developed the local boundary line using our collected samples. The upper threshold of the relationship between prior growth and percent-growth change was constructed using the procedure proposed by Black, Abrams (2004). We modified the method according to Nagel et al. (2007). The average of top ten values calculated for each 0.5 mm prior growth segment were fitted by the modified negative exponential function with additive linear term. The final boundary line yielded the highest R2 value (Fig. 1, bottom). For the identification of growth pulses we used the threshold 10 % suggested by Black, Abrams (2003). The percent-growth changes that did not reach the given threshold were dropped from further analysis. Once the final boundary line (BL) was constructed, we scaled the maximum growth changes of each identified growth pulse as a fraction of the boundary line. The pulses were classified according to Black, Abrams (2003) as follows: below 20 % of the BL "no release – effect of climate"; 20−49.9 % "moderate release"; above 50 % "major release". The disturbance history is then expressed as a portion of trees showing the release event for each decade of chronology. For the reconstruction of vertical shifts of trees within the forest space we assessed the "canopy accession events" for each tree. Following Svoboda et al. (2012), the first major release was considered as a canopy accession. For some cases the moderate release could be used as an indicator of canopy entering but it has to be the first and only release during the life of tree. Rest of the trees that did not fulfill the criteria indicating the gap recruitment was sorted with respect to their overall growth pattern (Lorimer, Frelich 1989, Svoboda et al. 2012).
In studied sample, a relatively high variability regarding the individuals age was recorded. The age of sampled spruces ranged from 47 to 226 yr with the mean ageof145±50 yr. Diameter structure was relatively homogenous, with the average diameter of 41.9±13.9 cm. When the age-diameter relation was examined, the regression analysis showed a quite weak relationship (R2=0.49, p=0.001) (Fig.2, top).
Regarding the recruitment of spruce trees, the analysis exhibited the fairly continuous recruitment during the whole studied period, except the decades 1790 and 1920 (Fig. 2, bottom). We recorded three periods of high tree recruitment: 1800−1830 (34 % of all sampled trees), 1860 (12 % of trees during one decade) and 1910−1930 (25 % of all recruited trees).The analysis confirmed one period of low tree recruitment (1880−1900) and a decreasing tendency in tree recruitment in the period since the 1940 that is dominated exclusively by under-canopy originated individuals.
Through the analysis of abrupt growth changes we detected 226 maximum growth changes with an average value 4.7±2.2 of growth pulse per tree. Growth pulses characterized by the maximum growth changes were scaled