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Samples can be accurately classified to sampling time based on community composition. A random forest model shows the frequency at which microbiome samples from a given time point are correctly assigned based on taxonomic composition. This model included 698 unique sequence features (best model) and had an overall accuracy of 72% (n = 17 fish at 1100 and 2000 h and 18 fish at 1230, 1400, and 1600 h).
