Molecular Insights Into Vegetation Classification: A Comparative Analysis of Standard Observations and Belowground Metabarcoding of the Phytocoenosis

ABSTRACT Question Vegetation classification is pivotal for understanding, managing, and conserving plant communities, yet standard approaches typically rely on aboveground observations only. Recent studies highlight that belowground components may harbour substantial hidden diversity, potentially influencing classification results. Here, we compare vegetation classifications derived from conventional aboveground surveys with DNA metabarcoding data from belowground plant parts. Location Opole Silesia region, SW Poland. Methods We surveyed 54 plots (1 m 2 each) in three Central European grassland types (wet, mesic, and dry) under three management intensities (low, moderate, high). Aboveground species composition was recorded using standard botanical methods, while belowground samples were analysed by high‐throughput sequencing using three DNA regions (ITS2, trnL–trnF, and trnH–psbA). Results The results showed consistently higher species richness in the belowground samples, revealing numerous ephemeral, perennial, or rhizomatous species not detected in the 1‐day aboveground surveys. Despite these additions, TWINSPAN classification and non‐metric multidimensional scaling (NMDS) showed similar delineations of the major grassland types, with dry meadows being particularly well defined by all methods. Of the three DNA regions, ITS2 and trnL–trnF showed the best agreement with the standard aboveground classification results, while trnH–psbA showed a weaker match. Notably, differences in species composition due to additional belowground detections did not substantially alter cluster assignments or key diagnostic species for each grassland type. Conclusion Our results highlight the robustness of conventional vegetation classification, even when confronted with additional belowground molecular survey data. Nevertheless, the synergy of molecular and observational methods may provide a more holistic view of phytocoenotic diversity, highlighting the value of integrating DNA metabarcoding approaches for more comprehensive biodiversity monitoring and conservation strategies.