4.7 Article

DNA metabarcoding of stream invertebrates reveals spatio-temporal variation but consistent status class assessments in a natural and urban river

Journal

ECOLOGICAL INDICATORS
Volume 115, Issue -, Pages -

Publisher

ELSEVIER
DOI: 10.1016/j.ecolind.2020.106383

Keywords

Metabarcoding; Macroinvertebrates; Biomonitoring; Seasonality; Stressors

Funding

  1. German Federal Ministry of Education and Research [FKZ 01LI1101, 01LI1501]
  2. Emschergenossenschaft/Lippeverband

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DNA metabarcoding of macroinvertebrates is increasingly used for aquatic bioassessment and -monitoring. A major strength of metabarcoding is the high taxonomic resolution provided while the inability to deliver reliable abundance data is regarded a main drawback. Data on the potential of metabarcoding to disentangle site-specific and seasonal variation with presence/absence data have been poorly explored. In addition, the robustness of ecological status assessments compliant with the European Water Framework Directive (Directive 2000/60/EG) have only been compared in few studies, none of which adressed changes across seasons. Therefore, we here investigated seasonal as well as site-specific effects on macroinvertebrate communities at six river sites in a nearnatural (Sieg) and urban (Emscher) German river through metabarcoding. Furthermore, we evaluated the usability of the method for ecological status assessments. Our data showed distinct seasonal effects on OTU composition at the near-natural river Sieg. However, ecological status assessment was constant through seasons and comparable to assessments based on available morphological identification. In contrast to the river Sieg, we found strong site and stressor-specific impacts in the heterogeneous urban river Emscher. Here, ecological status assessment varied between sampling sites ranging from good to bad status but was largely consistent between seasons. Our study demonstrates the ability of presence/absence metabarcoding data to reliably assess invertebrate community composition in streams and infer environmental (natural or anthropogenic) impacts. Together with the technical robustness, our study encourages the wider adoption of the technique in stream bioassessment and -monitoring.

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