Rapid climate change has wide-ranging implications for the Arctic region, including sea ice loss, increased geopolitical attention, and expanding economic activity resulting in a dramatic increase in shipping activity. As a result, the risk of harmful non-native marine species being introduced into this critical region will increase unless policy and management steps are implemented in response. Using data about shipping, ecoregions, and environmental conditions, we leverage network analysis and data mining techniques to assess, visualize, and project ballast water-mediated species introductions into the Arctic and dispersal of non-native species within the Arctic. We first identify high-risk connections between the Arctic and non-Arctic ports that could be sources of non-native species over 15 years (1997–2012) and observe the emergence of shipping hubs in the Arctic where the cumulative risk of non-native species introduction is increasing. We then consider how environmental conditions can constrain this Arctic introduction network for species with different physiological limits, thus providing a tool that will allow decision-makers to evaluate the relative risk of different shipping routes. Next, we focus on within-Arctic ballast-mediated species dispersal where we use higher-order network analysis to identify critical shipping routes that may facilitate species dispersal within the Arctic. The risk assessment and projection framework we propose could inform risk-based assessment and management of ship-borne invasive species in the Arctic.
The spread of nonindigenous species by shipping is a large and growing global problem that harms coastal ecosystems and economies and may blur coastal biogeographical patterns. This study coupled eukaryotic environmental DNA (eDNA) metabarcoding with dissimilarity regression to test the hypothesis that ship‐borne species spread homogenizes port communities. We first collected and metabarcoded water samples from ports in Europe, Asia, Australia and the Americas. We then calculated community dissimilarities between port pairs and tested for effects of environmental dissimilarity, biogeographical region and four alternative measures of ship‐borne species transport risk. We predicted that higher shipping between ports would decrease community dissimilarity, that the effect of shipping would be small compared to that of environment dissimilarity and shared biogeography, and that more complex shipping risk metrics (which account for ballast water and stepping‐stone spread) would perform better. Consistent with our hypotheses, community dissimilarities increased significantly with environmental dissimilarity and, to a lesser extent, decreased with ship‐borne species transport risks, particularly if the ports had similar environments and stepping‐stone risks were considered. Unexpectedly, we found no clear effect of shared biogeography, and that risk metrics incorporating estimates of ballast discharge did not offer more explanatory power than simpler traffic‐based risks. Overall, we found that shipping homogenizes eukaryotic communities between ports in predictable ways, which could inform improvements in invasive species policy and management. We demonstrated the usefulness of eDNA metabarcoding and dissimilarity regression for disentangling the drivers of large‐scale biodiversity patterns. We conclude by outlining logistical considerations and recommendations for future studies using this approach.
more » « less- Award ID(s):
- 1849227
- PAR ID:
- 10404758
- Author(s) / Creator(s):
- ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; more »
- Publisher / Repository:
- Wiley-Blackwell
- Date Published:
- Journal Name:
- Molecular Ecology
- Volume:
- 32
- Issue:
- 23
- ISSN:
- 0962-1083
- Format(s):
- Medium: X Size: p. 6696-6709
- Size(s):
- p. 6696-6709
- Sponsoring Org:
- National Science Foundation
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