Application of Generalized Mixed Model for selection of indicator effects of aquaculture on wild fish

Project facts

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Target groups
Researchers or scientists
Initial project cost:
Final project cost:
From EEA Grants:
€ 3,587
The project is carried out in:

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Aquaculture and fisheries are significant Industries that share the same resources and areas. The current knowledge and evidence for how salmon farming affects the ecosystem is indirect, circumstantial or confounded by other ecosystem modifying factors. The objective of the project is analyze globally a huge data base on fish mussel and liver issues produced during PROCOEX project for defining the best indicator of fish farming impact on wild populations. At the same time, define the best indicator that explains the fish quality for consumer and establish protocols for managers and decision makers regarding to fish farming environmental management form the point of view of sustainability. The Norwegian Institute for Nature Research (NINA) is Norway’s leading institution for applied ecological research. NINA offers broad-based ecological expertise covering the genetic, population, species, ecosystem and landscape level, in terrestrial, freshwater, and coastal marine environments.

Summary of project results

Wild fish populations are found to aggregate around fish farms but may also avoid areas with farming activity. This has several important implications for the use of resources and nurture area conflicts between the stakeholders. During the stay at NINA, the Spanish researcher was building the database of PROCOEX project and working with the data analysis of physiological and chemical variables of muscle and liver tissue samples from saith (Pollachius virens), with the aim to identify the best physiological and biological indicators of salmon aquaculture influence on this species of commercial interest. For achieving that, several statistical approaches were applied to obtain the most robust indicators with respect to the evaluation of salmon farming impact on local fisheries. Three strategies were used: Bayesian models for selection of sets of explicative variables; multivariate and univariate methods; mixed-model for definition of explicative models. Next steps will be to apply the statistical methods to the rest of variables, with the aim to identify the metabolites fatty acid and trace element print on muscle and liver, in order to select the most informative variable for monitoring salmon farming activity and evaluate the potential negative effects on wild fish population. Additionaly it will be possible to define the best indicator to explain fish physiology and health using the hepatosomatix index. Therefore it will be possible to understand the effect of salmon farming on fish health and liver metabolic status. A scientific paper is under preparation.

Summary of bilateral results

The project allows defining the best biological and physiological indicators for monitoring the influence of salmon farming on wild fish health, as well as establishing correlation among different indicators produced by different chemicals, which allows producing recommendations to managers for monitoring marine environment and help on sustainable use of marine space and living resources. The complexity of the data base and the importance of the result for Norwegians strategic sector make very important to analyses the data in a consensus way. Spanish team has been enforced by Norwegian experience on fish farming environmental management and NINA team benefited from University of Alicante’s experience on statistical analysis and study of wild fish population. NINA and UA have been collaborating form the last 8 years. They has been partners in a European protect (Prevent. Escape), a Norwegian project (COASl-ACE) and PROCOEX project. As a result of this EEA Grants project, partners are producing a joint scientific paper, and University of Alicante has been included in two proposals submitted by NINA to the Norwegian Research Council in September 2014: INDICATE – Exploring a set of management strategies to realize the successful scenarios of innovation and sustainable development of the aquaculture industry, coordinated by SINTEF; and COMPACT – Combined impacts of anthropogenic stressors on Northern coastal ecosystems: knowledge for sustainable development, coordinated by NINA.