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Coastal dunes near the Baltic Sea are often stabilized by Scots pine forests and are characterized by a mild climate. These ecosystems are affected by water shortages and might be influenced by climate extremes. Considering future climate change, utilizing tree rings could help assess the role of climate extremes on coastal forest growth. We used superposed epoch analysis to study Scots pine responses to droughts and cold winters, with focus on frequency, timing, and duration. We measured ring widths (RW) and latewood blue intensity (LBI) on samples extracted from trees growing at dune ridge and bottom microsites at the south Baltic Sea. At the regional scale, we observed some similarities in tree responses to both extremes between RW and LBI within the same microsite type and region. At the local scale, RW and LBI were more frequently influenced by cold winters than droughts. RW and LBI from dune ridges were more frequently influenced by droughts than RW and LBI from dune bottoms. LBI from both microsites was more often influenced by droughts than RW. RW and LBI from both microsites were similarly often influenced by cold winters. At both scales, the response time of RW and LBI after droughts predominantly lagged by one year, while cold winters were recorded in the same year. The typical duration of growth reductions after both extremes was one year for both RW and LBI. Our study indicates that Scots pine from the Baltic Sea region is sensitive to climate extremes, especially cold winters.
Observed recent and expected future increases in frequency and intensity of climatic extremes in central Europe may pose critical challenges for domestic tree species. Continuous dendrometer recordings provide a valuable source of information on tree stem radius variations, offering the possibility to study a tree's response to environmental influences at a high temporal resolution. In this study, we analyze stem radius variations (SRV) of three domestic tree species (beech, oak, and pine) from 2012 to 2014. We use the novel statistical approach of event coincidence analysis (ECA) to investigate the simultaneous occurrence of extreme daily weather conditions and extreme SRVs, where extremes are defined with respect to the common values at a given phase of the annual growth period. Besides defining extreme events based on individual meteorological variables, we additionally introduce conditional and joint ECA as new multivariate extensions of the original methodology and apply them for testing 105 different combinations of variables regarding their impact on SRV extremes. Our results reveal a strong susceptibility of all three species to the extremes of several meteorological variables. Yet, the inter-species differences regarding their response to the meteorological extremes are comparatively low. The obtained results provide a thorough extension of previous correlation-based studies by emphasizing on the timings of climatic extremes only. We suggest that the employed methodological approach should be further promoted in forest research regarding the investigation of tree responses to changing environmental conditions.