1. Post-Calibration of Fluorescence Data from Continuous Monitors (To adjust or not to adjust, and if so, how?) A Gang of N Production Elgin Perry - Statistics Consultant Marcia Olson - NOAA/CBP Beth Ebersole - MD DNR Bill Romano - MD DNR Presented to the Tidal Monitoring and Analysis Workgroup on 3 December 2003

2. (Kim Mikitas data)

3. Tidal cycle Diel cycle

5. log(x/y)=log x - log y LNRAT = LNCHL_F – LNCHL_A

6. Model Evaluated Season Sonde deployed Light Turbidity Log ratio as a function of:

7. Station Signed-rank Test SeasonSondeLightTurbidity Turville CreekP<0.0001NS BishopvilleNS Shelltown0.0042NS CHWSNS Rehobeth0.0008NS ChicamacomicoNS0.01350.0045NS Ben OaksNS 0.0020NS Sherwood0.04250.0316NS0.0276NS WhitehurstNS StoningtonNS Model Results

8. At higher light levels, extractive samples exceed fluorescence data?

9. Fluorescence exceeds extractive at all light levels, so no light effect.

10. Fluorescence exceeds extractive under all light levels, so no light effect.

11. Similar pattern to Turville Creek and Shelltown.

12. Chlorophyll Adjustment Methods Regression method – CF (adj) = ß 0 + ß 1 CF (Model CS = CF) Multiple regression – CF (adj) = ß 0 + ß 1 CF + ß 2 Turb (Model CS = CF, Turbidity) Ratio method – CF (adj) = CF x (CS/CF) Subtract background fluorescence

13. Linear Regression Assumptions Y is linearly related to X Expected value of the error term is zero Constant variance in the error terms, which are uncorrelated Independent variable(s) is measured without error Independent variables are not linearly related

20. Correction Using Ratio of Extractive to In Vivo

22. Conclusions Stop collecting data Full speed ahead (one size fits all) Test various models and select one that minimizes root mean square error on a per station basis Hire an expert to assess covariate measurement error problem Log transform for correction and then back transform