Campbell Colin, Yang Suann, Shea Katriona, Albert Réka
Department of Physics, The Pennsylvania State University, University Park, Pennsylvania 16802, USA.
Phys Rev E Stat Nonlin Soft Matter Phys. 2012 Aug;86(2 Pt 1):021924. doi: 10.1103/PhysRevE.86.021924. Epub 2012 Aug 31.
The ability to predict the collapse of ecological communities is of significant concern in light of global patterns of rapid species extinctions. Here, we use a recently developed dynamic Boolean network-based model of mutualistic plant-pollinator community formation to investigate the stability of simulated ecological communities in the face of sequential species extinctions. We assess communities in terms of the relative change in biodiversity after species loss, and find that communities that experience a significant loss of biodiversity differ from more robust communities according to a number of topological characteristics. Notably, we show that high nestedness, a property commonly believed to promote community stability, may in extreme circumstances promote a critical over-reliance on individual species. Furthermore, the species important to the survival of the rest of the ecosystem occupy different positions in the network than less important species. Our results suggest that network measures may be applied to real ecosystems to yield insight into both their stability and the identity of potentially critical species.
鉴于全球物种快速灭绝的趋势，预测生态群落崩溃的能力备受关注。在此，我们使用一种最近开发的基于动态布尔网络的互利共生植物-传粉者群落形成模型，来研究模拟生态群落在物种相继灭绝情况下的稳定性。我们根据物种丧失后生物多样性的相对变化来评估群落，并发现生物多样性显著丧失的群落与更具韧性的群落相比，在一些拓扑特征上存在差异。值得注意的是，我们表明，高度嵌套性这一通常被认为能促进群落稳定性的特性，在极端情况下可能会导致对个别物种的过度依赖。此外，对生态系统其他部分生存至关重要的物种在网络中的位置与不太重要的物种不同。我们成果表明，网络测度可应用于真实生态系统，以深入了解其稳定性以及潜在关键物种的身份。
