Toward a synthesis of phytoplankton community composition methods for global‐scale application

Author:

Kramer Sasha J.1ORCID,Bolaños Luis M.2ORCID,Catlett Dylan3ORCID,Chase Alison P.4ORCID,Behrenfeld Michael J.5ORCID,Boss Emmanuel S.6ORCID,Crockford E. Taylor3ORCID,Giovannoni Stephen J.7ORCID,Graff Jason R.5ORCID,Haëntjens Nils6ORCID,Karp‐Boss Lee6ORCID,Peacock Emily E.3ORCID,Roesler Collin S.8ORCID,Sosik Heidi M.3ORCID,Siegel David A.1ORCID

Affiliation:

1. Earth Research Institute, University of California Santa Barbara Santa Barbara California USA

2. School of Biosciences, University of Exeter Exeter UK

3. Biology Department Woods Hole Oceanographic Institution Woods Hole Massachusetts USA

4. Applied Physics Laboratory, University of Washington Seattle Washington USA

5. Department of Botany and Plant Pathology, Oregon State University Corvallis Oregon USA

6. School of Marine Sciences, University of Maine Orono Maine USA

7. Department of Microbiology Oregon State University Corvallis Oregon USA

8. Earth and Oceanographic Science Department, Bowdoin College Brunswick Maine USA

Abstract

AbstractThe 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 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.

Funder

TED

National Aeronautics and Space Administration

National Defense Science and Engineering Graduate

Simons Foundation

Publisher

Wiley

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