Biodiversity is threatened by a wide range of anthropogenic activities. Monitoring offers critical insights into how and why biodiversity is changing, helping to identify effective measures for maintaining biodiversity and its ecosystem services. However, conventional biodiversity monitoring methods are labor-intensive, and standardized long-term monitoring series are scarce. DNA-based approaches like metabarcoding environmental DNA (eDNA) promise rapid, cost-efficient, and highly resolved community data. At the same time, scientists are looking for alternative data sources that can compensate for the lack of long-term monitoring data to study past biodiversity changes. This work explores the potential of the German Environmental Specimen Bank (ESB), a pollution monitoring archive, which appears particularly promising for retrospective biodiversity monitoring. Biota samples from different ecosystems across the country are collected and archived at an exceptional level of standardization. Sampling species act as natural eDNA samplers, accumulating genetic traces from surrounding organisms. The cryogenic storage at the ESB preserves any eDNA in the samples in its original state. In this thesis, Chapter I serves as an introductory chapter, outlining the general chances and challenges of metabarcoding for assessing biodiversity. Chapter II focuses on primer design and testing the utility of ESB sampling species like mussels and macroalgae for characterizing the surrounding community. Both chapters form the basis for Chapters III to V, which report the use of ESB time series to uncover sample-associated communities and the changes they undergo. Chapter III illustrates the value of these time series by revealing the invasion trajectory of an alien barnacle into German coastal waters and linking the process to climate change. Chapter IV forms the core of this thesis by presenting an expanded measurement of biodiversity change in ESB time series across different taxonomic groups and ecosystem types. Here, a gradual compositional change (turnover) is reported from bacterial, fungal, microeukaryotic, and metazoan communities tending to either spatial homogenization or differentiation. Observed trends are tested for significance using a dynamic model of community ecology based on the equilibrium theory of island biogeography. The model reveals significantly accelerated turnover rates across all taxonomic groups and ecosystems investigated, suggesting a common, anthropogenically induced driver of biodiversity change. Since these analyses most likely include DNA derived from dead as well as from living organisms, Chapter V aims to separate both groups by metabarcoding both DNA and less stable ribosomal RNA from mussel samples. Contrary to the hypothesis, RNA is detectable from both living endobionts and dietary taxa. However, it outcompetes DNA in detecting microeukaryotic biodiversity. In summary, this thesis demonstrates the outstanding potential of archived ESB samples for retrospective biodiversity monitoring, a resource that offers many further untapped opportunities for future biodiversity research at multiple scales.