- مبلغ: ۸۶,۰۰۰ تومان
- مبلغ: ۹۱,۰۰۰ تومان
Water resources globally are affected by a complex mixture of stressors resulting from a range of drivers, including urban and agricultural land use, hydropower generation and climate change. Understanding how stressors interfere and impact upon ecological status and ecosystem services is essential for developing effective River Basin Management Plans and shaping future environmental policy. This paper details the nature of these problems for Europe's water resources and the need to find solutions at a range of spatial scales. In terms of the latter, we describe the aims and approaches of the EU-funded project MARS (Managing Aquatic ecosystems and water Resources under multiple Stress) and the conceptual and analytical framework that it is adopting to provide this knowledge, understanding and tools needed to address multiple stressors. MARS is operating at three scales: At the water body scale, the mechanistic understanding of stressor interactions and their impact upon water resources, ecological status and ecosystem services will be examined through multi-factorial experiments and the analysis of long time-series. At the river basin scale, modelling and empirical approaches will be adopted to characterise relationships between multiple stressors and ecological responses, functions, services and water resources. The effects of future land use and mitigation scenarios in 16 European river basins will be assessed. At the European scale, large-scale spatial analysis will be carried out to identify the relationships amongst stress intensity, ecological status and service provision, with a special focus on large transboundary rivers, lakes and fish. The project will support managers and policy makers in the practical implementation of the Water Framework Directive (WFD), of related legislation and of the Blueprint to Safeguard Europe's Water Resources by advising the 3rd River Basin Management Planning cycle, the revision of the WFD and by developing new tools for diagnosing and predicting multiple stressors.