生物多样性 ›› 2023, Vol. 31 ›› Issue (8): 23171.  DOI: 10.17520/biods.2023171

• 综述 • 上一篇    下一篇

生态网络分析: 从集合群落到集合网络

冯志荣1,2, 陈有城1,3, 彭艳琼1, 李莉3, 王波1,*()   

  1. 1.中国科学院西双版纳热带植物园热带森林生态学重点实验室, 云南勐腊 666303
    2.中国科学院大学, 北京 100049
    3.贵州师范大学生命科学学院, 贵阳 550025
  • 收稿日期:2023-05-26 接受日期:2023-08-19 出版日期:2023-08-20 发布日期:2023-08-27
  • 通讯作者: *E-mail: wangbo@xtbg.ac.cn
  • 基金资助:
    国家自然科学基金(32171527);国家自然科学基金(31770463)

Ecological network analysis: From metacommunity to metanetwork

Zhirong Feng1,2, Youcheng Chen1,3, Yanqiong Peng1, Li Li3, Bo Wang1,*()   

  1. 1. Key Laboratory of Tropical Forest Ecology, Xishuangbanna Tropical Botanical Garden, Chinese Academy of Sciences, Mengla, Yunnan 666303
    2. University of Chinese Academy of Sciences, Beijing 100049
    3. School of Life Sciences, Guizhou Normal University, Guiyang 550025
  • Received:2023-05-26 Accepted:2023-08-19 Online:2023-08-20 Published:2023-08-27
  • Contact: *E-mail: wangbo@xtbg.ac.cn

摘要:

在景观尺度上, 沿不同环境梯度分布着多个局域群落, 这些局域群落通过物种扩散相联系, 形成了集合群落(metacommunity)。当同时考虑集合群落的物种组成和种间互作时, 出现了集合网络(metanetwork)的概念。近年来, 基于集合网络的概念, 运用网络分析的方法描述物种互作在多个群落中的分布和动态成为生态网络研究的新趋势。在网络分析中, 研究的尺度及对应于不同数据类型的众多网络指标及其统计推断思路常常让研究者感到困惑。本文首先对网络指标进行了归类整理, 将其划分为全局网络指标和局域网络指标, 解释了网络指标的应用场景、计算过程和生态学意义, 讨论了采样强度对网络指标的影响以及指标之间的相关性; 介绍了基于互作多样性的网络β多样性指标。随后, 梳理了网络分析中基于单一网络指标和网络β多样性指标的统计推断思路。在此基础上, 总结了近年来从集合群落到集合网络的研究趋势的演变。我们对网络分析面临的问题进行了总结并对未来的研究方向进行了展望。强调在研究性论文中应该考虑物种系统发育关系对网络组成和互作的影响。多层网络能从更广泛的物种互作尺度反映群落结构, 揭示更加全面的群落动态。集合网络的分析思路应保持一致, 以利于在不同研究之间进行比较。

关键词: 生态网络, 集合群落, 集合网络, 网络指标, 网络β多样性

Abstract

Background & Aims: At the landscape scale, multiple local communities are distributed along environmental gradients, and these local communities are interconnected through species dispersal, together forming metacommunity. When considering both the species composition and interspecific interactions of metacommunity, the concept of metanetwork emerges. With methods in network analysis, metanetwork illustrate the distribution of species interactions across multiple communities. The research scale and numerous network metrics corresponding to different data types often confuse researchers.
Progress: We begin by categorizing and organizing network metrics, and then proceed to differentiate between global and local network metrics. This provides explanations for their application scenarios, computation processes, and ecological significance, while also discussing the impact of sampling intensity on these metrics and exploring their relationships. We introduce the network β-diversity metrics that are computed based on interaction diversity. Subsequently, we outline the statistical inference approaches used in network analysis, incorporating both individual network metrics and network β-diversity metrics. Finally, we provide a summary of the recent research trends, which has shifted from metacommunity to metanetwork.
Prospects: We stress the significance of taking into account the influence of phylogenetic relationships on network composition and interactions in research papers. Multilayer networks offer the capability to represent community structures at a wider scale of species interactions, thus revealing more comprehensive community dynamics. Consistency in the analytical approach of metanetworks is vital for facilitating comparisons across diverse studies.

Key words: ecological networks, metacommunity, metanetwork, network metrics, network β-diversity