Recent climatic extreme events, such as the 2018-2020 drought period, demonstrate that ongoing climate change has a significant impact on our plant ecosystems, resulting in a variety of consequences such as temporal shifts in the growing season, biodiversity loss, and increased tree mortality. Forest ecosystems are especially endangered because the trees’ long lifecycles and their sessile nature impairs the potential to adapt or evade negative impacts in time. Nonetheless, forests are particularly essential because they accomplish key functions in our economic, ecological, and social lives, such as supplying timber, regulating carbon- and water cycling, or providing recreational benefits. Consequently, we need to investigate and comprehend the climatic impact on forest growth at both temporal and spatial scales. Additionally, we must examine the current state of forest vitality and productivity in order to make predictions about forest growth under changing climate. This thesis adds to our understanding of the climate-growth responses of two economically and ecologically important tree species in Central Europe within their low elevational and central distribution ranges: European beech (Fagus sylvatica L.) and Scots pine (Pinus sylvestris L.). We examine patterns in climate-driven growth responses at different spatiotemporal scales, ranging from regional to site-specific extents, and from retrospective to near real-time monitoring. In addition, we look at the possibility of employing tree-ring width (TRW) and remote-sensing (RS) data to assess forest vitality and productivity. A deeper knowledge of climate-growth responses in European beech and Scots pine will provide a foundation for decision making and forest management, assisting in the development of a resistant and resilient forest of the future. Chapter 1 provides an overview of the research objectives by situating them in the context of the present state of the art, framing the research objectives, introducing the study design, and finally formulating the research questions for this thesis. For that reason, we employ two tree-ring networks with varying spatial scales: the regional-scale Baltic Sea Network and the site-specific BDF-F-Network. The Baltic Sea Network includes TRW data from 119 pine and 55 beech study sites spread throughout the southern Baltic Sea region, which is distinguished by its predominantly medium nutritious soils, low elevation, and transitional climate ranging from maritime to more continental conditions. The BDF-F-Network, situated within the spatial extents of the Baltic Sea Network, spans along a precipitation gradient in northern Germany. It comprises 54 permanent monitoring plots with substantial information on soil and tree status dating back 40 years. During this PhD project, we extended the exhaustive data base of site-specific information by collecting TRW data for the entire network. As a result, the newly established BDF-F-Network acts as the thesis' centering point. In Chapters 2 and 3, we investigate the spatio-temporal growth responses of beech and pine in their low-elevational and central distribution ranges. Both species exhibit species-specific climate-growth responses with similar patterns at different spatial scales, i.e. when comparing the Baltic Sea and BDF-F-Network. While beech growth is predominantly impacted by summer drought conditions, winter temperature has the greatest impact on pine. We show that the main climatic drivers stay stable across spatial scales, whereas secondary climatic drivers, or climatic drivers with weaker correlations, may vary. Further, we investigate temporal instabilities in climate-growth responses for both networks by applying spatial segregation analyses and comparing growth responses for an early and a later period. We show that during the last few decades, both beech and pine have responded instable to their main climatic drivers, with increased sensitivity to summer drought and winter temperature, respectively. These temporal instabilities are visible at both regional and site-specific scales. Furthermore, Chapter 3 addresses how non-climatic and site-specific soil- and stand characteristics may influence tree growth across the BDF-F-Network's precipitation gradient. We use multilinear regression modeling to examine how stand parameters such as average tree height, diameter at breast height, and TRW differ across the gradient, and if they are impacted by soil water availability or soil type. However, our findings indicate no significant differences in site-specific soil- and stand-characteristics, with the exception of a minor effect on average tree height of European beech. In Chapter 4, we estimate the potential of TRW to assess long-term trends in beech vitality. At 9 sites, we compare the growth trends, climate sensitivities, and drought resistance of 10-20 pairs of vital and non-vital trees that are visually classified by crown condition. Moreover, we use individual heterozygozity as a proxy to determine if differences in growth behavior are caused by genetic predisposition. Surprisingly, growth responses and individual heterozygozity are similar in non-/vital trees. At several study sites, some as vital classified trees exhibit an even greater reduction in TRW than non-vital trees. In summary, we show that TRW is a better proxy for assessing long-term trends in tree vitality, compared to crown condition assessments that are defined by a high year-to-year dynamic. Similarly, Chapter 5 seeks to study the potential of satellite-derived leaf area index (LAI) series to monitor and evaluate forest productivity using European beech as an example. We employ an interdisciplinary approach by combining medium resolution LAI time series derived from two separate satellite sensors (SPOT-VGT/PROBA-V and MODIS), as well as long-term masting monitoring and TRW data from BDF-F-Network sites. By applying site-specific and across-network correlation analysis, we analyze the link between these three target parameters and identify common climatic drivers. While SPOT-VGT/PROBA-V LAI is negatively correlated with masting and positively correlated with TRW, finer resolved MODIS data does not show any significant relationships. We show that RS data from the SPOT-VGT/PROBA-V sensor could be a useful tool for assessing forest vitality and productivity if the LAI time series are sufficiently long. Furthermore, our findings indicate that masting and TRW are both influenced by summer climate conditions, whereas RS LAI appears to be climatically de-coupled. Our findings suggest that RS data has the potential to explore masting and hence forest productivity, but it should always be evaluated in light of the restrictions of different RS products. Finally, Chapter 6 summarizes the preceding chapters' findings and discusses them in the context of the research questions provided at the beginning of the thesis.