Abstract Title

Session S-07E: Aquatic Vegetation

Keywords

Habitat

Start Date

1-5-2014 3:30 PM

End Date

1-5-2014 5:00 PM

Description

We developed a biomass model to support the Puget Sound Partnership’s goal of increasing the area of eelgrass (Zostera marina) in Puget Sound by 20% by 2020. The model has helped with the identification of potential restoration sites by predicting eelgrass growth based upon inputs of light, temperature, salinity and water depth. We built upon a tropical seagrass model first adapted to Z. marina by the US EPA Western Ecology Division. We made further adaptations for Puget Sound, using data on the effects of light, temperature, and salinity on photosynthesis and respiration collected in Sequim Bay and our laboratory. To predict the potential for eelgrass growth, we ran the model using water elevation, temperature, and salinity output from a 3D hydrodynamic model of Puget Sound. Data on turbidity are scarce; we used marine water quality monitoring data to characterize light attenuation for regions with particular water quality characteristics. We found that model predictions were improved by using functions and parameters developed from the local eelgrass population. The model reasonably predicted a ten-week time series of biomass data collected in Sequim Bay. When used as an index of habitat suitability, the model predicted eelgrass cover fairly well in some areas of Puget Sound (e.g. river deltas, Northern Puget Sound) and less well in others (South Sound, highly developed areas of Central Puget Sound). Model results were used to locate sites for test plantings towards identifying restoration sites. Future applications include estimating restoration potential within smaller regions using local monitoring data. The model would benefit from additional data, including physiological data over a broader range of environmental conditions, subpopulations, and seasons. In addition, improved information on light attenuation is necessary for spatially and temporally comprehensive predictions in areas as complex and variable as Puget Sound.

Share

COinS
 
May 1st, 3:30 PM May 1st, 5:00 PM

Eelgrass (Zostera marina) biomass models for predicting restoration potential in Puget Sound

Room 613-614

We developed a biomass model to support the Puget Sound Partnership’s goal of increasing the area of eelgrass (Zostera marina) in Puget Sound by 20% by 2020. The model has helped with the identification of potential restoration sites by predicting eelgrass growth based upon inputs of light, temperature, salinity and water depth. We built upon a tropical seagrass model first adapted to Z. marina by the US EPA Western Ecology Division. We made further adaptations for Puget Sound, using data on the effects of light, temperature, and salinity on photosynthesis and respiration collected in Sequim Bay and our laboratory. To predict the potential for eelgrass growth, we ran the model using water elevation, temperature, and salinity output from a 3D hydrodynamic model of Puget Sound. Data on turbidity are scarce; we used marine water quality monitoring data to characterize light attenuation for regions with particular water quality characteristics. We found that model predictions were improved by using functions and parameters developed from the local eelgrass population. The model reasonably predicted a ten-week time series of biomass data collected in Sequim Bay. When used as an index of habitat suitability, the model predicted eelgrass cover fairly well in some areas of Puget Sound (e.g. river deltas, Northern Puget Sound) and less well in others (South Sound, highly developed areas of Central Puget Sound). Model results were used to locate sites for test plantings towards identifying restoration sites. Future applications include estimating restoration potential within smaller regions using local monitoring data. The model would benefit from additional data, including physiological data over a broader range of environmental conditions, subpopulations, and seasons. In addition, improved information on light attenuation is necessary for spatially and temporally comprehensive predictions in areas as complex and variable as Puget Sound.