Spatio-temporal patterns in stable isotope composition of a benthic intertidal food web reveal limited influence from salt marsh vegetation and green tide

Assessing fluxes of matter and energy in food webs within and across benthic habitats is important to understand the ecological functioning in bays and estuaries, where the productivity is favoured by a wide diversity of primary producers. The temporal variability (March vs September 2019) in the carbon and nitrogen stable isotope composition of primary food sources and benthic invertebrates consumers was investigated in a large intertidal area (Western English-Channel, France). The study area is influenced by megatidal conditions and characterised by salt marshes in the sheltered part, and seasonal Ulva spp. blooms. The spatio-temporal variability in the structure of the benthic food web was analysed at the scales of both the whole bay and the different assemblages, which constitute the mosaic of habitats. Inferences on potential sources fuelling the food web were supported by spatio-temporal patterns based on covariations and stable isotope trajectory analysis. Results highlighted that phytoplankton, microphytobenthos and SOM were, most likely, the main food sources. The trophic connectivity between salt marsh and benthic habitats within the bay was limited to some macrofauna species inhabiting muddy creeks within the salt marsh. Unexpectedly, the influence of Ulva blooms appeared also limited. Spatial patterns illustrates the constancy of the spatial variability in the benthic pelagic coupling, with a higher influence of microphytobenthos in the upper shore compared to low shore assemblages. This first attempt to characterize intertidal benthic food web constitutes a relevant baseline for the conservation of the bay of Saint-Brieuc where a National nature reserve has been created in 1998 for the conservation of overwintering birds. The spatial and temporal patterns of the benthic food web observed in this study (1) confirm the importance to consider food web variability at spatial and temporal scales from sampling designs to data analysis, and (2) demonstrate the