Screening for High-Risk Marine Invaders in the Hudson Bay Region, Canadian Arctic - Goldsmit, Jesica; McKindsey, Christopher W.; Stewart, D. Bruce; Howland, Kimberly L. (Frontiers in Ecology and Evolution, 2021)
The Canadian Arctic is receiving increased ship traffic, largely related to non-renewable resource exploitation and facilitated by climate change. This traffic, much of which arrives in ballast, increases opportunities for the spread of aquatic invasive species (AIS). One of the regions at greatest risk is the Hudson Bay Complex. A horizon scanning exercise was conducted using the semi-quantitative Canadian Marine Invasive Screening Tool (CMIST) to identify AIS of potential concern to the region. This screening-level risk assessment tool, uses documented information to answer questions related to the likelihood and impact of invasion. Species were analyzed by ecological categories (zoobenthos, zooplankton, phytobenthos) and taxonomic groups, with 14 species (out of 31) identified as being of highest relative risk. Crabs, molluscs, macrozooplankton and macroalgae were the taxonomic groups with the highest overall risk scores, through a combination of higher likelihood of invasion and impact scores relative to other taxa. Species that may pose the highest AIS risk are currently mainly distributed on the east and west coasts of the North Atlantic Ocean. Their distributions coincide with source ports and shipping pathways that are well connected to the Hudson Bay Complex. This first horizon scan to identify potential high-risk AIS for the Canadian Arctic incorporated two novel approaches into the CMIST analysis: i) use of the tool to assess two new ecological categories (phytobenthos and zooplankton), and ii) use of averaged CMIST results to interpret general risk patterns of ecological categories. This study is also the first to use CMIST scores to highlight common source regions and connected ports for the highest risk species. In a scenario of climate change and increasing ship traffic, this information can be used to support management actions such as the creation of watch lists to inform adaptive management for preventing AIS establishment, and mitigating associated environmental and economic impacts.