Tracing Carbon Through Lotic Food Webs Using Amino Acid Stable Isotope Analysis

Abstract

Understanding the flow of carbon in ecosystems is important for the conservation and management of diverse organisms and environments. In lotic systems, quantifying the trophic basis of production on which entire food webs rely is a primary research goal because flowing waters are characterized by complex and often cryptic energy pathways. Carbon compound-specific stable isotope analysis of individual amino acids (CSIA-AA) is an emerging tool that allows researchers to obtain more accurate and detailed estimates of basal resource assimilation by consumers. In this dissertation, I first contributed a review of best practices for carbon CSIA-AA to be used by new and current users of the method to lower the barrier of entry into its use and encourage further collaboration. As part of this review, I analyzed a wide variety of potential food resources for freshwater systems. I found that carbon amino acid isotope values (δ13CAA) of broad taxonomic groups of terrestrial plants and aquatic algae were conserved across broad spatiotemporal scales, suggesting that these data can be used by others conducting CSIA-AA studies in similar environments. Second, I conducted a laboratory experiment to investigate whether fungal δ13CAA differed based on the amino acid contents of their media substrates and found evidence for direct uptake of certain essential amino acids by fungi. This finding has implications for the way that researchers incorporate and interpret the role of fungi as a pathway for allochthonous carbon into food webs. Third, I carried out a cross-continental assessment of basal resources supporting fish consumers in streams located in three ecoregions of the understudied temperate steppe biome using CSIA-AA. I found that autochthonous resources provided consistent support for fish production across a wide variety of low-order stream sites, independent of riparian canopy coverage and across a range of hydrogeomorphic conditions, which contributes to our understanding of stream headwaters at the global scale.