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ŠUMARSKI LIST 7-8/2021 str. 47     <-- 47 -->        PDF

the clusters, and the Euclidean distance to define the distance between the studied populations. For the discriminant analysis, standardized data were used. The plot was constructed by two discriminant functions showing analyzed individuals and populations.
The above statistical analyses were conducted using the SPSS Statistics 23.0 (Nie et al. 1975; IBM Corp 2015), SYN-TAX 2000 (Podani 2001), and Past 3x (Hammer et al. 2001) statistical programs.
RESULTS
REZULTATI
Average values of needle characteristics of the 206 trees belonging to eight natural Scots pine populations from Turkey are given in Table 2. The highest mean values for needle length were observed in the two eastern populations TS and AH. In contrast, the shortest needles were observed in the AÇ, GE and BA populations, respectively. Furthermore, the longest sheaths were observed in AH and GE populations, and the widest needles in AY and GE populations. In addition, the highest values for the ratio of needle length to needle width were observed in the populations AH and TS, and the lowest for the population GE.
As expected, strong correlations between needle morphological traits were observed. Almost all measured needle traits correlated with each other at a statistically significant level. Using Spearman’s correlation coefficient, a highly positive correlation was found between altitude and needle width. On the other hand, needle length and the ratio of needle length to needle width were highly negatively correlated with the altitude.
The ANOVA revealed significant differences with respect to needle properties among the eight populations examined, with the exception of sheath length, which did not significantly differ among tested populations. The trees within populations differ significantly for all studied ­variables.
The structure of the eight Scots pine populations was inferred by the cluster analysis. The results are presented with the hierarchical tree (Figure 1), where the unweighted pair-group method with arithmetic mean (UPGMA) was used to join the clusters. The results clearly indicated that studied populations can be divided into three distinct sub-clusters. The first sub-cluster consisted only of GE population. The second sub-cluster consisted of AH and TS populations. Finally, the third sub-cluster consisted of the