Climate change and its consequences pressure the Arctic Siberian shelf region and impact marine benthic organisms severely. Polar ecosystems are used to long-term stable conditions and even small changes could have wide-ranging effects on benthic communities, food webs, and ecosystem functions. The interaction between marine organisms and their local environment generate different regional patterns in community composition. Analysing these relationships and identifying their spatial scales is an essential step in understanding how climate change affects marine biodiversity and in guiding future conservation and management strategies. To achieve this purpose, we combine benthic community data (412 species in 228 samples) from 10 different regions within the Siberian Arctic and selected environmental parameters (e.g. bathymetry, sea-ice cover and temperature) and employ recent multivariate spatial modelling techniques to study the composition and distributional patterns of the Artic Siberian macrobenthos. The ecological community data necessary for this investigation originate from several “TRANSDRIFT” expeditions in various seas in the Arctic Siberian shelf from 1992 until 2014. The abiotic data is provided by public online databases. We then employ Moran’s eigenvector mapping (MEM), which is a multivariate modelling framework, to model the spatial structure of our benthic and environmental data. MEM detects the different broad, meso and fine spatial scales within a community, it describes the relationship between spatial structure and abiotic factors and identifies which species are associated with which spatial scale. This analysis reveals that mainly environmental variables from the water column (e.g. water depths, sea-ice cover, temperature) describe the composition of macrobenthic communities on broader scales (>50 kilometres). Environmental factors describing the seafloor (e.g. sediment type) are more responsible for structuring the community on smaller scales (metres up to a few kilometres).