HPLC-Based Detection of Two Distinct Red Tide Causative Species (Mesodinium rubrum and Margalefidinium polykrikoides) in the South Sea of Korea

Abstract

Various approaches have been applied to red tide monitoring in Korea since reliable information on phytoplankton communities is crucial. In this study, we employed a high-performance liquid chromatography (HPLC) method to analyze two types of red tide, Mesodinium rubrum and Margalefidinium polykrikoides (also known as Cochlodinium polykrikoides), along the southern coasts of Korea. During the M. rubrum red tide on 8 August 2022, an unusual dominance of cryptophytes was observed, being the most dominant phytoplankton group. A significant positive correlation was found between alloxanthin concentrations, a marker pigment of cryptophytes, and M. rubrum cell numbers (p < 0.01, r = 0.830), indicating that HPLC-derived alloxanthin concentrations can serve as a valuable indicator for identifying red tides caused by M. rubrum and estimating cell numbers. However, it is crucial to consider the temporal dynamics of the prey–predator relationship between cryptophytes and M. rubrum. Further investigation is required to understand the environmental conditions that promote cryptophyte predominance and their role in M. rubrum red tide development. In the second field campaign on 29 August 2022, we observed a significant correlation between the concentration of peridinin, a marker pigment for dinoflagellates, and M. polykrikoides cell numbers (p < 0.01, r = 0.663), suggesting that peridinin can serve as a reliable indicator of M. polykrikoides red tides. In conclusion, HPLC-derived pigments, namely alloxanthin and peridinin, can be used to effectively monitor red tides caused by M. rubrum and M. polykrikoides, respectively. However, to overcome certain methodological limitations of HPLC, future studies should explore additional markers or analytical techniques capable of differentiating M. polykrikoides from other coexisting dinoflagellate species. Furthermore, the broad applicability of our method requires thorough investigation in diverse ecosystems to fully comprehend its scope and limitations. Future research should focus on evaluating the method’s efficacy in different contexts, accounting for the distinct traits of the ecosystems under consideration.