85 
shift toward a large component of blue-green algae. Blue-green algae increase in 
abundance during mid to late summer, particularly in tidal-fresh to low-salinity habi¬ 
tats. The calibration data from both the continuous monitors and the Dataflow water 
quality mapping show that the negative bias of the in situ measure becomes greater 
in summer. It was determined that two season groups would be needed. 
It must be recognized that forming two season groups implements a model that 
captures the average condition, but may not capture the condition that exists in a 
particular tributary on a given date. The seasonal appearance of blue-green algae is 
not the same across tributaries and not even the same within a tributary from year to 
year. Even if the model predictions agree well with the observed data for the past 
three years, it is quite possible that a blue-green bloom could form at some unusual 
time of year in the future and lead to biased prediction. Truly reliable calibration of 
in situ chlorophyll to in vitro chlorophyll requires that some information on the 
concentration of blue-green cells be included in the calibration model. 
Geographic Patterns 
Geography is another general factor that may influence the in situ to in vitro chloro¬ 
phyll a relationship. Again, this influence is likely to be a phytoplankton species 
composition effect. Other factors (e.g., turbidity), however, may play a role. It is 
recommended that the analysis model the geography by treating locations (fixed- 
stations for continuous monitors or river systems for Dataflow) as discrete 
categorical predictors. If these predictors are statistically significant, the geography 
portion of the model should be simplified using surrogate variables, such as salinity 
and turbidity. 
Spatial patterns emerge with data set analysis. These patterns, when viewed 
geographically, appear to follow arrangements expected based on phytoplankton 
species composition. In the Virginia Dataflow data, the trend is longitudinal within 
the estuaries. In the tidal-fresh region, the in situ and in vitro measurements appear 
similar, with a negative bias of in situ relative to in vitro emerging in downstream 
stations (Figure VII-12). In the upper tidal Mattaponi River, one region occurs in 
which in situ has a positive bias relative to in vitro. This situation may occur due to 
high background fluorescence from tannins (dissolved organic carbon) in the water. 
In Maryland, the negative bias (yellow squares) appears in regions where blue-green 
populations have been identified; however, the data do not show a longitudinal 
gradient similar to the Virginia data (Figure VII-13). 
Diet Patterns 
In continuous monitoring data, many locations exhibit distinct diel patterns in the in 
situ chlorophyll. This diel pattern often shows that chlorophyll is higher at night and 
lower during the day. Other research has shown that fluorometric chlorophyll read¬ 
ings made in direct sunlight will be biased low because sunlight inhibits 
phytoplankton fluorescence. This finding, coupled with the observed pattern of lower 
in situ chlorophyll during the day, raised the concern that continuous monitoring of 
chapter vii 
Shallow-water Monitoring and Application tor Criteria Assessment 
