Integrating high-throughput sequencing observations into remotely sensible phytoplankton functional type determinations
Integrating high-throughput sequencing observations into remotely sensible phytoplankton functional type determinations
Abstract:
Phytoplankton community composition plays an integral role in the structure and function of marine ecosystems as different phytoplankton species and functional groups exert variable impacts on marine food webs and biogeochemical cycles. Ocean color remote sensing currently offers the only feasible method for continuously monitoring phytoplankton functional type (PFT) variations on large spatiotemporal scales. Current ocean color PFT algorithms are validated almost exclusively with High Performance Liquid Chromatography (HPLC) determinations of phytoplankton biomarker pigment concentrations. However, HPLC pigments are associated with relatively high taxonomic ambiguity, and uncertainty in the relationships of pigment concentrations with carbon biomass, cell abundances, and/or primary production. Here, we use simultaneous observations of HPLC pigment concentrations and Illumina sequencing of the V9 hypervariable region of the 18S rRNA gene of phytoplankton to explore sources of uncertainty in PFT determinations in the Santa Barbara Channel, CA (SBC). While positive relationships between HPLC- and sequencing-derived abundances are generally observed for the major SBC PFTs (diatoms, dinoflagellates, prymnesiophytes, and green algae), large discrepancies between the two methods are also found for most PFTs. For diatom and dinoflagellate abundances, these discrepancies are explained by the taxonomic ambiguity of biomarker pigments; dinoflagellates containing the diatom biomarker pigment are frequently (and unexpectedly) abundant in the SBC. Large discrepancies observed for prymnesiophytes and green algae are more difficult to explain. Nonetheless, in most cases, the two methods produce qualitatively similar patterns of community dissimilarity and distinguish ~3-4 unique community states. Our results have important implications for coherently defining “remotely sensible” PFT indices based on the strengths and weaknesses of the validation data.