Skip to main content

Kristin DeMarco

thumbnail
This dataset provides bi-monthly data on seed biomass collected in shallow water habitats across the fresh to saline gradient at coastal sites in Barataria Bay, Louisiana. This project was co-funded by the Gulf Coast Prairie and the Gulf Coastal Plains and Ozarks Landscape Conservation Cooperatives and the South Central Climate Adaptation Science Center. An alternate reference to this product can be found here: https://www.sciencebase.gov/catalog/item/5a78c158e4b00f54eb1e84a6.
thumbnail
This data set includes bi-monthly data on submerged aquatic vegetation species composition, percent cover, above and below ground biomass and environmental data at coastal sites across the fresh to saline gradient in Barataria Bay, LA. This project was co-funded by the South Central Climate Adaptation Science Center and the Gulf Coast Prairie and the Gulf Coastal Plains and Ozarks Landscape Conservation Cooperatives. An alternate reference to this product can be found here.
Submerged aquatic vegetation (SAV) creates highly productive habitats in coastal areas, providing support for many important species of fish and wildlife. Despite the importance and documented loss of SAV across fresh to marine habitats globally, we lack consistent baseline data on estuarine SAV resources, particularly in the northern Gulf of Mexico (NGOM) estuaries. To understand SAV distribution in the NGOM, SAV biomass and species identity were collected at 384 sites inter-annually (June–September; 2013–2015) from Mobile Bay, Alabama, to San Antonio Bay, Texas, USA. Coastwide, SAV distribution and biomass were consistent across years, covering an estimated 87,000 ha, and supporting approximately 16 ± 1% total...
Categories: Publication; Types: Citation
thumbnail
This dataset provides bi-monthly data on seed biomass collected in shallow water habitats across the fresh to saline gradient at coastal sites in Barataria Bay, Louisiana. This project was co-funded by the South Central Climate Adaptation Science Center and the Gulf Coast Prairie and the Gulf Coastal Plains and Ozarks Landscape Conservation Cooperatives. An alternate reference to this product can be found here.
To generate a down-scaled likelihood occurrence model for the SAV community to predict potential impacts of restoration activities aimed at addressing documented NRDA damage to SAV.
View more...
ScienceBase brings together the best information it can find about USGS researchers and offices to show connections to publications, projects, and data. We are still working to improve this process and information is by no means complete. If you don't see everything you know is associated with you, a colleague, or your office, please be patient while we work to connect the dots. Feel free to contact sciencebase@usgs.gov.