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Toward integrative management advice of water quality, oil spills, and fishery in the Gulf of Finland: a Bayesian approach. | LitMetric

AI Article Synopsis

  • Understanding ecosystems impacted by human activities requires methods to analyze multiple factors together in one framework.
  • A probabilistic approach is necessary because scientific knowledge about these systems often contains uncertainty.
  • This article outlines a Bayesian decision model that evaluates three stressors in the Gulf of Finland, providing probability distributions for future nutrient levels, herring stock biomass, and the likelihood of meeting water quality goals.

Article Abstract

Understanding and managing ecosystems affected by several anthropogenic stressors require methods that enable analyzing the joint effects of different factors in one framework. Further, as scientific knowledge about natural systems is loaded with uncertainty, it is essential that analyses are based on a probabilistic approach. We describe in this article about building a Bayesian decision model, which includes three stressors present in the Gulf of Finland. The outcome of the integrative model is a set of probability distributions for future nutrient concentrations, herring stock biomass, and achieving the water quality targets set by HELCOM Baltic Sea Action Plan. These distributions can then be used to derive the probability of reaching the management targets for each alternative combination of management actions.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3888659PMC
http://dx.doi.org/10.1007/s13280-013-0482-7DOI Listing

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