Using MixSIAR to quantify mixed contributions of primary producers from amino acid δ15N of marine consumers. (January 2023)

• Record Type: Journal Article
• Authors: García-Seoane, R.; Viana, I.G.; Bode, A.
• Is Part Of: Marine environmental research. Volume 183(2023)
• Publication Date: 2023-01
• Subjects: Amino acids -- Beta value -- Compound-specific isotope analysis -- Food web -- MixSIAR -- Nitrogen sources -- Trophic discrimination factor -- Trophic position; Marine pollution -- Environmental aspects -- Periodicals; Marine ecology -- Periodicals; Mer -- Pollution -- Aspect de l'environnement -- Périodiques; Écologie marine -- Périodiques; Electronic journals; 577.705
• DOI: 10.1016/j.marenvres.2022.105792
• Languages: English
• ISSNs: 0141-1136

Abstract

Abstract: Estimations of the trophic position and the food web nitrogen baseline from compound-specific isotope analysis of individual amino acids (CSIA-AA) are challenged when the diet of consumer organisms relies on different proportions of vascular and non-vascular primary producers. Here we propose a method to infer such proportions using mixing models and the δ 15 N CSIA-AA values from marine herbivores. Combining published and new data, we first characterized CSIA-AA values in phytoplankton, macroalgae and vascular plants, and determined their characteristic β values (i.e. the isotopic difference between trophic and source AA). Then, we applied MixSIAR Bayesian isotope mixing models to investigate the transfer of these isotopic signals to marine herbivores (molluscs, green turtles, zooplankton and fish), and their utility to quantify autotrophic sources. We demonstrated that primary producer groups have distinct δ 15 NAA fingerprints that can be tracked into their primary consumers, thus offering a rapid solution to quantify resource utilization and estimate βmix values in mixed-sourced environments. Graphical abstract: Image 1 Highlights: Difficulty to characterize and quantify N basal sources in complex aquatic food webs. Tracing amino acids δ 15 N-fingerprints from primary producers to primary consumers. Bayesian mixing models distinguish vascular and non-vascular autotrophic sources. Bayesian mixing models estimate N source contributions to marine primary consumers. Improved trophic position estimates of consumers in aquatic environments.