| Summary: | Predicting and anticipating the effects of current and future climate warming on plant communities requires a comprehensive understanding of past ecosystem dynamics. In this context, Palaeoecological studies using sedimentary ancient DNA (sedDNA) offer unique advantages over conventional pollen and macrofossil methods due to higher taxonomic resolution and better detection of insect pollinated taxa than pollen, and higher detectability than macrofossil. Like macrofossils, sedDNA is mainly deposited within the catchment and thus provide a more geographically constrained catchment area than pollen. To ensure accurate reconstructions, it is vital to comprehend DNA preservation and degradation processes in sediments. Molecular ecology techniques like metabarcoding, shotgun sequencing, and capture probe methods have revolutionized the detection of floral diversity through sedDNA analysis. These methods enhance our ability to identify plant species and lineages with remarkable precision, enriching our understanding of past vegetation dynamics. However, it is essential to acknowledge potential biases in sedDNA methods when reconstructing past floral compositions. Factors such as DNA preservation, incomplete reference databases, and amplification biases must be considered to avoid misinterpretation. The applications of sedDNA extend to various ecological inquiries, including reconstructing past vegetation dynamics, studying plant dispersal and establishment, and investigating Arctic and Alpine ecosystem responses to environmental change. Moreover, sedDNA can trace single species and explore genetic adaptations over time. Sedimentary DNA analysis also holds promise in detecting human impact on vegetation and domesticated taxa, offering valuable insights into the past influence of human activities on plant communities. Future directions in sedDNA research involve method refinement, broadening regional applications, and integrating sedDNA data with other paleoecological proxies. This approach allows us to continue ...
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