植物生态学报 ›› 2016, Vol. 40 ›› Issue (1): 48-59.DOI: 10.17521/cjpe.2015.0246

• 研究论文 • 上一篇    下一篇

浙江天童木本植物叶片性状空间变异的地统计学分析

许洺山1,2, 赵延涛1,2, 杨晓东3, 史青茹4, 周刘丽1,2, 阎恩荣1,2,*   

  1. 1华东师范大学生态与环境科学学院, 上海 200241
    2浙江天童森林生态系统国家野外科学观测研究站, 浙江宁波 315114
    3新疆大学资源与环境科学学院, 乌鲁木齐 830046
    4宝山区青少年科学技术指导站, 上海 200904
    5Department of Environmental Sciences, Abdul Wali Khan University, Mardan 23200, Pakistan
  • 出版日期:2016-01-01 发布日期:2016-01-28
  • 通讯作者: 阎恩荣
  • 作者简介:# 共同第一作者
  • 基金资助:

    国家自然科学基金(30770365和31070383)。

Geostatistical analysis of spatial variations in leaf traits of woody plants in Tiantong, Zhejiang Province

XU Ming-Shan1,2, ZHAO Yan-Tao1,2, YANG Xiao-Dong3, SHI Qing-Ru4, ZHOU Liu-Li1,2, ZHANG Qing-Qing1,2, Ali ARSHAD1,2,5, YAN En-Rong1,2,*   

  1. 1School of Ecological and Environmental Sciences, East China Normal University, Shanghai 200241, China
    2Tiantong National Forest Ecosystem Observation and Research Station, Ningbo, Zhejiang 315114, China
    3Institute of Resources and Environment Science, Xinjiang University, Ürümqi 830046, China
    4Youth Science and Technology Guide Station of Baoshan District, Shanghai 200904, China
    5Department of Environmental Sciences, Abdul Wali Khan University, Mardan 23200, Pakistan
  • Online:2016-01-01 Published:2016-01-28
  • Contact: En-Rong YAN
  • About author:# Co-first authors

摘要:

探究叶片性状的空间变异性和环境关联性有助于我们理解植物对环境的适应策略和群落建构机制。该研究以浙江天童5 hm2大型动态样地所有胸径≥1 cm的木本植物为对象, 测定了20 253株个体的单叶面积、比叶面积和叶片干物质含量, 土壤总氮、总磷、总碳、pH值、体积含水率、容重和腐殖质, 以及海拔、坡度和凹凸度等; 并用地统计学等方法分析了叶片性状的空间变异性及其与环境因子的相关性。结果表明: 1)单叶面积的空间变异最大, 比叶面积次之, 叶片干物质含量最小。三者在0-5.16 m空间范围内表现出较弱的空间自相关, 其半变异函数的最优模型分别为高斯模型、指数模型和指数模型。2)叶片性状空间变异具有方向性, 单叶面积空间变异在东北-西南方向上最大, 在西北-东南方向上最小; 比叶面积和叶片干物质含量的空间变异均在西北-东南方向最大, 在东北-西南方向最小。3)单叶面积与地形因子显著负相关(r = -0.12, p < 0.0001); 比叶面积与土壤养分显著负相关(r = -0.16, p < 0.0001), 叶片干物质含量与土壤养分显著正相关(r = 0.13, p < 0.0001)。4)东北-西南方向上, 地形因子对单叶面积、比叶面积和叶片干物质含量空间变异的影响大于土壤养分; 西北-东南方向上, 地形因子对单叶面积空间变异的影响相对较大, 而土壤养分对比叶面积和叶片干物质含量空间变异的影响较大。总之, 在研究样地内, 植物叶片性状随空间距离和方向存在很大的变异性, 叶片性状与地形因子、土壤养分的关联性间接表明了环境过滤对群落构建的影响。

关键词: 叶片性状, 空间变异, 土壤养分, 地形因子, 地统计学分析

Abstract: AimsExploring spatial variations in leaf traits and their relationships with environmental properties is crucial for understanding plant adaptation strategies and community assembly. This study aimed to reveal how leaf traits varied spatially and the role of environmental factors.MethodsThe study was conducted in a 5-hm2 forest plot in Tiantong, Zhejiang Province. Three leaf traits, including individual leaf area (ILA), specific leaf area (SLA), and leaf dry matter content (LDMC) were measured for 20253 individual trees with diameter at breast height (DBH) ≥1 cm. Soil properties measured included contents of soil total nitrogen, soil total phosphorus, soil total carbon, soil pH value, soil volumetric water content, bulk density, and humus depth. Topographic variables measured included elevation, slope and convexity. We used geostatistical analysis to reveal spatial variations of the three leaf traits. Relationships between leaf variability and environmental factors were analyzed using principal component analysis (PCA) and Pearson’s correlation.Important findings Spatial variability followed the order of ILA > SLA > LDMC. Spatial autocorrelation of three leaf traits was weak within a distance of 5.16 m. The optimal model of the semi-variogram function was Gaussian model for ILA, and exponential model for SLA and LDMC. ILA showed the largest variability at the direction of northeast-southwest, and smallest variability at the direction of northwest-southeast. In contrast, SLA and LDMC had the highest variability at the direction of northwest-southeast and least variability at the direction of northeast-southwest. There were significantly negative relationships between ILA and topographic factors (r = -0.12, p < 0.0001), and between SLA and soil nutrients (r = -0.16, p < 0.0001). In contrast, LDMC was positively correlated with soil nutrients (r = 0.13, p < 0.0001). Relative to soil nutrients, topographic factors affected much more variations in ILA, SLA and LDMC at the direction of northeast-southwest. Distinctly, at the direction of northwest-southeast, variability of ILA was affected mainly by topographic factors, while soil nutrients resulted in the most variability of SLA and LDMC. In conclusion, leaf traits varied considerably with spatial direction in the studied forest plot. Associations between leaf traits and topographic factors and soil nutrients indirectly indicated effects of environmental filtering on community assembly.

Key words: leaf traits, spatial variation, soil nutrients, topographic factors, geostatistical analysis