Understanding ecosystem dynamics over time is essential for managing the effects of climate change and environmental threats such as invasive species, and emerging pathogens. Traditional monitoring approaches are often invasive, costly, time-consuming, and limited in spatial and temporal scope, impeding effective ecosystem monitoring. We are pioneering a new methodology in ecosystem science by applying high-throughput sequencing to environmental DNA (eDNA) from a unique, 60-year archive of air filters sampled weekly since the 1960's at 6 locations across Sweden. This "molecular time machine" allows us to identify and track a broad spectrum of organisms, from microbes to mammals, with unprecedented temporal and taxonomic precision, effectively reconstructing historical ecosystems. Our approach is capable of establishing ecological baselines, identifying long-term trends, and supporting real-time monitoring of biological threats. It represents a paradigm shift in biodiversity surveillance: from organism-specific, laborious methods to holistic, high-throughput environmental sensing. Our flagship analysis of a 34-year period in northern Sweden revealed a significant decline in forest biodiversity, a trend best explained by land-use changes. We are now expanding this work to track and forecast the impacts of climate change, map the spread of pathogens and invasive species that threaten our forests and agriculture, and understand the erosion of genetic diversity in key species.
This innovative approach provides crucial data for informed conservation efforts, enhanced biopreparedness, and sustainable resource management, ultimately fostering a deeper understanding of ecosystem responses to environmental pressures and guiding proactive solutions for a healthier planet.