| Description: |
The North Sea has one of the longest histories of extensive human use of all oceans of the world, and for generations, its fish stocks have been targeted by fleets of all adjacent nations. In recent years, some of its overexploited stocks have recovered, yet fleet sizes continue to decline, and many fleets are struggling to survive. Economic pressures such as surging fuel costs and dwindling prices for key target species, spatial competition with offshore energy production, marine conservation and other forms of use, and climate-driven ecosystem changes have significant effects on those fleets and call for new strategies in fisheries research and management. In this thesis, a holistic approach towards these pending issues is presented, covering some of the core areas necessary to comprehend the complexity of demersal North Sea fisheries: Data collection schemes, bio-economic modeling, species distribution changes, and alternative management approaches. In the first chapter, a technical improvement of the EU's fisheries Data Collection Framework (DCF) is presented. The DCF is one of the pillars of the Common Fisheries Policy (CFP) of the EU, in which member states coordinate the collection and processing of all relevant fisheries data. One obligation of the member states active in the DCF is, therefore, the collection of socio-economic data of fisheries, a task requiring the separation of a nation’s fishing fleet into fleet segments. Since the current DCF segmentation scheme is solely based on technical characteristics of the vessels, operational characteristics and fishing strategies are not well accounted for, hampering targeted management strategy evaluation and applicability of the collected data in research and management. In order to improve this process, an alternative approach to the segmentation of fishing fleets based on multivariate statistics and applying machine learning functions for automation was developed. To test the approach’s efficiency, it was applied to two decades of German fishing fleet ... |