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Fisheries and Optimal Eutrophication Management: A Bayesian Approach Public Deposited

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  • The paper puts forward a Bayesian Network model to study the optimal eutrophication control in coastal waters by reducing nutrient loads and removing fish biomass (bottom-up and top-down ecosystem mechanisms). The model combines an aquatic ecosystem model with an economic model and examines the economic and ecological consequences of nutrient reduction and fisheries policies. The existing literature mostly focuses on bottom-up (nutrients) control of eutrophication, while the combined effect of top-down (fisheries) and bottom-up control remains unknown. The fisheries management options include subsidizing fisheries with low or no commercial value to improve water quality. Removal of fish feeding on zooplankton or on benthic fauna may affect the nutrient dynamics and eutrophication via several mechanisms, but the relative strengths of these processes are uncertain. The Bayesian Network model allows studying uncertain causal linkages within the aquatic ecosystem and between the ecosystem and its management. The social utility function accounts for both the market and non-market values of the ecosystem goods and services- fish and water quality- provided by the studied aquatic ecosystem. The results suggest the most efficient set of management options to achieve good environmental status of the coastal waters of the Baltic Sea requested by the European Union's Marine Strategy Framework Directive
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  • Oinonen, Soile, H. Peltonen, O. Heikinheimo, L. Uusitalo, M. Lindroos. 2014. Fisheries and Optimal Eutrophication Management: A Bayesian Approach. In: Towards ecosystem based management of fisheries: what role can economics play?: Proceedings of the Seventeenth Biennial Conference of the International Institute of Fisheries Economics and Trade, July 7-11, 2014, Brisbane, Australia. Complied by Ann L. Shriver & Melissa Errend. Corvallis, OR: International Institute of Fisheries.
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  • Fisheries Research & Development Corporation, World Wildlife Fund, MG Kailis Group, AquaFish Innovation Lab, NOAA Fisheries, The European Association of Fisheries Economists, Japan International Fisheries Research Society, United Nations University, NORAD
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  • description.provenance : Approved for entry into archive by Susan Gilmont(susan.gilmont@orst.edu) on 2015-04-01T20:48:31Z (GMT) No. of bitstreams: 1 IIFET_Oinonen_100714.pdf: 1226058 bytes, checksum: 5649533a25db0e6245b3ec51ad2b521f (MD5)
  • description.provenance : Made available in DSpace on 2015-04-01T20:48:31Z (GMT). No. of bitstreams: 1 IIFET_Oinonen_100714.pdf: 1226058 bytes, checksum: 5649533a25db0e6245b3ec51ad2b521f (MD5) Previous issue date: 2014-06-07
  • description.provenance : Submitted by Melissa Errend (melissa.errend@gmail.com) on 2015-03-30T17:57:57Z No. of bitstreams: 1 IIFET_Oinonen_100714.pdf: 1226058 bytes, checksum: 5649533a25db0e6245b3ec51ad2b521f (MD5)

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