Understanding the spatial and temporal dynamics of environmental DNA for monitoring and management of priority invasive species

Invasive non-native species (INNS) are one of the five global drivers of biodiversity loss and the rate of biological invasions is increasing. Dreissenid mussels (zebra mussels Dreissena polymorpha and quagga mussels D. rostriformis bugensis) are INNS that are high on the UK priority list for monitoring and management, due to their potential for rapid spread and negative impacts to biodiversity, infrastructure and human health (e.g. Karatayev et al. 2015). Dreissenids can rapidly colonise hard surfaces, causing major problems for the water industry and power companies by clogging pipes and encrusting other artificial structures. In Yorkshire alone, removal of zebra mussels from pipework currently costs £600K per annum.
Early detection is key to preventing establishment and further spread of INNS, but this is particularly challenging for species that have microscopic life stages. Environmental DNA (eDNA) is a sensitive new method that is starting to revolutionise how we monitor INNS (Lawson Handley 2015; Blackman et al. 2018). We have recently developed eDNA assays for Dreissenid mussels that are highly sensitive for detection of both adult and larval stages (Blackman et al. 2018; Stroud 2018). The student will use these tools to obtain novel insights into the dynamics of Dreissenid eDNA and to improve understanding of the species' distribution and impact. Methods and data generated during the studentship will be critical for facilitating Dreissenid monitoring, management and mitigation.
Objective 1: to understand the temporal dynamics of Dreissenid eDNA and inform future sampling campaigns. eDNA production and degradation rates are likely to vary throughout the year due to differences in Dreissenid activity and population dynamics, and environmental factors such as water mixing and UV. How these factors interact to influence detection probability of Dreissenid eDNA is currently unknown. The studentship will use site occupancy modelling to generate eDNA detection probabilities at different times of the year, determine which seasonal variables influence detection, and inform future sampling campaigns.
Objective 2: to understand the spatial dynamics of eDNA distribution and determine which key environmental variables influence the probability of detection of Dreissenid eDNA. The detection of eDNA is influenced by the physical, chemical and biological properties of the environment (Barnes & Turner 2015). The studentship will investigate how environmental variables (e.g. substrate type, DOC chlorophyll, pH etc) effect Dreissenid populations, eDNA production and persistence. The impact of different environmental variables on the probability of eDNA detection, will be investigated using site occupancy modelling.
Objective 3: to use eDNA to identify key pathways and vectors for Dreissenid spread. Identification of high risk vectors and pathways for INNS spread is essential for drafting management plans, but research into pathways is often limited by the low power of current methods to detect species at low density. The studentship will use eDNA methods to investigate the relative importance of different pathways and inform a pathway management plan, and also explore the use of in situ detection methods for rapid, cost-effective and sensitive monitoring.
Objective 4: to evaluate the impact of Dreissenids on the structure and function of invaded ecosystems. Dreissenids are thought to have wide-ranging impacts on invaded communities, with positive effects on some species but reductions in others (Churchill 2013; Ward & Ricciardi 2013), but their impacts have not yet been comprehensively investigated at the whole ecosystem level. The studentship will generate data over time and space on entire communities, using DNA metabarcoding, which together with comprehensive environmental metadata, will allow unique insights into impact of Dreissenids on the structure and function of invaded ecosystems.