Predicting invasive signal crayfish (Pacifastacus leniusculus) spread using a traditional survey and river network simulation

Rivers are among the most vulnerable ecosystems to biological invasions. After introduction, predicting the timing and magnitude of population growth and range expansion is critical to decision making on where management tactics will be most efficient. Yet, management is often hindered by the lack of knowledge on species-specific attributes and the spatially complex structure of river networks that influences connectivity between sites. We analysed the population structure and predicted the range expansion of signal crayfish (Pacifastacus leniusculus), an invasive species in North-western Italy which was first recorded in the Valla Stream in 2009 and then spread to adjacent rivers including Erro Stream in 2020. A total of 1,284 individual P. leniusculus crayfish were collected in the Valla Stream. No significant difference was found in density or body condition along a downstream gradient for different sex and maturity classes. These empirical data were combined with the available scientific literature to obtain key life-history information for P. leniusculus, including carrying capacity, downstream versus upstream dispersion and proliferation rate. We used the OCNet R package to simulate the Erro Stream network and applied a meta-population model to predict the range expansion of this species over time. Results indicate P. leniusculus may completely invade the Erro Stream network in 30–40 years, depending on the proliferation rate and without additional introductions. These findings represent one of the first attempts to use optimal channel networks simulation in R to predict the meta-population dynamics of aquatic invasive species, a potential key tool to prevent invasive species spread.