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The rapid reorganization of global biodiversity has triggered an intense research effort to understand its consequences for ecosystem functioning. However, efforts to monitor biodiversity change and evaluate the outcomes for ecosystem states and processes are currently poorly aligned. While most monitoring programs evaluate ecosystem status by reporting measures of taxonomic diversity, it is not the number of species but rather the exhibited traits of these species that regulate function. Trait-based approaches assume that trait diversity and variability relate to changes in functions across environmental gradients, but this relationship remains to be explored for most marine benthic ecosystems. Using macrozoobenthic communities from the Dutch Wadden Sea as a model, we compiled information on traits related to animal-sediment relationships. This trait information was then combined with species’ abundance data from a 19 years-long database to calculate different taxonomic and functional metrics that reflect macrozoobenthic diversity, function, and community structure. Finally, we compared how these taxonomic and functional metrics change along with sediment texture gradients. Our analyses showed that the structure of macrozoobenthic communities and various diversity metrics all changed with sediment gradients. The observed changes in the communities’ species composition were associated with directional shifts in the relative presence of specific functional traits with increasing sediment grain size, from communities dominated by small body size, deposit-feeding, and short life span to communities characterized by large to medium body size, suspension-feeding, and long life span. We observed limited functional redundancy and high sensitivity of functional trait-based measures to changes in the community composition along sediment gradients. Our findings suggest that a trait-based approach provides valuable information about the ecological function of marine macrozoobenthic species complementary to traditional biodiversity measures (e.g., species richness, Simpson diversity, etc.). Hence, these measures may be used to characterize changes in ecosystem functioning in time and space using traditional monitoring datasets.