The Danube Delta, the second-largest wetland in Europe, provides people with multiple ecosystem services, consisting of drinking water, food, flood protection, nutrient recycling, and recreation, as it is a complex social–ecological system. Nowadays, the area faces heavy depopulation due to its failure in achieving an equilibrium between social, economic, and environmental issues. Therefore, its resurgence is the core element of its sustainable development strategy, and particular sectors such as fishing and aquaculture, agriculture, and tourism national strategies deal individually with essential issues without considering the potential conflicts that may arise from a particular sector’s development. This study develops a complex method for decision making concerning the sustainable development of the Danube Delta Biosphere Reserve based on the consultation of both local and higher-level stakeholders in decision making, and the identification of social, economic, and environmental key problems. After their validation by experts, we developed a system dynamics model and ran the identified scenarios together with the stakeholders and recommended policies for the sustainable development of the area. The scenario that combines the transition towards the moderate Intensification of aquaculture with ecological agriculture and slow tourism brings a reduced impact on water quality, but measures to reduce nutrients are still recommended.

The European honey bee species (Apis mellifera L.) is under increasing pressure from anthropogenic and other stressors. Winter mortality of entire colonies is generally attributed to biological, environmental, and management conditions. The rates of winter mortality can vary extremely from place to place. A landscape approach is used here to examine the dependency between spatially distributed winter mortality rates, environmental and biological conditions, and apiary management. The analysis was applied to data for the region of Wallonia in Belgium with winter mortality rates obtained from the European project EPILOBEE. Potential explanatory variables were spatially allocated based on GIS analysis, and subjected to binomial linear regression to identify the most predominant variables related to bee winter mortality. The results point to infestation with Varroa, the number of frost days, the potential flying hours, the connectivity of the natural landscape, and the use of plant protection products as most dominant causes for the region of Wallonia. The outcomes of this study will help focus beekeeping and environmental management to improve bee health and the effectiveness of apiary practices. The approach surpasses application to the problem of bee mortality and could be used to compare and rank the causes of other environmental problems by their significance, particularly when these are interdependent and spatially differentiated.

Model selection is a critical aspect of designing a tool for integrated river basin management. Without scientific guidelines models may be selected in an ad‐hoc manner based on practical considerations such as data availability and computational load. A more systematic approach for model selection can be achieved by examining the interaction of coupled models in terms of sensitivity and uncertainty propagation at an early stage of the design. Such a design approach is also referred to by the term ‘appropriate modeling’. The recently completed decision‐support system (dss) for the River Elbe in Germany includes a large‐scale floodplain vegetation model and a 1D river schematization to describe the hydraulic conditions at a regional (500 km) scale. The key factors that influence the vegetation patterns are the flooding frequency in the floodplains and the land‐use practice in the floodplain area. The choice between a 1D hydrostatic and 2D hydrodynamic schematization to describe the effect of dike shifting on the floodplain vegetation is used as case example to demonstrate the principle of appropriate modeling. Whether a 1D approach will be sufficient depends on the purpose and sensitivity of the models that are coupled. The differences between the vegetation patterns obtained with the 1D and 2D hydraulic approach are compared with the effects of climate change, land use, and data uncertainty to illustrate this.