Exploring the eDNA dynamics of the host-pathogen pair Pacifastacus leniusculus (Decapoda) and Aphanomyces astaci (Saprolegniales) under experimental conditions

The oomycete Aphanomyces astaci causes crayfish plague, a disease threatening native European crayfish. It is carried and transmitted by American crayfish species, which are the original hosts of A. astaci. In recent years, environmental DNA (eDNA) methods have been successfully implemented to monitor the spread of both A. astaci and its hosts. However, still little is known about how population density and other en-vironmental factors influence the detectability of this host-pathogen complex. In a mesocosm experiment, we tested the influence of crayfish density, temperature and food availability on the detectability of eDNA for A. astaci and its host, signal crayfish Pacifastacus leniusculus. We also compared eDNA results with crayfish population density measured by catch per unit effort (CPUE) from two lakes with varying cray-fish density and A. astaci prevalence. The mesocosm experiment revealed that a limited set of controlled factors can substantially change the detectable amount of eDNA, even though the physical presence of the target organisms remains the same. In cold, clear water, eDNA quantities of both targets increased far more than in a linear fashion with increased crayfish density. However, the presence of food decreased the detectability of crayfish eDNA, presumably through increased microbial-induced eDNA degradation. For A. astaci, where eDNA typically represents living spores, food did not affect the detectability. However, high water temperature strongly reduced it. The increased complexity and variability of factors influenc-ing eDNA concentration under natural conditions, compared to a controlled experimental environment, suggests that establishing a reliable relationship between eDNA quantities and crayfish density is difficult to achieve. This was also supported by field data, where we found minimal correspondence between eDNA quantity and CPUE data. A comparison between quantitative real-time PCR (qPCR) analysis and droplet-digital PCR (ddPCR) analysis revealed higher detection success of the targets in field samples when using qPCR. Overall, our results support eDNA as an effective tool for presence-absence monitor-ing, but it seems less suited for biomass quantification and population density estimates. Detection of A. astaci and P. leniusculus is not influenced uniformly by respective environmental factors. Consequently, we recommend a strategy of monitoring both targets, where the detection of one may point towards the presence of the other.