Food web flows through a sub-arctic deep-sea benthic community

The benthic food web of the deep Faroe–Shetland Channel (FSC) was modelled by using the linear inverse modelling methodology. The reconstruction of carbon pathways by inverse analysis was based on benthic oxygen uptake rates, biomass data and transfer of labile carbon through the food web as revealed by a pulse-chase experiment. Carbon deposition was estimated at 2.2 mmol C m−2 d−1. Approximately 69% of the deposited carbon was respired by the benthic community with bacteria being responsible for 70% of the total respiration. The major fraction of the labile detritus flux was recycled within the microbial loop leaving merely 2% of the deposited labile phytodetritus available for metazoan consumption. Bacteria assimilated carbon at high efficiency (0.55) but only 24% of bacterial production was grazed by metazoans; the remaining returned to the dissolved organic matter pool due to viral lysis. Refractory detritus was the basal food resource for nematodes covering ∼99% of their carbon requirements. On the contrary, macrofauna seemed to obtain the major part of their metabolic needs from bacteria (49% of macrofaunal consumption). Labile detritus transfer was well-constrained, based on the data from the pulse-chase experiment, but appeared to be of limited importance to the diet of the examined benthic organisms (<1% and 5% of carbon requirements of nematodes and macrofauna respectively). Predation on nematodes was generally low with the exception of sub-surface deposit-feeding polychaetes that obtained 35% of their energy requirements from nematode ingestion. Carnivorous polychaetes also covered 35% of their carbon demand through predation although the preferred prey, in this case, was other macrofaunal animals rather than nematodes. Bacteria and detritus contributed 53% and 12% to the total carbon ingestion of carnivorous polychaetes suggesting a high degree of omnivory among higher consumers in the FSC benthic food web. Overall, this study provided a unique insight into the functioning of a deep-sea benthic community and demonstrated how conventional data can be exploited further when combined with state-of-the-art modelling approaches.