Echosounder buoys data obtained from instrumented drifting FADs represent an
unprecedented information source for assessing the spatio-temporal distribution
of tropical tuna. Using machine learning algorithms, we transform 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 spatio-temporal 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