Measuring biodiversity with DNA metabarcoding: applications in forest management.

Biodiversity data play a central role in the iterative process of adaptive forest management, offering insights into the sustainability of forest practices. Traditional indicators of forest integrity have relied heavily on above ground taxa, primarily vertebrates and plants, which operate across regional to stand level scales. In contrast, below ground and freshwater biomes—including soil communities, aquatic microbiomes, and deadwood associated taxa—remain comparatively understudied. Recent advances in molecular methods, particularly metabarcoding, have transformed our ability to characterize this biodiversity enabling rapid, comprehensive assessments of community composition from environmental DNA (eDNA) in substrates such as soil, water, and wood. These tools provide opportunities to evaluate how forest management influences ecological processes and to support improved sustainable forest management(SFM). This review provides background on the application and utility of metabarcoding for generating biodiversity data in forest ecosystems to inform decision making. We outline the conceptual background of eDNA metabarcoding, survey emerging research specific to forest management, and present a practical workflow from field sampling to biodiversity data generation. By clarifying both the potential and limitations of these methods, this paper aims to equip non experts with the understanding needed to confidently interpret metabarcoding results and integrate them into efforts to measure forest integrity.