Invasive species detection and management using genomic methods

Invasive alien species (IAS) cause significant economic and environmental damage worldwide. For decades, genetic approaches have been used to detect IAS, clarify their taxonomy, determine pathways of introduction, estimate levels of gene flow (between populations and between invasive and native species), and measure the success of eradication efforts. More recently, we have benefitted from technologies that enable detection from environmentally derived samples, even at low IAS densities. Further, the development of in-field testing devices and PCR-free detection technologies are now extending capabilities to manage IAS. Next-generation sequencing is now commonly employed to characterise populations of IAS. While whole genome resequencing remains the gold standard, reduced-representation sequencing approaches can often provide sufficient genome-wide data without the need for expensive whole genome sequencing. Using such data, it is possible to carefully monitor changes in invasive populations, including whether adaptation is occurring, which may signify whether populations are approaching the exponential expansion phase often seen in well-established invasions. Coupled with these advances in sequencing technology and computing capabilities, modelling and data analyses are extending our ability to understand how evolutionary processes affect invasive populations, enabling the design of more effective approaches in their management. Here we present current and developing technologies of use in the genetic management of IAS. We also discuss how these data can be translated to useful management advice.