Unraveling long-term trends and drivers of fish biodiversity change using eDNA metabarcoding of archived samples

Long-term biodiversity data are critical for detecting and understanding ecosystem change, yet systematic long-term datasets remain scarce. We present the longest eDNA metabarcoding time series for freshwater fishes based on archived suspended particulate matter (SPM) from Germany's Environmental Specimen Bank, covering 17 years (2005–2021) across six major European river systems (Rhine, Danube, Elbe, and tributaries). From 211 annual samples collected according to highly standardized procedures at 13 sites, we detected 63 fish and lamprey species and traced their spatiotemporal trajectories. eDNA metabarcoding captured significantly declining trends at multiple sites with no recoveries. Common and sensitive species declined at nearly half of sites while invasive species like round gobies expanded consistently. Site occupancy and relative read abundance trends were correlated, supporting their use as semi-quantitative biodiversity indicators. Alpha and beta diversity shifted significantly over time and Bayesian hierarchical models revealed site specific trends and that 11% of species showed significant declines in relative read abundance at the national level. The eDNA-derived trends showed strong concordance with long-term regulatory fish monitoring trends, supporting that eDNA metabarcoding data can generate comparable bioindicaton results. Random forest models and multivariate analyses identified anthropogenic stressors such as pesticides, heavy metals, temperature, and fine sediment as key correlates of biodiversity patterns, with site-specific stressor combinations explaining 29% of community variation. Critically, these chemical and biological signals derive from the same archived SPM samples, demonstrating a dual-purpose monitoring matrix that integrates pollution and biodiversity assessment simultaneously. Archived SPM samples thus represent an underexploited resource for reconstructing freshwater biodiversity baselines and supporting evidence-based environmental management.

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Journal
Ecological Indicators
Published
2026-09-11
DOI
https://doi.org/10.1016/j.ecolind.2026.115447
Primary Topic
Environmental DNA in Biodiversity Studies
Type
article
Field-Weighted Citation Impact
0.00

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article

Unraveling long-term trends and drivers of fish biodiversity change using eDNA metabarcoding of archived samples

Till‐Hendrik Macher, Robin Schütz, Jens Arle, Jan Koschorreck et al.
Ecological Indicators
Environmental DNA in Biodiversity Studies
article

Unraveling long-term trends and drivers of fish biodiversity change using eDNA metabarcoding of archived samples

Till‐Hendrik Macher, Robin Schütz, Jens Arle, Jan Koschorreck, Arne J. Beermann, Martin Friedrichs-Manthey, Florian Leese
article en

Abstract

Long-term biodiversity data are critical for detecting and understanding ecosystem change, yet systematic long-term datasets remain scarce. We present the longest eDNA metabarcoding time series for freshwater fishes based on archived suspended particulate matter (SPM) from Germany's Environmental Specimen Bank, covering 17 years (2005–2021) across six major European river systems (Rhine, Danube, Elbe, and tributaries). From 211 annual samples collected according to highly standardized procedures at 13 sites, we detected 63 fish and lamprey species and traced their spatiotemporal trajectories. eDNA metabarcoding captured significantly declining trends at multiple sites with no recoveries. Common and sensitive species declined at nearly half of sites while invasive species like round gobies expanded consistently. Site occupancy and relative read abundance trends were correlated, supporting their use as semi-quantitative biodiversity indicators. Alpha and beta diversity shifted significantly over time and Bayesian hierarchical models revealed site specific trends and that 11% of species showed significant declines in relative read abundance at the national level. The eDNA-derived trends showed strong concordance with long-term regulatory fish monitoring trends, supporting that eDNA metabarcoding data can generate comparable bioindicaton results. Random forest models and multivariate analyses identified anthropogenic stressors such as pesticides, heavy metals, temperature, and fine sediment as key correlates of biodiversity patterns, with site-specific stressor combinations explaining 29% of community variation. Critically, these chemical and biological signals derive from the same archived SPM samples, demonstrating a dual-purpose monitoring matrix that integrates pollution and biodiversity assessment simultaneously. Archived SPM samples thus represent an underexploited resource for reconstructing freshwater biodiversity baselines and supporting evidence-based environmental management.

Ecological IndicatorsVol. 191
Helmholtz Centre for Environmental Research (DE), German Centre for Integrative Biodiversity Research (DE), German Environment Agency (DE), University of Duisburg-Essen (DE), Friedrich Schiller University Jena (DE), Universität Trier (DE)
Deutsche Forschungsgemeinschaft, Umweltbundesamt, Deutsches Zentrum für integrative Biodiversitätsforschung Halle-Jena-Leipzig
Openalex Percentile: Top 11%
Environmental DNA in Biodiversity Studies
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