Norway is the largest producer of Atlantic salmon, and the government has established a strategy against escapes from aquaculture facilities with a vision that genetic influence on wild salmon populations shall not occur. The strategy has a two-pronged approach; 1) through escape-proof design and operation of aquaculture facilities and risk-based supervision by management , escapes of farmed fish shall be reduced as much as possible, and 2) in the event of escapes, genetic effects on wild populations (genetic introgression ) shall be reduced to a minimum.
Since 2019, the Institute of Marine Research has assessed the risk of further genetic change in wild populations due to introgression of aquaculture Atlantic salmon escapees, using Bayesian networks (Figure 1) . This method illustrates risk factors that can lead to possible consequences, and the uncertainty associated with these factors. Thus far t he 13 production areas along the Norwegian coast have been assessed . While management have conveyed that this methodology provides the opportunity to operationalize risk-based supervision, the current per production area resolution is too low for assessing the consequences of escapes from a given location. Thus, i n order to identify farming locations that in the event of escape have increased risk of causing further genetic introgression, the Norwegian Directorate of Fisheries put forward an order to the Institute of Marine Research, a neutral knowledge provider in advisory capacity to the Ministry of Trade, Industry and Fisheries.
The purpose of the order was to investigate the possibility of increasing the resolution of the current risk assessment in such a way that it could be used to assess the consequences of escape from a given location , on the individual wild populations . In the ongoing pilot project, the dispersal of escaped Atlantic salmon the geographical location of aquaculture facilities in connection to nearby water courses, the water courses attractiveness to escaped salmon and the resilience of the wild populations were assessed. The current talk therefore provides an example of “from science to advise” in a risk assessment framework.