Cai Qing, Liu Jiming
Department of Computer Science, Hong Kong Baptist University, Kowloon Tong KLN, Hong Kong.
Sci Rep. 2016 Oct 27;6:35904. doi: 10.1038/srep35904.
To study the robustness of ecosystems is crucial to promote the sustainable development of human society. This paper aims to analyze the robustness of ecosystems from an interesting viewpoint of the species loss of community. Unlike the existing definitions, we first introduce the notion of a community as a population of species belonging to the same trophic level. We then put forward a novel multiobjective optimization model which can be utilized to discover community structures from arbitrary unipartite networks. Because an ecosystem is commonly represented as a multipartite network, we further introduce a mechanism of competition among species whereby a multipartite network is transformed into a unipartite signed network without loss of species interaction information. Finally, we examine three strategies to test the robustness of an ecosystem. Our experiments indicate that ecosystems are robust to random species loss of community but fragile to target ones. We also investigate the relationships between the robustness of an ecosystem and that of its community composed network both to species loss. Our experiments indicate that the robustness analysis of a large-scale ecosystem to species loss may be akin to that of its community composed network which is usually small in size.
研究生态系统的稳健性对于促进人类社会的可持续发展至关重要。本文旨在从群落物种丧失这一有趣的视角分析生态系统的稳健性。与现有定义不同，我们首先引入将群落视为属于同一营养级的物种群体的概念。然后，我们提出了一种新颖的多目标优化模型，该模型可用于从任意单部网络中发现群落结构。由于生态系统通常表示为多部网络，我们进一步引入了物种间的竞争机制，通过该机制多部网络可转化为单部带符号网络，且不会丢失物种相互作用信息。最后，我们考察了三种测试生态系统稳健性的策略。我们的实验表明，生态系统对群落的随机物种丧失具有稳健性，但对目标物种丧失则较为脆弱。我们还研究了生态系统的稳健性与其由群落组成的网络对物种丧失的稳健性之间的关系。我们的实验表明，大规模生态系统对物种丧失的稳健性分析可能类似于其通常规模较小的由群落组成的网络的稳健性分析。
