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Coastal Forest Aboveground Biomass Data at six sites in the Chesapeake Bay and Delaware Bay region, 2021
This dataset contains aboveground biomass measurement and vegetation inventory of 17 coastal forest sites collected during June 1-8 of 2021 across Virginia (n = 6 in Goodwin Island and Phillips Creek), Maryland (n = 4, Monie Bay and Moneystump Swamp) and Delaware (n = 7, Milford Neck and Donas landing). The aboveground biomass was computed with allometric equations and all study sites were located within a narrow elevation range of 0-5m above sea level.
Gap-filled Meteorological Data for the Virginia Coast Reserve LTER - 1989-2022
This is a gap-filled dataset of the VCR-LTER meteorological sensor data on a daily level. It includes the csv of the generated data, as well as the R script used to generate it.
Satellite-based remote sensing of water clarity in the shallow coastal lagoons of Virginia 2013-2021
This dataset contains raw data, analysis products and code for a study of satellite-based estimation of water clarity. The files are: Match-up.csv: In situ Secchi depths collected by the Virginia Coast Reserve Long Term Ecological Research project (VCR LTER), matched with satellite (Landsat-8/Sentinel-2) Secchi depth estimates from 2013-2022 from NASA SeaDAS 8.2. Satellite overpasses occurred +/- 0-1 days within in situ sampling. Valid remote sensing reflectance values (Rrs) from NASA SeaDAS (not masked by quality flags) were recovered at 12 of 17 in situ sampling sites: 6 ocean inlet sites, 2 lagoon site, and 3 mainland tidal creek sites. Therefore, there are 12 in situ sites available for comparison with satellite estimates. compare_L8S2.csv: Satellite data and water clarity estimates from 150 randomly sampled sites across 5 clear day images in the Virginia Coast Reserve, 2021. Satellite data are from Landsat-8 and Sentinel-2 and processed/atmospherically-corrected using NASA SeaDAS 8.2. The Virginia Coast Reserve is a coastal lagoon system located in Virginia, USA, near the southern tip of the Delmarva Peninsula. Due to low nitrogen inputs and frequent exchange with the Atlantic Ocean via inlets between barrier islands, water quality is high relative to many other coastal bays in the United States and worldwide. Spatial_averaging_analysis.csv: Secchi depths at in situ water quality sites at 10 m resolution (Sentinel-2 only), 30 m resolution (Landsat-8 and Sentinel-2), and 90 m resolution (Landsat-8 and Sentinel-2) where there are in situ match-ups. atmocorrect.csv: In situ Secchi depths collected by the Virginia Coast Reserve Long Term Ecological Research project (VCR LTER), matched with satellite (Landsat-8/Sentinel-2) Secchi depth estimates from 2013-2022 from NASA SeaDAS 8.2 and ACOLITE Version 2022022.00. L8_ALL.csv: All Landsat-8 Secchi depth data available between 2013-2021 at in situ water quality sites. S2_ALL.csv: All Sentinel-2 Secchi depth data availab
Groundwater, soil moisture, light and weather data in Brownsville forest, Nassawadox, VA, 2019-2023
This dataset includes groundwater, soil moisture, weather and light data collected in eight study sites in the Brownsville forested area (VA). In particular, sites H5 and H7 characterize the high forest where healthy Pinus taeda dominate, sites L1 and L6 characterize the low forest, where barren or dead Pinus taeda are present, sites M1 and M2 characterize the medium forest, representing transition between high and low forest, transition site where dead trees and saltmarsh vegetation live together and marsh site dominated by saltmarsh vegetation. Data collection, started in January 2019, is done for VCR-LTER and CCZN (Coastal Critical Zone Network) long term projects. CTD-Diver are used to measure groundwater pressure, specific conductance and temperature. They hang from a cable in six wells, one for each study site. Water pressure is compensated using barometric pressure data collected by the weather station nearby. Water levels are georeferenced to NAVD 88. Two soil moisture sensors for each site are placed 7-10 cm and 30 cm below the ground surface to detect water content, specific conductance and temperature of the first soil layer. Two weather stations are always installed in different sites. Their position is periodically changed to cover all sites. This material is based upon work supported by the National Science Foundation under Grant No. 2012322, Collaborative Research: Network Cluster: The Coastal Critical Zone: Processes that transform landscapes and fluxes between land and sea.
Oyster and associated fauna counts and lengths from restored and reference reefs in the coastal bays of Virginia, 2005-2019
This dataset has been superceded by Lusk, B., R. Smith, and M.C.N. Castorani. 2024. Oyster fauna lengths, counts, and biomass from restored and reference reefs in Virginia coastal bays, 2005-2023 ver 1. Environmental Data Initiative. https://doi.org/10.6073/pasta/d68de69f29cee5f737313a07f813f245 (Accessed 2024-02-22). which includes additional years and parameters. Oyster and associated reef fauna counts and lengths were sampled at 16 natural reference reefs and 61 restored shell plant reefs located at 18 sites in the Virginia Coast Reserve. Overfishing and disease decimated oyster reefs in the Virginia Coast Reserve in the 1900s. Reference reefs were defined as remnant reefs that naturally recovered in the early 2000s to develop the pronounced vertical structure and multiple oyster size classes that represent the desired endpoint of restoration efforts. Nearly every year since 2003, The Nature Conservancy and Virginia Marine Resource Commission have constructed oyster reefs in intertidal areas in the VCR. To construct the restored reefs, practitioners applied dredged, fossilized oyster shell to intertidal locations chosen for their bottom stability and accessibility (locations lacked oysters prior to construction). Whelk shell supplemented the oyster shell at 9 of the restored reefs.
Reciprocal Transplant Experiment in a Coastal Forest, Nassawadox, VA
In the Mid-Atlantic region, accelerated sea-level rise is provoking rapid shifts in many coastal areas. As salt water intrusion occurs, tidal wetland species are colonizing space opened up by upland dieback and can even invade coastal forest understory prior to said dieback. One such species is the high marsh grass Spartina patens, which is known to exhibit divergent growth forms under the differing conditions of marsh, dune, and swale habitats. It is now colonizing the understory of coastal pine forests experiencing salt water intrusion. I established plots at three sites on the Delmarva peninsula in adjacent marsh and forest areas and conducted a reciprocal transplant experiment to address the following questions: a) How do environmental conditions for S. patens differ between marsh and forest habitats? b) How do S. patens traits differ between these habitats and are these differences a product of plasticity? Our results showed lower salinity and light availability in the forest which corresponded to greater height and leaf area of S. patens plants. Though some traits showed an effect of their habitat of origin, many functional traits exhibited strong phenotypic plasticity in response to environment. This plasticity may prove crucial to the species' resilience to future change.
Invertebrates in a retreating coastal forest near Nassawadox, VA , 2019-2020
Sampling was conducted on the Eastern Shore of Virginia at Brownsville Preserve, part of the Virginia Coast Reserve LTER and adjacent to Upper Phillips Creek (37.463, -75.835). Plots were established in five zones along the forest-to-salt marsh gradient based on vegetation communities and seedling recruitment. The high forest (HF) is characterized by both coniferous and deciduous tree species, with maximum seedling recruitment. The mid forest (MF) contains primarily coniferous trees and shrubs and shows reduced seedling recruitment. The low forest (LF) canopy shows partial mortality due to salt stress and no tree recruitment; the understory contains primarily invasive (Phragmites australis) but also salt marsh (Spartina patens, Distichlis spicata) plant species. The transition zone (TZ) contains mostly dead mature trees, with its understory dominated by S. patens, D. spicata, and P. australis. The high marsh (HM) does not contain trees and is dominated by S. patens and D. spicata. 2019 data was collected September 16-18, 2019. 2020 data was collected September 8-9, 2020.
Forest Transition Experiment - Soil Pore Water Salinity in a Coastal Virginia Forest
A pore water sipper was be used to collect a pore water sample from the top 15 cm of the soil, and was read using a portable refractometer in the field.
Forest Transition Experiment - Vegetation Monitoring on a Coastal Virginia Forest, 2019-2023
This dataset contains data on vegetation (shrubs, trees, non-woody vegetation, seedlings and Phragmites occurrence in permanent plots at the Brownsville Forest near Nassawadox, VA.
Camera detections of small mammals on the coast of Virginia, 2020-2023
Specially-designed "mousecam" cameras were used to detect and identify small mammals at locations on the coast of Virginia. This dataset contains information on the images, the species observed and the date, time and location of observation. A second table contains information on the identity of the specific camera used and its location. This dataset includes a limited number of miscellaneous images from locations on the mainland as well.
Abundance and Size of Seagrass-Associated Fishes in the Virginia Coastal Lagoons, 2019-2024
These data comprise annual summer estimates of the abundance (counts) and size (length) of fishes across restored seagrass meadows of the Virginia coastal lagoons. Fish were collected using a 25-ft (7.62-m) wide beach seine hauled by hand over a 25 m linear swath of the seafloor. Seine hauls were collected in June at 31 sites (1 haul per site). All fish caught in the seine were identified to lowest practical taxonomic level, counted, measured (total length), and released. Data collection began in June 2019 and continues annually (sampling was not carried out in 2020 due to logistical interruptions associated with the COVID-19 pandemic). Data on water temperature, salinity, and conductivity were collected while sampling occurred using a YSI 30 probe. Dissolved oxygen measurements were collected using a YSI ProODO probe. In 2019, these data were collected on at the top and bottom of the water column, but in 2021 and subsequent sampling only one observation (mid-water column) was made. To reconcile this difference for the combined data set, top and bottom environmental measurements from 2019 were averaged. Each fish collection site is co-located with a nearby synoptic site where long-term measurements of seagrass, sediments, and fauna are made. The relationship between site names and coordinates are given in Synoptic_fish_sites.csv. The sites where fish sampling occurred are different and are given by the "fish_sites" column, with coordinates for these sites under the "fish_longitude" and "fish_latitude" columns. Importantly, the coordinates of where sampling occurred will differ slightly between years without a change to the name of the site. Site geographic coordinates for individual years are in the PhysicalSamples.csv file. Sites are separated by at least 300 meters. In 2023, three new sites were added to represent unvegetated areas outside of but near the seagrass meadows. These sites are HI29, SPDR-bare, and SS-bare, and are designed to serve as references for se
Snail Consumption of Marsh Grasses in Mesocosms, 2018 and 2020
This experiment evaluated the effects of resource availability via nutrient addition and snail herbivory on the plant traits of Spartina alterniflora. Marsh periwinkles (Littoraria irrorata) and smooth cordgrass (Spartina alterniflora) were collected from Cushman's Landing marsh on the Eastern Shore in the summer of 2018 and set up in mesocosm tanks at the Virginia Institute of Marine Science in Gloucester Point, VA. There were four treatments: nutrient addition only, herbivory only, nutrient addition plus herbivory, and a control. At the end of the experiment, plants were analyzed for a series of plant traits. Dried and ground plant tissues were then resuspended in agar and a feeding assay was conducted in the summer of 2020 to evaluate how treatments influenced subsequent snail grazing. Six types of data were collected: 1) Feeding Assay Snail Morphometrics, 2) Final Plant Measurements, 3) Initial Plant Measurements, 4) Mesocosm Snail Morphometrics, 5) Plant Traits and 6) Snail Consumption.
Abundance, biomass, and length of seagrass-associated invertebrates in the Virginia coastal lagoons, 2019-2023
These data comprise annual summer estimates of the abundance (counts), biomass (dry mass), and individual lengths of infaunal and epifaunal invertebrates across restored seagrass meadows (eelgrass Zostera marina) of the coastal lagoons of Virginia, USA. Infauna were collected during low tide by hand using cylindrical benthic cores. Epifauna were collected during low tide using cubic weighted throw traps that were sampled with dip nets. Incidentally captured fishes are included in these data. In 2019-2022, 50 sites were sampled, using 3 replicates per sampling method per site. Beginning with 2023 sampling, two additional sites were added that are consistently bare of seagrass (unvegetated seafloor). At sites with patchy areas of seagrass and bare substrate, cores were collected within seagrass only and thus represent seagrass-associated fauna at those sites, rather than a spatially haphazard sample. At the few sites that lack seagrass, cores were collected in bare substrate. All cores were separated by 25 m. Regardless of substrate and seagrass conditions, throw traps were deployed haphazardly and separated by at least 10 m. In the laboratory, invertebrates were first sorted to broad taxonomic groups and later identified to lowest practical taxonomic level and enumerated. Most taxonomic groups were either dried and weighed by taxon or measured as individual length by specimen. Existing data include one table with counts and weights for broad taxonomic groups (2019-2023) and three tables related to lowest practical taxonomic identification (2019-2020), including one for counts and biomass, one for individual lengths, and one for taxonomic information. Data collection began in July 2019 and continues annually in June-July.
Comparison of high-marsh and ghost-forest invertebrates in Virginia, 2020
This dataset includes data on two invertebrates (Orchestia grillus and Pardosa littoralis) found in a coastal marsh in Virginia, and in the associated "ghost forest." It includes information on the locations (Table 1); information on the composition of the habitat where they were found (Table 2); plant biomass, including detritus (Table 3); size of invertebrates (Table 4); Carbon, Nitrogen and Sulphur stable isotope levels in invertebrate tissues and food plants (Table 5); and macroinfauna (Table 6).
Seagrass shoot density and benthic chlorophyll density from the Seagrass Recovery Experiment, South Bay, VA 2020-2022
To understand intra-meadow stability, the Seagrass Recovery Experiment was designed to ask 1) is recovery faster at sites with less thermal stress owing to greater exchange with cooler oceanic water at the meadow edge? 2) what is the shape of recovery? and 3) what are the recovery mechanisms? To conduct this experiment, aboveground seagrass biomass was removed from 28.3 m2 plots within the interior and along an edge of a restored seagrass meadow in South Bay, VA. Sites 1-3 correspond to the meadow interior while sites 4-6 correspond to the northern edge. Each site was comprised of a control (i.e., C) where no seagrass was disturbed and a treatment (i.e., T) where seagrass was removed (n = 12 sites total, e.g., 1C, 1T, 2C...). This dataset includes monthly seagrass shoot counts between June-October 2020, May-October 2021, and April-October 2022. To further characterize differences between the meadow interior and edge, benthic chlorophyll samples were also collected.
High-frequency water and sediment temperature from the Seagrass Recovery Experiment, South Bay, VA 2020-2022
To understand intra-meadow stability, the Seagrass Recovery Experiment was designed to ask 1) is recovery faster at sites with less thermal stress owing to greater exchange with cooler oceanic water at the meadow edge? 2) what is the shape of recovery? and 3) what are the recovery mechanisms? To conduct this experiment, aboveground seagrass biomass was removed from 28.3 m2 plots within the interior and along an edge of a restored seagrass meadow in South Bay, VA. Sites 1-3 correspond to the meadow interior while sites 4-6 correspond to the northern edge. Each site was comprised of a control (i.e., C) where no seagrass was disturbed and a treatment (i.e., T) where seagrass was removed (n = 12 sites total, e.g., 1C, 1T, 2C...). To further characterize differences between the meadow interior and edge, water and sediment temperatures were collected continuously. Water temperature was monitored at fixed positions 20 cm above the sediment surface at the center of each plot, while sediment temperature was monitored at 5 cm depth at the center of two sites within the central and northern edge South Bay locations.
Surface water quality from the Seagrass Recovery Experiment, South Bay, VA 2020-2022
To understand intra-meadow stability, the Seagrass Recovery Experiment was designed to ask 1) is recovery faster at sites with less thermal stress owing to greater exchange with cooler oceanic water at the meadow edge? 2) what is the shape of recovery? and 3) what are the recovery mechanisms? To conduct this experiment, aboveground seagrass biomass was removed from 28.3 m2 plots within the interior and along an edge of a restored seagrass meadow in South Bay, VA. Sites 1-3 correspond to the meadow interior while sites 4-6 correspond to the northern edge. Each site was comprised of a control (i.e., C) where no seagrass was disturbed and a treatment (i.e., T) where seagrass was removed (n = 12 sites total, e.g., 1C, 1T, 2C...). To further characterize differences between the meadow interior and edge, surface water quality samples were also collected and include turbidity, total suspended solids (TSS) concentration, TSS ash-free dry weight, TSS percent organic matter, pelagic chlorophyll concentration, dissolved oxygen saturation, dissolved oxygen concentration, salinity, water temperature, and specific conductivity. These discrete samples were collected monthly between June-October 2020, May-October 2021, and April-October 2022 using a 1-L Nalgene bottle and a handheld YSI Pro Plus Multiparameter meter.
Barrier Island Plant and Soil Properties on Hog and Metompkin Islands, Virginia, 2021-2022
Dune building has the potential to impact the entire barrier island ecosystem, and these grasses therefore serve as ecosystem engineers. Protection offered by dune ridges directly impacts the adjacent swale habitat, modifying both biotic and abiotic factors. In order to better understand how dune building impacts the island ecosystem as a whole, we quantified sediment accretion, plant percent cover, stem numbers, and soil characteristics (chlorides, bulk density, %OM, %C, %N). These characteristics were assessed on two islands with varied disturbance intensities. Hog island is infrequently disturbed, and resists change driven by storms and overwash. Metompkin island is frequently disturbed and undergoes high rates of overwash and island migration.
Water Temperatures and Climatology for Wachapreague, VA, 1982-2021
Daily average measured near-surface water temperature from 1982-2021 constructed for the site in the Virginia coastal bays where the NOAA Wachapreague station is located (Site CBW (Coastal Bay Wachapreague); 37.61N, 75.69W; water depth 1m) and for a site in the coastal ocean just outside the bays (Site COC (Coastal Ocean CHLV2); 36.91N, 75.71W; water depth 15m). Daily climatological mean temperature and marine heatwave threshold (90th percentile) calculated using 30 years of the record (1987-2016) are also provided.
Fowling Point Marsh Flux Tower Data, 2014-2017
A flux tower was operated on Fowling Point Marsh near Nassawadox, VA from 2014-2017. The flux tower is located about 2 km from the mainland and about 85 m away from a major creek edge. The marsh soil is tidally inundated on a semi-diurnal cycle, with extreme levels of inundation reaching 1.0 m above the mean marsh surface. Continuous meteorological and eddy covariance measurements were made on a 7-m flux tower located in the salt marsh. An eddy covariance unit was mounted at 3.7 m above the sediment surface. Data for BioMet sensors are provided as a table. BioMET data consists of 1min averaged meteorological data. Proprietary LiCOR .ghg files at 20Hz are included in Tape ARchive (TAR) files. Individual GHG files can be renamed as .zip files and uncompressed to reveal an internal metadata file and the data itself. A PDF file identifies the instrumentation and the wiring used to connect them. A summary file contains statistical summaries of the original GHG files.
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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.