In vivo fluorometers use chlorophyll
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Abstract a fluorescence (F chl) as a proxy to monitor phytoplankton biomass. However, the fluorescence yield ofF chlis affected by photoprotection processes triggered by increased irradiance (nonphotochemical quenching; NPQ), creating diurnal reductions inF chlthat may be mistaken for phytoplankton biomass reductions. Published correction methods are mostly designed for pelagic oceans and are ill suited for inland waters or for high‐frequency data collection. A machine learning‐based method was developed to correct vertical profiler data from an oligotrophic lake. NPQ was estimated as a percent reduction inF chlby comparing daytime values to mean, unquenched values from the previous night. A random forest regression was trained on sensor data collected coincident withF chl; including solar radiation, water temperature, depth, and dissolved oxygen saturation. The accuracy of the model was assessed using a grouped 10‐fold cross validation (mean absolute error [MAE]: 7.6%; root mean square error [RMSE]: 10.2%), which was then used to correctF chlprofiles. The model also predicted NPQ and corrected unseenF chlprofiles from a future period with excellent results (MAE: 9.0%; RMSE: 14.4%).F chlprofiles were then correlated to laboratory results, allowing corrected profiles to be compared directly to collected samples. The correction reduced error (RMSE) due to NPQ from 0.67μ g L−1to 0.33μ g L−1when compared to uncorrectedF chldata. These results suggest that the use of machine learning models may be an effective way to correct for NPQ and may have universal applicability. -
Abstract To measure chlorophyll
a (Chla ) fluorescence (F chl ), fluorometers use an excitation wavelength that is within the visible spectrum of most zooplankton, and as a result has the potential to cause a phototactic response in zooplankton. The transparent bodies of herbivorous zooplankton may allow viable chlorophylla within an individual's digestive tract to fluoresce in response to sensor excitation light, resulting in measurement bias. To test for this bias, a fully factorial (± zooplankton and ± light) experiment was conducted in an oligotrophic lake. Excitation light from fluorometers triggered a positive phototactic response during nighttime hours, resulting in swarms of zooplankton congregating beneath the sensor. The maximum hourly meanF chl from nighttime/open treatments was higher and more variable than nighttime/zooplankton exclusion treatments, with the greatest single hour difference of 7.34 relative fluorescence units (RFU) vs. 0.26 RFU. In open treatments, sustained periods ofF chl exceeded 31x the values of exclusion treatments. A second series of experiments pulsed excitation lights in alternating periods in order to characterize zooplankton response times. Sensor bias was detected in as little as 20 s after initial illumination. Collectively, these results suggest that swarms of phototactic zooplankton can cause substantial bias inF chl measurements at night. To correct for this bias, post‐processing methods using time series decomposition were demonstrated to remove the majority ofF chl bias.