1. Indices quantifying the functional aspect of biodiversity are essential in understanding relationships between biodiversity, ecosystem functioning and environmental constraints. Many indices of functional diversity have been published but we lack consensus about what indices quantify, how redundant they are and which ones are recommended.
2. This study aims to build a typology of functional diversity indices from artificial data sets encompassing various community structures (different assembly rules, various species richness levels) and to identify a set of independent indices able to discriminate community assembly rules.
3. Our results confirm that indices can be divided into three main categories, each of these corresponding to one aspect of functional diversity: functional richness, functional evenness and functional divergence. Most published indices are highly correlated and quantify functional richness while quadratic entropy (Q) represents a mix between functional richness and functional divergence. Conversely, two indices (FEve and FDiv respectively quantifying functional evenness and functional divergence) are rather independent to all the others. The power analysis revealed that some indices efficiently detect assembly rules while others performed poorly.
4. To accurately assess functional diversity and establish its relationships with ecosystem functioning and environmental constraints, we recommend investigating each functional component separately with the appropriate index. Guidelines are provided to help choosing appropriate indices given the issue being investigated.
5. This study demonstrates that functional diversity indices have the potential to reveal the processes that structure biological communities. Combined with complementary methods (phylogenetic and taxonomic diversity), the multifaceted framework of functional diversity will help improve our understanding of how biodiversity interacts with ecosystem processes and environmental constraints.