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<p>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.</p>

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Umwelt-DNA und maschinelles Lernen: neue Wege im Biomonitoring

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2026年5月16日

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  • Theodor Sperlea,
  • Matthias Labrenz

摘要

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.