Chin J Plant Ecol ›› 2018, Vol. 42 ›› Issue (12): 1168-1178.doi: 10.17521/cjpe.2018.0196

• Research Articles • Previous Articles     Next Articles

Leaf phenotypic variation in natural populations of Cerasus dielsiana

ZHU Hong,ZHU Shu-Xia,LI Yong-Fu,YI Xian-Gui,DUAN Yi-Fan,WANG Xian-Rong()   

  1. Co-Innovation Center for Sustainable Forestry in Southern China, College of Biology and the Environment, Key Laboratory of State Forestry and Grassland Administration on Subtropical Forest Biodiversity Conservation, Nanjing Forestry University, Nanjing 210037, China
  • Received:2018-08-10 Revised:2018-11-02 Online:2019-04-04 Published:2018-12-20
  • Contact: WANG Xian-Rong ORCID: 0000-0003-4048-2748 E-mail:wangxianrong66@njfu. edu.cn

Abstract:

Aims Cerasus dielsianais a wild cherry species endemic to the subtropical forest of China, and was regarded as a promising ornamental resource. Our objectives were to determine the leaf phenotypic variation, adaptation and patterns in eight natural C. dielsiana populations.

Methods We analyzed eleven leaf phenotypic traits from five provinces of China in eight natural populations of C. dielsianaby using multiple comparisons, nested analysis of variance, correlation analysis, principal component analysis (PCA), principal coordinate analysis (PCoA) and unweighted pair-group method with arithmetic mean (UPGMA) cluster analysis.

Important findings Results showed that 1) Rich leaf phenotypic variation existed among and within populations, and the average coefficient of variation (CV) was 22.44%, the maximum and the minimum were leaf area (CV = 50.83%) and primary lateral veins (CV = 7.96%), respectively. The mean differentiation coefficient (Vst) for all traits was 30.78%, and the variation within populations (51.55%) was higher than that among populations (22.55%). 2) The principal component analysis showed that the cumulative contribution rate of the first three main components of variation from leaf phenotypic traits of C. dielsiana made a major contribution reached to 92.400%, and can be comprehensively summarized and sorted as “size traits” (73.242%) and “shape traits” (19.158%). 3) Leaf width (r = -0.641), leaf area (r = -0.658) and primary lateral veins (r = 0.659) showed significant negative or positive correlation with longitude, and the temperature seasonality and precipitation of wettest quarter were showed more influence on leaf phenotype variation. 4) The eight natural populations of C. dielsiana could be divided into four groups according to principal coordinate analysis (PCA) and UPGMA cluster analysis. To sum up, leaf phenotypic variation in C. dielsiana is abundant, with a certain of continuity in quantity, and “size trait” is the main source of inter-trait variation. The mean differentiation coefficient at a moderate level, the phenotypic variation within populations was the main source of leaf traits variation. The results of phenotypic differentiation among populations were found to be consistent with the geographical location, and presented a gradient variation pattern dominated by longitude geographically. Meanwhile, the “climate variability” and “leaf-expansion period” are the main climatic factors that drive leaf phenotypic variation. We speculate the phenomena results from a long evolutionary adaptation of C. dielsiana to the subtropical monsoon climate.

Key words: Cerasus dielsiana, natural population, geography and climatic factors, leaf phenotypic differentiation

Table 1

Four dominant climatic variables that affect Cerasus dielsiana after principal component analysis (PCA) screening and its contributions"

代码
Code
气候变量
Climatic variables
特征值
Eigenvalue
作为第1主成分的贡献率
Variance contribution rate as first principal component (%)
bio4 气温季节变化 Temperature seasonality (SD × 100) -0.151 97.459%
bio12 年降水量 Annual precipitation (mm) 0.784
bio16 最湿季降水量 Precipitation of wettest quarter (mm) 0.420
bio18 最暖季降水量 Precipitation of warmest quarter (mm) 0.403

Table 2

Geographical locations of the eight natural populations of Cerasus dielsiana and characters of dominant climatic factors"

种群
Population
纬度
Latitude
(N)
经度
Longitude
(E)
平均海拔
Mean
altitude (m)
气温季节变化
Temperature
Seasonality
bio4 (SD × 100)
年降水量
Annual
precipitation
bio12 (mm)
最湿季降水量
Precipitation of
wettest quarter
bio16 (mm)
最暖季降水量
Precipitation of
warmest quarter
bio18 (mm)
四川峨眉山 Mt. Emei, Sichuan (EMS) 29.57° 103.37° 1 365 7.53 1 264.00 92.13 710.00
湖北神农架 Shennongjia, Hubei (SNJ) 31.45° 110.25° 860 8.15 1 696.00 51.61 557.00
湖北星斗山 Mt. Xingdou, Hubei (XDS) 30.02° 109.12° 839 8.19 1 772.00 60.22 568.00
湖南莽山 Mt. Mangshan, Hunan (MS) 24.97° 112.88° 1 228 7.66 1 492.00 56.44 601.00
湖南张家界 Zhangjiajie, Hunan (ZJJ) 29.32° 110.42° 1 118 7.91 1 591.00 62.14 556.00
江西金竹飞瀑 Jinzhufeipu, Jiangxi (JZFP) 27.00° 115.92° 966 7.20 1 508.00 60.26 609.00
江西仙姑坛 Xiangutan, Jiangxi (XGT) 28.45° 114.38° 1 364 6.86 1 405.00 62.72 591.00
台湾阿里山 Mt. Ali, Taiwan (ALS) 23.50° 120.80° 1 182 8.20 3 747.00 80.66 1 780.00

Table 3

Variations of eleven leaf phenotypic traits among eight natural populations of Cerasus dielsiana"

叶表型性状
Leaf phenotypic trait
种群 Population
EMS SNJ XDS MS ZJJ JZFP XGT ALS 平均值
Mean
变异系数 CV (%)
叶长 LL (mm) 88.80 ± 22.85a 79.08 ± 8.62b 83.40 ± 17.18ab 87.48 ± 11.27a 89.63 ± 12.56a 54.57 ± 12.41d 62.87 ± 8.19c 69.17 ± 9.14c 76.94 23.61
叶宽 LW (mm) 43.95 ± 8.73a 37.15 ± 5.44bc 33.90 ± 9.02c 34.93 ± 4.96bc 38.92 ± 8.12b 22.64 ± 6.34e 26.68 ± 4.44d 37.43 ± 3.93bc 34.45 26.39
叶长宽比 LWR 2.01 ± 0.21c 2.15 ± 0.19c 2.50 ± 0.27ab 2.53 ± 0.35a 2.36 ± 0.38b 2.44 ± 0.27ab 2.37 ± 0.19b 1.86 ± 0.14d 2.28 14.93
叶柄长
PL (mm)
11.84 ± 3.86a 8.86 ± 1.49b 7.59 ± 2.46cd 11.10 ± 2.11a 8.25 ± 1.60bc 6.63 ± 1.35d 8.53 ± 0.89bc 7.54 ± 0.89cd 8.80 29.92
叶面积
LA (mm2)
2 746.99 ± 1 337.93a 1 870.77 ± 476.40bc 2 045.84 ±
1 040.24bc
2 020.51 ± 516.34bc 2 306.43 ± 829.25a 890.91 ± 463.20f 1 095.62 ± 295.07e 1 826.66 ± 482.46d 1 846.13 50.83
叶周长
LP (mm)
213.94 ± 50.90a 183.08 ± 21.64cd 191.98 ± 44.07bc 198.99 ± 24.00abc 207.05 ± 32.44ab 127.23 ± 29.26e 146.15 ± 18.91d 171.85 ± 22.61c 179.81 23.77
叶形指数 LI 0.73 ± 0.04b 0.69 ± 0.05c 0.65 ± 0.05d 0.63 ± 0.06d 0.65 ± 0.07d 0.64 ± 0.06d 0.63 ± 0.03d 0.77 ± 0.03a 0.67 8.90
一级侧脉数 PLV 11.00 ± 0.46c 12.00 ± 0.71b 12.00 ± 1.32b 12.00 ± 0.44b 12.00 ± 0.70b 12.00 ± 0.77b 13.00 ± 0.46a 13.00 ± 0.34a 11.88 7.96
叶脉密度 VD 0.06 ± 0.01d 0.07 ± 0.01c 0.07 ± 0.01c 0.07 ± 0.01cd 0.07 ± 0.03cd 0.11 ± 0.01a 0.10 ± 0.01b 0.10 ± 0.01b 0.08 24.42
叶尖夹角
AA (°)
27.57 ± 3.42cd 28.99 ± 3.5bc 28.54 ± 4.36bc 24.56 ± 2.79e 31.02 ± 5.67b 25.22 ± 7.02de 22.99 ± 2.64e 40.24 ± 4.46a 28.64 22.87
叶基夹角
BA (°)
114.47 ± 14.05b 114.88 ± 11.04b 113.87 ± 14.78b 128.34 ±
8.24a
103.60 ±
9.34c
121.53 ± 17.54b 116.68 ± 15.03b 130.67 ± 13.33a 116.72 13.31
平均值 Mean - - - - - - - - - 22.44

Table 4

Nested variance analysis of eleven leaf phenotypic traits among eight natural populations of Cerasus dielsiana"

叶表型性状
Leaf phenotypic
trait
均方 Mean square FF value
种群间
Among polulations
种群内
Within polulations
随机误差
Random errors
种群间
Among polulations
种群内
Within polulations
LL (mm) 174.11 333.09 203.98 23.41** 44.79**
LW (mm) 41.10 83.58 47.29 27.00** 54.91**
LWR 0.16 0.12 0.07 21.94** 16.46**
PL (mm) 6.80 18.95 4.21 19.45** 54.20**
LA (mm2) 442 870.00 889 674.00 636 437.00 16.55** 33.25**
LP (mm) 262.46 1 858.26 1 160.49 22.60** 117.18**
LI 0.01 0.00 0.00 24.74** 11.63**
PLV 3.46 0.84 0.47 23.06** 5.60
VD 0.00 0.00 0.00 43.74** 55.25**
AA (°) 30.31 42.98 19.13 39.61** 56.17**
BA (°) 905.20 227.54 159.85 10.97** 2.76

Table 5

Variance component and phenotypic differentiation coefficient of leaf phenotypic traits among Cerasus dielsiana populations"

叶表型性状
Leaf phenotypic
trait
方差分量 Variance component 方差分量百分比 Percentage of variance component (%) 表型分化系数
Phenotype
differentiation
coefficient (%)
种群间
Among populations
种群内
Within populations
随机误差
Random errors
种群间
Among populations
种群内
Within populations
随机误差
Random Errors
LL (mm) 6.359 25.822 13.324 13.98 56.75 29.28 19.76
LW (mm) 1.699 7.259 3.343 13.81 59.01 27.18 18.97
LWR 0.002 0.001 0.005 29.27 60.67 29.27 14.22
PL (mm) 0.486 0.517 0.272 38.13 40.54 21.33 48.47
LA (mm2) 17 872.160 50 647.400 35 586.960 17.17 48.65 34.18 26.08
LP (mm) 63.832 139.554 74.330 22.98 50.25 26.76 31.38
LI 0.000 0.001 0.000 22.49 55.32 22.19 28.91
PLV 0.105 0.075 0.034 15.74 35.19 15.74 58.23
VD 0.000 0.000 0.000 12.69 65.29 22.02 16.27
AA (°) 0.507 4.771 1.719 7.25 68.18 24.57 9.61
BA (°) 22.105 13.537 9.101 54.49 27.21 18.30 66.69
平均值 Mean - - - 22.55 51.55 24.62 30.78

Table 6

Principal component analysis of leaf phenotypic traits of Cerasus dielsiana"

叶表型性状
Leaf phenotypic trait
主成分 Main components 叶表型性状
Leaf phenotypic trait
主成分 Main components
PC1 PC2 PC3 PC1 PC2 PC3
LL (mm) 0.312 -0.093 -0.268 PLV -0.020 0.071 0.021
LW (mm) 0.367 0.149 0.163 VD -0.332 0.182 0.302
LWR -0.055 -0.242 -0.431 AA (°) 0.109 0.604 0.244
PL (mm) 0.186 -0.667 0.650 BA (°) 0.022 0.102 0.242
LA (mm2) 0.706 0.117 -0.027 特征值 Eigenvalue 0.092 0.015 0.011
LP (mm) 0.327 -0.039 -0.139 贡献率
Variance contribution rate (%)
73.242 11.319 7.839
LI 0.051 0.195 0.251 累计贡献率
Cumulative Contribution rate (%)
73.242 84.561 92.400

Table 7

Person correlation analysis among leaf phenotypic traits and geographic-climatic factors of Cerasus dielsiana"

叶表型性状
Leaf phenotypic trait
纬度
Latitude (N)
经度
Longitude (E)
海拔
Altitude (m)
气温季节变化Temperature seasonality bio4 (SD × 100) 年降水量
Annual precipitation bio12 (mm)
最湿季降水量
Precipitation of wettest quarter bio16 (mm)
最暖季降水量
Precipitation of warmest quarter bio18 (mm)
LL (mm) 0.163 -0.554 0.091 -0.613* -0.008 0.221 -0.017
LW (mm) 0.284 -0.641* 0.176 0.545 0.002 0.443 0.057
LWR -0.363 0.431 -0.260 -0.098 -0.028 -0.600* -0.175
PL (mm) -0.094 -0.469 0.430 0.006 -0.151 0.482 0.040
LA (mm2) 0.227 -0.658* 0.162 0.551 -0.016 0.459 0.037
LP (mm) 0.184 -0.593 0.141 0.585 -0.009 0.315 0.008
LI 0.347 -0.535 0.093 0.340 0.084 0.651* 0.206
PLV -0.248 0.659* 0.087 -0.395 0.118 -0.499 0.017
VD -0.220 0.590 -0.035 0.651* 0.007 -0.222 0.018
AA (°) 0.324 -0.249 -0.429 0.809** 0.303 0.127 0.181
BA (°) -0.478 0.168 0.277 -0.090 0.059 -0.075 0.121

Fig. 1

Relationships between leaf phenotypic traits and geographic-climatic factors of the eight natural populations of Cerasus dielsiana. A, Output from principal coordinate analysis. B, Output from unweighted pair-group method with arithmetic mean cluster analysis. ALS, Mt. Ali, Taiwan. EMS, Mt. Emei, Sichuan; JZFP, Jinzhufeipu, Jiangxi; MS, Mt. Mangshan, Hunan; SNJ, Shennongjia, Hubei; XDS, Mt. Xingdou; Hubei; XGT, Xiangutan, Jiangxi; ZJJ, Zhangjiajie, Hunan."

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