Characterizing niche differentiation among marine consumers with amino acid δ(13)C fingerprinting

Marine food webs are highly compartmentalized, and characterizing the trophic niches among consumers is important for predicting how impact from human activities affects the structuring and functioning of marine food webs. Biomarkers such as bulk stable isotopes have proven to be powerful tools to elucidate trophic niches, but they may lack in resolution, particularly when spatiotemporal variability in a system is high. To close this gap, we investigated whether carbon isotope (δ(13)C) patterns of essential amino acids (EAAs), also termed δ(13)C(AA) fingerprints, can characterize niche differentiation in a highly dynamic marine system. Specifically, we tested the ability of δ(13)C(AA) fingerprints to differentiate trophic niches among six functional groups and ten individual species in the Baltic Sea. We also tested whether fingerprints of the common zooplanktivorous fishes, herring and sprat, differ among four Baltic Sea regions with different biochemical conditions and phytoplankton assemblages. Additionally, we investigated how these results compared to bulk C and N isotope data for the same sample set. We found significantly different δ(13)C(AA) fingerprints among all six functional groups. Species differentiation was in comparison less distinct, due to partial convergence of the species' fingerprints within functional groups. Herring and sprat displayed region‐specific δ(13)C(AA) fingerprints indicating that this approach could be used as a migratory marker. Niche metrics analyses showed that bulk isotope data had a lower power to differentiate between trophic niches than δ(13)C(AA) fingerprinting. We conclude that δ(13)C(AA) fingerprinting has a strong potential to advance our understanding of ecological niches, and trophic linkages from producers to higher trophic levels in dynamic marine systems. Given how management practices of marine resources and habitats are reshaping the structure and function of marine food webs, implementing new and powerful tracer methods are urgently needed to improve the knowledge base for policy makers.