Multidecadal molecular isotope records indicate pelagic benthic coupling through microbial pathways in the Gulf of Maine
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Pelagic-benthic coupling provides essential ecosystem functions, including energy transfer in surface and deep ocean food webs, regulation of biogeochemical cycling, and climate feed-back mechanisms. Despite its importance, access to long-term data sets of export production through different food web pathways are scarce. Therefore, to fill a critical data gap in our understanding of the patterns and drivers of variation in export production on ecologically relevant time scales, this study applied compound-specific stable nitrogen isotope analysis of amino acids to a 38 year (1981-2019) time series of pelagic copepod bioarchives (large-bodied Calanus finmarchicus and small-bodied Centropages typicus) and deep ocean bioarchives (deep-sea coral Primnoa resedaeformis) in the Gulf of Maine. Key metrics of food web dynamics that regulate export production were calculated including water nitrogen source (d15N), degree of heterotrophic microbial reworking on organic matter (∑V), and relative contribution to the trophic position of metazoan (TPGlx-Phe) and microbial (TPAla-Phe), all of which revealed strong pelagic-benthic coupling in both magnitude and temporal trend. As hypothesized, there was particularly strong agreement across all metrics between large-bodied C. finmarchicus and deep-sea P. resedaeformis, including a steady increase in the heterotrophic microbial reworking of exported production over time. The strong reliance of C. finmarchicus on microbial loop processes, including elevated TPAla-Phe transfers (4+/- 0.3) and a high level of ∑V (2.0 ± 0.5), was mirrored in P. resedaeformis, creating a direct mechanism to link surface microbial loop food web dynamics to the deep ocean through the biological pump. Identifying this strong microbial loop connectivity between the pelagic and benthic systems improves our understanding of Gulf of Maine export dynamics and our ability to better parameterize new mechanistic General Ecosystem Models.