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Nutrient concentrations in three small streams on the coast of the Delmarva Peninsula 2002-2009
This dataset contains dissolved nutrient measurements for three small creeks on the Atlantic side of the Delmarva Peninsula in Virginia.
Annual heron counts on Chincoteague Island, Virginia 1992-2011
This dataset has the number of breeding pairs of herons nesting on Chincoteague, VA region.This data is also available from the Center for Conservation Biology at the College of William and Mary as part of the Virginia Coastal Avian Partnership (VCAP).
End of Year Biomass in Marshes of the Virginia Coast Reserve 1999-2021
Background: Brinson et al. (1995) developed a model representing the change that occurs in ecosystem state (or habitat type) along the shorezone, from the forest -> high marsh -> low marsh -> mud flat, in response to the increased inundation caused by rising sea-level. They suggested that a seaward shift in ecosystem state is largely dependent on local slope and sediment supply. The states are associated with the dominant vegetation found within each. The most seaward (lowest in elevation) state is the mud flat. It is frequently inundated by tide and typically supports algal species. The next landward state is the mineral low marsh; it is dominated by Spartina alterniflora and is typically flooded at high tide. Sediments here may be largely mineral in origin. The next landward state is the high marsh; it may be dominated by S. patens, Distichlis spicata, and Juncus roemerianus. It is occasionally inundated by high tides and the soil is usually organic. The transition zone between the high marsh and the forest is typically dominated by Iva frutescens, Baccharis hamifolia, and Juniperus virginiana. It is only inundated during severe storm surges. The forest may be dominated by either pines or hardwoods and is again flooded with sea water only by storm surges. Goals: The goal of this long-term project is to evaluate how sea-level rise affects marsh evolution and ecosystem state change. Seventeen sites along Virginia's eastern shore have been selected to study marsh evolution on both the mainland and the barrier islands. These sites will be available for long-term seasonal to annual observations. Some sites will also be available for experimentation and short-term studies. The initial project is to establish initial site characteristics. Note, in 2017 a freezer failure caused decomposition of all unprocessed samples. For that reason, most of the data from that year does not distinguish live from dead and many of the species are unidentified. Affected samples are identif
Groundwater Levels on Hog Island, VA. 2007-2021
This dataset contains hourly measurements of groundwater levels on Hog Island, VA - off the Atlantic Coast of the Delmarva Peninsula. It continues measurements of groundwater levels that were initiated in by Frank Day in July 1990 (dataset VCR99066) and by Mark Brinson in October 1997 (dataset VCR05130). Refer to these datasets for previous measurements. The groundwater measurements use the same wells and locations, but differ in sensor technology and frequency of measurement. In August 2007, a system of wirelessly-connected data loggers designed by Thomas Williams was installed with help from Arthur Schwarzschild, Chris Buck, John Hayward and John Porter. The system was decomissioned December 31, 2021
Density of Seagrass in Virginia Coastal Bays, 2007-2021
This dataset contains measurements of seagrass shoot density in restored Z. marina meadows in the Virginia coastal bays. Measurements were made annually in June-July at plots in Hog Island Bay and South Bay, VA. GPS locations of sampling plots are available in the companion data set VCR11180.
Benthic Chlorophyll of Seagrass Sediment in Virginia Coastal Bays 2008-2021
This data set contains measurements of benthic chlorophyll content in surface sediments in restored Z. marina plots in the Virginia coastal bays. Samples were collected annually during June-July at restored seagrass plots and adjacent bare sediment plots. GPS locations of sampling plots are available in the companion data set VCR11180.
Above- and Below-Ground Biomass and Canopy Height of Seagrass in Virginia Coastal Bays 2007-2021
This data set contains measurements of above and belowground biomass and canopy height in restored Z. marina meadows in the Virginia coastal bays. Samples were collected annually in June-July. GPS locations of sampling plots are available in the companion data set VCR11180.
Organic Matter of Seagrass Sediment in Virginia Coastal Bays 2007-2021
This data set contains measurements of sediment organic matter and bulk density from plots in the restored Z. marina meadows in Hog Island Bay and South Bay, VA. Samples were collected annually in June-July. GPS locations of sampling plots are available in the companion data set VCR11180.
Sediment Carbon and Nitrogen of Seagrass Restoration in Virginia Coastal Bays 2007-2021
This data set contains measurements of sediment carbon and nitrogen content in restored Z. marina meadows in Hog Island Bay and South Bay, VA. Sediments were sampled annually in June-July. GPS locations of sampling plots are available in the companion data set VCR11180.
GPS Locations of Seagrass Sites in Hog Island Bay and South Bay, VA 2010-2021
This dataset contains the GPS coordinates for plots within the Z. marina restoration in the Hog Island Bay and South Bay, VA that are sampled annually as part of the long-term restoration experiment. Plots were seeded between 2001-2008; 64 plots in Hog Island Bay (58 seagrass plots and 6 bare plots) and 12 plots in South Bay (6 seagrass plots and 6 bare plots) were sampled beginning in 2010. The bare sites in South Bay were no longer sampled after 2013 due to colonization by seagrass. Additional sites were identified in 2017 in areas of natural seagrass expansion - 6 in Hog Island Bay and 6 in South Bay.
Species-level map of Smith Island, VA from remote sensing 2003
Species-level vegetation map for Smith Island off the tip of the Delmarva Peninsula in Virginia. Created by Charles M. Bachmann of the Naval Research Laboratory based classification of hyperspectral imagery using 3-season data (two PROBE2 scenes and a Hymap scene).
Integrated Topography and Bathymetry for the Eastern Shore of Virginia
Description This dataset integrates elevation and bathymetry data from multiple sources into a single mostly-seamless digital elevation model (DEM) that covers the entire Eastern Shore of Virginia and its surrounding coastal waters. Data sources include airborn LiDAR, VCRLTER and ODU bathymetric surveys, NOAA navigational data, NOS oceanographic surveys, USGS NED data plus contours and features from topo quad maps, and VGIN-VBMP aerial imagery. Proposed uses for the dataset include deriving detailed watershed boundaries, hypsometric curves, tidal prisms, 3-D physical models, and input for numerical hydrodynamic simulation models. The version 2.0 DEM (August 2014) is suitable for both local- and regional-scale analyses. It has a resolution matched to the LiDAR data (3.048 m. or 10 ft.), resulting in 31,152 x 46,002 cells (5.4 Gigabyte in ESRI GRID format). Users can aggregate to coarser cell resolutions as needed. The data is projected in UTM Zone 18 North coordinates relative to the WGS84 horizontal datum. All elevations are in meters relative to the NAVD88 vertical datum. Spatially modelled conversion factors between NAVD88 and local sea level datums (MSL, MLW, MHW, etc.) based on NOAA VDATUM data are available as a separate dataset (VCR13215). See "METHODS" for full details on data sources and integration methodologies.
Incentive mechanisms and the provision of public goods: Field experiment data for testing alternative economic frameworks to supply ecosystem restoration on Virginia's Eastern Shore: 2008 data.
This dataset consists of participant responses in one of two economic experiments conducted on Virginia's Eastern Shore during 2008 and 2009 by Elizabeth C. Smith used to gauge resident preferences and willingness-to-pay for ecosystem restoration activities. This dataset was designed to be used to examine a practical method to implement an individualized pricing approach to public good provision, grounded in Lindahl's marginal benefit theory. The study's focus was on ecosystem valuation and market approaches that have potential to provide public goods, examining the potential to generate revenues for public goods from consumers. While willingness-to-pay measurement techniques have been used to assess preferences for many environmental goods, this research goes a step further to explore real money auctions that generate revenues sufficient to pay for restoration activities. The data from the field experiments conducted in coastal Virginia were used, along with laboratory experiment data, to evaluate the performance of auction mechanisms in generating revenues relative to potential (Hicksian) willingness to pay for marginal increments in public goods. The field execution of this experiment involved residents of Virginia's Eastern Shore and local public goods. This application involved half-acre increments of ecosystem restoration for sea grass habitat in coastal lagoons, plantings for migratory bird habitat, and, in some auctions, clam-based increments of water quality services, defined as delaying the harvest of clams for six months beyond normal harvest by an existing aquaculture firm. To perform these tasks, participants were provided a budget, between $90 and $150. The auctioneer described for participants the ecosystem services that may result from additional ecosystem restoration associated with each activity. The actual levels of ecosystem restoration provided were based on aggregate offers reaching a pre-determined (but unknown to the participants) provision p
Incentive mechanisms and the provision of public goods: Field experiment data for testing alternative economic frameworks to supply ecosystem restoration on Virginia's Eastern Shore: 2009 data.
This dataset consists of participant responses in one of two economic experiments conducted on Virginia's Eastern Shore during 2008 and 2009 by Elizabeth C. Smith used to gauge resident preferences and willingness-to-pay for ecosystem restoration activities. This dataset was designed to be used to examine a practical method to implement an individualized pricing approach to public good provision, grounded in Lindahl's marginal benefit theory. The study's focus was on ecosystem valuation and market approaches that have potential to provide public goods, examining the potential to generate revenues for public goods from consumers. While willingness-to-pay measurement techniques have been used to assess preferences for many environmental goods, this research goes a step further to explore real money auctions that generate revenues sufficient to pay for restoration activities. The data from the field experiments conducted in coastal Virginia were used, along with laboratory experiment data, to evaluate the performance of auction mechanisms in generating revenues relative to potential (Hicksian) willingness to pay for marginal increments in public goods. The field execution of this experiment involved residents of Virginia's Eastern Shore and local public goods. This application involved half-acre increments of ecosystem restoration for sea grass habitat in coastal lagoons, plantings for migratory bird habitat, and, in some auctions, clam-based increments of water quality services, defined as delaying the harvest of clams for six months beyond normal harvest by an existing aquaculture firm. To perform these tasks, participants were provided a budget, between $90 and $150. The auctioneer described for participants the ecosystem services that may result from additional ecosystem restoration associated with each activity. The actual levels of ecosystem restoration provided were based on aggregate offers reaching a pre-determined (but unknown to the participants) provision p
Water Quality Sampling - integrated measurements for the Virginia Coast, 1992-2025
This dataset contains information about the aquatic environment along two transects that run from inlet to the mainland shore on the southern part of the Delmarva Peninsula since 1992. It has a large number of columns (111) that integrate information on water column and benthic measurements. Frequency of sampling varies from monthly to quarterly, and not all variables are necessarily measured on the same dates. However, all the data from a given date and location appears on a single line of the dataset.
Hourly Meteorological Data for the Virginia Coast Reserve LTER 1989-present
Data from VCR/LTER meteorological stations is listed in comma-separated-value (CSV) files by year. A combined file for all years is also available, sorted by station, date and time, however, unlike the annual files, this combined file is too large for most spreadsheets to handle. A compressed copy of all the .CSV files is included in a single .ZIP file for users who wish to conveniently download a copy of all the data.
Wave and turbidity measurements, Fowling Point, Hog Island Bay, VA, Summer 2017
Time series of turbidity, water surface elevation, wave height and period, and water temperature were measured at sites along a bay-to-marsh transect along the east-facing margin of Fowling Point, Hog Island Bay, VA in summer 2017. The measurements were made to characterize suspended sediment concentrations in the water inundating Fowling Point marsh during high tides and storms, as a proxy for the availability of sediment for wetland accretion. The time series includes a spring-neap cycle and a wind-driven resuspension event. The measurements were made to support marsh depositional modeling being carried out as part of an NSF-sponsored Coastal SEES research project.
Carbon and Nitrogen in Seagrass Tissue from Virginia Coastal Bays, 2010-2021
This dataset contains measurements of carbon and nitrogen content of Z. marina tissue sampled in plots in the restored seagrass meadows in Hog Island Bay and South Bay, VA. Samples were collected annually during late June-early July. GPS locations of sampling plots are available in the companion data set VCR11180.
Land cover for the barrier islands of the Delmarva Peninsula in Virginia, 1984-2016
We quantified state change from sand, grassland, and woody vegetation in seven undeveloped barrier islands over three time intervals because the ecological and economic value of upland barrier systems is significant, yet often overlooked. We focused on seven islands with woody land cover: Cedar, Parramore, Hog, Cobb, Wreck, Smith, and Fishermans. Landsat TM5 satellite images were obtained from the USGS Global Visualization Viewer for the following dates: September 21, 1984, September 12, 1998, August 15, 2011 and September 12, 2016. Images were chosen from available dates within the growing season and were cloud-free in order to minimize uncertainties due to heterogeneous atmospheric conditions. Barrier islands provide the first line of defense against storms for millions of people living in coastal areas. Upland vegetation (that is, grassland, shrubland, and maritime forest) has received little attention, even though this land surface is most strongly affected by development pressures. We use remote sensing analysis to assess state change on seven undeveloped Virginia barrier islands over 32 years (1984-2016) that are free from direct human influence. Our analysis highlights the spatial-temporally dynamic nature of barrier island upland land area and vegetation, with rapidly changing ecosystem states. Between 1984 and 2011, upland vegetation was dramatically reduced by 29% whereas woody vegetation cover increased 40% across all islands. Although conversions between sand, grassland, and woody vegetation were variable within each island, three major patterns of vegetative land cover change were apparent: overall loss of vegetative cover,frequent transitions between grass and woody cover, and gain in woody cover. These patterns are valuable for understanding natural evolution of barrier islands in response to sea-level rise. Evaluation of temporal dynamics in barrier upland is needed to characterize underlying processes including island resilience or chronic stress, a
Marsh to Upland: Vegetation Monitoring in Coastal Virginia, 2018-2022
This dataset includes data from vegetation plots along a marsh to upland gradient in three salt-marshes along the Eastern Shore of Virginia. Coastal wetlands serve as vital habitats and provide various ecosystems services. These ecosystems are experiencing novel abiotic conditions driven by anthropogenic change, including changes in salinity and moisture due to sea level rise. A key component of wetland ecosystems are their vegetation communities, which often show a transition from non-woody marsh plants like grasses and sedges to woody shrubs and larger trees in the upland reaches of the wetland. This dataset was collected from three coastal wetlands: Boxtree Preserve (Boxtree), Cushmans Landing (Cushmans), and Mockhorn Wildlife Management Area GATR Tract (GATR). Measurements of emergent vegetation percent cover and tree and shrub characteristics are taken annually at maximum biomass for the plant community, which occurs in August in this system (Moore 2013). At each site sampling occurs along four transects which run through the low marsh, high marsh, transitional area, lowest elevation upland forest, and slightly higher elevation upland forest. Each transect is segmented into five zones based on these plant communities, which roughly correspond to elevation bins of 1m. Each zone contains one sampling location.
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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.