Umwelt-DNA und maschinelles Lernen: neue Wege im Biomonitoring

Abstract

Environmental DNA-based taxon identification is transitioning from research to official biomonitoring. To assess whether combining amplicon sequencing with machine learning holds additional promise, we conducted a year-long, high-resolution sampling campaign in the War-now Estuary and along the Baltic Sea coast near Rostock. Our results highlight the use of large environmental amplicon datasets in combination with machine learning methods for research and biomonitoring.

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