and the local physical regime (Table 3). Successful model development will require long-term 
continuous data sets using instruments to measure important plant parameters (e.g., spectral 
irradiance, temperature, and salinity). It is critical that monitoring be conducted at appropriate 
temporal and spatial intervals that are relevant to the organism(s) and system(s) in question. 
Development and implementation of any long-term monitoring plan for use in modeling 
activities should be a cooperative effort involving the appropriate personnel (e.g., modelers, 
biologists, and field technicians). 
Field Monitoring 
The purpose of the field monitoring portion of this plan is to collect data on the range of 
responses and variability that are present in coastal systems and to provide input data to generate 
or refine models. Aquatic environments in general, and particularly estuaries, are stochastic 
systems that often exhibit large variations along many temporal and spatial scales. Long-term 
data sets are required to determine if variability expressed in a system is a consequence of natural 
variability (e.g., storm events) or anthropogenic impacts. 
Direct Experimentation (Field and/or Mesocosm Studies) 
One of the most important features of a model is the ability to develop testable hypotheses that 
will provide confidence in the model. In most cases, field experiments would be the preferred 
experimental environment; however, it is often difficult if not impossible to control all of the 
variables in the field (e.g., water column nutrient concentrations). The ability to replicate 
treatments also permits statistical data analysis. Consequently, mesocosm experiments bring 
together the best features of field and laboratory experiments offering environmental parameter 
control and a natural environment, while facilitating quantitative data collection (for review see 
Lain 1990). 
Development of the proposed models would provide testable hypotheses about the influence of 
any number of factors, such as the toxicity thresholds of SA V to various water column and 
sediment constituents (e.g., nitrate, ammonium, or sulfide concentrations). Another example 
would be determination of dessication stress, or sediment and water column anoxia on 
photosynthesis, or the interactions controlling the relationships between nutrients and 
phytoplankton versus epiphytes versus macroalgae versus seagrass. Physical factors such as the 
impact of wave exposure could also be investigated using replicated mesocosm experiments. 
Current Activities 
AED is developing empirical relationships between nitrogen loading and the areal extent of SAV 
normalized to historical SAV habitat extent. MED is investigating the relationship between 
nutrient loading and several quantitative attributes of wetland SAV including: % cover, diversity, 
relative abundance, and maximum depth of macrophyte growth. GED is in the fourth year of 
developing a database of changes on water quality, light availability, and changes in the 
deepwater margin of SAV beds. WED is developing models of seagrass growth and production 
based on field data including seagrass biomass and production, underwater light, and sediment 
biogeochemistiy. Other activities that support this SAV plan include GIS mapping of seagrass 
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