| 摘要: |
| 为了揭示带翅植物风传播特征与种子性状间的关系,明确种子风传播机制和植物迁移能力,该研究以10种典型风传播植物为对象,以手工法采集了植物种子并在室内测定其形态特征,以沉降法测定了种子沉降速度,采用Pearson相关系数分析、逐步回归和主成分方法分析了植物种子沉降速度与形态指标关系。结果表明:(1)10种植物种子沉降速度范围为0.477 0~2.016 6 m·s-1(变异系数5.8%~20.0%)。在单位风速条件下,种子水平传播距离范围为0.59~94.34 m,其中云杉种子传播最远(94.34 m)、松叶猪毛菜种子传播最近(0.59 m)。(2)10种植物种子形态指标差异显著(P<0.05),细裂槭种子千粒重、翅载力最大,种翅长/质量、种翅宽/质量、种翅长宽比/质量最小;白蜡树种子长度、种子长宽比、种翅长度、种翅长宽比、种子长/种翅长最大,种子宽度最小;甘肃枫杨种子宽度、种翅宽度最大,种子长宽比、种翅长宽比/质量最小;松叶猪毛菜种子千粒重、种子长度、种翅长度、种子宽度均最小;木猪毛菜种翅长宽比最小;臭椿种子长/种翅长最小;云杉种翅长/质量、种翅宽/质量、种翅长宽比/质量最大而翅载力最小。(3)植物种子沉降速度与种子长度、种子长/种翅长、翅载力呈显著正相关性(P<0.05);在种子沉降速度与形态特征指标逐步回归方程中,大果青杄、松叶猪毛菜种子种翅宽/质量,油松、木猪毛菜种翅长/质量,云杉种子质量,甘肃枫杨种子长/种翅长,白蜡树种翅长宽比,霸王、细裂槭、臭椿翅载力指标系数达到显著水平(P<0.05);主成分分析表明,种翅宽/质量、种子长宽比、种子长/种翅长和翅载力对10种植物种子沉降速度影响最大。结论:影响不同植物种子沉降速度因素存在差异,但翅载力是影响种子沉降速度最关键因素。 |
| 关键词: 种子风传播,种翅形态特征,沉降速度,逐步回归,主成分分析 |
| DOI:10.11931/guihaia.gxzw202505017 |
| 分类号: |
| 基金项目::国家重点研发计划项目 (No.2022YFF0802304);西藏自治区重点研发与转化项目(XZ202501ZY0119)。 |
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| Seed morphological characteristics and wind dispersal ability of ten winged plants |
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WANG Siyu, WU Jianguo*
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Key Laboratory of Regional Ecological Process and Function Assessment for Environmental Protection, Institute of Ecology, Chinese Research Academy of Environmental Sciences, Beijing 100012, China
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| Abstract: |
| To identify the relationship between wind dispersal characteristics and seed traits in winged-seed plants for deepening the understanding of wind-driven seed dispersal mechanisms and plant migration capabilities, seeds of ten typical wind-dispersed plant species were manually collecting in filed, and morphological traits were measuring in the laboratory, seed settling velocity was determined using the terminal velocity method, the relationships between seed settling velocity and morphological indices were analyzed using Pearson correlation analysis, stepwise regression analysis, and principal component analysis (PCA). The results were sa follows:(1) The settling velocities of seeds from the ten species ranged from 0.4770 to 2.0166 m·s-1 with the coefficient of variation as 5.8- 20.0, and their horizontal dispersal distance per unit wind speed ranged from 0.59 m to 94.34 m, with Picea asperata seeds dispersing the farthest (94.34 m) and Salsola laricifolia seeds the shortest distance (0.59 m). (2) Seed morphological indices differences were significant among the species (P < 0.05); Acer stenolobum had the highest thousand-seed weight and wing loading but the lowest wing length/mass, wing width/mass, and wing aspect ratio/mass; Fraxinus chinensis had the greatest seed length, seed aspect ratio, wing length, wing aspect ratio, and seed length/wing length ratio but the smallest seed width; Pterocarya macroptera var. insignis had the largest seed width and wing width but the smallest seed aspect ratio and wing aspect ratio/mass; Salsola laricifolia had the smallest thousand-seed weight, seed length, wing length, and seed width; Salsola arbuscula had the smallest wing aspect ratio; Ailanthus altissima had the smallest seed length/wing length ratio; Picea asperata had the highest wing length/mass, wing width/mass, and wing aspect ratio/mass but the lowest wing loading. (3) Seed settling velocity showed a significant positive correlation with seed length, seed length/wing length ratio, and wing loading(P < 0.05). In the stepwise regression equations for settling velocity vs. morphological traits, the coefficients for wing width/mass (Picea neoveitchii, Salsola laricifolia), wing length/mass (Pinus tabuliformis, Salsola arbuscula), seed mass (Picea asperata), seed length/wing length ratio (Pterocarya macroptera var. insignis), wing aspect ratio (Fraxinus chinensis), and wing loading (Zygophyllum xanthoxylon, Acer stenolobum, Ailanthus altissima) reached significance (P < 0.05). PCA indicated that wing width/mass, seed aspect ratio, seed length/wing length ratio, and wing loading had the greatest influence on seed settling velocity. Conclusion: Factors influencing seed settling velocity differ among plant species, with wing loading being the core factor. |
| Key words: seed wind dispersal, morphological traits of seed wings, terminal velocity, stepwise regression, principal component analysis |