Monitoring aquatic biodiversity at scale depends on the efficient collection of environmental DNA (eDNA). However, the standard approach, actively filtering liters of water, often becomes slow or infeasible in turbid systems, where filters clog and field logistics escalate. A new study published in Environment Internationalshows that water movement itself can be leveraged to improve eDNA capture. Under faster flow, passive collectors accumulate DNA quickly and, in running waters, can even outperform conventional filtration.

Researchers led by Prof. HE Dekui from the Institute of Hydrobioloay (IHB) of the Chinese Academy of sciences combined controlled flume experiments with field deployments across 21 sites to test how hydrodynamic conditions govern passive eDNA sampling efficiency. Using a flow–adsorption framework, they evaluated glass-fiber (GF) membranes as a passive eDNA sampler and compared them against a commonly used 2-L filtration benchmark in the laboratory. They then benchmarked multiple passive substrates against filtration in natural lentic (still) and lotic (flowing) habitats.

In the laboratory, the team exposed GF membranes to four flow regimes, ranging from stagnant conditions to high velocity, and quantified DNA accumulation using droplet digital PCR (ddPCR). DNA captured by the passive membranes increased with exposure time under all flow treatments, but accumulation accelerated sharply under high flow. At the highest velocity tested, GF samplers exceeded the 2-L filtration benchmark within 30 minutes, demonstrating that brief deployments can generate filtration-equivalent (or higher) yields when water movement increases encounter rates between DNA-bearing particles and the collector surface.

To test whether these patterns hold in real ecosystems, the researchers deployed passive samplers for 24 hours across seven lentic sites and fourteen lotic sites in Shennongjia National Park, while simultaneously collecting paired 2-L filtration samples. They used fish 12S metabarcoding to compare biodiversity recovery among methods and habitats. Across all samples, metabarcoding detected 37 fish taxa, and the overlap between passive methods and filtration was substantial, with 73% of taxa shared across all methods, indicating broad agreement in community detection.

Crucially, performance depended on flow regime. In running waters, GF membranes achieved the highest amplicon sequence variant (ASV) richness and outperformed filtration, while in still waters GF was broadly comparable to filtration and competitive with other passive substrates. Statistical models showed that adsorption efficiency increased with velocity for GF, supporting the central conclusion that flow strengthens passive adsorption and boosts biodiversity recovery in lotic environments.

Together, the findings provide practical guidance for monitoring design. Short passive immersions can be sufficient in swift rivers, but longer soak times are needed in lakes and reservoirs where flow is limited. The study positions GF-based passive samplers as a low-effort, scalable option for standardized aquatic biodiversity monitoring, especially in systems where filtration is slowed by clogging, turbidity, or logistical constraints.

(Editor: MA Yun)

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