Expected Results Impact

Scientifc-Technical, social and economic impact

The potential impact of IMPRESS is very high because it has been designed to provide effective information for fisheries stock assessment and to fit in the “2030 Agenda for Sustainable Development”. Indeed, On 5 December 2017, the United Nations declared that a Decade of Ocean Science for Sustainable Development would be held from 2021 to 2030. This Decade will provide a common framework to ensure that ocean science can fully support countries to achieve the 2030 Agenda for Sustainable Development. The Decade will mobilise resources and technological innovation in ocean science needed to “transform knowledge systems to support sustainable development” or “deliver best available knowledge to decision-makers”, objectives that fit in the IMPRESS.

Internationalization and dissemination

We will publish our results in high impact peer-review journals and we will present our scientific results at fisheries, marine ecology and modelling scientific meetings such as for example ICES/ACS conferences (www.ices.dk) and ICES assessment working groups (e.g. WGHANSA, WGEF, WGCEPH).

More importantly, we will generate relevant information for the stock assessment of several fisheries and stocks. All this knowledge will be highly relevant to contribute to current stock assessments advisor as could be also applied in different geographical areas and for other species. Therefore, we plan to outreach our results to fisheries advisory bodies as Fisheries Departments in the Autonomic Regions’ governments and Central Spanish government, ICES and STECF among others.

Finally, to outreach our results we will create a project website and social network profiles (e.g. Twitter) where information about the project and updates will be published periodically. In addition, we will make available all the scientific information using web capabilities to disseminate results from our models to a general public that do not have a statistical and/or programming background (e.g. R-Shiny package to build a web application with results from the stock assessment models and MSE applications).