Environmental DNA (eDNA) metabarcoding is an emerging tool for plant biodiversity monitoring, offering a non-invasive and scalable alternative to traditional field surveys. By amplifying and sequencing trace genetic material from environmental samples, eDNA enables detection of multiple taxa with minimal disturbance. Despite its widespread application in animal and microbial monitoring, plant-focused eDNA studies remain underdeveloped, comprising only a small fraction of total eDNA research.

Given the foundational role of plants in ecosystem function, improving methods for plant biodiversity monitoring is imperative. In particular, freshwater plant communities are undergoing significant biodiversity loss, and effective monitoring is critical for detecting changes and informing conservation strategies. Yet, standardized sampling designs are lacking, which risks introducing bias or inconsistency into biodiversity assessments. To fully realize the potential of eDNA for plant ecology, optimized and reliable field practices are essential. This study evaluates how vertical sampling position (surface vs. benthic) affects eDNA-based plant diversity estimates in freshwater lakes.

We analyzed 950 water samples collected from 22 lakes across Michigan, using surface (Smith-Root backpack samplers) and benthic (Van Dorn samplers) collection methods. DNA was extracted and amplified using primers targeting the plastid gene region rbcL, a widely used barcode for vascular plants. Species richness and Shannon diversity were calculated for aquatic, wetland, and terrestrial plant groups, and compared using Wilcoxon rank-sum tests.

Our results revealed no consistent differences in alpha diversity between surface and benthic samples across most lakes and plant groups. These findings suggest that single-depth sampling may often suffice for estimating local plant diversity, offering opportunities to streamline field protocols and reduce sampling effort.

By identifying conditions under which simplified sampling strategies yield comparable results, this study contributes to the scalability and cost-efficiency of plant eDNA monitoring programs. Future work should examine how depth influences beta diversity and community composition, and consider other spatial factors, such as distance from shore, that may differentially affect the detectability of aquatic versus terrestrial taxa. As environmental pressures intensify, flexible and robust tools like eDNA