Trophic interactions among multiple species are ubiquitous in nature and their importance for structuring ecological communities has been extensively demonstrated at local spatial scales. However, how local species interactions scale-up to large spatial scales and how they contribute to shape species distributions and diversity patterns at macroecological extents remains less clear. Here, we provide an overview of recent and potential future developments in macroecology that explore the role of antagonistic and mutualistic interactions among multiple species across trophic levels. Recent studies broadly represent two analytical methods (analyses of species richness and ecological networks) and provide evidence that plant–animal interactions (e.g. pollination, frugivory) and predator–prey interactions influence large-scale richness patterns and that ecological network structure varies systematically at macroscales. Current methodological problems and challenges are related to defining the functional links in cross-trophic richness analyses, understanding trait effects in multispecies interactions, and addressing sampling effects when analyzing multiple ecological networks across large spatial extents. Key topics for future research are 1) testing paleoclimatic imprints on interaction diversity, 2) understanding macroevolution and the phylogenetic structure of multispecies interactions, 3) quantifying contemporary spatial and temporal variability in complex ecological networks, and 4) predicting novel interactions under global change. Moreover, we see great potential for a deeper bidirectional integration of macroecology and network research, e.g. by analyses of trait complementarity and functional diversity of interacting groups and by employing species distribution modeling to predict changes in functional network structure. Addressing these key topics and achieving a better integration between these two research fields will significantly advance our understanding of the ecological and evolutionary drivers of multispecies interactions. This could also help to develop more realistic forecasts of changes in biodiversity under climate and land use change.