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Amino acid d13C dataset for nearshore marine primary producers

Citation

Elliott Smith, Emma; Fox, Michael; Fogel, Marilyn; Newsome, Seth (2022), Amino acid d13C dataset for nearshore marine primary producers, Dryad, Dataset, https://doi.org/10.5061/dryad.zw3r22897

Abstract

Carbon isotope fingerprinting, or multivariate analysis using δ13C values of individual compounds, is a powerful tool in ecological studies, particularly measurements of essential amino acids (EAA δ13C). Despite the widespread application of this technique, there has been little methodological validation to determine (1) whether multivariate EAA δ13C signatures (fingerprints) of primary producer groups vary across space and time, and (2) what biochemical mechanisms drive these patterns.

Here, we evaluate the spatiotemporal consistency in EAA δ13C fingerprints among nearshore primary producers: Chlorophyta (Ulva sp.), Ochrophyta (kelps), particulate organic matter (POM) and phytoplankton, and Rhodophyta. We analyzed 135 samples from 14 genera collected in Alaska, California, and Chile. The collections included historical museum samples (1896-1980 CE) of the giant kelp, Macrocystis pyrifera. We employed canonical analysis of principal coordinates and generalized linear models (GLMs) to respectively characterize isotopic fingerprints and evaluate the effect of taxonomy, local upwelling regimes, ecological setting, and time on individual EAA δ13C values and associated fingerprints. We also calculated amino acid discrimination values (D13C) to identify key biochemical pathways responsible for these patterns.

We found remarkable consistency in EAA δ13C fingerprints of marine algae across space and through time. Kelps and rhodophytes exhibited statistically distinct multivariate isotopic patterns regardless of geographic location, species identity, or time (kelps). In contrast, isotopic fingerprints of POM/phytoplankton and Ulva overlapped substantially. GLMs indicated that producer family, presumably due to the presence/absence of carbon concentrating mechanisms, and site locality are important determinants of individual amino acid δ13C values. Taxonomy was also a key variable for EAA δ13C fingerprints. The calculated discrimination values suggest variation in (1) metabolism of pyruvate and oxaloacetate-derived amino acids, and (2) production of storage and structural carbohydrates, are responsible for taxonomic differences in isotopic fingerprints. 

We conclude EAA δ13C fingerprinting is a robust method for tracing the contribution of diverse primary producer taxa to coastal food webs. We show that this technique can be applied to modern and historical samples, as well as consumers collected across continental scales. The high fidelity of EAA δ13C multivariate patterns coupled with biochemical mechanisms provides a powerful framework for future studies of carbon flow across broad biogeographical and ecological contexts.

Usage Notes

Taxonomic designations (e.g., Family and Phylum) come from AlgaeBase, as accessed in March 2021. Column 'CCMs' deontes the presence (Y), or absence (N), of carbon concentrating mechanisms in a given taxa. Column 'Ocea' denotes the general oceanography of a region, including downwelling (Down), seasonal upwelling (SeasUp), and consistent upwelling (ConsUp), as well as laboratory cultures (Cultured). Column 'Time' indiactes whether samples are modern, or come from the Smithsonian Insitituion NMNH Botany Collections. The cataloge number for NMNH samples and the associated year of collection can be found in the column 'ID'; for example, sample 'NMNH-71452-MAPY-1896-Bl", comes from NMNH Macrocystis specimen 71452 whichwas collected in CE 1896.

Empty cells (e.g., missing values) represent data that were not determined for a particular isptopic measurement and sample.

Funding

National Science Foundation, Award: GRFP-1418062