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The in-situ fluorescence method is more susceptible to bias and interferences than 
the laboratory method. Instrument manufacturers recognize that low temperatures 
and high turbidities can affect the fluorescence response and note that different 
phytoplankton species can fluoresce differently in-situ even if the actual chlorophyll 
content is the same (YSI, Inc. 1999). To overcome these effects, it is a common prac¬ 
tice to “calibrate” the in-situ data to the laboratory results by collecting and 
analyzing a set of chlorophyll a samples in the laboratory concurrent with in-situ 
measurements, and establishing a quantitative relationship, or “calibration” between 
the methods via simple linear regression. The calibration may be done for each day 
of sampling but better estimates may result if greater numbers of observations are 
incorporated into a statistical model. 
STATISTICAL MODELING 
The usual approach for calibrating in situ fluorescence to in vitro chlorophyll is to 
develop a model of the form: 
Chlorophyll = f(fluorescence, other variables). Equation 4 
Usually the function f is a linear regression model and the estimates of the coeffi¬ 
cients for this model are obtained using least squares. With this model, a measured 
value of fluorescence may be used as an argument to obtain a predicted chlorophyll 
value. By evaluating other water quality variables measured by the monitoring 
program, it was determined that fluorescence, temperature, turbidity, pH, and 
seasonal variables be used as independent variables as described above. 
One problem with this standard approach is that least squares estimation requires 
that data used as independent variables be measured without error. Clearly this 
assumption is not satisfied for fluorescence. An alternative approach that treats both 
in vitro and in situ chlorophyll as variables with measurement error estimates the 
logarithm of their ratio with a linear regression model: 
Log (R) = LogCChL / Chl 2 ) = f(other variables) Equation 5 
where: 
Chi) = in vitro chlorophyll 
Chl 2 = in situ chlorophyll (note: fluorometers used to collect data for this 
study convert the fluorescence signal to chlorophyll with a standard 
algorithm and this is the number recorded); and 
R = the ratio of these two chlorophyll measures. 
An estimate of in vitro chlorophyll is obtained from the in situ measurement by first 
estimating the logarithm of R given the independent variables, back-transforming to 
obtain an estimate of the ratio, and multiplying the in situ chlorophyll by the ratio to 
estimate the in vitro chlorophyll. 
chapter vii 
Shallow-water Monitoring and Application for Criteria Assessment 
