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arXiv 2201.03193q-bio.PE
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竞争生态网络中密度调节与稳定性之间的相互联系

Interconnection between density-regulation and stability in competitive ecological network

Amit Samadder, Arnab Chattopadhyay, Anurag Sau, Sabyasachi Bhattacharya

AI总结:

本研究利用随机矩阵理论分析theta-逻辑斯蒂竞争模型,发现强密度依赖性物种比例增加及网络连接度提高可增强生态群落稳定性,且该结论在不同网络架构下均稳健。

摘要:

在自然生态系统中,物种可以通过其生长曲线的非线性密度依赖性自我调节来表征。许多分类群的物种在低种群规模下表现出显著的密度依赖性降低。然而,许多物种表现出相反的趋势;密度调节在种群规模较小时最小,而当种群规模接近环境容纳量时显著增加。theta-逻辑斯蒂增长方程可以描绘生长曲线中的种内密度调节,其中theta是密度调节参数。在本研究中,我们借助竞争性物种相互作用的数学模型,考察了这些不同生长曲线对竞争性生态群落稳定性的作用。本文运用随机矩阵理论来理解经典theta-逻辑斯蒂竞争相互作用模型的稳定性。我们的结果表明,拥有更多具有强密度依赖性(即在低密度下自我调节)的物种会导致群落更加稳定。此外,稳定性还取决于生态网络的复杂性。物种网络连接度(链接密度)显示出增加稳定性的持续趋势,而群落规模(物种丰富度)则显示出依赖于情境的效应。我们还从两种不同的生活史策略——r选择和K选择——的角度来解释我们的结果。我们的结果表明,竞争网络的稳定性随着群落中r选择物种比例的增加而提高。我们的结果是稳健的,无论网络架构如何。

英文摘要:

In natural ecosystems, species can be characterized by the nonlinear density-dependent self-regulation of their growth profile. Species of many taxa show a substantial density-dependent reduction for low population size. Nevertheless, many show the opposite trend; density regulation is minimal for small populations and increases significantly when the population size is near the carrying capacity. The theta-logistic growth equation can portray the intraspecific density regulation in the growth profile, theta being the density regulation parameter. In this study, we examine the role of these different growth profiles on the stability of a competitive ecological community with the help of a mathematical model of competitive species interactions. This manuscript deals with the random matrix theory to understand the stability of the classical theta-logistic models of competitive interactions. Our results suggest that having more species with strong density dependence, which self-regulate at low densities, leads to more stable communities. With this, stability also depends on the complexity of the ecological network. Species network connectance (link density) shows a consistent trend of increasing stability, whereas community size (species richness) shows a context-dependent effect. We also interpret our results from the aspect of two different life history strategies: r and K-selection. Our results show that the stability of a competitive network increases with the fraction of r-selected species in the community. Our result is robust, irrespective of different network architectures.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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