Phytoplankton communities quantified from hyperspectral ocean reflectance correspond to pigment-based communities

Abstract

Community detection analysis is a powerful tool to separate groups of samples that are similar based on their composition. Here, we use a paired global dataset of in-water hyperspectral remote sensing reflectance (Rrs) spectra and high-performance liquid chromatography (HPLC) pigment concentrations to investigate the similarity in phytoplankton composition of the communities detected from each method. Samples were separated into optical communities using network-based community detection analysis applied to the Rrs residual (δRrs), which is calculated by subtracting a modeled hyperspectral Rrs spectrum from a measured hyperspectral Rrs spectrum. The δRrs spectrum accentuates short spectral scale features (<=10 nm) that should be related to phytoplankton pigment composition metricsTo test whether these optical communities correspond to phytoplankton communities, we also used network-based community detection analysis to separate HPLC pigment-based communities from twelve accessory pigment ratios to total chlorophyll-a. Our results demonstrate that three distinct phytoplankton communities can be separated from both hyperspectral Rrs data and HPLC pigment data and that a majority of these samples (74%) were assigned to the same communities. Differences in community assignment were also identified and potential sources for discrepancies were discussed. Importantly, the optical communities assigned here offer a new tool for assessing phytoplankton community composition on global scales using hyperspectral Rrs observations, such as those provided by the Ocean Color Instrument (OCI) on NASA’s new Plankton, Aerosol, Cloud, ocean Ecosystem (PACE) satellite.