Established and potentially invasive fish of the Laurentian Great Lakes
Jerde, Christopher; Mahon, Andrew; Grey, Erin (2022), Established and potentially invasive fish of the Laurentian Great Lakes, Dryad, Dataset, https://doi.org/10.25349/D9KW49
Environmental DNA (eDNA) metabarcoding has shown promise as a tool for estimating biodiversity and early detection of invasive species. In aquatic systems, advantages of this method include the ability to concurrently monitor biodiversity and detect incipient invasions simply through the collection and analysis of water samples. However, depending on the molecular markers chosen for a given study, reference libraries containing target sequences from present species may limit the usefulness of eDNA metabarcoding. To explore the extent of this issue and how it may be resolved to aid biodiversity and invasive species early detection goals, we focus on fishes in the well-studied Laurentian Great Lakes region. First, we provide a synthesis of species currently known from the region and of non-indigenous species identified as threats by international, national, regional, and introduction pathway-specific fish risk assessments. With these species lists, we then evaluate 23 primer pairs commonly used in fish eDNA metabarcoding with available databases in terms of sequence coverage and species specificity. Finally, we identify established and potentially invasive non-indigenous fish that should be prioritized for genetic sequencing to ensure robust eDNA metabarcoding going forward for the region. Our results should increase confidence in using eDNA metabarcoding for fisheries conservation and management in the Great Lakes region and help prioritize reference sequencing efforts. The ultimate utility of eDNA metabarcoding approaches will come when conservation management of existing fish communities is integrated with early detection efforts for invasive species surveillance to assess total fish biodiversity.
To generate an inclusive species list of fish species currently present in the Great Lakes (GL) basin we merged two databases. The first species list is the default generated by the GAPeDNA program for freshwater fish (Marques et al. 2021). This list is sourced from a global database of freshwater fish occurrences by basin and was compiled by extensive searches of available peer-reviewed literature, reports, and theses (Tedesco et al. 2017). The second list was compiled by Roth et al. (2013) as a checklist of fish species found within the Great Lakes and their watersheds. Both lists were compared to reconcile species name changes or synonyms using FishBase (Froese & Pauly 2000).
To complement our biodiversity database for fish already present in the GL basin, we identified fish risk assessments of potential invasive freshwater species conducted for the Laurentian Great Lakes, the United States, and globally. We considered both peer-reviewed literature and grey literature publications. For the Great Lakes, we identified three lists: Snyder et al. (2014), Davidson et al. (2014), and an application of the Howeth et al. (2015) quantitative risk assessment to the Great Lakes available at http://takeaim.org/wp-content/uploads/2016/11/FishRA_assesses_species_PC_May_19.pdf. The species lists for these risk assessments are denoted as Snyder, Davidson, and NDSTAIR, respectively. While a decision tree approach to Great Lakes fish risk assessment was developed by Kolar and Lodge (2002) for Ponto Caspian region of origin, we used the update of this approach provided by Snyder et al. (2014) for this study. The Davidson list is comprehensive to identify invasive species to the entirety of the Great Lakes, but Snyder considers only potential invaders from the Ponto Caspian region. The NDSTAIR risk assessment emphasizes the trade pathway and considers only that vector for fish introduction.
At the national level, we identified two risk assessments: the US Fish and Wildlife High Risk Species (https://www.fws.gov/fisheries/ANS/erss_high_risk.html) used for rapid assessment of potentially invasive fish that is coupled to a Bayesian network decision tool (Marcot et al. 2019), and the species listed under the US Lacey Act found at https://www.fws.gov/injuriouswildlife/list-of-injurious-wildlife.html. The species lists for these risk assessments are denoted as USFWS and Lacey, respectively. The former is meant to inform resources managers, stakeholders, and the public about species with the potential to become invasive and motivate further research. It is based on two key factors similarity of climate between the native and/or established range and the United States and history of invasiveness. The Lacey Act fish species list is reactive to invasive species identified as causing damages (Fowler et al. 2007), but in our framework, we consider the listed fish that have not established in the Great Lakes.
Two risk assessments identified potentially invasive freshwater fish at the global scale - the “100 of the World’s Worst Invasive Alien Species Lists” developed by the IUCN’s Global Invasive Species Database in 2014 and available at http://www.iucngisd.org/gisd/100_worst.php, and a list of potential invaders for current and future climates as determined by the FISK risk assessment tool (Copp 2013, Vilizzi et al. 2021). The species lists for these risk assessments are denoted as WW and Vilizzi respectively. In contrast to the USFWS risk assessment, these fish may not have an appropriate climate match for the Great Lakes, but given their history of global invasiveness, and as Vilizzi et al. (2021) pointed out, with our changing climate, it is potentially advantageous to further consider some of these ‘unlikely to establish under current conditions but known to be damaging’ fish for surveillance.
NASA Headquarters, Award: NNX14AR62A
Bureau of Ocean Energy Management, Award: MC15AC00006