Assessing Populations Diversity of Small Panel Oak (Quercus brantii) in Western Forests of Iran: a Major Effort in Reforestation Programs

Adele Rafezi, Mohammad Reza Azimi,Mehrshad Zeinalabedini,Mohammad Reza ghaffari

Journal of Nuts(2024)

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摘要
Persian oak (Quercus brantii) is a critical, economic, and environmental species of Zagros forests in Iran. The effects of climate change and drought have caused a decline in Persian oak populations, leading to a severe reduction in genetic resources for future conservation programs. This study aims to evaluate the diversity and population structure of Persian oak in the western forests of Iran using morphological features. A total of 187 samples were collected from 15 locations in the Ilam province. Twenty phenotypic traits related to leaf, seed, and trunk characteristics were evaluated. Several multivariate statistical analyses were performed. The results revealed significant morphological diversity among the Persian oak ecotypes. Correlation analyses revealed a significant positive correlation between leaf length attribute and distance from leaf base to maximum leaf width (0.55) and maximum width of the leaflet (0.64) traits. The leaf width at 50% attribute with the maximum width of the leaflet and distance from leaf base to maximum leaf width have a positive (0.8 and 0.51 respectively) and significant correlation (p≤0.05). According to principal component analysis, the components of leaf and seed traits have the most impact on morphological variance. Hierarchical cluster analysis divided the locations into two groups, with some oak locations distributed in two clusters, indicating higher diversity of this species in different locations. Further research is needed to determine the optimal ecotype; however, the oaks in Ghallaje region have characteristics that can increase their ability to resist water scarcity, making them potentially appropriate for reforestation in Ilam province.
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关键词
ecotype,hierarchical clustering,multivariate analysis,persian oak,population structure
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