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•Research is also needed into the preservation of wilderness especially the interactions of these events with sea level rise (e.g. areas in Europe, restoration of such areas, and their importance high storm tides), may be beyond scope. However, the accuracy for conserving valuable ecosystems and biodiversity. These regions of the predictions can at some point probably be estimated more represent a form of natural resource capital that, ideally, should be realistically than is possible today. Climate and ecosystem model passed to future generations; and analyses must be understood in terms of uncertainties, and ef- forts must be made to ensure the proper communication of these •As mentioned in the draft of Horizon 2020, a coordinated data- uncertainties to policymakers and the public. In addition, changes gathering network is needed to provide comprehensive long-term tend to become essential to ecosystems, as well as societal and observations of climate and ecosystems, and monitors the climate economic systems, only beyond a certain level of change. Decision impacts on ecosystems. Several such networks are already estab- makers might profi t signifi cantly by scientists’ ability to constrain this lished, but more are needed. In particular, these networks must level well, as this can translate into time left for action. cover the high latitudes areas, where ecosystems are experiencing very rapid changes. The information gained must be easily usable Main research areas include: and readily accessible by a wide scientifi c community. •Reducing model uncertainties by statistical comparison of model outputs; UNDERSTANDING UNCERTAINTIES IN THE PREDICTION OF FUTURE CLIMATE CHANGE AND •Increasing the spatial resolution of models and improving the ITS ECOSYSTEM CONSEQUENCES representation of processes; Models constitute important instruments to predict future conse- quences of global change. Reducing the uncertainty of model •Studies of predictability on a decadal timescale as well as predictions and assessing the robustness of model outcomes predictability limits for highrisk and high-uncertainty events. These essentially relies on the improved understanding of climate, must be followed by strategies for decision making in case of their ecosystem, and resource management mechanisms due to, for occurrence; example, process studies and advanced data assimilation meth- ods between models and observations. Thus, the improvement •Constraining critical levels of change; of model predictions draws heavily on progress made in the two previously mentioned research areas. •New approaches to modelling biological processes in ecosystem models; and It is an important and necessary element of especially climate research to improve our understanding of climate change and use •Including more advanced societal and economic models in future this knowledge to improve the climate models, hence providing more climate prediction models. accurate future climate projections (see above). However, climate models can never provide forecasts with the degree of certainty and detail that nonclimate researchers expect or need. People are mainly concerned about local impacts of climate extremes, which is the aspect that is most diffi cult to quantify. A detailed prediction of, for example, extreme weather events, and 68


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