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GRIME AI Water Segmentation Model for the USGS Monitoring Site Beggars Bridge Creek Near Dawley Corners, VA, 2023-2024
Ground-based observations from fixed-mount cameras have the potential to fill an important role in environmental sensing, including direct measurement of water levels and qualitative observation of ecohydrological research sites. All of this is theoretically possible for anyone who can install a trail camera. Easy acquisition of ground-based imagery has resulted in millions of environmental images stored, some of which are public data, and many of which contain information that has yet to be used for scientific purposes. The goal of this project was to develop and document key image processing and machine learning workflows, primarily related to semi-automated image labeling, to increase the use and value of existing and emerging archives of imagery that is relevant to ecohydrological processes. This data package includes imagery, annotation files, water segmentation model and model performance plots, and model test results (overlay images and masks) for the USGS Monitoring Site Beggars Bridge Creek Near Dawley Corners, VA, 2023-2024. All imagery was acquired from the USGS Hydrologic Imagery Visualization and Information System (HIVIS; see https://apps.usgs.gov/hivis/camera/VA_Beggars_Cr_nr_Dawley_Corners_RSIE for this specific data set) and/or the National Imagery Management System (NIMS) API. Water segmentation models were created by tuning the open-source Segment Anything Model 2 (SAM2, https://github.com/facebookresearch/sam2) using images that were annotated by team members on this project. The models were trained on the "water" annotations, but annotation files may include additional labels, such as "snow", "sky", and "unknown". Image annotation was done in Computer Vision Annotation Tool (CVAT) and exported in COCO format (.json). All model training and testing was completed in GaugeCam Remote Image Manager Educational Artificial Intelligence (GRIME AI, https://gaugecam.org/) software (Version: Beta 16). Model performance plots were automatically generated du
High and Low Tides of Hog Island Bay, Redbank, VA, and Oyster, VA for the Virginia Coast Reserve 2007-2025
This dataset is a summary version of the 12-minute tide data. It records the date, time and level of tides at high and low tide (as indicated by the data). Water temperatures are also recorded.
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
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).
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.
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.
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.
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.
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.
Hog Island VA Small-Mammal Trapping 1989-2020
This dataset contains information on long-term small mammal trapping on the Virginia Coast Reserve LTER. Four transects on Hog Island are included in the data, each of which was trapped at least twice each year, typically in the spring and autumn (note: Transect T2 was not trapped every year). Along each transect Sherman Live Traps were placed every 12.5 m along the transect, with an alternating offset of 2.5 m (to remove traps from the path running down the transect). This leaves a total inter-trap distance of 15 m. Traps were baited with peanut butter wrapped in waxed paper and were run sequentially for at least 3 nights in a row. Traps in areas that would experience tidal flooding were placed on styrofoam plastic platforms to provide flotation during high tides. Captured animals were individually tagged with numbered fingerling fish tags placed in the right ear, inspected for sex and sexual characteristics, weighed with a spring scale to the nearest gram and released at the point of capture.
Time series of in situ Uv-Vis absorbance spectra and high-frequency predictions of total and soluble Fe and Mn concentrations measured at multiple depths in Falling Creek Reservoir (Vinton, VA, USA) in 2020 and 2021
High-frequency measurements of light absorbance were collected at multiple depths in Falling Creek Reservoir (FCR; Vinton, VA, USA) using a s::can Spectrolyser UV-Visible spectrophotometer coupled with a multiplexor pumping system. The system pumps water samples from individual depths into a flow-through cuvette where the UV-vis absorbance spectra of the sample are measured by the spectrophotometer. The system used in our study collected measurements of light absorbance every 2.5 nm wavelengths from 200 nm to 732.5 nm (optical path length of 10 mm) approximately at an hourly time step for seven monitoring depths in the reservoir. Data was collected during two periods; the first deployment (16 October to 9 November 2020) was to observe changes in Fe and Mn concentrations before, during, and after reservoir fall turnover and the second deployment (26 May to 21 June 2021) was to observe the effects of engineered hypolimnetic oxygenation on Fe and Mn concentrations. Partial least squares regression models were developed to generate predictions of total and soluble Fe and Mn concentrations based on the correlation between absorbance spectra and sampling data.
ADCP wave and current data at Hog Island and Chimney Pole Marsh, VA 2009
Two acoustic doppler profilers were deployed in on Hog Island and Chimney Pole Marsh in 2009. all quantites (velocity, waves, water elevation, attenuation) are described in the file *.hdr (header file)
Atmospheric pressure on Hog Island, Phillips Creek Marsh and Oyster, VA 2012-2025
Barometric pressure is measured hourly at meteorological stations on the Atlantic Coast of the Delmarva Peninsula. Data is available as a long table that gives the average, minimum and maximum air pressure for each station at each time, or as a table that gives the average values for each of the stations, along with the median value across stations on each line.
Hydrodynamic, sediment, and bivalve data from seagrass edges in South Bay, VA, 2021 to 2022
The northern edge of the South Bay seagrass meadow was studied for two years to quantify flow characteristics, sediment movement, and bivalve abundance. ADCPs (Aquadopp, Vector, Vectrino) and wave gauges were used to measure hydrodynamic conditions, sediment sensors and sediment traps were used to measure sediment movement, and sediment cores were used to measure bivalve abundance. Data were collected across seagrass edges in vegetated and unvegetated locations, or along transects spanning the natural edge of meadow vegetation. Manmade bare patches were also created in the study area to collect data along patch edges. Study sites 1 and 2 were approximately 100m apart along the northern edge of the seagrass meadow. A PDF figure describing the locations is included as Site_Figure.pdf along with the data tables.
Sediment elevation transects for the Seagrass Recovery Experiment, South Bay, VA 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 meadow 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...). A nor'easter storm moved through the area in early May 2022 producing 59% and 48% of the year's total Gale and Near Gale force winds. After the storm passed, depressions were noticed within the edge treatment sites. To quantify the depression depths a survey of the sediment surface depth was coordinated among all sites in October 2022. Results provide evidence that the edge treatment sites were depressed by 9.4-10.4 cm relative to outside of the treatment plots.
A grazing crab drives saltmarsh carbon storage and recovery in VA, SC, and GA
Consumers can directly (e.g., consumption) and indirectly (e.g., trophic cascades) influence carbon cycling in blue carbon ecosystems. Previous work found that large grazers have nuanced effects on carbon stocks, yet, small, bioturbating-grazers, which remove plant biomass and alter sediment properties, remain an understudied driver of carbon cycling. We used field-derived and remote sensing data to quantify the grazing effects of the purple marsh crab, Sesarma reticulatum, on carbon stocks, flux, and recovery in salt marshes. Sesarma fronts led to a carbon loss of around 40-70% and Sesarma front migration rates accelerated over time. Despite latitudinal differences, front migration rate had no effect on carbon stocks, flux, or time to replacement. When we included Sesarma disturbance in carbon flux calculations, we found it may take 5-100 years for marshes to replace lost carbon, if at all. Combined, we show that small grazers cause a net loss in carbon stocks as they move through the landscape, and irrespective of migration rate, these grazer-driven impacts persist for decades. This work showcases the significant role of consumers in carbon storage and flux, challenging the classic paradigm of plant-sediment feedbacks as the primary ecogeomorphic driver of carbon cycling in blue carbon ecosystems.
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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)
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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.