Inferring phytoplankton community composition with a fatty acid mixing model

Abstract

The taxon specificity of fatty acid composition in algal classes suggests that fatty acids could be used as chemotaxonomic markers for phytoplankton composition. The applicability of phospholipid‐derived fatty acids as chemotaxonomic markers for phytoplankton composition was evaluated by using a Bayesian fatty acid‐based mixing model. Fatty acid profiles from monocultures of chlorophytes, cyanobacteria, diatoms, euglenoids, dinoflagellates, raphidophyte, cryptophytes and chrysophytes were used as a reference library to infer phytoplankton community composition in five moderately humic, large boreal lakes in three different seasons (spring, summer and fall). The phytoplankton community composition was also estimated from microscopic counts. Both methods identified diatoms and cryptophytes as the major phytoplankton groups in the study lakes throughout the sampling period, together accounting for 54–63% of the phytoplankton. In addition, both methods revealed that the proportion of chlorophytes and cyanobacteria was lowest in the spring and increased towards the summer and fall, while dinoflagellates peaked in the spring. The proportion of euglenoids and raphidophytes was less than 8% of the phytoplankton biomass throughout the sampling period. The model estimated significantly lower proportions of chrysophytes in the seston than indicated by microscopic analyses. This is probably because the reference library for chrysophytes included too few taxa. Our results show that a fatty acid‐based mixing model approach is a promising tool for estimating the phytoplankton community composition, while also providing information on the nutritional quality of the seston for consumers. Both the quantity and the quality of seston as a food source for zooplankton were high in the spring; total phytoplankton biomass was ~56 μg C L−1, and the physiologically important polyunsaturated fatty acids 20:5n‐3 and 22:6n‐3 comprised ~22% of fatty acids.

Keywords

• algae
• Bayesian mixing model
• chemotaxonomic marker
• FASTAR
• food quality
• freshwater phytoplankton