Unraveling Zooplankton Diversity in a Pre-Alpine Lake: A Comparative Analysis of ZooScan and DNA Metabarcoding Methods

Author:

Vogelmann Christian12ORCID,Barco Andrea3,Knust Jean-Michel2,Stibor Herwig1

Affiliation:

1. Department II, Faculty of Biology, Aquatic Ecology, Ludwig-Maximilians-Universität München, Großhaderner Str. 2, 82152 Planegg-Martinsried, Germany

2. Bavarian State Research Center for Agriculture (LfL), Institute for Fisheries, Weilheimer Str. 8, 82319 Starnberg, Germany

3. biome-id Dres. Barco & Knebelsberger GbR, c/o Jade InnovationsZentrum, Emsstraße 20, 26382 Wilhelmshafen, Germany

Abstract

Zooplankton, integral to aquatic ecosystems, face diverse environmental influences. To comprehend their dynamics, critical for ecological insights and fisheries management, traditional morphological analysis proves laborious. Recent advances include automated systems like ZooScan and DNA metabarcoding. This study examines two methods on the same samples to identify similarities and dependencies between them, potentially reducing the required workload and enhancing the quality of the results. Ten Lake Starnberg vertical tows in September 2021 provided zooplankton samples preserved in ethanol. Subsamples underwent ZooScan morphological identification and subsequent DNA metabarcoding. High concordance between ZooScan counts and DNA reads (86.8%) was observed, while biomass calculations from body length (major axis) and equivalent spherical diameter (ESD) showed slightly lower agreement (78.1% and 79.6%, respectively). Linear regression analysis revealed a correlation between counts and DNA reads (r2 = 0.59). This study underscores the complementary strengths and limitations of ZooScan and DNA metabarcoding for zooplankton analysis. ZooScan aids biomass estimation and morphological differentiation, whereas DNA metabarcoding offers superior taxonomic resolution and low-abundance taxon detection. Combining both methods on the same sample enhances understanding and facilitates future advanced analyses.

Funder

Bayerisches Staatsministerium für Umwelt und Verbraucherschutz

Bayerisches Staatsministerium für Ernährung, Landwirtschaft und Forsten

Publisher

MDPI AG

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