bioRxivEcology
Toward a synthesis of phytoplankton community composition methods for global-scale application
S. J. Kramer, L. M. Bolanos, D. Catlett, A. P. Chase, M. J. Behrenfeld, E. S. Boss, E. T. Crockford, S. J. Giovannoni, J. R. Graff, N. Haëntjens, L. Karp-Boss, E. E. Peacock, C. S. Roesler, H. M. Sosik, D. A. Siegel
Abstract
The composition of the marine phytoplankton community has been shown to impact many biogeochemical processes and marine ecosystem services. A variety of methods exist to characterize phytoplankton community composition (PCC), with varying degrees of taxonomic resolution. Accordingly, the resulting PCC determinations are dependent on the method used. Here, we use surface ocean samples collected in the North Atlantic and North Pacific Oceans to compare high performance liquid chromatography (HPLC) pigment-based PCC to four other methods: quantitative cell imaging, flow cytometry, and 16S and 18S rRNA amplicon sequencing. These methods allow characterization of both prokaryotic and eukaryotic PCC across a wide range of size classes. PCC estimates of many taxa resolved at the class level (e.g., diatoms) show strong positive correlations across methods, while other groups (e.g., dinoflagellates) are not well captured by one or more methods. Since variations in phytoplankton pigment concentrations are related to changes in optical properties, this combined dataset expands the potential scope of ocean color remote sensing by associating PCC at the genus- and species-level with group- or class-level PCC from pigments. Quantifying the strengths and limitations of pigment-based PCC methods compared to PCC assessments from amplicon sequencing, imaging, and cytometry methods is the first step toward the robust validation of remote sensing approaches to quantify PCC from space.
- assay: metagenomics
- assay: flow cytometry
- assay: imaging
- assay: DNA methylation
- research focus: benchmarking
- approach: statistical model
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