Integrating stochastic age-structured population dynamics into complex fisheries economic models for management evaluations: the North Sea saithe fishery as a case study
Author(s) -
Sarah Simons,
Heleen Bartelings,
Katell G. Hamon,
Alexander Kempf,
Ralf Döring,
Axel Temming
Publication year - 2014
Publication title -
ices journal of marine science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.348
H-Index - 117
eISSN - 1095-9289
pISSN - 1054-3139
DOI - 10.1093/icesjms/fsu049
Subject(s) - fishing , stock (firearms) , discards , profit (economics) , fishery , net present value , net profit , fisheries management , disinvestment , population , economics , business , engineering , incentive , microeconomics , demography , production (economics) , sociology , biology , mechanical engineering
There is growing interest in bioeconomic models as tools for understanding pathways of fishery behaviour in order to assess the impact of alternative policies on natural resources. A model system is presented that combines stochastic age-structured population dynamics with complex fisheries economics. Explicitly, the economic response of fleet segments to changes in stock development is analysed by applying observed values and stochastic recruitment. The optimization 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. This tool was applied to the North Sea saithe fishery, where ICES re-evaluated the existing EU–Norway management plan, focusing on biological reference points only. Two scenarios were tested with alternative harvest control rules and then contrasted with one unregulated scenario with no quotas and driven by optimizing the net profit of the whole fleet. The model showed the success of both harvest control rules in rebuilding the stock and the associated costs to the fleets in terms of maximal 21% reduction in net profits, 21% reduction in crew wages and 11% reduction in fleet size in the midterm (2007–2015). In the long term (2022), successful stock recovery coincided with net profits almost equalling that of the unrestricted fishery. The model is highly sensitive to the parameter values but can be used strategically, providing a qualitative understanding of the anticipated relative changes.
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