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Potential risks of trophic impacts by escaped transgenic salmon in marine environments
Li, L.; Pitcher, T.J.; Devlin, R.H. (2015). Potential risks of trophic impacts by escaped transgenic salmon in marine environments. Environ. Conserv. 42(2): 152-161.
In: Environmental Conservation. Cambridge University Press: Lausanne,. ISSN 0376-8929, more
Peer reviewed article  

Available in Authors 

    Ecosystems; Growth hormones; Salmon; Transgenic; Marine
Author keywords
    Bottom-up effects; Ecopath with Ecosim; Monte Carlo simulation; Trophic interactions; Vulnerabilities

Authors  Top 
  • Li, L.
  • Pitcher, T.J.
  • Devlin, R.H.

    There is significant concern about potential ecological effects of introduced organisms, including non-indigenous species and those created by genetic modification. This paper presents an Ecopath with Ecosim modelling approach, designed to examine long-term trophic effects of growth hormone (GH) transgenic coho salmon should they ever escape to a coastal salmonid ecosystem, namely the Strait of Georgia in British Columbia (Canada). The model showed that the effects of introduced GH transgenic coho salmon varied with their biomass, diet, structure of the invaded ecosystem, and environmental conditions. Occasional escapes of non-reproductive salmon did not have a significant impact on the example ecosystem. However, effects of GH coho salmon varied with their diet when large numbers of these fish were present in the simulated ecosystem (for example, when they constituted 20% of total current aquaculture production in the area). Further, climate-driven changes in the biomass of low trophic levels (bottom-up effects) could have a greater impact on the ecosystem than the introduction of large numbers of GH coho salmon. A new version of Ecopath with Ecosim's Monte Carlo approach showed that the model predictions were robust to GH coho salmon's Ecopath parameters, but more sensitive to vulnerabilities of prey to GH coho salmon. Modelling ecosystem effects of genetically modified organisms provides a complementary approach for risk assessments when data from nature are not readily obtainable.

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