A multi-biomarker approach supports the use of compound-specific stable isotope analysis of amino acids to quantify basal carbon source use in a salt marsh consumer.

Rationale: Determining the flow of energy from primary producers to higher trophic levels in complex systems remains an important task for ecologists. Biomarkers can be used to trace carbon or energy sources contributing to an organism's tissues. However, different biomarkers vary in their ability to trace carbon sources based on how faithfully they transfer between trophic levels. Comparing emerging biomarker techniques with more commonly used techniques can demonstrate the relative efficacy of each in specific systems.

Methods: Two common biomarker techniques, fatty acid analysis (FAA) and bulk stable isotope analysis (SIA), and one emerging biomarker technique, compound-specific stable isotope analysis of amino acids (CSIA-AA), were compared to assess their ability to characterize and quantify basal carbon sources supporting the seaside sparrow (Ammodramus maritimus), a common salt marsh species. Herbivorous insect and deposit-feeding fiddler crab biomarker values were analyzed as proxies of major terrestrial and aquatic basal carbon sources, respectively.

Results: All three biomarker techniques indicated that both terrestrial and aquatic carbon sources were important to seaside sparrows. However, FAA could only be evaluated qualitatively, due to a currently limited understanding of trophic modification of fatty acids between primary producer and this consumer's tissues. Quantitative stable isotope (SIA or CSIA-AA) mixing models predicted nearly equal contributions of terrestrial and aquatic carbon sources supporting seaside sparrows, yet estimates based on CSIA-AA had greater precision.

Conclusions: These findings support the use of CSIA-AA as an emerging tool to quantify the relative importance of basal carbon sources in salt marsh consumers. Integrating multiple biomarker techniques, with their differing benefits and limitations, will help to constrain models of carbon and energy flow in future ecosystem studies.