Modeling the economic impact of welfare interventions in fish farming—A case study from the UK rainbow trout industry

Actions that aim to improve animal welfare are likely to involve costs for the producer, although at the same time such actions may improve the profitability of production. In this article we introduce a quantitative bio-economical approach for estimating the economic consequences for improving animal welfare in the aquaculture industry; for farmers and the industry as a whole. The decision tool can be used with different welfare indicators, different species and production systems. It can be used to rank the economic consequences of different techniques that aim to improve welfare. We illustrate the decision tool with a case study relating to the use of triploids in rainbow trout farming. We highlight the probability how the benefits gained from changes in bio-economical productivity factors, and consumers' willingness to pay can overcome the costs associated with implementing a specific welfare intervention

A multi-disciplinary framework for bio-economic modeling in aquaculture: a welfare case study

This article summarizes the framework that translated data from multiple disciplines into a bio-economic decision tool for modeling the costs and benefits of improving fish welfare in commercial aquaculture. This decision tool formed the basis of a recent EU research project, BENEFISH which was funded via the European Commission's Sixth Framework (FP6) initiative. The bio-economic decision model can incorporate biological data, productivity data, micro (farm) and macro (industry) level economic data, and consumer marketing and business to business data. It can identify areas for potential added value that might be achieved by improving fish welfare across a range of species and husbandry systems within European aquaculture. This article provides a brief overview of the minimum data requirements for successfully modeling the bio-economic impacts of improvements in farmed fish welfare using the model developed during the BENEFISH project. It also highlights potential bottlenecks and the minimum prerequisites for each potential data set to be used for successful modeling