canopy data from larger permanent plots) included multiple (2-5) remeasurements over 23-40 years, with longest periods and most remeasurements for upland forest types. The Dukes Research Natural Area (RNA) (https://www.fs.usda.gov/research/nrs/rnas/locations/dukes) in the Hiawatha National Forest (Marquette Co., MI) includes ca. 100 ha of largely unlogged, original forest. Publications cited below include more detailed information about the site. About half of the RNA supports upland forests intergrading from hemlock (Tsuga candensis) dominance to mixtures of hemlock and northern hardwoods species. Sugar maple (Acer saccharum) is dominant over much of the upland area, with, locally, significant admixtures of beech (Fagus grandifolia), yellow birch (Betula alleghaniensis), and red maple (Acer rubrum). Topographic relief is very slight with total elevational change within the RNA only about 10 m. The stand is within a few km of the western limit of the continuous range of beech. In 1935, 248 continuing forest inventory (CFI) plots (circular, 0.2 acre) were established on a regular grid throughout the RNA, and these have been the subject of repeated sampling through 2018-2019 and support continuing long-term study addressing canopy tree communities (canopy data to be deposited in a separate project). Examples of resulting publications are cited elsewhere in metadata, and can provide more detailed information about the RNA. In 1978-80, U.S. Forest Service researchers, directed by Jan Schultz and Frederick Metzger, initiated studies of understory communities, including herbaceous species and woody seedlings. Data were derived from four sub-quadrats within each of the CFI plots. These quadrats were re-estab
Soil Sampling at the Cienega Springs Ecological Reserve, Santa Clara River Watershed, CA 2020
Soil samples were collected throughout the 283-acre Cienega Springs Ecological Reserve to plan an Arundo donax removal and restoration project. Data on soil characteristics were used to model habitat suitability and plant species selection for revegetation efforts.
Qualitative Larval Fish Sampling at the California Department of Water Resource’s State Water Project
The California Department of Water Resource’s State Water Project utilizes the John E. Skinner Delta Fish Protective Facility (Skinner Fish Facility) to salvage fishes that would otherwise become entrained during operations to divert water from the Sacramento-San Joaquin River Delta (Delta). Water is diverted from the Delta to meet California’s agricultural, municipal, industrial, and environmental needs. The Skinner Fish Facility, located in Contra Costa County and situated ahead of the Harvey O. Banks Pumping Plant, began salvaging fish in 1968 but historically, only recorded fork length measurements for fish greater than 20 millimeters. Beginning in 2009, the Skinner Fish Facility implemented qualitative larval sampling in response to the 2008 U.S. Fish and Wildlife Service Biological Opinion on the coordinated operations of the Central Valley Project (CVP) and State Water Project (SWP). This entailed collecting, retaining, and identifying larval fishes to better understand SWP impacts on Delta Smelt. Qualitative larval sampling took place annually from 2009 through 2025, during the Old and Middle River management period and based upon Delta Smelt spawning (typically mid-February to June). The California Department of Water Resources collected and processed samples from 2020 through 2025. Data from 2009 through 2019 were processed and retained by others and are not included in this dataset.
Nitrogen and carbon concentrations and stable isotope ratios (δ¹⁵N and δ¹³C) in European moss samples, 2005-2006
This dataset contains nitrogen (N) and carbon (C) concentrations and stable isotope ratios (δ¹⁵N and δ¹³C) measured in moss samples collected across Europe within the framework of the ICP Vegetation programme (International Cooperative Programme on Effects of Air Pollution on Natural Vegetation and Crops, UNECE LRTAP Convention). Moss surveys are conducted every five years and the data presented here correspond specifically to the first sampling campaign, carried out in 2005/2006. During the 2005/2006 European moss survey, approximately 3,000 moss samples were collected at non-urban and semi-natural sites across 16 European countries following a standardized biomonitoring protocol. The dataset used in this study comprises a subset of 1,022 moss samples (approximately 35 % of the total survey), provided by 12 European countries, which were selected for the determination of nitrogen and carbon concentrations and their corresponding stable isotope signatures (δ¹⁵N and δ¹³C). Moss samples collected by each participating country were sent to the Integrated Environmental Quality Laboratory (LICA), Institute for Biodiversity and Environment (BIOMA - University of Navarra), where all chemical and isotopic analyses were subsequently performed under uniform analytical conditions. In addition, this dataset incorporates moss data from Sweden, Croatia and Macedonia for the same sampling year, which were not included in the official ICP Vegetation 2005/2006 dataset. The European moss biomonitoring network was established to provide a complementary, high spatial resolution and time-integrated measure of atmospheric deposition of nitrogen and other pollutants within terrestrial ecosystems. The approach is based on the ability of ectohydric mosses to accumulate nutrients and trace elements directly from wet and dry atmospheric deposition, enabling dense spatial sampling across large geographical areas. This biomonitoring framework supports the assessment of spatial patterns of atmos
CBP01 Variable distance line-transect sampling of bird population numbers in different habitats on Konza Prairie (Reformatted to the ecocomDP Design Pattern)
This data package is formatted as an ecocomDP (Ecological Community Data Pattern). For more information on ecocomDP see https://github.com/EDIorg/ecocomDP. This Level 1 data package was derived from the Level 0 data package found here: https://pasta.lternet.edu/package/metadata/eml/knb-lter-knz/26/11. The abstract below was extracted from the Level 0 data package and is included for context: Records of bird species based on line transect sampling, giving perpendicular distance of sighting from the transect line on 16 separate transects. Bird surveys were conducted 2-4 times per year in January, April, June, and October for a 29-year period from 1981 to 2009. Transects were designed to determine bird communities and population numbers associated with tallgrass prairie habitats with different experimental treatments (fire frequency, grazed by bison vs. ungrazed), riparian habitats on forest edge, and gallery forests dominated by oak woodland.
Plot-level field data and model simulation results, archived to accompany Turner et al. manuscript; reports data from summer 2017 sampling of short-interval fires that burned during summer 2016 in Greater Yellowstone.
Subalpine forests in the northern Rocky Mountains have been resilient to stand-replacing fires that historically burned at 100–300-yr intervals. Fire intervals are projected to decline drastically as climate warms, and forests that reburn before recovering from previous fire may lose their ability to rebound. We studied recent fires in Greater Yellowstone (Wyoming, USA) and asked whether short-interval (less than 30 yrs) stand-replacing fires can erode lodgepole pine (Pinus contorta var. latifolia) forest resilience via increased burn severity, reduced early postfire tree regeneration, reduced carbon stocks, and slower carbon recovery. During 2016, fires reburned young lodgepole pine forests that regenerated after wildfires in 1988 and 2000. During 2017, we sampled 0.25-ha plots in stand-replacing reburns (n=18) and nearby young forests that did not reburn (n=9). We also simulated stand development with and without reburns to assess carbon recovery trajectories. Nearly all prefire biomass was combusted ("crown fire plus") in some reburns in which prefire trees were dense and small (≤ 4 cm basal diameter). Postfire tree seedling density was reduced six-fold relative to the previous (long-interval) fire, and high-density stands (greater than 40,000 stems ha-1) were converted to sparse stands (less than 1,000 stems ha-1). In reburns, coarse wood biomass and aboveground carbon stocks were reduced by 65% and 62%, respectively, relative to areas that did not reburn. Increased carbon loss plus sparse tree regeneration delayed simulated carbon recovery by greater than 150 yrs. Forests did not transition to nonforest, but extreme burn severity and reduced tree recovery foreshadow an erosion of forest resilience.
Sampling sites where ecological indices were used to assess the impact of different environmental stressors in aquatic environments in Argentina
Dataset is a compilation of all sampling sites of articles where ecological indices were used to assess the impact of different environmental stressors in aquatic environments from Argentina. Points of this dataset were extracted from 78 papers published between 1996 and 2018. We selected articles that use ecological indices to analyze some local environmental problematics or stressors. Using the type of index from each article we performed the kml file, which contained the categorized sampling sites by different symbols according to the ecological index: physico-chemical, biological, geomorphological and multimetric. We carried out a map (shapefile) with all the sampling sites referenced to the ecoregions of Argentina proposed by Burkart (1999).
Mohonk Preserve Stream Water Quality Invasive Species and Macroinvertebrate Sampling in from 2017-Present
The mission of the Mohonk Preserve is to protect the Shawangunk Mountains region and inspire people to care for, enjoy, and explore their natural world. Among these 8,000 acres are the vernal pools, permanent springs, tributaries, Humpo Marsh, and the Humpo Kill, and parts of the Kleine Kill and Coxing Kill watersheds within the Hudson River Drainage Basin. Not only are the areas around the Shawangunks established habitats for New York State (NYS) protected species, including an Audubon-designated Important Bird Area, but the watershed also encapsulates more than one agricultural land use area, as well as Rondout Creek, which is an important waterway for the New York City water supply. A conservation plan must be implemented in these areas in particular, keeping in line with the Mohonk Preserves goal to conserve the Shawangunk region for both humans and the greater ecosystem within it. Recognizing the immediate and long-term conservation needs of the streams in this region by employing volunteer data collection will be a catalyst to the Preserves understanding of which environmental threats of this area should be prioritized. The StreamWatch citizen science program will be the newest addition to an array of volunteer research areas, which include collection of weather data, phenology observations, monitoring of peregrine falcon breeding activities, and monitoring of fall hawk migration. Using concise stream monitoring protocol designed for volunteer safety and maximum data accuracy, StreamWatch will evaluate water quality using an array of parameters. Following thorough observation and assessment (which will include analyzing appearance and smell of the water, shape of the stream, canopy cover, nearby land uses, recent weather, and presence of riparian vegetation including invasive species) water quality will be evaluated by means of temperature, dissolved oxygen, pH, and turbidity measurements, in addition to a macroinvertebrate count. Width and depth will also be
ScienceDex guides
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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
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.