Man-made floating objects in the surface of tropical oceans, also called drifting fish aggregating devices (DFADs), attract tens of marine species, including tunas and nontuna species. In the Indian Ocean, around 80% of the sets currently made by the EU purse-seine fleet are on DFADs. Due to the importance and value of this fishery, understanding the habitat characteristics and dynamics of pelagic species aggregated under DFADs is key to improve fishery management and fishing practices. This study implements Bayesian hierarchical spatial models to investigate tuna and non-tuna species seasonal distribution based on fisheries-independent data derived from fishers’ echo-sounder buoys, environmental information (Sea Surface Temperature, Chlorophyll, Salinity, Eddie Kinetic Energy, Oxygen concentration, Sea Surface Height, Velocity and Heading) and DFAD variables (DFAD identification, days at sea). Results highlighted group-specific spatial distributions and habitat preferences, finding higher probability of tuna presence in warmer waters, with higher sea surface height and low eddy kinetic energy values. In contrast, highest probabilities of non-tuna species were found in colder and productive waters. Days at sea were relevant for both groups, with higher probabilities at objects with higher soak time. Our results also showed speciesspecific temporal distributions, suggesting that both tuna and non-tuna species may have different habitat preferences depending on the monsoon period. The new findings provided by this study will contribute to the understanding of the ecology and behavior of target and non-target species and their sustainable management.