ABSTRACT
Rapid Assessment Surveys are routinely used to document biodiversity and is particularly important for the identification of non-indigenous species. However, the methods associated with these surveys have traditionally relied solely on morphological data, which for broad scale surveys, can be time consuming and expensive. In this study we incorporated DNA barcoding into a recent RAS of native and non-indigenous fauna associated with floating dock communities at several marinas in the New England region of the United States. We focused specifically on the polychaetes – a notoriously problematic group to barcode. Results from the rapid assessment survey, carried out over three days, yielded 48 polychaete specimens in total, representing 11 distinct species and six families. Three different primer pairs were used to amplify a 550–710 bp fragment of the CO1 gene for each of the 11 morphologically identified species. CO1 amplification was successful for all species and each morphologically identified species was molecularly confirmed using the GenBank database (identity scores ranged from 92 to 100%). Phylogenetic analysis along with low intraspecific genetic distance estimates (0.000–0.019) strongly supported the similarity indices. Four of the 11 species identified are part of species complexes in other parts of the world and are assigned here as pseudo-cosmpolitan while the remaining seven species are likely cryptogenic. This is the first DNA barcoding study on polychaetes from floating dock communities on the New England coast which adds to a growing number of studies that are incorporating molecular barcoding into rapid assessment surveys.
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Acknowledgements
The authors would like to acknowledge the gracious support of our sponsors: the Buzzards Bay National Estuary Program, the Casco Bay Estuary Partnership, the Massachusetts Bays National Estuary Program and the Massachusetts Office of Coastal Zone Management. We would also like to thank Adrienne Pappal and Cristina Kennedy for the logistics and organization of the 2018 Rapid Assessment Survey. Lab space for initial identification was provided by Prof. Larry Harris at the University of New Hampshire. The authors would also like to thank Dr. Judith Pederson and Ms. Megan McCuller for assistance during sampling and Dr. James Carlton for valuable input during the revision process.
Disclosure statement
No potential conflict of interest was reported by the authors.