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Peconic Estuary Eelgrass Restoration |
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The purpose of the project was to find sites within the Peconic Estuary which had the highest potential for eelgrass restoration. Through studies and field observations it has been determined that individual areas have differing environmental conditions and therefore exhibit varying potential for eelgrass growth. A GIS database was created, which contained Estuary-wide information on biological, physical and chemical properties of the water. This information was subsequently incorporated into a GIS model which predicts the optimal areas to focus restoration efforts.
The Peconic Estuary Eelgrass Restoration
project was funded
by the National Fish and Wildlife Foundation. |
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The GIS model works by breaking down the 150,000+ acres of the Peconic Estuary into numerous potential restoration sites. Imagine laying a grid over the estuary, with each square being roughly 1.25 acres for a total of 120,000 potential restoration sites. Each grid square has many parameters associated with it, such as water temperature and depth. The goal was to design a model, which based on the assumptions of ideal eelgrass growth conditions, will find the grid sections which most closely match the ideal environment.
The first step in creating the model involves determining if the grid cell encompasses what we call the "exclusive parameters". These are the conditions that a grid cell must meet in order to still be considered a potential restoration site. If it does not meet all of the conditions and would therefore preclude eelgrass growth, the cell is removed from further analysis. The following parameters were used to determine if a grid cell meets the minimum requirements (click to view map):
EXCLUSIVE PARAMETERS
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Depth
(must be between 1.0 - 3.25m) |
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Historical Eelgrass
(must be within 100m of an historical eelgrass bed) |
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Existing Eelgrass
(must not be within 100m of an existing eelgrass bed) |
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Shoreline Hardening (must not be within 15m of a hardened shoreline structure) |
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Mooring Fields
(must not be located within a mooring field) |
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Total Nitrogen
(must be less than or equal to 0.05mg/l) |
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Temperature
(must be less than 28.0°C) |
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Light Extinction
(Kd, must be less than or equal to 0.46) |
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Total Phosphate
(must be less than or equal to 0.08mg/l) |
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| The following figure shows the results of combining the above parameters. A total of 2,174 grid squares (less than 1% of what we started with) were found to be potential eelgrass restoration areas. Since all these squares are located in the Eastern half of the Peconic Estuary, only this area is shown. |

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Results |
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Once we determined where the potential eelgrass restoration areas were (above), we classified them based on which were the most ideal. In this second step, we incorporated the 8 following parameters below into the model. The values within each parameter were assigned scores (e.g., eelgrass survives better in cooler waters, so cooler waters were scored higher). Also, the 8 parameters were weighted based on their perceived importance (e.g., temperature is deemed to be more important then substrate type). Click on the parameters below to view their goegraphical representation.
RANKED PARAMETERS
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Shellfish Closures
(0 or 20pts, areas closed to shellfishing
get 20 pts) |
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Macroalgae
(0 or 10pts, areas without competing macroalgae get 10pts) |
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Substrate
(0-5pts, more ideal substrates (e.g. sand) scored higher ) |
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Wind Exposure
(0-10pts; more sheltered areas scored higher) |
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Temperature
(0-20pts, cooler areas scored higher) |
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Total Nitrogen
(0-10pts, areas with less nitrogen scored higher) |
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Total Phosphates
(0-10pts, areas with less phosphates scored higher) |
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Light Extinction
(0-15pts, areas with more light scored higher) |
| The result is that each of the remaining grid squares received a score between 0 and 100; the closer to 100 the score the more ideal the location is for eelgrass restoration efforts. In the figure to the right, the most ideal areas are in dark green. Areas in yellow, orange, or red are less ideal. |

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Results |
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The Peconic Estuary Eelgrass Restoration database demonstrates the power of utilizing GIS. It allows us to collect and manipulate numerous types of geographically referenced information for the purpose of running complex predictive models. The information generated from the above GIS database and model is currently being applied; several of the areas which ranked the highest are already being actively restored!!
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