Proteorhodopsins (PR) are retinal-binding membrane proteins that function as light-driven proton pumps to generate energy for metabolism and growth. Recently PR-like genes have been identified in some marine eukaryotic protists, including diatoms, dinoflagellates, haptophytes and cryptophytes. These rhodopsins are homologous to green-light-absorbing, ATP-generating PRs present within bacteria. Here we show that in the oceanic diatom Pseudo-nitzschia granii, PR-like gene and protein expressions increase appreciably under iron limitation. In a survey of available transcriptomes, PRlike genes in diatoms are generally found in isolates from marine habitats where seasonal to chronic growth limitation by the micronutrient iron is prevalent, yet similar biogeographical patterns are not apparent in other phytoplankton taxa. We propose that rhodopsin-based phototrophy could account for a proportion of energy synthesis in marine eukaryotic photoautotrophs, especially when photosynthesis is compromised by low iron availability. This alternative ATP-generating pathway could have significant effects on plankton community structure and global ocean carbon cycling.

Understanding the roles of phytoplankton community composition in the functioning of marine ecosystems and ocean biogeochemical cycles is important for many ocean science problems of societal relevance. Remote sensing currently offers the only feasible method for continuously assessing phytoplankton community structure on regional to global scales. However, methods are presently hindered by the limited spectral resolution of most satellite sensors and by uncertainties associated with deriving quantitative indices of phytoplankton community structure from phytoplankton pigment concentrations. Here we analyze a data set of concurrent phytoplankton pigment concentrations and phytoplankton absorption coefficient spectra from the Santa Barbara Channel, California, to develop novel optical oceanographic models for retrieving metrics of phytoplankton community composition. Cluster and Empirical Orthogonal Function analyses of phytoplankton pigment concentrations are used to define up to five phytoplankton pigment communities as a representation of phytoplankton functional types. Unique statistical relationships are found between phytoplankton pigment communities and absorption features isolated using spectral derivative analysis and are the basis of predictive models. Model performance is substantially better for phytoplankton pigment community indices compared with determinations of the contributions of individual pigments or taxa to chlorophyll a. These results highlight the application of data‐driven chemotaxonomic approaches for developing and validating bio‐optical algorithms and illustrate the potential and limitations for retrieving phytoplankton community composition from hyperspectral satellite ocean color observations.

Advances in high‐throughput DNA sequencing methods reveal the vast diversity of marine protists. Amplicon sequencing of “barcode” genes, such as the 18S small subunit ribosomal RNA gene (henceforth, 18S gene), is a cost‐effective and widely used genetic method for assessing the composition of marine protist communities. This method is now being applied from local to global scales to interrogate the causes and consequences of protist community variations. Significant efforts have been made to validate amplicon methods targeting prokaryotes, but the precision, accuracy, and quantitative potential of 18S gene amplicon sequencing methods for marine protists remain unclear. Here, we use artificial (mock) communities and environmental samples collected from the Santa Barbara Channel, CA to evaluate the precision and accuracy in an amplicon workflow targeting the V9 hypervariable region of the 18S gene for marine protists. Overall, we find that this amplicon workflow has high precision and reasonable accuracy, but the magnitude of analytical uncertainty can increase significantly unless certain procedural issues are avoided. Finally, we demonstrate the value of positive and negative controls in, and the quantitative potential of, amplicon sequencing assessments of marine protist communities.

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Quantifying phytoplankton composition is critical to predicting marine ecosystem structure and function. DNA meta‐barcoding and high‐performance liquid chromatography (HPLC) pigment analysis are two widely used methods for assessing phytoplankton composition; however, comparing their performance has been done only rarely. Here, we integrate DNA meta‐barcoding and HPLC pigment observations to determine eukaryotic phytoplankton composition in the Santa Barbara Channel, California. We find that both methods identify the same four dominant eukaryotic phytoplankton taxa (diatoms, dinoflagellates, chlorophytes, and prymnesiophytes), but inter‐ and intra‐lineage variability in biomarker pigmentation (associated with both a lack of taxonomic specificity of biomarker pigments and intrinsic differences in accessory pigmentation) drives substantial disagreement between the methods. Covariation network analysis circumvents this disagreement and reveals that diverse assemblages of phytoplankton and other protists covary with distinct suites of biomarker pigments. Our results highlight the strengths and weaknesses of each method in characterizing phytoplankton composition and reveal novel insights into phytoplankton physiology that could only be gained by integrating the two methods. Finally, we suggest a path to monitor eukaryotic plankton communities on unprecedented spatiotemporal scales based on the covariation of unique phytoplankton and protistan assemblages with remotely sensible phytoplankton pigment concentrations.