Eukaryotic microalgae play critical roles in the structure and function of marine food webs. The contribution of microalgae to food webs can be tracked using compound-specific isotope analysis of amino acids (CSIA-AA). Previous CSIA-AA studies have defined eukaryotic microalgae as a single functional group in food web mixing models, despite their vast taxonomic and ecological diversity. Using controlled cultures, this work characterizes the amino acid δ 13 C (δ 13 C AA ) fingerprints-a multivariate metric of amino acid carbon isotope values-of four major groups of eukaryotic microalgae: diatoms, dinoflagellates, raphidophytes, and prasinophytes. We found excellent separation of essential amino acid δ 13 C (δ 13 C EAA ) fingerprints among four microalgal groups (mean posterior probability reclassification of 99.2 AE 2.9%). We also quantified temperature effects, a primary driver of microalgal bulk carbon isotope variability, on the fidelity of δ 13 C AA fingerprints. A 10 C range in temperature conditions did not have significant impacts on variance in δ 13 C AA values or the diagnostic microalgal δ 13 C EAA fingerprints. These δ 13 C EAA fingerprints were used to identify primary producers at the base of food webs supporting consumers in two contrasting systems: (1) penguins feeding in a diatom-based food web and (2) mixotrophic corals receiving amino acids directly from autotrophic endosymbiotic dinoflagellates and indirectly from water column diatoms, prasinophytes, and cyanobacteria, likely via heterotrophic feeding on zooplankton. The increased taxonomic specificity of CSIA-AA fingerprints developed here will greatly improve future efforts to reconstruct the contribution of diverse eukaryotic microalgae to the sources and cycling of organic matter in food web dynamics and biogeochemical cycling studies.

Foraging habitat selection and diet quality are key factors that influence individual fitness and meta-population dynamics through effects on demographic rates. There is growing evidence that sea turtles exhibit regional differences in somatic growth linked to alternative dispersal patterns during the oceanic life stage. Yet, the role of habitat quality and diet in shaping somatic growth rates is poorly understood. Here, we evaluate whether diet variation is linked to regional growth variation in hawksbill sea turtles (Eretmochelys imbricata), which grow significantly slower in Texas, United States versus Florida, United States, through novel integrations of skeletal growth, gastrointestinal content (GI), and bulk tissue and amino acid (AA)-specific stable nitrogen (δ15N) and carbon (δ13C) isotope analyses. We also used AA δ15N ΣV values (heterotrophic bacterial re-synthesis index) and δ13C essential AA (δ13CEAA) fingerprinting to test assumptions about the energy sources fueling hawksbill food webs regionally. GI content analyses, framed within a global synthesis of hawksbill dietary plasticity, revealed that relatively fast-growing hawksbills stranded in Florida conformed with assumptions of extensive spongivory for this species. In contrast, relatively slow-growing hawksbills stranded in Texas consumed considerable amounts of non-sponge invertebrate prey and appear to forage higher in the food web as indicated by isotopic niche metrics and higher AA δ15N-based trophic position estimates internally indexed to baseline nitrogen isotope variation. However, regional differences in estimated trophic position may also be driven by unique isotope dynamics of sponge food webs. AA δ15N ΣV values and δ13CEAA fingerprinting indicated minimal bacterial re-synthesis of organic matter (ΣV < 2) and that eukaryotic microalgae were the primary energy source supporting hawksbill food webs. These findings run contrary to assumptions that hawksbill diets predominantly comprise high microbial abundance sponges expected to primarily derive energy from bacterial symbionts. Our findings suggest alternative foraging patterns could underlie regional variation in hawksbill growth rates, as divergence from typical sponge prey might correspond with increased energy expenditure and reduced foraging success or diet quality. As a result, differential dispersal patterns may infer substantial individual and population fitness costs and represent a previously unrecognized challenge to the persistence and recovery of this critically endangered species.

The use of stable isotopes of sulfur (δ 34S) to infer avian diets, foraging habitats, and movements is relatively uncommon, resulting in a lack of information on patterns of δ 34S incorporation in avian tissue. In a controlled study of Gentoo Penguins (Pygoscelis papua), we found that diet-tissue isotopic discrimination factors (Δ 34Sdiet-tissue) differed among egg components and feathers synthesized from a common diet, ranging from –0.4 to –1.7‰. We also found that methodical choices such as lipid extraction and prey tissue selection influenced calculated Δ 34Sdiet-tissue values. Specifically, Δ 34Sdiet-tissue values were lower (i.e., more negative) when calculated using whole fish relative to fish muscle and lipid-extraction biased egg yolk, but not fish tissue, δ 34S values. The Δ 34Sdiet-tissue values obtained for Gentoo Penguins fed a marine fish diet were generally lower than those reported for freshwater fish consumption by Double-crested Cormorants (Phalacrocorax auritus), the only other bird species in which Δ 34Sdiet-tissue has been quantified. We found support for the hypothesis that tissue Δ 34Sdiet-tissue values are inversely related to dietary δ 34S values in birds, similar to what has been observed in mammals. Given this relationship, the discrimination factors reported here for Gentoo Penguins may be broadly applicable to other avian species with a similar marine diet. Finally, we provide recommendations for future studies seeking to quantify Δ 34Sdiet-tissue in avian tissues and guidance to allow for greater application of sulfur stable isotope analysis in ornithological research.