© 2015 Staats- und Universitätsbibliothek
Hamburg, Carl von Ossietzky

Öffnungszeiten heute09.00 bis 24.00 Uhr alle Öffnungszeiten

Eingang zum Volltext in OPUS

Hinweis zum Urheberrecht

Dissertation zugänglich unter
URN: urn:nbn:de:gbv:18-71018
URL: http://ediss.sub.uni-hamburg.de/volltexte/2014/7101/

Integrating biological components into a spatially explicit, complex economic model for fisheries management evaluations : the North Sea saithe fishery as a case study

Integration biologischer Komponenten in ein räumlich aufgelöstes, komplexes, ökonomisches Model zur Evaluation des Fischereimanagements : die Nordsee Seelachsfischerei als Fallbeispiel

Simons, Sarah

 Dokument 1.pdf (3.946 KB) 

SWD-Schlagwörter: Populationsdynamik
Freie Schlagwörter (Deutsch): Bio-ökonomische Modellierung , Fischereimanagementbewertung
Freie Schlagwörter (Englisch): Bio-economic modeling , fisheries management evaluation
Basisklassifikation: 43.30
Institut: Biologie
DDC-Sachgruppe: Naturwissenschaften
Dokumentart: Dissertation
Hauptberichter: Temming, Axel (Prof. Dr.)
Sprache: Englisch
Tag der mündlichen Prüfung: 31.10.2014
Erstellungsjahr: 2014
Publikationsdatum: 16.12.2014
Kurzfassung auf Englisch: It is increasingly acknowledged that the performance of future fisheries management relies to a large extent on how well one is able to evaluate and forecast the combined biological and economic impacts of management measures. When designing and implementing management plans that should sustain the resource it is essential to understand how fishermen will response to these plans, but also to ecological and economic changes that might occur simultaneously. Nowadays there is growing interest in developing bio-economic models as tools for understanding pathways of fishes' behaviour in order to assess the potential impact of alternative policies on natural resources. However, in the past the majority of models have ignored fishers' respond to management options and to natural variations. This thesis addresses the need of such an integrative bio-economic model and presents a framework, which includes the economics of multiple fleet segments, the impact of fishing on stock development and the spatio-temporal interplay of fleet segments and fish stocks. This modelling approach is based on the bio-economic optimisation and simulation model “FishRent”. Compared with other economic models, the basic version of FishRent is an advanced model, because it includes prices, costs, and fishers’ behaviour, in terms of investment, disinvestment and fishing effort distributions between fleet segments for a long period of time. The biological component of this basic version of FishRent was extended by replacing the Schaefer model, a simple deterministic stock growth production function, with a dynamic age-structured population model that accounts for stochasticity in the stock–recruitment relationship. Additionally seasonal migrations of species and dispersal of individuals to adjacent areas were included in the model. In the extended version of the model the maximisation of net profits determines the fishing effort and the investment and disinvestment behaviour of fleet segments, which, in turn, affect the level of catch rates and discards. Thus changes in fishing behaviour in terms of effort allocation patterns or entry and exit of vessels affect the catch, fishing mortality of species and ultimately the development of the fish stocks. To show the potential of the extended model it was applied to a case study, namely the North Sea saithe fishery, where the stock has been declining despite the existence of a long-term management plan. Furthermore, there has never been an impact assessment that takes into account the fleet dynamics and their impact on the fish stock under different management plan options. Thus the aim of this thesis was to improve understanding of the North Sea saithe fishery. By applying the extended model that accounts for fishers’ behaviour it was possible to determine the economic performance of several fleet segments and the development of the fish stock under different management scenarios.


keine Statistikdaten vorhanden