Linking phytoplankton absorption to community composition in Chinese marginal seas

Phytoplankton pigments significantly affect photosynthesis and play a crucial role in regulating marine ecological and biogeochemical processes. Assessment of phytoplankton pigments through optical means is desirable as it may be extended to satellite remote sensing. Here, using an extensive data set of high performance liquid chromatography (HPLC) phytoplankton pigment concentrations and phytoplankton absorption spectra (a(ph)(lambda)) collected through five cruise surveys of the Chinese marginal seas during 2016 and 2017, we explore the potentials of using (a(ph)(lambda) to estimate twenty pigments. Specifically, the first and second derivatives of (a(ph)(lambda) are used to construct an (a(ph)(lambda) - pigment model. The validation of the (a(ph)(lambda)-derived pigment classes, specific to individual phytoplankton community and size groups, shows a generally satisfactory model performance. Additionally, hierarchical cluster analysis also exhibits high similarity within the classification results based on the measured and modeled pigments, where only two pigments were decided into different clusters. Although still preliminary in nature, this proof-of-concept study for the Chinese marginal seas shows the potentials of using satellite remote sensing to assess phytoplankton pigment composition once hyperspectral satellite data are available and (a(ph)(lambda) inversion algorithms are developed and validated.

Automated summary

This study explores the potential of using phytoplankton pigments and absorption spectra to estimate pigment concentrations, showing generally satisfactory model performance based on data collected from Chinese marginal seas. The research demonstrates the possibility of applying satellite remote sensing to assess phytoplankton pigment composition, once hyperspectral satellite data and inversion algorithms are available.