Harnessing stemflow as a diagnostic tool for canopy disease detection and monitoring

Monitoring diseases within tree canopies is challenging due to their inaccessibility and the complexity of canopy ecosystems. Here, we explore the potential of stemflow sampling as a novel, ground-based method for detecting and monitoring canopy-associated pathogens. In a case study focused on Litylenchus crenatae ssp. mccannii (LCM), the nematode associated with Beech Leaf Disease (BLD), we collected stemflow samples from 18 Fagus grandifolia Ehrh. (American beech) trees across 12 storm events. eDNA assays detected LCM presence in 7 of those storms, with quantitative PCR-derived gene concentrations ranging from 80 to 158,000 copies mL −1 . Higher detections and concentrations coincided with leaf senescence and bud formation periods, and they correlated conditionally with event rainfall amount and pre-storm changes in relative humidity. Although based on a single site and season, these findings demonstrate the potential for stemflow sampling to capture a pathogen’s eDNA ( i.e. , canopy distress signals) at ground level. This method could complement traditional monitoring, offering another affordable, non-invasive tool for pathogen detection. Additional validation, particularly regarding live versus dead organisms and across varied site conditions, will be essential to evaluate the breadth of value stemflow eDNA offers for canopy disease management and ecological research. • Stemflow sampling offers a low-cost, ground-based method for detecting tree canopy pathogens. • Beech leaf disease-associated nematodes detected in stemflow across diverse storm conditions using eDNA assays. • Rain amount and pre-storm humidity strongly predict nematode presence in stemflow. • Scalable approach: Applicable to diverse forest environments beyond the case study.