Modeling climate variability effects on eelgrass productivity and resilience
Presentation Abstract
Climate change and variability has the potential to affect the resilience and restoration potential of eelgrass (Zostera marina) both positively and negatively. As part of a project to identify suitable sites for eelgrass restoration in Puget Sound, we have developed a model of eelgrass biomass production using data on eelgrass productivity and respiration collected from local stocks in Sequim Bay, WA. The model uses modeled or observed time series of water depth, light availability, temperature and salinity to predict the potential for eelgrass growth at a site. To test the model’s sensitivity to climate variability, we compared model predictions with 20 years of observations of eelgrass growth rates in Sequim Bay that show correlations to climate factors including the Oceanic Nino Index. We also compared predictions using observed temperature and sea level data from nearby locations with predictions using output from the Salish Sea hydrodynamic model for several years in the time series. The success of the model in predicting observed eelgrass growth depended in part on the ability of observed environmental data to replicate nearshore and intertidal conditions. Our findings highlight the importance of collecting high-quality time series data on environmental conditions and eelgrass productivity in both highly and marginally suitable eelgrass habitats in order to improve and test models and better understand the role of climate in long-term eelgrass dynamics.
Session Title
The Role of Eelgrass Ecosystems in the Salish Sea
Conference Track
Habitat
Conference Name
Salish Sea Ecosystem Conference (2016 : Vancouver, B.C.)
Document Type
Event
Start Date
2016 12:00 AM
End Date
2016 12:00 AM
Location
2016SSEC
Type of Presentation
Oral
Genre/Form
conference proceedings; presentations (communicative events)
Contributing Repository
Digital content made available by University Archives, Heritage Resources, Western Libraries, Western Washington University.
Subjects – Topical (LCSH)
Primary productivity (Biology)--Washington (State)--Puget Sound; Zostera marina--Monitoring--Washington (State)--Puget Sound; Zostera marina--Ecology--Washington (State)--Puget Sound
Geographic Coverage
Salish Sea (B.C. and Wash.); Puget Sound (Wash.)
Rights
This resource is displayed for educational purposes only and may be subject to U.S. and international copyright laws. For more information about rights or obtaining copies of this resource, please contact University Archives, Heritage Resources, Western Libraries, Western Washington University, Bellingham, WA 98225-9103, USA (360-650-7534; heritage.resources@wwu.edu) and refer to the collection name and identifier. Any materials cited must be attributed to the Salish Sea Ecosystem Conference Records, University Archives, Heritage Resources, Western Libraries, Western Washington University.
Type
Text
Language
English
Format
application/pdf
Modeling climate variability effects on eelgrass productivity and resilience
2016SSEC
Climate change and variability has the potential to affect the resilience and restoration potential of eelgrass (Zostera marina) both positively and negatively. As part of a project to identify suitable sites for eelgrass restoration in Puget Sound, we have developed a model of eelgrass biomass production using data on eelgrass productivity and respiration collected from local stocks in Sequim Bay, WA. The model uses modeled or observed time series of water depth, light availability, temperature and salinity to predict the potential for eelgrass growth at a site. To test the model’s sensitivity to climate variability, we compared model predictions with 20 years of observations of eelgrass growth rates in Sequim Bay that show correlations to climate factors including the Oceanic Nino Index. We also compared predictions using observed temperature and sea level data from nearby locations with predictions using output from the Salish Sea hydrodynamic model for several years in the time series. The success of the model in predicting observed eelgrass growth depended in part on the ability of observed environmental data to replicate nearshore and intertidal conditions. Our findings highlight the importance of collecting high-quality time series data on environmental conditions and eelgrass productivity in both highly and marginally suitable eelgrass habitats in order to improve and test models and better understand the role of climate in long-term eelgrass dynamics.
