How to design optimal eDNA sampling strategies for biomonitoring in river networks

Abstract

The current biodiversity crisis calls for appropriate methods for assessing biodiversity. In this respect, environmental DNA (eDNA) holds great promise, especially for aquatic ecosystems. While initial eDNA studies assessed biodiversity at single sites, technology now allows analyzing samples from many points simultaneously. However, the selection of these sites has been mostly motivated on an ad-hoc basis. To this end, hydrology-based models might offer a unique guidance on where to sample eDNA to most effectively reconstruct spatial patterns of biodiversity. Here, we performed computer simulations to identify best-practice criteria for the choice of positioning of eDNA sampling sites in river networks. To do so, we combined a hydrology-based eDNA transport model with a virtual river network reproducing the scaling features of real rivers. In particular, we conducted simulations investigating scenarios of different number and location of eDNA sampling sites in a riverine network, different spatial taxon distributions, and different eDNA measurement errors. We found that, due to hydrological controls, non-uniform patterns of eDNA concentration arise even if the taxon distribution is uniform and decay is neglected. Best practices for sampling site selection depend on the taxon's spatial distribution: when taxa are concentrated in some hotspots and only few sampling sites can be placed, it is better to preferentially locate them in the downstream part of the catchment; when taxa are more evenly distributed, and/or many sites can be placed, these should be preferentially located upstream. We also found that uncertainties in eDNA concentration estimates do not necessarily hamper model predictions. Knowledge of eDNA decay rates improves model predictions, highlighting the need for empirical estimates of these rates under relevant environmental conditions. Our simulations help define strategies for designing eDNA sampling campaigns in river networks and can guide the sampling effort of field ecologists and environmental authorities.