Open Access. Powered by Scholars. Published by Universities.®

Physical Sciences and Mathematics Commons

Open Access. Powered by Scholars. Published by Universities.®

William & Mary

Discipline
Keyword
Publication Year
Publication
Publication Type
File Type

Articles 1051 - 1080 of 4602

Full-Text Articles in Physical Sciences and Mathematics

Assessing The Impact Of Local And Regional Influences On Nitrogen Loads To Buzzards Bay, Ma, Shanna C. Williamson, Jennie E. Rheuban, Et Al Jan 2017

Assessing The Impact Of Local And Regional Influences On Nitrogen Loads To Buzzards Bay, Ma, Shanna C. Williamson, Jennie E. Rheuban, Et Al

VIMS Articles

Nitrogen and chlorophyll-a concentrations in estuarine systems often correlate positively with increased nitrogen input. To determine the interactions between nitrogen load, physical drivers, and water quality indicators, we estimated nitrogen inputs to 28 estuaries within the Buzzards Bay, Massachusetts (USA) watershed from 1985 to 2013. Estimates were derived by combining parcel specific wastewater disposal, point source wastewater discharge, land use, and atmospheric nitrogen deposition data with a previously verified nitrogen loading model. Linear regression analysis was used to quantify temporal trends in individual data sets and characterize relationships between variables. The land-use data indicated that fractional coverage of impervious surfaces …


Review Of Boat Wake Wave Impacts On Shoreline Erosion And Potential Solutions For The Chesapeake Bay, Donna M. Bilkovic, Molly Mitchell, Jenny Davis, Elizabeth Andrews, Angela King, Pamela Mason, Julie Herman, Navid Tahvildari, Jana Davis Jan 2017

Review Of Boat Wake Wave Impacts On Shoreline Erosion And Potential Solutions For The Chesapeake Bay, Donna M. Bilkovic, Molly Mitchell, Jenny Davis, Elizabeth Andrews, Angela King, Pamela Mason, Julie Herman, Navid Tahvildari, Jana Davis

Reports

No abstract provided.


Parsing The Aggregation- And Photodegradation-Induced Effects Of Rhodamine-Sensitized Tio2 And Zro2 Films, James Cassidy Jan 2017

Parsing The Aggregation- And Photodegradation-Induced Effects Of Rhodamine-Sensitized Tio2 And Zro2 Films, James Cassidy

Dissertations, Theses, and Masters Projects

The impact of rhodamine aggregates on the photophysical properties of rhodamine dyes adsorbed to TiO2 were investigated using diffuse reflectance spectroscopy, steady-state fluorescence, and time-correlated single photon counting (TCSPC). Photocatalyzed de-alkylation of rhodamine dyes containing tertiary amine groups (5-ROX, R101, and RB) was observed on TiO2, which resulted in a ~50 nm hypsochromic shift. Therefore, concentration dependent diffuse reflectance spectra of R560/TiO2 samples, which contained primary amines, demonstrated the formation of H- and J-aggregates at the expense of the monomers. The formation of J-aggregates resulted in FRET between monomers and J-aggregates which yielded a bathochromic shifted fluorescence spectra as a …


Multispectrum Analysis Of The Oxygen A-Band, Brian J. Drouin, D. Chris Benner, Linda R. Brown, (...), V. Malathy Devi, Et Al. Jan 2017

Multispectrum Analysis Of The Oxygen A-Band, Brian J. Drouin, D. Chris Benner, Linda R. Brown, (...), V. Malathy Devi, Et Al.

Arts & Sciences Articles

Retrievals of atmospheric composition from near-infrared measurements require measurements of airmass to better than the desired precision of the composition. The oxygen bands are obvious choices to quantify airmass since the mixing ratio of oxygen is fixed over the full range of atmospheric conditions. The OCO-2 mission is currently retrieving carbon dioxide concentration using the oxygen A-band for airmass normalization. The 0.25% accuracy desired for the carbon dioxide concentration has pushed the required state-of-the-art for oxygen spectroscopy. To measure 02 A-band cross-sections with such accuracy through the full range of atmospheric pressure requires a sophisticated line shape model (Rautian or …


Gis Data: Henrico County, Virginia Shoreline Management Model, Marcia Berman, Karinna Nunez, Sharon Killeen, Tamia Rudnicky, Julie Bradshaw, Karen Duhring, Kallie Brown, Jessica Hendricks, David Weiss, Carl Hershner Jan 2017

Gis Data: Henrico County, Virginia Shoreline Management Model, Marcia Berman, Karinna Nunez, Sharon Killeen, Tamia Rudnicky, Julie Bradshaw, Karen Duhring, Kallie Brown, Jessica Hendricks, David Weiss, Carl Hershner

Data

The Shoreline Management Model is a GIS spatial model that determines appropriate shoreline best management practices using available spatial data and decision tree logic. Available shoreline conditions used in the model include the presence or absence of tidal marshes, beaches, and forested riparian buffers, bank vegetation cover, bank height, wave exposure (fetch), nearshore water depth, and proximity of coastal development to the shoreline. The model output for shoreline best management practices is displayed in the locality Comprehensive Map Viewer. One GIS shapefile is developed that describes two arcs or lines representing practices in the upland area and practices at the …


Gis Data: King George County, Virginia Tidal Marsh Inventory, Marcia Berman, Karinna Nunez, Sharon Killeen, Tamia Rudnicky, Julie Bradshaw, Kory Angstadt, Karen Duhring, Kallie Brown, Jessica Hendricks, David Weiss, Carl Hershner Jan 2017

Gis Data: King George County, Virginia Tidal Marsh Inventory, Marcia Berman, Karinna Nunez, Sharon Killeen, Tamia Rudnicky, Julie Bradshaw, Kory Angstadt, Karen Duhring, Kallie Brown, Jessica Hendricks, David Weiss, Carl Hershner

Data

The 2017 Tidal Marsh Inventory update for King George County, Virginia was generated using on-screen digitizing techniques in the most recent version of ArcGIS® - ArcMap while viewing conditions observed in the most recent imagery from the Virginia Base Mapping Program (VBMP). Dominant plant community types were primarily determined during field surveys from shallow-draft boats moving along the shoreline. Land-based surveys were performed in some locations. One shapefile is developed that portrays tidal marsh areas represented as polygons. A metadata file accompanies the shapefile to define attribute accuracy, data development, and any use restrictions that pertain to the data.


Gis Data: The County Of Isle Of Wight, Virginia Shoreline Management Model, Marcia Berman, Karinna Nunez, Tamia Rudnicky, Julie Bradshaw, Karen Duhring, Kallie Brown, Jessica Hendricks, David Stanhope, Kory Angstadt, Christine Tombleson, David Weiss, Carl Hershner Jan 2017

Gis Data: The County Of Isle Of Wight, Virginia Shoreline Management Model, Marcia Berman, Karinna Nunez, Tamia Rudnicky, Julie Bradshaw, Karen Duhring, Kallie Brown, Jessica Hendricks, David Stanhope, Kory Angstadt, Christine Tombleson, David Weiss, Carl Hershner

Data

The Shoreline Management Model is a GIS spatial model that determines appropriate shoreline best management practices using available spatial data and decision tree logic. Available shoreline conditions used in the model include the presence or absence of tidal marshes, beaches, and forested riparian buffers, bank vegetation cover, bank height, wave exposure (fetch), nearshore water depth, and proximity of coastal development to the shoreline. The model output for shoreline best management practices is displayed in the locality Comprehensive Map Viewer. One GIS shapefile is developed that describes two arcs or lines representing practices in the upland area and practices at the …


Using Water Quality Models In Management - A Multiple Model Assessment, Analysis Of Confidence, And Evaluation Of Climate Change Impacts, Isaac Irby Jan 2017

Using Water Quality Models In Management - A Multiple Model Assessment, Analysis Of Confidence, And Evaluation Of Climate Change Impacts, Isaac Irby

Dissertations, Theses, and Masters Projects

Human impacts on the Chesapeake Bay through increased nutrient run-off as a result of land-use change, urbanization, and industrialization, have resulted in a degradation of water quality over the last half-century. These direct impacts, compounded with human-induced climate changes such as warming, rising sea-level, and changes in precipitation, have elevated the conversation surrounding the future of water quality in the Bay. The overall goal of this dissertation project is to use a combination of models and data to better understand and quantify the impact of changes in nutrient loads and climate on water quality in the Chesapeake Bay. This research …


Using High-Resolution Glider Data And Biogeochemical Modeling To Investigate Phytoplankton Variability In The Ross Sea, Daniel Edward Kaufman Jan 2017

Using High-Resolution Glider Data And Biogeochemical Modeling To Investigate Phytoplankton Variability In The Ross Sea, Daniel Edward Kaufman

Dissertations, Theses, and Masters Projects

As Earth’s climate changes, polar environments experience a disproportionate share of extreme shifts. Because the Ross Sea shelf has the highest annual productivity of any Antarctic continental shelf, this region is of particular interest when striving to characterize current and future changes in Antarctic systems. However, understanding of mesoscale variability of biogeochemical patterns in the Ross Sea and how this variability affects assemblage dynamics is incomplete. Furthermore, it is unknown how the Ross Sea may respond to projected warming, reduced summer sea ice concentrations, and shallower mixed layers during the next century. to investigate these dynamics and explore their consequences …


The Role Of Seabed Resuspension On Oxygen And Nutrient Dynamics In Coastal Systems: A Numerical Modeling Study, Julia Miege Moriarty Jan 2017

The Role Of Seabed Resuspension On Oxygen And Nutrient Dynamics In Coastal Systems: A Numerical Modeling Study, Julia Miege Moriarty

Dissertations, Theses, and Masters Projects

Seabed resuspension can impact organic matter fate and water column biogeochemistry in coastal environments. Cycles of erosion and deposition can, for example, affect remineralization rates, seabed-water column fluxes of dissolved oxygen and nutrients, and light attenuation. Yet, models that incorporate both sediment transport and biogeochemical processes are rare, and nearly all neglect the effect of resuspension on oxygen and nutrient dynamics. Development of a novel tool, i.e. a coupled hydrodynamic-sediment transport-biogeochemical model, allowed for an investigation of the role of resuspension on oxygen and nitrogen dynamics within three distinct coastal environments. Called HydroBioSed, the coupled model was built within the …


Gis Data: King George County, Virginia Shoreline Management Model, Marcia Berman, Karinna Nunez, Sharon Killeen, Tamia Rudnicky, Julie Bradshaw, Kory Angstadt, Karen Duhring, Kallie Brown, Jessica Hendricks, David Weiss, Carl Hershner Jan 2017

Gis Data: King George County, Virginia Shoreline Management Model, Marcia Berman, Karinna Nunez, Sharon Killeen, Tamia Rudnicky, Julie Bradshaw, Kory Angstadt, Karen Duhring, Kallie Brown, Jessica Hendricks, David Weiss, Carl Hershner

Data

The Shoreline Management Model is a GIS spatial model that determines appropriate shoreline best management practices using available spatial data and decision tree logic. Available shoreline conditions used in the model include the presence or absence of tidal marshes, beaches, and forested riparian buffers, bank vegetation cover, bank height, wave exposure (fetch), nearshore water depth, and proximity of coastal development to the shoreline. The model output for shoreline best management practices is displayed in the locality Comprehensive Map Viewer. One GIS shapefile is developed that describes two arcs or lines representing practices in the upland area and practices at the …


Gis Data: Surry County, Virginia Tidal Marsh Inventory, Marcia Berman, Karinna Nunez, Sharon Killeen, Tamia Rudnicky, Julie G. Bradshaw, Karen Duhring, Kallie Brown, Jessica Hendricks, David Stanhope, David Weiss, Carl Hershner Jan 2017

Gis Data: Surry County, Virginia Tidal Marsh Inventory, Marcia Berman, Karinna Nunez, Sharon Killeen, Tamia Rudnicky, Julie G. Bradshaw, Karen Duhring, Kallie Brown, Jessica Hendricks, David Stanhope, David Weiss, Carl Hershner

Data

The 2017 Tidal Marsh Inventory update for Surry County, Virginia was generated using on-screen digitizing techniques in the most recent version of ArcGIS® - ArcMap while viewing conditions observed in the most recent imagery from the Virginia Base Mapping Program (VBMP). Dominant plant community types were primarily determined during field surveys from shallow-draft boats moving along the shoreline. Land-based surveys were performed in some locations. One shapefile is developed that portrays tidal marsh areas represented as polygons. A metadata file accompanies the shapefile to define attribute accuracy, data development, and any use restrictions that pertain to the data.


Gis Data: The County Of Chesterfield And The Cities Of Colonial Heights, Petersburg, And Richmond, Virginia Tidal Marsh Inventory, Marcia Berman, Karinna Nunez, Sharon Killeen, Tamia Rudnicky, Julie Bradshaw, Karen Duhring, Kallie Brown, Jessica Hendricks, David Weiss, Carl Hershner Jan 2017

Gis Data: The County Of Chesterfield And The Cities Of Colonial Heights, Petersburg, And Richmond, Virginia Tidal Marsh Inventory, Marcia Berman, Karinna Nunez, Sharon Killeen, Tamia Rudnicky, Julie Bradshaw, Karen Duhring, Kallie Brown, Jessica Hendricks, David Weiss, Carl Hershner

Data

The 2017 Tidal Marsh Inventory update for the County of Chesterfield and the Cities of Colonial Heights, Petersburg, and Richmond, Virginia was generated using on-screen digitizing techniques in the most recent version of ArcGIS® - ArcMap while viewing conditions observed in the most recent imagery from the Virginia Base Mapping Program (VBMP). Dominant plant community types were primarily determined during field surveys from shallow-draft boats moving along the shoreline. Land-based surveys were performed in some locations. One shapefile is developed that portrays tidal marsh areas represented as polygons. A metadata file accompanies the shapefile to define attribute accuracy, data development, …


Gis Data: The County Of Spotsylvania Shoreline Inventory Report, Marcia Berman, Karinna Nunez, Tamia Rudnicky, Julie Bradshaw, Karen Duhring, Kallie Brown, Jessica Hendricks, David Weiss, Carl Hershner Jan 2017

Gis Data: The County Of Spotsylvania Shoreline Inventory Report, Marcia Berman, Karinna Nunez, Tamia Rudnicky, Julie Bradshaw, Karen Duhring, Kallie Brown, Jessica Hendricks, David Weiss, Carl Hershner

Data

The 2017 Inventory for Spotsylvania County was generated using on-screen, digitizing techniques in ArcGIS® -ArcMap v10.4.1while viewing conditions observed in Bing high resolution oblique imagery, Google Earth, and2013imagery from the Virginia Base Mapping Program (VBMP).Four GIS shapefiles are developed. The first describes land use and bank conditions (Spotsylvania_lubc_2017). The second portrays the presence of beaches (Spotsylvania_beaches_2017). The third reports shoreline structures that are described as arcs or lines (e.g. riprap)(Spotsylvania_sstru_2017). The final shapefile includes all structures that are represented as points (e.g. piers)(Spotsylvania_astru_2017).The metadata file accompanies the shapefiles and defines attribute accuracy, data development, and any use restrictions that pertain …


Gis Data: The County Of Spotsylvania, Virginia Tidal Marsh Inventory, Marcia Berman, Karinna Nunez, Tamia Rudnicky, Julie G. Bradshaw, Karen Duhring, Kallie Brown, Jessica Hendricks, David Weiss, Carl Hershner Jan 2017

Gis Data: The County Of Spotsylvania, Virginia Tidal Marsh Inventory, Marcia Berman, Karinna Nunez, Tamia Rudnicky, Julie G. Bradshaw, Karen Duhring, Kallie Brown, Jessica Hendricks, David Weiss, Carl Hershner

Data

The 2017 Tidal Marsh Inventory update for the County of Spotsylvania, Virginia was generated using on-screen digitizing techniques in the most recent version of ArcGIS® - ArcMap while viewing conditions observed in the most recent imagery from the Virginia Base Mapping Program (VBMP). Dominant plant community types were primarily determined during field surveys from shallow-draft boats moving along the shoreline. Land-based surveys were performed in some locations. One shapefile is developed that portrays tidal marsh areas represented as polygons. A metadata file accompanies the shapefile to define attribute accuracy, data development, and any use restrictions that pertain to the data.


Gis Data: The County Of Spotsylvania, Virginia Shoreline Manangement Model, Marcia Berman, Karinna Nunez, Tamia Rudnicky, Julie Bradshaw, Karen Duhring, Kallie Brown, Jessica Hendricks, David Weiss, Carl Hershner Jan 2017

Gis Data: The County Of Spotsylvania, Virginia Shoreline Manangement Model, Marcia Berman, Karinna Nunez, Tamia Rudnicky, Julie Bradshaw, Karen Duhring, Kallie Brown, Jessica Hendricks, David Weiss, Carl Hershner

Data

The Shoreline Management Model is a GIS spatial model that determines appropriate shoreline best management practices using available spatial data and decision tree logic. Available shoreline conditions used in the model include the presence or absence of tidal marshes, beaches, and forested riparian buffers, bank vegetation cover, bank height, wave exposure (fetch), nearshore water depth, and proximity of coastal development to the shoreline. The model output for shoreline best management practices is displayed in the locality Comprehensive Map Viewer. One GIS shapefile is developed that describes two arcs or lines representing practices in the upland area and practices at the …


Gis Data: The County Of Isle Of Wight, Virginia Shoreline Inventory Report, Marcia Berman, Karinna Nunez, Tamia Rudnicky, Julie Bradshaw, Karen Duhring, Kallie Brown, Jessica Hendricks, David Stanhope, Kory Angstadt, Christine Tombleson, David Weiss, Carl Hershner Jan 2017

Gis Data: The County Of Isle Of Wight, Virginia Shoreline Inventory Report, Marcia Berman, Karinna Nunez, Tamia Rudnicky, Julie Bradshaw, Karen Duhring, Kallie Brown, Jessica Hendricks, David Stanhope, Kory Angstadt, Christine Tombleson, David Weiss, Carl Hershner

Data

The 2017 Inventory for the Isle of Wight County was generated using on-screen, digitizing techniques in ArcGIS® -ArcMap v10.4.1while viewing conditions observed in Bing high resolution oblique imagery, Google Earth, and2013imagery from the Virginia Base Mapping Program (VBMP). Four GIS shapefiles are developed. The first describes land use and bank conditions (IsleofWight_lubc_2017). The second portrays the presence of beaches (IsleofWight_beaches_2017). The third reports shoreline structures that are described as arcs or lines(e.g. riprap)(IsleofWight_sstru_2017). The final shapefile includes all structures that are represented as points(e.g. piers)(IsleofWight_astru_2017).The metadata file accompanies the shapefiles and defines attribute accuracy, data development, and any use restrictions …


Gis Data: The County Of Isle Of Wight, Virginia Tidal Marsh Inventory, Marcia Berman, Karinna Nunez, Tamia Rudnicky, Julie Bradshaw, Karen Duhring, Kallie Brown, Jessica Hendricks, David Stanhope, Kory Angstadt, Christine Tombleson, David Weiss, Carl Hershner Jan 2017

Gis Data: The County Of Isle Of Wight, Virginia Tidal Marsh Inventory, Marcia Berman, Karinna Nunez, Tamia Rudnicky, Julie Bradshaw, Karen Duhring, Kallie Brown, Jessica Hendricks, David Stanhope, Kory Angstadt, Christine Tombleson, David Weiss, Carl Hershner

Data

The 2017 Tidal Marsh Inventory update for the County of Isle of Wight, Virginia was generated using on-screen digitizing techniques in the most recent version of ArcGIS® - ArcMap while viewing conditions observed in the most recent imagery from the Virginia Base Mapping Program (VBMP). Dominant plant community types were primarily determined during field surveys from shallow-draft boats moving along the shoreline. Land-based surveys were performed in some locations. One shapefile is developed that portrays tidal marsh areas represented as polygons. A metadata file accompanies the shapefile to define attribute accuracy, data development, and any use restrictions that pertain to …


2016 Aerial Imagery Acquired To Monitor The Distribution And Abundance Of Submerged Aquatic Vegetation In Chesapeake Bay And Coastal Bays, Robert J. Orth, David J. Wilcox, Jennifer R. Whiting, Anna K. Kenne, Erica R. Smith, L. Nagey Jan 2017

2016 Aerial Imagery Acquired To Monitor The Distribution And Abundance Of Submerged Aquatic Vegetation In Chesapeake Bay And Coastal Bays, Robert J. Orth, David J. Wilcox, Jennifer R. Whiting, Anna K. Kenne, Erica R. Smith, L. Nagey

Data

Multispectral aerial imagery acquired in 2016 to monitor the distribution and abundance of submerged aquatic vegetation in Chesapeake Bay and coastal bays.


Associated Dataset: Assimilating Bio-Optical Glider Data During A Phytoplankton Bloom In The Southern Ross Sea, Daniel E. Kaufman, Marjorie A.M. Friedrichs, John C.P. Hemmings, Walker O. Smith Jan 2017

Associated Dataset: Assimilating Bio-Optical Glider Data During A Phytoplankton Bloom In The Southern Ross Sea, Daniel E. Kaufman, Marjorie A.M. Friedrichs, John C.P. Hemmings, Walker O. Smith

Data

No abstract provided.


Gis Data: City Of Fredericksburg,Virginia, Shoreline Inventory, Marcia Berman, Karinna Nunez, Sharon Killeen, Tamia Rudnicky, Julie Bradshaw, Karen Duhring, Kallie Brown, Jessica Hendricks, David Weiss, Carl Hershner Jan 2017

Gis Data: City Of Fredericksburg,Virginia, Shoreline Inventory, Marcia Berman, Karinna Nunez, Sharon Killeen, Tamia Rudnicky, Julie Bradshaw, Karen Duhring, Kallie Brown, Jessica Hendricks, David Weiss, Carl Hershner

Data

The 2017 Inventory for the City of Fredericksburg was generated using on-screen, digitizing techniques in ArcGIS® -ArcMap v10.4.1 while viewing conditions observed in Bing high resolution oblique imagery, Google Earth, and 2013 imagery from the Virginia Base Mapping Program (VBMP).Four GIS shapefiles are developed. The first describes land use and bank conditions (Fredericksburg_lubc_2017). The second portrays the presence of beaches (Fredericksburg_beaches_2017). The third reports shoreline structures that are described as arcs or lines(e.g. riprap)(Fredericksburg _sstru_2017). The final shapefile includes all structures that are represented as points(e.g. piers)(Fredericksburg _astru_2017).The metadata file accompanies the shapefiles and defines attribute accuracy, data development, and …


Gis Data: Surry County, Virginia Shoreline Inventory Report, Marcia Berman, Karinna Nunez, Sharon Killeen, Tamia Rudnicky, Julie Bradshaw, Karen Duhring, Kallie Brown, Jessica Hendricks, David Stanhope, David Weiss, Carl Hershner Jan 2017

Gis Data: Surry County, Virginia Shoreline Inventory Report, Marcia Berman, Karinna Nunez, Sharon Killeen, Tamia Rudnicky, Julie Bradshaw, Karen Duhring, Kallie Brown, Jessica Hendricks, David Stanhope, David Weiss, Carl Hershner

Data

The 2017 Inventory for Surry County was generated using on-screen, digitizing techniques in ArcGIS® -ArcMap v10.4.1 while viewing conditions observed in Bing high resolution oblique imagery, Google Earth, and 2013 imagery from the Virginia Base Mapping Program (VBMP).Four GIS shapefiles are developed.The first describes land use and bank conditions (Surry_lubc_2017). The second portrays the presence of beaches (Surry_beaches_2017). The third reports shoreline structures that are described as arcs or lines(e.g. riprap)(Surry_sstru_2017). The final shapefile includes all structures that are represented as points(e.g. piers)(Surry_astru_2017).The metadata file accompanies the shapefiles and defines attribute accuracy, data development, and any use restrictions that pertain …


Gis Data: King George County, Virginia Shoreline Inventory Report, Marcia Berman, Karinna Nunez, Sharon A. Killeen, Tamia Rudnicky, Julie G. Bradshaw, Kory Angstadt, Karen A. Duhring, Kallie Brown, Jessica Hendricks, David Weiss, Carl Hershner Jan 2017

Gis Data: King George County, Virginia Shoreline Inventory Report, Marcia Berman, Karinna Nunez, Sharon A. Killeen, Tamia Rudnicky, Julie G. Bradshaw, Kory Angstadt, Karen A. Duhring, Kallie Brown, Jessica Hendricks, David Weiss, Carl Hershner

Data

The 2017 Inventory for King George County was generated using on-screen, digitizing techniques in ArcGIS® -ArcMap v10.4.1 while viewing conditions observed in Bing high resolution oblique imagery, Google Earth, and 2013 imagery from the Virginia Base Mapping Program (VBMP).Four GIS shapefiles are developed. The first describes land use and bank conditions (King_George_lubc_2017). The second portrays the presence of beaches (King_George _beaches_2017). The third reports shoreline structures that are described as arcs or lines(e.g. riprap)(King_George _sstru_2017). The final shapefile includes all structures that are represented as points(e.g. piers)(King_George_astru_2017).The metadata file accompanies the shapefiles and defines attribute accuracy, data development, and any …


Associated Dataset: Climate Change Impacts On Southern Ross Sea Phytoplankton Composition, Productivity And Export, Daniel E. Kaufman, Marjorie A.M. Friedrichs, Walker O. Smith Jr., Eileen E. Hofmann, Michael S. Dinniman, John C.P. Hemmings Jan 2017

Associated Dataset: Climate Change Impacts On Southern Ross Sea Phytoplankton Composition, Productivity And Export, Daniel E. Kaufman, Marjorie A.M. Friedrichs, Walker O. Smith Jr., Eileen E. Hofmann, Michael S. Dinniman, John C.P. Hemmings

Data

This dataset includes data used in the publication Kaufman et al., 2017, JGR-Oceans, which investigates how these climatic changes in the Ross Sea, Antarctica, may alter phytoplankton composition, primary productivity and export. A one-dimensional version of the Model of Ecosystem Dynamics, nutrient Utilisation, Sequestration and Acidification was adapted for use in the Ross Sea (MEDUSA-RS). Glider measurements were used to force MEDUSA-RS, which includes diatoms and both solitary and colonial forms of Phaeocystis antarctica. Model performance was evaluated with glider observations, and experiments were conducted using projections of physical drivers for mid- and late-21st century. Additional scenarios examined the …


Catch The King Tide 2017 Data: Virginia Beach, Virginia, Jon Derek Loftis Jan 2017

Catch The King Tide 2017 Data: Virginia Beach, Virginia, Jon Derek Loftis

Data

No abstract provided.


Catch The King Tide 2017 Data: Chesapeake, Virginia, Jon Derek Loftis Jan 2017

Catch The King Tide 2017 Data: Chesapeake, Virginia, Jon Derek Loftis

Data

"Catch the King" was a citizen science GPS data collection effort centered in Hampton Roads, VA, that sought to map the King Tide's maximum inundation extents with the goal of validating and improving predictive models for future forecasting of increasingly pervasive "nuisance" flooding. GPS data points were collected by volunteers to effectively breadcrumb/trace the high water line by pressing the 'Save Data' button in the Sea Level Rise App every few steps along the water's edge during the high tide on the morning of Nov. 5th, 2017.

Response from the event's dedicated volunteers, fueled by the local media …


Catch The King Tide 2017 Data: Newport News, Virginia, Jon Derek Loftis Jan 2017

Catch The King Tide 2017 Data: Newport News, Virginia, Jon Derek Loftis

Data

"Catch the King" was a citizen science GPS data collection effort centered in Hampton Roads, VA, that sought to map the King Tide's maximum inundation extents with the goal of validating and improving predictive models for future forecasting of increasingly pervasive "nuisance" flooding. GPS data points were collected by volunteers to effectively breadcrumb/trace the high water line by pressing the 'Save Data' button in the Sea Level Rise App every few steps along the water's edge during the high tide on the morning of Nov. 5th, 2017.

Response from the event's dedicated volunteers, fueled by the local media …


Catch The King Tide 2017 Data: York & Poquoson, Virginia, Jon Derek Loftis Jan 2017

Catch The King Tide 2017 Data: York & Poquoson, Virginia, Jon Derek Loftis

Data

"Catch the King" was a citizen science GPS data collection effort centered in Hampton Roads, VA, that sought to map the King Tide's maximum inundation extents with the goal of validating and improving predictive models for future forecasting of increasingly pervasive "nuisance" flooding. GPS data points were collected by volunteers to effectively breadcrumb/trace the high water line by pressing the 'Save Data' button in the Sea Level Rise App every few steps along the water's edge during the high tide on the morning of Nov. 5th, 2017.

Response from the event's dedicated volunteers, fueled by the local media …


Catch The King Tide 2017 Data: Norfolk, Virginia, Jon Derek Loftis Jan 2017

Catch The King Tide 2017 Data: Norfolk, Virginia, Jon Derek Loftis

Data

"Catch the King" was a citizen science GPS data collection effort centered in Hampton Roads, VA, that sought to map the King Tide's maximum inundation extents with the goal of validating and improving predictive models for future forecasting of increasingly pervasive "nuisance" flooding. GPS data points were collected by volunteers to effectively breadcrumb/trace the high water line by pressing the 'Save Data' button in the Sea Level Rise App every few steps along the water's edge during the high tide on the morning of Nov. 5th, 2017.

Response from the event's dedicated volunteers, fueled by the local media …


Assessment Of Critical Habitats For Recovering The Chesapeake Bay Atlantic Sturgeon Distinct Population Segment, Bob Greenlee, David H. Secor, Greg C. Garman, Matthew Balazak, Eric J. Hilton, Matthew T. Fisher Jan 2017

Assessment Of Critical Habitats For Recovering The Chesapeake Bay Atlantic Sturgeon Distinct Population Segment, Bob Greenlee, David H. Secor, Greg C. Garman, Matthew Balazak, Eric J. Hilton, Matthew T. Fisher

Reports

The states of Virginia and Maryland along with Virginia Commonwealth University (VCU), Virginia Institute of Marine Science (VIMS) and University of Maryland Center for Environmental Science (UMCES) partnered to assess critical habitat for recovering the Chesapeake Bay Atlantic sturgeon (Acipenser oxyrinchus oxyrinchus) distinct population segment. The primary objectives were to assess reproductive habitat in the James River, nursery habitat in the James and York Rivers and the degree of dependence of those populations to habitat in the Chesapeake Bay.