Phenotypic variation in Phoebe bournei populations preserved in the primary distribution area

Abstract

Phoebe bournei (Hemsl.) Yang is a rare and protected plant in China. This study was conducted to determine the phenotypic variation in this species and to document phenotypic variation within and among populations of P. bournei. Nested analysis of variance, coefficient of variation, multiple comparisons, principal component analysis (PCA) and correlation analysis were used to analyze ten phenotypic traits in ten natural populations of P. bournei from both the northeastern and the primary region of the range of this species. Significant differences among and within populations were observed in leaf and seed phenotypic traits. Variation among populations (34.92%) was greater than that within populations (26.19%). The mean phenotypic differentiation coefficient was 53.77% among populations, indicating that variation among populations comprised the majority of the phenotypic variation of P. bournei. The coefficient of variance (CV) of ten traits varied from 6.44 to 18.45%, with an average of 12.03%. The CV of leaf traits among populations (15.64%) was higher than that of seed traits (8.60%), indicating that seed traits were more stable. The results from CV and PCA indicated that leaf area, leaf length and thousand seed weight were the main factors accounting for the observed phenotypic variations. Significant or highly significant correlations were observed among most leaf and/or in seed phenotypic traits, whereas no significant correlations were observed between phenotypic traits and geographic factors. Based on cluster analysis, the ten populations can be divided into three clusters. These clusters were not a result of geographic distances.

DOI: 10.1007/s11676-017-0409-4

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Cite this paper

@article{Li2017PhenotypicVI, title={Phenotypic variation in Phoebe bournei populations preserved in the primary distribution area}, author={Yingang Li and Xinhong Liu and Junwei Ma and Xiaomian Zhang and Li-an Xu}, journal={Journal of Forestry Research}, year={2017}, pages={1-10} }