生物多样性 ›› 2016, Vol. 24 ›› Issue (6): 629-638.DOI: 10.17520/biods.2016112

• • 上一篇    下一篇

天童常绿阔叶林中常绿与落叶物种的物种多度分布格局

方晓峰1,2,3, 杨庆松1,3, 刘何铭1,3, 马遵平1,3, 董舒1,3, 曹烨1,3, 袁铭皎1,3, 费希旸1,3, 孙小颖1,3, 王希华1,3,,A;*()   

  1. 1 华东师范大学生态与环境科学学院, 上海 200241
    2 河北地质大学水资源与环境学院, 石家庄 050031
    3 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
  • 收稿日期:2016-04-26 接受日期:2016-06-06 出版日期:2016-06-20 发布日期:2016-06-20
  • 通讯作者: 王希华
  • 基金资助:
    国家自然科学基金重大国际合作项目(31210103920)

Distribution of species abundance of evergreen and deciduous woody plants in the evergreen broad-leaved forests at Tiantong, Zhejiang

Xiaofeng Fang1,2,3, Qingsong Yang1,3, Heming Liu1,3, Zunping Ma1,3, Shu Dong1,3, Ye Cao1,3, Mingjiao Yuan1,3, Xiyang Fei1,3, Xiaoying Sun1,3, Xihua Wang1,3,*()   

  1. 1 School of Ecological and Environmental Sciences, East China Normal University, Shanghai 200241
    2 School of Water Resources and Environment, Hebei GEO University, Shijiazhuang 050031
    3 Tiantong National Forest Ecosystem Observation and Research Station, Ningbo, Zhejiang 315114
  • Received:2016-04-26 Accepted:2016-06-06 Online:2016-06-20 Published:2016-06-20
  • Contact: Wang Xihua

摘要:

物种多度分布是对群落内不同物种多度情况的数量描述, 作为理解群落性质的基石, 其形成机制受到广泛关注。常绿与落叶物种是两类有着不同物候性状与生长策略的物种集合, 它们普遍共存于常绿阔叶林中。在天童20 ha常绿阔叶林动态监测样地内, 虽然常绿物种在物种多度和胸高断面积等指标上占有绝对优势, 但其在物种丰富度上却不及落叶物种。分析两者在常绿阔叶林中的物种多度分布特征, 能够为理解常绿阔叶林内物种多样性的维持机制提供一个全新的视角。为此, 我们基于天童样地的植被调查数据, 一方面利用累积经验分布函数对两类生活型植物的物种多度分布进行描述, 使用Kolmogorov-Smirnov检验(K-S检验)判断其差异性; 另一方面, 采用纯统计模型、生态位模型和中性理论模型对二者的物种多度分布曲线进行拟合, 并基于K-S检验的结果以及AIC值进行最优模型的筛选。结果显示: (1)常绿与落叶物种的物种多度分布曲线间并无显著差异。(2)在选用的3类模型中, 中性理论模型对于两类物种多度分布曲线的拟合效果都最好, 而生态位模型的拟合效果则一般。从上述结果可以看出, 尽管常绿与落叶物种在物种数量和多度等方面均存在差异, 但它们却有着近似的物种多度分布格局以及相近的多样性维持机制。然而, 鉴于模型拟合的结果只能作为理解群落多样性构建机制的必要非充分条件, 故而只能初步判定中性过程对于常绿与落叶物种的物种多样性格局影响更大, 却不能排除或衡量诸如生态位分化等其他过程在两类生活型多样性格局形成中的贡献。

关键词: 累积经验分布函数, 模型拟合, 中性理论模型, 生态位模型, 纯统计模型, 物种多度分布

Abstract:

Species abundance distribution (SAD) delineates abundance of all species sampled within a community. As one major stepping stone in understanding the community, the generation mechanisms of SAD have attracted much attention. Evergreen and deciduous plants are two types of species with distinct phenological traits and growth strategies. They widely coexist in evergreen broad-leaved forests (EBLFs). Compared to deciduous plants, evergreen species have slightly lower species richness but substantially higher abundance and basal area in the 20 ha EBLF plot at Tiantong. This study independently analyzing their SAD characteristics provided a new perspective on the understanding of species diversity maintenance in EBLFs. Therefore, in order to compare SADs and determine reasons for differences, an empirical cumulative distribution function (ECDF) was utilized to describe the SADs of evergreen and deciduous trees in Tiantong plot. A Kolmogorov-Smirnov test (K-S test) was employed to detect the significance of these differences. Additionally, three types of models, including statistic model (log-normal model and log-series model), niche model (broken-stick model and niche preemption model) and neutral theory model (metacommunity zero-sum multinomial distribution model and Volkov model), were used to fit the SAD of each lifeform. The K-S test and AIC values were applied to test the goodness of fit for each model. We found that the differences in SAD between the two life forms were not significant based on the results of the K-S test. Among the three types of models, the neutral theory model was the best fitting model, and the niche model was the poorest fit. Thus we conclude that evergreen and deciduous trees had similar SAD patterns, although they differed in species richness and abundance. However, the model fitting results were found to be a necessary but insufficient condition in understanding the maintenance mechanism of biodiversity. Hence we may only preliminarily conclude that neutral processes had a major effect on the generation of biodiversity patterns of both evergreen and deciduous trees, whereas the possible contributions made by other processes, such as niche differentiations, could not be excluded and measured by this method.

Key words: empirical cumulative distribution function, model fitting, neutral theory model, niche model, purely statistical model, species abundance distribution