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Biodiversity of macrobenthic nematodes in the intertidal and shallow subtidal zones in the Eastern Canadian Arctic. Polar Biol 2022. [DOI: 10.1007/s00300-021-02989-z] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/19/2022]
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Goldsmit J, McKindsey CW, Stewart DB, Howland KL. Screening for High-Risk Marine Invaders in the Hudson Bay Region, Canadian Arctic. Front Ecol Evol 2021. [DOI: 10.3389/fevo.2021.627497] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/15/2023] Open
Abstract
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, mollusks, 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.
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Saebi M, Xu J, Curasi SR, Grey EK, Chawla NV, Lodge DM. Network analysis of ballast-mediated species transfer reveals important introduction and dispersal patterns in the Arctic. Sci Rep 2020; 10:19558. [PMID: 33177658 PMCID: PMC7658980 DOI: 10.1038/s41598-020-76602-4] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/11/2020] [Accepted: 10/22/2020] [Indexed: 11/09/2022] Open
Abstract
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.
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Affiliation(s)
- Mandana Saebi
- Department of Computer Science and Engineering, University of Notre Dame, Notre Dame, IN, 46556, USA
- Center for Network and Data Science (CNDS), Notre Dame, IN, 46556, USA
| | - Jian Xu
- Department of Computer Science and Engineering, University of Notre Dame, Notre Dame, IN, 46556, USA
- Citadel LLC, Chicago, IL, 60603, USA
| | - Salvatore R Curasi
- Department of Biological Sciences, University of Notre Dame, Notre Dame, IN, 46556, USA
| | - Erin K Grey
- Division of Science, Mathematics and Technology, Governors State University, University Park, IL, 60484, USA
| | - Nitesh V Chawla
- Department of Computer Science and Engineering, University of Notre Dame, Notre Dame, IN, 46556, USA
- Center for Network and Data Science (CNDS), Notre Dame, IN, 46556, USA
| | - David M Lodge
- Cornell Atkinson Center for Sustainability, and Department of Ecology and Evolutionary Biology, Cornell University, Ithaca, NY, 14850, USA.
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Goldsmit J, McKindsey CW, Schlegel RW, Stewart DB, Archambault P, Howland KL. What and where? Predicting invasion hotspots in the Arctic marine realm. GLOBAL CHANGE BIOLOGY 2020; 26:4752-4771. [PMID: 32407554 PMCID: PMC7496761 DOI: 10.1111/gcb.15159] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 09/26/2019] [Revised: 05/03/2020] [Accepted: 05/04/2020] [Indexed: 06/11/2023]
Abstract
The risk of aquatic invasions in the Arctic is expected to increase with climate warming, greater shipping activity and resource exploitation in the region. Planktonic and benthic marine aquatic invasive species (AIS) with the greatest potential for invasion and impact in the Canadian Arctic were identified and the 23 riskiest species were modelled to predict their potential spatial distributions at pan-Arctic and global scales. Modelling was conducted under present environmental conditions and two intermediate future (2050 and 2100) global warming scenarios. Invasion hotspots-regions of the Arctic where habitat is predicted to be suitable for a high number of potential AIS-were located in Hudson Bay, Northern Grand Banks/Labrador, Chukchi/Eastern Bering seas and Barents/White seas, suggesting that these regions could be more vulnerable to invasions. Globally, both benthic and planktonic organisms showed a future poleward shift in suitable habitat. At a pan-Arctic scale, all organisms showed suitable habitat gains under future conditions. However, at the global scale, habitat loss was predicted in more tropical regions for some taxa, particularly most planktonic species. Results from the present study can help prioritize management efforts in the face of climate change in the Arctic marine ecosystem. Moreover, this particular approach provides information to identify present and future high-risk areas for AIS in response to global warming.
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Affiliation(s)
- Jesica Goldsmit
- Fisheries and Oceans CanadaMaurice Lamontagne InstituteMont‐JoliQCCanada
- Department of Biology, Science and Engineering FacultyArcticNetTakuvikLaval UniversityQuebec CityQCCanada
- Fisheries and Oceans CanadaArctic Research DivisionFreshwater InstituteWinnipegMBCanada
| | | | | | | | - Philippe Archambault
- Department of Biology, Science and Engineering FacultyArcticNetTakuvikLaval UniversityQuebec CityQCCanada
| | - Kimberly L. Howland
- Fisheries and Oceans CanadaArctic Research DivisionFreshwater InstituteWinnipegMBCanada
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