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Abstract: Assessments of future tree species’ distributions should account for time lags in the adaptation of their external range limits to climatic changes. In simulation experiments it is therefore necessary to capture processes that influence such time lags, in particular tree species’ migration. We hypothesise that directional processes such as migration are sensitive to the exact sequence of simulated climate influences, and that the uncertainty associated with a given interannual climate variability has to be accounted for when simulating migration explicitly. In this paper we used the intermediate-complexity multi-species model TreeMig to examine whether different realisations of future climate influences with the same temporal mean and the same interannual variability cause fundamental differences in simulated migration. We assume that the impact of interannual climate variability becomes most apparent in situations which critically influence regeneration and survival. Such situations arise, for example, when species’ sensitivities to climate, competition and spatial fragmentation interact. We therefore developed an illustrative and realistic simulation setup representing this situation. We simulated the northwards migration of the sub-Mediterranean tree species Ostrya carpinifolia Scop. (European Hop Hornbeam) through the highly fragmented and climatically heterogeneous landscape of the Swiss Alps. Situations critically influencing regeneration and survival can lead to low species’ abundances. Before investigating effects of interannual climate variability, we therefore tested whether the continuous representation of species’ cell populations in TreeMig, which allows for infinitesimal population densities, can have side effects on simulated migration. Specifically, we tested for effects of minimum density thresholds, i.e. thresholds below which a species is treated as absent. We found that small thresholds in the magnitude of one individual per km2 cell have a considerable impact on simulated migration, and can even impede migration in situations critical for regeneration and survival. To test for effects of interannual climate variability, we compared simulation results from multiple repetitions driven by different annual climate time series generated stochastically from the same probability distribution. Results from these repetitions were additionally compared to results from simulations driven by cyclically repeated climate and steadily applied mean climate, respectively. These comparisons were conducted for different species parameter sets within the plausible parameter range of O. carpinifolia to account for potential interactions between species’ sensitivities and the environment. Simulated tree species’ migration was highly dependent on the species parameters applied and markedly influenced by interannual climate variability. Notable divergence in species’ spread resulted amongst multiple realisations of annual climate time series stochastically sampled from the same probability distribution. We conclude that uncertainty associated with interannual climate variability has to be accounted for. Single realisations can be insufficient and mean value simulations as well as averages of output results can be too simplistic to reflect possible outcomes of tree species’ migration. [Copyright &y& Elsevier]

Abstract: Sound decisions in international climate policy depend on comprehensive and reliable emission data as well as accurate analysis and comparisons of policy proposals. In this context, the emission module of the Potsdam Real-time Integrated Model for the probabilistic Assessment of emission Paths (PRIMAP) has been developed. This article describes its design and functionality. The emission module allows for the flexible combination of data sources contained in its custom-built database into composite datasets, and the calculation of national, regional and global emission pathways following various emission allocation schemes. The resulting emission pathways can further be used to determine atmospheric CO2 concentrations and temperature probability distributions using the PRIMAP climate module, which currently incorporates the reduced complexity climate and carbon-cycle model MAGICC. In addition to the calculation of emission pathways, the PRIMAP emission module supports analysis of policy options, like the quantification of different land use, land-use change and forestry (LULUCF) accounting provisions for Annex I countries. We discuss three applications of the PRIMAP emission module. In a bottom-up approach, we implement the pledges from the Copenhagen Accord, the announced developed country emission targets, in which provisions from LULUCF are taken into account. For the derivation of developing country emission pathways two different approaches are applied: capped per capita emissions and equal cumulative per capita emissions at average developed country levels. As a third example we implement a top-down approach, which equalises cumulative per capita emissions in a global emission pathway to achieve the 2 °C target with a likely (greater than 66%) probability. [Copyright &y& Elsevier]

Abstract: Science in general and modelling in particular provide in-depth understanding of environmental processes and clearly demonstrate the present unsustainable use of resources on a global scale. The latest report by the Intergovernmental Panel on Climate Change (IPCC), for instance, shows that climate is changing and with a 95% certainty it is the humans have caused the change. The future climatic conditions are shown to be largely adversely affecting human wellbeing on this planet. Yet we see in numerous examples that societies are very slow in reacting to this rapid depletion of natural resources. What still seems lacking is the translation of scientific reports and the results of analysis and modelling into corrective actions. We argue that one of the reasons for this is the traditional workflow of environmental modelling, which starts with the purpose, the goal formulation, and ends with problem solutions or decision support tools. Instead, modelling, and applied science in general, has to enhance its scope beyond the problem solving stage, to do more on the problem definition and solution implementation phases. Modelling can be also used for identification of societal values and for setting purposes by appropriate communication of the modelling process and results. We believe this new approach for modelling can impact and bring the social values to the forefront of socio-environmental debate and hence turn scientific results into actions sooner rather than later. Instead of being separated from the modelling process, the translation of results should be an intrinsic part of it. We discuss several challenges for recent socio-environmental modelling and conclude with ten propositions that modellers and scientists in general can follow to improve their communication with the society and produce results that can be understood and used to improve awareness and education and spur action. [Copyright &y& Elsevier]

• The climate change signal is detectable in increasing evapotranspiration. • Land use enhances (reduces) evapotranspiration in afforested (deforested) areas. • The dominant role of climate change mainly depends on the impacts of precipitation. Climate change (CLI), elevated CO 2 concentration (CO 2), and land use change (LUC) have strongly altered land evapotranspiration (ET) during the recent decades. The fingerprints of these drivers in ET change, however, have not previously been detected due to the lack of these three scenarios from global climate models (GCMs). Here we applied an optimal fingerprint method to detect and attribute ET change by integrated utilization of state-of-the-art global ecosystem models and GCMs. Results indicate that CLI provides the greatest contribution to increasing ET, and its fingerprint is detectable at different timescales. CO 2 reduces ET in most areas covered by forests. LUC decreases ET over the tropics, while increases ET over temperate and high-latitude regions. To further subdivide the impacts of CLI, we extend the Budyko framework to quantify the contribution of precipitation (P) and potential evapotranspiration (PET) and find that the dominant role of CLI mainly depends on the contribution of P. [ABSTRACT FROM AUTHOR]