Dendritic stream networks are inherently spatially and hierarchically structured, but the effects of this structure on stream communities are largely unknown. My aim was to investigate spatial patterns in stream networks using extensive spatial sampling of both adult and benthic macroinvertebrates in four stream networks on the West Coast of the South Island, New Zealand. Using spatial modelling and analyses, I answered questions about appropriate spatial measurements to capture ecological processes in stream networks, metacommunity processes at different scales in space and time, and how local and regional processes interact to structure metacommunities in stream networks. Spatial eigenfunction analyses showed that distance measures that explained most variance in stream macroinvertebrate communities were stream distance and weighted stream distance measures. They performed better than Euclidean distance to measure spatial structure that is ecologically relevant to stream network communities. The spatial pattern of benthic stream macroinvertebrates was stable over time, whereas community composition changed significantly, as shown by space-time interactions modelled by MANOVA-like redundancy analysis. Thus, spatial processes structuring stream metacommunities remained constant, in agreement with neutral model predictions. Network-scale properties, particularly flood disturbances, influenced the relative importance of spatial and environmental variation in stream network metacommunities. Additionally, quantile regression indicated that three key variables, habitat size, isolation and local habitat conditions, jointly limited community structure in stream networks, providing empirical support for both island biogeography and metacommunity theories. My study indicated that spatial structuring has an important influence on stream macroinvertebrate communities. The results contribute to broader ecological theory and understanding of community assembly by relating empirical results to theoretical predictions. In particular, they advance understanding of spatial processes in stream networks. The research also highlights a number of new methods, which were successfully applied to stream systems to elucidate complex spatial patterns.