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Growth models can be used to assess forest vulnerability to climate warming. If global warming amplifies water deficit in drought-prone areas, tree populations located at the driest and southernmost distribution limits (rear-edges) should be particularly threatened. Here, we address these statements by analyzing and projecting growth responses to climate of three major tree species (silver fir, Abies alba; Scots pine, Pinus sylvestris; and mountain pine, Pinus uncinata) in mountainous areas of NE Spain. This region is subjected to Mediterranean continental conditions, it encompasses wide climatic, topographic and environmental gradients, and, more importantly, it includes rear-edges of the continuous distributions of these tree species. We used tree-ring width data from a network of 110 forests in combination with the process-based Vaganov-Shashkin-Lite growth model and climate-growth analyses to forecast changes in tree growth during the 21st century. Climatic projections were based on four ensembles CO2 emission scenarios. Warm and dry conditions during the growing season constrain silver fir and Scots pine growth, particularly at the species rear-edge. By contrast, growth of high-elevation mountain pine forests is enhanced by climate warming. The emission scenario ( RCP 8.5) corresponding to the most pronounced warming (+1.4 to 4.8 °C) forecasted mean growth reductions of −10.7% and −16.4% in silver fir and Scots pine, respectively, after 2050. This indicates that rising temperatures could amplify drought stress and thus constrain the growth of silver fir and Scots pine rear-edge populations growing at xeric sites. Contrastingly, mountain pine growth is expected to increase by +12.5% due to a longer and warmer growing season. The projections of growth reduction in silver fir and Scots pine portend dieback and a contraction of their species distribution areas through potential local extinctions of the most vulnerable driest rear-edge stands. Our modeling approach provides accessible tools to evaluate forest vulnerability to warmer conditions. [ABSTRACT FROM AUTHOR]

Species Distribution Models ( SDMs) were employed to assess the potential impact of climate change on the distribution of Pinus uncinata in the Pyrenees, where it is the dominant tree species in subalpine forest and alpine tree lines. Predicting forest response to climate change is a challenging task in mountain regions but also a conservation priority. We examined the potential impact of spatial scale on SDM projections by conducting all analyses at four spatial resolutions. We further examined the potential effect of dispersal constraints by applying a threshold distance of maximal advancement derived from a spatially explicit, individual-based simulation model of tree line dynamics. Under current conditions, SDM s including climatic factors related to stress or growth limitation performed best. These models were then employed to project P. uncinata distribution under two emission scenarios, using data generated from several regional climate models. At the end of this century, P. uncinata is expected to migrate northward and upward, occupying habitat currently inhabited by alpine plant species. However, consideration of dispersal limitation and/or changing the spatial resolution of the analysis modified the assessment of climate change impact on mountain ecosystems, especially in the case of estimates of colonization and extinction at the regional scale. Our study highlights the need to improve the characterization of biological processes within SDMs, as well as to consider simultaneously different scales when assessing potential habitat loss under future climate conditions. [ABSTRACT FROM AUTHOR]