12. Stress-Response Approach for Protection of SAV 
12.1 Introduction 
A previous report summarizes EPA research to develop mechanistic modeling approaches for 
examining the sensitivity of seagrasses to nutrient stressors (Kaldy and Eldridge, 2006). Here we use 
the mechanistic Seagrass Stressor-Response Model (SRM) developed by Kaldy and Eldridge (2006) in 
a heuristic fashion to assess the protective capacity of the Percentile approach (see Section 4.4). 
The SRM used the 25 th , median, and 75 th percentile results from the cumulative distribution 
function (CDF’s) developed in Sections 6.2 and 9.2 to determine if these potential criteria are 
protective of seagrass distribution and biomass in Yaquina Estuary. Our approach was to use the 
quartile values from the CDF’s as inputs to the seagrass SRM with the objective of testing which 
values maintained seagrass at present depth distributions and which values resulted in decline of 
seagrass. These evaluations will provide guidance to aid in the selection of water clarity criteria that 
are protective of seagrass habitat in PNW estuaries. The response variables of the SRM model were 
seagrass biomass and carbohydrate content. 
The SRM is composed of a set of mechanistic models that can be run in a variety of 
configurations depending on the study or management goals. The advantage of this approach is that, • 
unlike the regression model approach, we can examine the direct and indirect effects of particular 
environmental conditions. Full model details and validation description are provided by Kaldy and 
Eldridge (2006). 
12.2 Description of Model 
The seagrass SRM was developed through an integrative effort that used a variety of data 
sources such as field studies and manipulative experiments, published literature, and existing and new 
models. A detailed description of the SRM development, calibration and validation is provided by 
Kaldy and Eldridge (2006). Briefly, the SRM is composed of an Allocation Model, a Plant 
Productivity Model and a Sediment Diagenetic Model. The Allocation Model integrates field data and 
provides estimates of carbon, nitrogen and phosphorus fluxes between plant components and the 
environment. These flux rates are then used to parameterize the Plant Productivity Model. The 
seagrass Plant Productivity model predicts above-ground biomass, carbohydrate reserves and plant 
growth in response to nutrients (both water-column and sediment porewater), salinity and underwater 
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