WRS MS Defense

TITLE: Optimization of Environmental DNA Methods for Detecting Multiple Aquatic Invasive Species (AIS) in Freshwater Ecosystems

Aquatic invasive species (AIS) are a threat to the ecological and economic integrity of freshwater ecosystems. Their impact includes the potential extirpation of native species, reduction in biodiversity, and habitat alteration. Early detection and monitoring of AIS is essential to effectively contain or eradicate a population and to prevent spread to other waterbodies. Traditional, physical AIS surveys require considerable effort, money, and time, often resulting in AIS being detected only after they have become established. A promising early detection approach that could address this issue is the analysis of environmental DNA (eDNA), which involves detecting organismal DNA shed into the environment using molecular methods. This method was first utilized in the 2000s to confirm the presence of AIS in freshwater samples and has grown since; however, refinements in some technical aspects, such as sample collection, preservation, and quantification methods, could help improve detection probability. This study aims to evaluate different field and lab eDNA methods to determine which combinations maximize detection probability of our target AIS. Both eDNA sample collection and traditional AIS surveys were conducted at five lakes in Minnesota, USA, varying in size, their invasion statuses, and their connections to river systems. AIS of interest included zebra mussel (Dreissena polymorpha), spiny waterflea (Bythotrephes longimanus), rusty crayfish (Faxonius rusticus), and common carp (Cyprinus carpio). We compared several different ways of harvesting eDNA (i.e., varied volume, filters, and sampling locations) as well as molecular detection methods to determine which methods were more effective at detecting our target nucleic acids at the low levels expected during early AIS establishment. By using a generalized linear mixed model, we found that a larger water volume and smaller filter pore size significantly increased the detection probability of the target AIS using eDNA. Additionally, the detection probability of eDNA methods was apparently less dependent on sampling locations (nearshore vs offshore and surface vs benthic). Finally, we conclude that the choice of detection method for the presence-absence of eDNA should be guided by the detection quantification limits of the target assay and other operational factors. We believe that eDNA sampling, coupled with physical detection methods, can increase detection productivity and precision, as some species (e.g., spiny waterflea) are harder to detect using one approach or another than other species (e.g., zebra mussel) are. Our findings suggest that natural resource managers should consider eDNA an additional AIS monitoring tool.