On the Simultaneous Identification and Quantification of Microalgae Populations Based on Fluorometric Techniques

Area of Science:

• Limnology and Aquatic Ecology
• Phycology
• Environmental Monitoring

Background:

• Freshwater reservoirs require effective tools for monitoring phytoplankton structure and detecting harmful algal blooms.
• Cyanobacteria blooms pose significant risks to water quality and ecosystem health.
• Accurate quantification of chlorophyll a (Chl a) from different algal groups is crucial for water quality assessment.

Purpose of the Study:

• To evaluate Beutler's method as a reliable tool for water quality control agencies in early detecting algae blooms, especially cyanobacteria.
• To assess the applicability of Beutler's method for estimating individual algal group contributions to total Chl a in a real freshwater reservoir.
• To construct and utilize norm spectra for key phytoplankton genera in Embalse Río Tercero.

Main Methods:

• Phytoplankton structure analysis using Beutler's method, based on fluorescence excitation spectra.
• Estimation of Chl a concentration per algal group by fitting sample spectra to a linear combination of norm spectra.
• Construction of norm spectra for five dominant algae genera: Microcystis, Chlorella, Cyclotella, Ceratium, and Porphyridium.
• Analysis of reservoir water samples collected between 2014 and 2016.

Main Results:

• Beutler's method demonstrated effectiveness in the rapid identification of algal genera present in the reservoir samples.
• The method tended to overestimate the Chl a content of the identified algal populations.
• Observed overestimation was linked to the significant heterogeneity within algal populations, particularly due to cell aging under environmental conditions.

Conclusions:

• Beutler's method shows promise for quick phytoplankton identification in freshwater systems, aiding water quality monitoring.
• Further refinement of the method is needed to address the overestimation of Chl a, potentially by accounting for cell age and physiological state.
• The study provides insights into the challenges and potential of spectral deconvolution techniques for ecological assessments in reservoirs.