Temporal and spatial trends in marine carbon isotopes in the Arctic Ocean and implications for food web studies

The Arctic is undergoing unprecedented environmental change. Rapid warming, decline in sea ice extent, increase in riverine input, ocean acidification and changes in primary productivity are creating a crucible for multiple concurrent environmental stressors, with unknown consequences for the entire arctic ecosystem. Here, we synthesized 30 years of data on the stable carbon isotope (delta C-13) signatures in dissolved inorganic carbon (delta C-13-DIC; 1977-2014), marine and riverine particulate organic carbon (delta C-13-POC; 1986-2013) and tissues of marine mammals in the Arctic. delta C-13 values in consumers can change as a result of environmentally driven variation in the delta C-13 values at the base of the food web or alteration in the trophic structure, thus providing a method to assess the sensitivity of food webs to environmental change. Our synthesis reveals a spatially heterogeneous and temporally evolving delta C-13 baseline, with spatial gradients in the delta C-13-POC values between arctic shelves and arctic basins likely driven by differences in productivity and riverine and coastal influence. We report a decline in delta C-13-DIC values (-0.011 parts per thousand per year) in the Arctic, reflecting increasing anthropogenic carbon dioxide (CO2) in the Arctic Ocean (i.e. Suess effect), which is larger than predicted. The larger decline in delta C-13-POC values and delta C-13 in arctic marine mammals reflects the anthropogenic CO2 signal as well as the influence of a changing arctic environment. Combining the influence of changing sea ice conditions and isotopic fractionation by phytoplankton, we explain the decadal decline in delta C-13-POC values in the Arctic Ocean and partially explain the delta C-13 values in marine mammals with consideration of time-varying integration of delta C-13 values. The response of the arctic ecosystem to ongoing environmental change is stronger than we would predict theoretically, which has tremendous implications for the study of food webs in the rapidly changing Arctic Ocean.