Work Package 6‎ > ‎

Task 6.1

Harvest control rules based on indicators capable of handling major ecosystem perturbations.

Task leader: Arne Eide (UoT)

The recent development of models for precautionary-approach management systems has, for the Barents Sea cod fishery, led to a sophisticated set of harvest control rules (HCR) based on core indicators. In Arctic animal populations, behaviour and human activities reflect adaptation to significant fluctuations among and within years. The later HCR development in the above mentioned cod fishery aims to reduce fluctuations in the fishery. Economically this may be less beneficial, as proven in several studies (Hannesson, 1975; Eide 2007) where pulse fisheries, taking advantage on natural environmental fluctuations, are shown to produce more economic rent than stable catches. The ecosystem may also be less vulnerable by choosing pulse fishing strategies, as it may lead to a lower fishing pressure when stock levels are low.

The new prognostic element in HCR rules demands better and more accurate ecosystem models in a period of global climatic change, with uncertainties related to ecosystem capability of adapting to environmental changes and increased probability of significant shifts in ecosystem structure. A stochastic ecosystem model based on cellular automata principles (Wolfram, 2002) will represent real systems, where the probability spaces are defined through the findings of other ATP workpackages. Cellular automata ecosystem modelling includes various types of spatial distribution of harvest activities, which may facilitate studies of the impact of changes in spatial distribution of species and economic activities.

The HCR concept also allows for meta-rules, which are rules on how HCR are changed as functions of new knowledge gained over time. Such dynamic HCR-rules may be studied through scenario-modelling as described by Hagen et al. (1998). The fleet model EconMult (Eide and Flaaten, 1998) is suitable as an object of HCR management in such a scenario model, covering natural fluctuations and possible impact of global warming, including abrupt changes. Stochastic representations of the Barents Sea commercial fish species, including a possible existence of system tipping points, will be utilised in a bio-economic study of different HCR systems. The HCR systems link to political decisions and the capacity of management institutions in the region (Action 3 in WP6), and to the work carried out in other work packages.

Deliverable 6.1:
Project document on the use of indicators in HCR, adaptive management, fuzzy logic and prognosis by the use of cellular automata
(May 2010)

Deliverable 6.4:
Draft paper on fisheries and harvest control rules
(August 2011)

Deliverable 6.6:
Paper on fisheries and harvest control rules submitted scientific journal
(December 2011)

Graphical presentations may serve to clarify problems, illustrate trends and give ideas about causes and effects. But it may also hide realities and confuse the viewer. One example may be the ice cover in the Arctic, at least according to the blogger authoring the short note you may read here.