Coastal Fish Production in the Northern Baltic Sea

By: Uusitalo et al, 2011

Environmental conditions play a crucial role in the distribution and abundance of fish species in any area, but the relative importance of various environmental factors is very difficult to determine. The coastline of Finland in the northern Baltic Sea offers a unique natural experimental setting that can be used to assess the relative importance of various environmental factors for the species occupying it. The area includes major variations in several crucial environmental factors: salinity, temperature regime, represented by winter ice duration, coastline characteristics, and eutrophic status. Furthermore, Finland has collected extensive and spatially representative data of water quality and environmental factors, as well as a long and extraordinarily spatially detailed data set of commercial catches of several fish species. This model attempts to correlate the environmental data to the commercial catches of fish species, assuming that the commercial catches reflect, to some reasonable degree, the productivity of that species in that area (compared to other areas and combinations of environmental factors, not to other species).We use a Bayesian network approach to examine the sensitivity of the species to the environmental factors. All of the probability distributions in the model are derived from data, with no priors or expert judgment. The data includes 36 statistical rectangles across the coast of Finland, and 21 years. The variables were discretized to approximate equal frequency of the marginal distribution, but striving also for ecological significance of the breakpoints where possible.

Select Input

Model Output(average catch (kg)/water surface(ha))

Herring

Vendace

Flounder

Pike

Roach

References

Uusitalo et al, 2011 Uusitalo, L., Kuikka, S., Kauppila, P., Soderkultalahti, P. and Back, S. (2011), Assessing the roles of environmental factors in coastal fish production in the northern Baltic Sea: A Bayesian network application. Integr Environ Assess Manag. doi: 10.1002/ieam.180

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