论文标题
复杂的生态社区中的人口噪音
Demographic noise in complex ecological communities
论文作者
论文摘要
我们介绍了一个基于随机相互作用的复杂生态社区的基于个体的模型。该模型包含大量物种，每个物种都有有限的个体人群，但可能会受离散的繁殖和死亡事件。确定这些事件速率的相互作用系数是从随机矩阵的集合中选择的，并及时固定。该设置使该模型减少到已知的广义Lotka-Volterra方程，其随机相互作用系数在每个物种的无限群体中的极限。基于个体模型中的人口噪声意味着将在Lotka-Volterra模型中生存的物种可能灭绝。这些噪声驱动的灭绝是本文的重点。我们发现，为了增加相互作用的复杂性，生态群落通常变得不易受到人口统计学噪声引起的灭绝。一个例外是完全由捕食者捕获对的系统。已知这些系统在具有随机相互作用的确定性Lotka-Volterra模型中是稳定的，但是，正如我们所表明的，它们尤其容易受到波动的影响。
We introduce an individual-based model of a complex ecological community with random interactions. The model contains a large number of species, each with a finite population of individuals, subject to discrete reproduction and death events. The interaction coefficients determining the rates of these events is chosen from an ensemble of random matrices, and is kept fixed in time. The set-up is such that the model reduces to the known generalised Lotka-Volterra equations with random interaction coefficients in the limit of an infinite population for each species. Demographic noise in the individual-based model means that species which would survive in the Lotka-Volterra model can become extinct. These noise-driven extinctions are the focus of the paper. We find that, for increasing complexity of interactions, ecological communities generally become less prone to extinctions induced by demographic noise. An exception are systems composed entirely of predator-prey pairs. These systems are known to be stable in deterministic Lotka-Volterra models with random interactions, but, as we show, they are nevertheless particularly vulnerable to fluctuations.
