Faculty of Biology
PhD thesis: Utility of Bayesian Belief Networks in assessment and management of aquatic ecosystems
Bayesian Belief Networks allow for combination of empirical data, values derived from literature, stakeholder and expert knowledge. Therefore, data gaps and uncertainties do not affect diagnosis and prognosis of complex cause-effect relationships. The development and application of Bayesian Belief Networks is part of both the international project Land2Sea and several national projects.
The scientific objective of Land2Sea is to develop and provide an integrative framework of coupled models in order to predict the impacts of land-use and climate change on aquatic biodiversity, aquatic ecosystem functions and aquatic ecosystems‘ contributions to people for various future scenarios. The dissertation’s contribution to Land2Sea is the development of Bayesian Belief Networks for a marine case study along the Swedish west coast and a freshwater case study in Northern Germany. The cause-effect relationships between land-use, climate change, aquatic biodiversity and ecosystem functions are primarily modelled.
The objective of the national projects is to develop Bayesian decision support tools for the management of running waters in order to improve their ecological status in future. The dissertation contributes to these projects by developing Bayesian Belief Networks for various types of running waters. These facilitate the identification of causes of degradation based on biological assessment results (according to the Water Framework Directive).