Final Report: The REFRESH Models
Abstract: This deliverable summarizes the efforts of partners in Workpackage 5 to develop a set of ecological models based on Bayesian belief networks (BBNs). These have become known as the REFRESH Models. The models are aimed at predicting the effects of climate and land use change on various ecological responses. These include classes of organisms used as ecological indicators such as phytoplankton, cyanobacteria, macroinvertebrates and macrophytes; wetland plant communities; Water Framework Directive status and key lake physical and chemical variables. The models were developed as part of the remit of REFRESH to develop and improve models of the biological and ecological response to environmental change, and to advance the state-of-the art in freshwater ecosystem science. As such, not all the models have developed to the point where they are able to make credible predictions, but they all have the prospect of doing so. Applications of BBNs were made to Lake Vansjø in Norway; forested steams in The Netherlands; the River Louros in Greece; and lowland wetland communities in the UK. This illustrates the versatility of these models. They allow the incorporation of different types of information, such as data, results from other models, and expert judgement, to be combined into a single model. They produce probabilistic predictions, recognising the uncertainties involved and presenting them in an accessible way. They facilitate the testing of hypotheses by making the assumptions involved in expert judgement explicit, and enabling testing of these judgements against data. All these advantages are illustrated in the case studies described here. The REFRESH Project has provided a valuable platform for the development of these models, so they can be taken forward in other projects.
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