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204 results for “Maryland”
Water Monitoring of the Choptank River and Pocomoke River, Maryland, USA
Water monitoring at four locations on the Choptank River and four locations on the Pocomoke River in Maryland, U.S.A., was conducted from 2021 through 2023. Funding and scientific rationale were provided by the National Science Foundation grant 2049073 (“Resolving Sediment Connectivity between Rivers and Estuaries by Tracking Particles with their Microbial Genetic Signature”). The monitoring locations were chosen to measure estuary dynamics from the tidal freshwater zone through the mesohaline estuary. Parameters measured included water temperature, water level, water conductivity (reported as specific conductivity), water turbidity, and water velocity.
ICESat-2 Arctic Sea Ice Surface Topography from the University of Maryland-Ridge Detection Algorithm: April 2019, 2020, and 2021
<p>This dataset is derived from the ICESat-2 (IS-2) Global Geolocated Photon Height Product (ATL03) using the University of Maryland-Ridge Detection Algorithm (UMD-RDA). The UMD-RDA is applied to ATL03 on a per-shot basis, nominally resulting in elevation measurements at IS-2's maximum along-track resolution of ~0.7 m. From these elevation measurements, the UMD-RDA can measure various sea ice parameters including, but not limited to, individual ridge crests and their respective sail heights, the distance between ridges, and sea ice surface roughness.</p> <p><strong>********Changes in Version 2********</strong></p> <p><em>Version 2 includes a column for time (seconds since 2018-01-01) in all parameter files in addition to longitude, latitude, and parameter value.</em></p> <p><em>The full resolution UMD-RDA derived elevation data was too large to host here, but is available upon request. If you need a particular track or segment for your research please contact me with your request by email: kd</em><em>uncan at umd dot edu</em></p>
Seasonal N dynamics and fluxes of nitrogen in leachate and runoff from experimental rainfalls on fertilized and unfertilized lawns in Baltimore County, Maryland
The aim of this research was to examine the spatial and temporal variation in export control points of nitrogen on residential lawns (locations prone to mobilizing nitrogen during a rain event) and to examine if previously measured hydrobiogeochemical properties were predictive of N mobilization in lawns. This data set contains measurements of saturated infiltration rates, sorptivity, soil moisture, soil organic matter, bulk density, pH, soil nitrate, soil ammonium, N2O, N2 and CO2 fluxes from soil cores, nitrogen mineralization rates and fluxes of N in runoff and leachate from fertilized and unfertilized residential and institutional lawns. Study lawns were located at homes of people who agreed to volunteer their lawn for the study from a door knocking campaign. Four sampling houses were located in an exurban neighborhood in Baisman Run. Five sampling houses were located in a suburban neighborhood in Dead Run. Two sampling locations on institutional lawns were located at University of Maryland Baltimore County. At the exurban study houses and institutional lawns sites, we identified one hillslope to conduct sampling on. At the Dead Run houses we identified one hillslope on the front yard and one in the backyard as there were distinct locations that were not present in the exurban neighborhood. Locations within the yards for sampling were selected based on sampling conducted in October 2017. Locations were grouped into four categories based on have either high or low potential denitrification rates and high or low saturated infiltration rates (n=48). These locations were also distributed across yard types (exurban, suburban or institutional), fertilizer treatments, and hillslope location (top or bottom of hillslope). At each sampling location we ran a Cornell Sprinkle Infiltrometer to generate an experimental rainfall during which we collected runoff and leachate to quantity N flux. We also measure sorptivity and saturated infiltration rates. Volumetric water conten
Forest Aboveground Biomass 2000-2022 for Maryland, USA
<p>This dataset provides 30-m resolution maps of estimated forest aboveground biomass (AGB) in the state of Maryland between 2000-2022. This dataset was produced by a novel forest carbon monitoring system which utilizes high resolution remote sensing of contemporary tree cover and canopy height as powerful constraints within a process-based ecosystem model to reconstruct the spatial and temporal dynamics in AGB while considering impacts of spatially and temporally transient meteorology, elevated CO2 and disturbance. This dataset reports AGB in unit of kg C/m2.</p> <p>This forest carbon monitoring system was built on a process-based ecosystem model called Ecosystem Demography (ED) (Hurtt et al 1998; Moorcroft et al 2001; Ma et al 2022), which can simulate plant dynamics including growth, mortality, and reproduction; carbon dynamics within the simulated plants; and dynamics of carbon pools in forest ecosystems.</p> <p>This forest carbon monitoring system ingests transient meteorology from Daymet (Thornton et al 2016) and MERRA2 (Gelaro et al. 2017) and CO2 concentrations from NOAA, remote sensing of forest change from the Global Forest Change (Hansen et al 2013), contemporary tree cover and canopy height from airborne lidar (e.g. Tang et al. 2021) and aerial imagery from National Agriculture Imagery Program (NAIP). More details about the system development can be found in Hurtt et al. 2022.</p> <p>This data is currently utilized in the State of Maryland’s Greenhouse Gas Inventory and is scheduled to be updated at least triennially as part of updates to the State’s inventory. This data is also serves as the basis for calculations within the University of Maryland Peer-Reviewed Offset Protocol for Maryland Reforestation/Afforestation Projects.</p> <p>For questions and support please contact lma6@umd.edu, rachlamb@umd.edu and gchurtt@umd.edu.</p> <p>This work was supported by contract from the Maryland Department of the Environment. We also gratefully acknowledge the support of NASA Carbon Monitoring System project (80NSSC21K1059).</p>
Fig. 6 in New Miocene Monachinae From The Western Shore Of The Chesapeake Bay (Maryland, Usa)
Fig. 6. Humeri. Left humerus of Leptophoca lenis from Maryland, USA (USNM 412115) in A — medial; B — cranial; and C — caudal views. Incomplete left humeri of Terranectes magnus (holotype, CMM-V-4710) in D — medial; E — lateral; F — caudal and G — cranial views; and T. parvus (CMM-V-4688) in H — medial; I — cranial and J — caudal views. Scale bars equal 5 cm/2 inches.
Fig. 12 in New Miocene Monachinae From The Western Shore Of The Chesapeake Bay (Maryland, Usa)
Fig. 12. Pes. Phalanges of Recent spotted seal (Phoca largha; UAM 11634) in A — hindfoot and B — forefoot. C — incomplete, reconstructed left hindfoot of Terranectes parvus (CMM-V-4691-4700). Metatarsal bones found separate and placement of some phalanges uncertain. Astragalus of T. parvus (CMM-V-4682) in D — cranial and E — lateral views.
Fig. 1 in New Miocene Monachinae From The Western Shore Of The Chesapeake Bay (Maryland, Usa)
Fig. 1. Phocid dispersal map. World map showing the likely origin of seals in the Paratethyan / Mediterranean basin (gray outline) and their westward dispersal. Both Phocinae (Leptophoca amphiatlantica, ~16 Ma) and Monachinae (Terranectes, ~ 11 Ma) crossed the Atlantic Ocean and settled on the western shore of the North Atlantic (black arrow with asterisks). The black rectangle indicates the Chesapeake group, the location of the oldest known phocine and monachine extinct seals in North America.
Fig. 4 in New Miocene Monachinae From The Western Shore Of The Chesapeake Bay (Maryland, Usa)
Fig. 4. Atlas and skull. Atlas (C1) of Leptophoca lenis from Maryland, USA (USNM 411889) in A — dorsal; B — ventral; C — caudal and D — cranial views. Skull fragment of Terranectes magnus (CMM-V-4680) in E — lateral view; and T. parvus (CMM-V-4679) in F — lateral and G, medial views. Atlas of T. magnus (CMM- V-4677) in H — cranial and I — caudal views. Cervical vertebra of T. magnus (CMM-V-4676) in J, ventral; K — dorsal, and L — caudal views.
Fig. 8 in New Miocene Monachinae From The Western Shore Of The Chesapeake Bay (Maryland, Usa)
Fig. 8. Fossil innominata. Innominate bones in lateral view: A — Terranectes magnus (L., incomplete, CMM- V-4708); B — Terranectes parvus (L., incomplete, CMM-V-4683); C — Homiphoca capensis (L., incomplete, South African Museum PQ-L30236; Muizon and Hendey 1980, fig. 12); D — Callophoca obscura (Ơ, incomplete, USNM 425886, from Lee Creek Mine, USA; Koretsky and Ray 2008, fig. 33); E — Acrophoca longirostris (L., incomplete, SAS 563; Muizon 1981a, pl.11, fig. 1); F — Piscophoca pacifica (R., SAS 682; Muizon 1981a, pl.5, fig.1). In medial view: G — T. magnus (L., incomplete, CMM-V-4708) and H — T. parvus (L., incomplete, CMM-V-4683). T. magnus (L., incomplete, CMM-V-4708) in I — cranial and J — caudal views. T. parvus (L., incomplete, CMM-V-4683) in K — caudal and L — cranial views.
Fig. 7 in New Miocene Monachinae From The Western Shore Of The Chesapeake Bay (Maryland, Usa)
Fig. 7. Modern and fossil innominate bones. Left innominate of Leptophoca lenis from Maryland, USA (USNM 263648) in A — lateral (reversed) and B — medial views. Innominate of Recent Phoca vitulina (CMM-O-399, L. and R.) in C — lateral and D — medial views.
Fig. 5 in New Miocene Monachinae From The Western Shore Of The Chesapeake Bay (Maryland, Usa)
Fig. 5. Sacrum. Sacrum of Leptophoca lenis from Maryland, USA (USNM 23231) in A — dorsal; B — ventral and C — cranial views.Sacrum of Terranectes magnus (CMM-V-4703) in D — lateral; E — ventral, and F — medial views.
Fig. 3 in New Miocene Monachinae From The Western Shore Of The Chesapeake Bay (Maryland, Usa)
Fig. 3. Stratigraphic correlation of the Chesapeake Group. Site #PQ-BH9812, in southern Southampton County, Virginia, near the North Carolina border, exposes beds of the Eastover Formation.
Forest Aboveground Biomass 1984-2016 for Maryland, USA
<p>This dataset provides 30-m resolution maps of estimated forest aboveground biomass (AGB) in the state of Maryland between 1984-2016. This dataset was produced by a novel forest carbon monitoring system which utilizes high resolution remote sensing of contemporary tree cover and canopy height as powerful constraints within a process-based ecosystem model to reconstruct the spatial and temporal dynamics in AGB while considering impacts of spatially and temporally transient meteorology, elevated CO2 and disturbance. This dataset reports AGB in unit of kg C/m2.</p> <p>This forest carbon monitoring system was built on a process-based ecosystem model called Ecosystem Demography (ED) (Hurtt et al 1998; Moorcroft et al 2001; Ma et al 2022), which can simulate plant dynamics including growth, mortality, and reproduction; carbon dynamics within the simulated plants; and dynamics of carbon pools in forest ecosystems.</p> <p>This forest carbon monitoring system ingests transient meteorology from Daymet (Thornton et al 2016) and MERRA2 (Gelaro et al. 2017) and CO2 concentrations from NOAA, remote sensing of forest change from the North American Forest Dynamics (NAFD), contemporary tree cover and canopy height from airborne lidar (e.g. Tang et al. 2021) and aerial imagery from National Agriculture Imagery Program (NAIP). More details about the system development can be found in Hurtt et al. 2022.</p> <p>This data is currently utilized in the State of Maryland’s Greenhouse Gas Inventory and is scheduled to be updated at least triennially as part of updates to the State’s inventory. This data is also serves as the basis for calculations within the University of Maryland Peer-Reviewed Offset Protocol for Maryland Reforestation/Afforestation Projects.</p> <p>For questions and support please contact lma6@umd.edu, rachlamb@umd.edu and gchurtt@umd.edu.</p> <p><strong>Reference</strong></p> <p>Hurtt, G.C., P.R. Moorcroft, S.W. Pacala, and S.A. Levin. 1998 Terrestrial models and global change: challenges for the future. Global Change Biology 4:581-590. https://doi.org/10.1046/j.1365-2486.1998.t01-1-00203.x</p> <p>Hurtt et al 2022. Beyond Forest Carbon Monitoring: Integrating High-Resolution Remote Sensing and Ecosystem Modeling for Geospatial Assessment and Attribution of Changes in Forest Carbon Stocks Over Maryland, USA (in prep).</p> <p>Ma, L., G. Hurtt, L. Ott, R. Sahajpal, J. Fisk, R. Lamb, H. Tang, S. Flanagan, L. Chini, A. Chatterjee, and J. Sullivan. 2022a. Global evaluation of the Ecosystem Demography model (ED v3.0). Geoscientific Model Development 15:1971–1994. https://doi.org/10.5194/gmd-15-1971-2022 </p> <p>Moorcroft, P. R., G.C. Hurtt. and S.W. Pacala, 2001 A method for scaling vegetation dynamics: the ecosystem demography model (ED) Ecol. Monogr. 71 557–86. https://doi.org/10.1890/0012-9615(2001)071[0557:AMFSVD]2.0.CO;2 </p> <p>Tang, H., L. Ma, A.J. Lister, J. O'Neil-Dunne, J. Lu, R. Lamb, R.O. Dubayah, and G.C. Hurtt. 2021. LiDAR Derived Biomass, Canopy Height, and Cover for New England Region, USA, 2015. ORNL DAAC, Oak Ridge, Tennessee, USA. https://doi.org/10.3334/ORNLDAAC/1854.</p> <p>Dr. Pieter Tans, NOAA/GML (gml.noaa.gov/ccgg/trends/) and Dr. Ralph Keeling, Scripps Institution of Oceanography (scrippsco2.ucsd.edu/).</p>
Fig. 3 in A revaluation of rhipidocystid echinoderms based on a new flattened blastozoan from the Upper Ordovician of Maryland, USA
Fig. 3. Rhipidocystid echinoderm Durhamicystis americana gen. et sp. nov. from the Upper Ordovician Chambersburg Formation, Maryland, USA. A. USNM 642510. B. USNM 642511a, b. Photographs of specimens submerged in water to increase contrast of plates and plate boundaries (A1, B1). Camera lucida drawings indicating plate arrangements (A2, B2). Abbreviations: FP, flooring plate (green); G, gonopore; H, hydropore; M1–M9, marginal plates (yellow); O1–O7, oral plates (red); Pe, periproct. Central plates colored in blue, stem in purple, and brachioles in brown.
Fig. 6 in A revaluation of rhipidocystid echinoderms based on a new flattened blastozoan from the Upper Ordovician of Maryland, USA
Fig. 6. Comparisson between the rhipidocystids Mandalacystis dockery Lewis, Sprinkle, Bailey, Moffit, and Parsley, 1987 (A), Petalocystites ikecanensis (Sprinkle, 1973) (B), Neorhipidocystis norvegica (Bockelie, 1981) (C), and Durhamicystis americana gen. et sp. nov. (D). Abbreviations: FP, flooring plate (green); M1–M9, marginal plates (yellow); O1–O7, oral plates (red); central plates (blue); stem (purple), brachioles (brown); Pe, periproct. Based on Lewis et al. 1987 (A), Sprinkle 1973 (B), and Bockelie 1981 (C).
Fig. 1 in A revaluation of rhipidocystid echinoderms based on a new flattened blastozoan from the Upper Ordovician of Maryland, USA
Fig. 1. Rhipidocystid echinoderm Durhamicystis americana gen. et sp. nov. from the Upper Ordovician Chambersburg Formation, Maryland, USA. A. Holotype USNM 642510 showing the theca, proximal stem, and brachioles; general view of the complete specimen in ventral view (A1), detail of oral area and proximal part of the brachioles (A2), specimen in lateral view showing the periproct surrounded by three plates (A3). B. Paratype USNM 642513; general view of the complete specimen in ventral view (B1), note central plates in thecal interior, and single columnal attached to basals; detail of the anal pyramid on left edge (B2). Specimens whitened with ammonium chloride sublimate.
Fig. 4 in A revaluation of rhipidocystid echinoderms based on a new flattened blastozoan from the Upper Ordovician of Maryland, USA
Fig. 4. Rhipidocystid echinoderm Neorhipidocystis norvegica (Bockelie, 1981) from the Late Ordovician of the Oslo Region, Norway. A. PMO 101.143, half complete specimen; detail of the oral area (A2). B. PMO 101.144 (holotype), almost complete specimen lacking the lower portion; detail of the oral area (B2), note V-shaped notches and cover plates on uniserial brachioles. Specimens are latex casts whitened with ammonium chloride sublimate. Scale bars 5 mm.
Fig. 5 in A revaluation of rhipidocystid echinoderms based on a new flattened blastozoan from the Upper Ordovician of Maryland, USA
Fig. 5. Camera lucida drawings and plate interpretations of the oral area in Neorhipidocystis norvegica (Bockelie, 1981). A. PMO 101.143. B. PMO 101.144, holotype. Abbreviations: CP, cover plates over ambulacra and brachioles; FP, flooring plates; G, gonopore; H, hydropore; M, marginal plates; O1–O6, oral plates.
Fig. 2 in A revaluation of rhipidocystid echinoderms based on a new flattened blastozoan from the Upper Ordovician of Maryland, USA
Fig. 2. Rhipidocystid echinoderm Durhamicystis americana gen. et sp. nov. from the Upper Ordovician Chambersburg Formation, Maryland, USA. A. Paratype USNM 642511a, b; general view showing two nearly complete superimposed specimens (A1); detail of the oral area, proximal brachioles attached to marginal, oral, and floor plates, and three apertures (periproct, hydropore slit, and tiny gonopore) (A2); specimen in left lateral view showing the thin central plates from both integuments (A3); specimen in right lateral view showing the position of the periproct (A4); detail of facets between brachiolar plates and cryptic vertical sutures indicated by arrows (A5); detail showing thin internal projections of weathered, U-shaped, marginal plates (A6). Specimens whitened with ammonium chloride sublimate.
Forest Aboveground Biomass 2000-2023 for Maryland, USA
<p>This dataset provides 30-m resolution maps of estimated forest aboveground biomass (AGB) in the state of Maryland between 2000-2023. This dataset was produced by a novel forest carbon monitoring system which utilizes high resolution remote sensing of contemporary tree cover and canopy height as powerful constraints within a process-based ecosystem model to reconstruct the spatial and temporal dynamics in AGB while considering impacts of spatially and temporally transient meteorology, elevated CO2 and disturbance. This dataset reports AGB in unit of kg C/m2.</p> <p>This forest carbon monitoring system was built on a process-based ecosystem model called Ecosystem Demography (ED) (Hurtt et al 1998; Moorcroft et al 2001; Ma et al 2022), which can simulate plant dynamics including growth, mortality, and reproduction; carbon dynamics within the simulated plants; and dynamics of carbon pools in forest ecosystems.</p> <p>This forest carbon monitoring system ingests transient meteorology from Daymet (Thornton et al 2016) and MERRA2 (Gelaro et al. 2017) and CO2 concentrations from NOAA, remote sensing of forest change from the Global Forest Change (Hansen et al 2013), contemporary tree cover and canopy height from airborne lidar (e.g. Tang et al. 2021) and aerial imagery from National Agriculture Imagery Program (NAIP). More details about the system development can be found in Hurtt et al. 2022.</p> <p>This data is currently utilized in the State of Maryland’s Greenhouse Gas Inventory and is scheduled to be updated at least triennially as part of updates to the State’s inventory. This data is also serves as the basis for calculations within the University of Maryland Peer-Reviewed Offset Protocol for Maryland Reforestation/Afforestation Projects.</p> <p>For questions and support please contact lma6@umd.edu, rachlamb@umd.edu and gchurtt@umd.edu.</p> <p>This work was supported by contract from the Maryland Department of the Environment. We also gratefully acknowledge the support of NASA Carbon Monitoring System project (80NSSC21K1059).</p>
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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
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DANDI Archive for NWB datasets
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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.