Binary presence-absence matrices are often used to quantify patterns of species co-occurrence and to infer possible biotic interactions from these patterns. Previous classifications of co-occurrence patterns as nested, segregated, or modular have led to contradictory results and conclusions. These analyses usually do not incorporate the functional traits of the species or the environmental characteristics of the sites, even though the outcome of species interactions often depend on trait expression and site quality. Species co-occurrence analyses have to incorporate realized functional and environmental niches. These niches can be defined from n-dimensional ellipsoids and calculated from the n eigenvectors and eigenvalues of the variance-covariance matrix of measured environmental or trait variables. Average niche overlap among species and the spatial distribution of niches define a triangle plot with axes of species segregation (low niche overlap), nestedness (high niche overlap), and modular co-occurrences (clusters of overlapping niches). Applied to temperate understorey plant communities in southwest Poland, this framework identified a consistent modular structure of species occurrences, a pattern not detected by conventional presence-absence analysis. Small scale habitat filtering appeared to be the most important process structuring understorey plant communities. Incorporating trait and environmental data into co-occurrence analysis improves pattern detection and provides a stronger theoretical framework for understanding community structure.