International audiencePalaeoceanographic studies often rely on microfossil species abundance changes, with littleconsideration for species traits (e.g. size) that could be related to environmental changes. Wehypothesize that whole-assemblage and species-specific planktonic foraminifera (PF) testsize could be good predictors of environmental variables, and we test this using an EquatorialIndian Ocean (EIO) core-top sample set (62 viable samples). We use an automated imagingand sorting system (MiSo) to identify PF species, analyze morphology and quantifyfragmentation using machine learning techniques. Machine accuracy was confirmed bycomparisons with human classifiers. Data for 25 mean annual environmental parameterswere extracted from modern...