AbstractMeasuring the multidimensional diversity properties of a community is of great importance for ecologists, conservationists and stakeholders. Diversity profiles, a plotted series of Hill numbers, simultaneously capture all the common diversity indices. However, diversity metrics require information on species abundance. They often rely on raw count data without accounting for imperfect and varying detection, although detectability can vary between species and study sites. Hierarchical occupancy models explicitly account for variation in detectability, and Hill numbers have been expanded to allow estimation based on occupancy probability. But agreement between occupancy and abundance-based diversity profiles has not been investigated.Here, we fit community occupancy models to simulated animal communities to explore how well occupancy-based diversity profiles reflect true abundance-based diversity. Because we expect occupancy-based diversity to be overestimated, we further tested a novel occupancy thresholding approach to reduce potential biases in the estimated diversity profiles. Finally, we use empirical data from a megadiverse bird community to present how the framework can be extended to consider trait or phylogeny-based similarity when calculating diversity profiles.The simulation study showed that occupancy-based diversity profiles produced among-community patterns in diversity similar to true abundance diversity profiles, although within-community diversity was overestimated with the exception of richness. While applying an occupancy threshold reduced this positive bias, this resulted in negative bias in species richness estimates and slightly reduced the ability to reproduce true differences among the simulated communities. Application of our approach to a large bird dataset revealed differential diversity patterns in communities of different habitat types. Accounting for phylogenetic and ecological similarities between species reduced diversity and its variability among habitats.Our framework allows investigating the complexity of diversity for incidence data, while accounting for imperfect and varying detection probabilities, as well as species similarities. Visualizing results in the form of diversity profiles facilitates comparison of diversity between sites or across time. Therefore, our extension to the diversity profile framework will be a useful tool for studying and monitoring biodiversity.