POSTER SESSION 1
15:30–17:30, Monday, September 14
Poster Session | 1 | 2 | 3 | 4 | Schedule at a Glance
ABSTRACT 1116 | POSTER 117
MODELING SURFACE OCEAN EUKARYOTIC PHYTOPLANKTON COMMUNITY COMPOSITION FROM 18S RRNA GENE SEQUENCING WITH IN SITU HYPERSPECTRAL REMOTE SENSING REFLECTANCE
Capturing coherent patterns in surface ocean phytoplankton community composition (PCC) is essential to describe changes in the global ocean from the cell level to the Earth system level. A major challenge remains in balancing the taxonomic diversity seen with in situ methods (on micron scales to the species level) with the spatiotemporal variability seen by ocean color satellites (on kilometer scales to the group level). Ultimately, these observations must be combined to characterize PCC on the scales that shape marine ecosystems. Phytoplankton pigments naturally connect PCC to ocean color, explored via models such as the Spectral Derivative Pigments (SDP) algorithm. SDP calculates 13 phytoplankton pigment concentrations (corresponding to five groups) from hyperspectral remote sensing reflectance (Rrs). Pigments are limited in taxonomic resolution, but metabarcoding approaches like sequencing the 18S rRNA gene reveal thousands of taxa to the species level. Here, we tested the coherence between optics and genes by compiling a global, coincident dataset of hyperspectral Rrs and 18S rRNA gene sequences. We used the Rrs residual (dRrs) from SDP to model the relative contributions of 13 eukaryotic phytoplankton classes identified from metabarcoding with high confidence (R2 = 0.53-0.8). The wavelength-specific model coefficients for the 18S rRNA gene-based groups were highly correlated with the model coefficients for the corresponding pigment groups, demonstrating the strength of the signal that emerges by magnifying the PCC component of Rrs. This work provides an initial proof-of-concept with a small (N = 40) but robust dataset for detecting eukaryotic PCC “beyond pigments” in the PACE era.
Sasha Kramer, Boston University, [email protected], https://orcid.org/0000-0002-9944-6779
Roy El Hourany, Laboratoire d’Océanologie et de Geosciences (LOG), [email protected], https://orcid.org/0000-0002-6454-1645
Poster Session | 1 | 2 | 3 | 4 | Schedule at a Glance
