light, and it provides boundary conditions for the Sediment Diagenetic Model. The Sediment 
Diagenetic Model provides estimates of the inorganic chemical environment in the root zone of the 
plant. The build-up or depletion of particular compounds in the sediments may have positive or 
negative effects on seagrass health and production. These models can be run independently or can be 
coupled together and run as the full SRM. Only the plant model configuration was used in the current 
analysis as there were no sediment geochemical data for the upper Yaquina Estuary (Zone 2). 
Calibration data for the plant model are shown in Appendix Figure E. 1. Field and mesocosm 
experiments were used to validate model predictions (Kaldy and Eldridge, 2006). 
The SRM has been used to examine seagrass response to a number of environmental variables 
including nutrients, canopy level irradiance, water turbidity, and organic matter input to sediments. 
The SRM can be used to assess the effectiveness of proposed nutrient loading criteria designed to be 
protective of seagrass. Assessment of the protective capacity of a particular water quality criterion was 
based on evaluation of trends in modeled seagrass biomass and carbohydrate for each depth interval. 
A downward trajectory in simulated biomass indicates that the water quality criterion was not 
protective at that depth. We also looked at the clustering of model outputs to assess breakpoints 
among the depth contours. Large differences in biomass or carbohydrate concentration between 
contours provides an approximation of the depth where conditions become inhospitable. 
Models are simplifications of observed processes; as such they are subject to a number of 
simplifying assumptions and caveats. Further these models are being revised to include new types of 
calibration data that presumably will produce more accurate predictions. For example, the SRM does 
• not include the effects of irradiance attenuation due to epiphytes, algae, self-shading or surface 
reflectance. As a result, the current simulations represent the “best case scenario” for underwater light. 
The model does include the effects of turbidity, nutrients, and salinity (Appendix Figure E.2). 
Furthermore, seagrass physiology was assumed to be similar between Zones 1 and 2. For presentation 
purposes, an upper margin for seagrass distribution of 0.2 m above mean lower low water (MLLW) 
was used; however, there are areas throughout the bay where the upper limit can not easily be defined 
by a single bathymetric level as a result of differential effects of desiccation, erosion, and sediment 
deposition. 
• i- 
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