Academic Field

Environmental and Earth Sciences, Study, Engineering

Faculty Mentor Name

George Kraemer

Presentation Type

Poster Presentation

Abstract

Nitrogen run off into Long Island Sound (LIS) and resulting eutrophication-driven hypoxia can be effectively mitigated with year round seaweed aquaculture. Geographic information systems (GIS) offers an invaluable tool for optimizing site selection. To maximize on an annual basis both nutrient removal and crop biomass, two species (sugar kelp Saccharina latissima and the red seaweed Gracilaria tikvaiae) were examined in this model. Unrestricted farmable areas of LIS were first identified. Water column data for these areas was then analyzed including; nitrogen, phosphorus, and chlorophyll-a concentrations, as well as temperature, salinity, and dissolved oxygen. Using GIS, seasonal and monthly variations in these water quality parameters allow planners to identify optimum planting times and areas as well as determine site specific crop biomass and nutrient removal capacity.

Keywords

Aquaculture GIS Long Island Sound Nutrient Bio-extraction Kelp Gracilaria

Start Date

10-4-2015 2:00 PM

End Date

10-4-2015 2:45 PM

Location

SERC House of Fields

Share

COinS
 
Apr 10th, 2:00 PM Apr 10th, 2:45 PM

GIS Modeling of Aquaculture Site in Long Island Sound for Nutrient Bio-extraction

SERC House of Fields

Nitrogen run off into Long Island Sound (LIS) and resulting eutrophication-driven hypoxia can be effectively mitigated with year round seaweed aquaculture. Geographic information systems (GIS) offers an invaluable tool for optimizing site selection. To maximize on an annual basis both nutrient removal and crop biomass, two species (sugar kelp Saccharina latissima and the red seaweed Gracilaria tikvaiae) were examined in this model. Unrestricted farmable areas of LIS were first identified. Water column data for these areas was then analyzed including; nitrogen, phosphorus, and chlorophyll-a concentrations, as well as temperature, salinity, and dissolved oxygen. Using GIS, seasonal and monthly variations in these water quality parameters allow planners to identify optimum planting times and areas as well as determine site specific crop biomass and nutrient removal capacity.