Résumé
Echosounder buoys data obtained from instrumented drifting FADs represent an unprecedented source of information for assessing the spatio-temporal distribution of tropical tuna. Using machine learning algorithms, we transformed acoustic data collected from one of the main echosounder buoys models used by the French purse seine fleet (M3I) into presence/absence of tuna aggregations, enabling the measurement of the amount of inhabited FADs on a given spatiotemporal strata. This paper presents the spatial and temporal distribution of the proportion of drifting fish aggregating devices (DFADs) occupied by tuna aggregations relative to the total number of FADs in the Indian Ocean on a monthly basis, on a 5° grid for year 2016. The perspectives opened up by this new approach in improving estimates of abundance of tropical tuna populations are discussed.