In freshwater ecosystems like rivers and lakes, mechanisms of food source use and energy transfer tend to be cryptic because consumer behavior is not easily observed, and a large pool of potential food sources tend to be present, often being consumed as small, degraded particles. Therefore, there has been little consensus among researchers on whether carbon derived from autochthonous, in-stream primary producers, or allochthonous carbon originating from the surrounding terrestrial environment, is most important in composing the food web base. Amino acid, compound specific stable isotope analysis (AA-CSIA) is a relatively new biochemical technique that offers precise dietary reconstruction by providing an isotopic signature for each amino acid in a tissue sample, allowing the use of food source “fingerprints” as dietary tracers. While AA-CSIA has been successfully established for use in marine systems, the tool has only been recently applied to freshwaters and, therefore, requires a thorough statistical and foundational evaluation. Here, we analyze a large survey of potential freshwater food sources (n=150) for essential AA-CSIA carbon signatures to determine whether or not they are statistically distinguishable from one another and to test the degree to which they can trace through a consumer food web.
Results/Conclusions
A principal component analysis (84.9% variation explained by PC1 and PC2), showed five food source groupings (green algae, cyanobacteria, C3 plants, C4 plants, and CAM plants), with some overlap between green algae and cyanobacteria. A linear discriminant analysis showed the same five food source groupings, and it was able to correctly classify food sources into their respective groups with a 99% probability. Values of linear discriminants showed that, of the 10 essential amino acids, Val, Ile, Leu, and Phe explained the most variation between food source groupings. Additionally, we tested the ability of a Bayesian mixing model (FRUITS) to trace these food source fingerprints through wild-caught bigmouth buffalo (Ictiobus cyprinellus), with results showing basal carbon contributions from both algae and C3 plants. Here, we found that a diverse set of food source genera are statistically distinguishable into major phylogenetic groups by AA-CSIA and that we can trace these food source fingerprints through to a fish consumer. To our knowledge, this is the largest AA-CSIA analysis of freshwater food sources to date. Baseline primary producer signatures gathered as part of this large dataset can be widely applied to future studies, furthering the accessibility and application of AA-CSIA to freshwater systems.