SICB Logo: Click Here to go to the SICB Home Page

Meeting Abstract

P2-32   -   Environmental DNA to Detect Invasive Invertebrates; Case Study in a Tide Pool Pierce, E.*; Frederich, M.; University of New England, Biddeford, ME; University of New England, Biddeford, ME & University of Maine, Orono, ME mfrederich@une.edu

Environmental DNA (eDNA) monitoring techniques can be applied in marine ecosystems to detect invasive invertebrates quickly and efficiently. Invasive invertebrates threaten natural biodiversity and some of the most valuable fisheries in the world. Visual surveys for these invasive species, the usual monitoring technique, can be inefficient and costly, and often detect invasions only once the species has already established a population. Once established, these invaders can outcompete native biodiversity, so detecting the invasion early is crucial to preventing environmental harm. We tested whether eDNA methods are comparable to visual surveys for detecting and quantifying invasive invertebrates in a tidepool in Maine. Quantitative PCR assays were compiled or designed for green crab, Carcinus maenas, Asian shore crab, Hemigrapsus sanguineus, European oyster, Ostrea edulis, and chain tunicate, Botrylloides violaceus-. Environmental DNA sampling and a visual survey were performed collected monthly. The visual survey was completed using the Marine Invader Monitoring Information Collaborative (MIMIC) survey methods. Preliminary results suggest that eDNA is able to detect some of the invasive species that were found in the visual survey, and that concentration correlates with abundance of some species but not all. Physiology and morphology likely play a role in eDNA shedding rates, affecting detection probability. This suggests that careful testing is required to confirm and field test that eDNA abundance is associated with the biomass of each species. Environmental DNA can be used to detect invasive invertebrates with accuracy, but these methods need refinement for management of invasive invertebrates. Funded by NSF EPSCoR grant# OIA-1849227