Sidhom Laura, Galla Tobias
Theoretical Physics, Department of Physics and Astronomy, School of Natural Sciences, The University of Manchester, Manchester M13 9PL, United Kingdom.
Theoretical Physics, Department of Physics and Astronomy, School of Natural Sciences, The University of Manchester, Manchester M13 9PL, United Kingdom and Instituto de Física Interdisciplinar y Sistemas Complejos, IFISC (CSIC-UIB), Campus Universitat Illes Balears, E-07122 Palma de Mallorca, Spain.
Phys Rev E. 2020 Mar;101(3-1):032101. doi: 10.1103/PhysRevE.101.032101.
We investigate the outcome of generalized Lotka-Volterra dynamics of ecological communities with random interaction coefficients and nonlinear feedback. We show in simulations that the saturation of nonlinear feedback stabilizes the dynamics. This is confirmed in an analytical generating-functional approach to generalized Lotka-Volterra equations with piecewise linear saturating response. For such systems we are able to derive self-consistent relations governing the stable fixed-point phase and to carry out a linear stability analysis to predict the onset of unstable behavior. We investigate in detail the combined effects of the mean, variance, and covariance of the random interaction coefficients, and the saturation value of the nonlinear response. We find that stability and diversity increases with the introduction of nonlinear feedback, where decreasing the saturation value has a similar effect to decreasing the covariance. We also find cooperation to no longer have a detrimental effect on stability with nonlinear feedback, and the order parameters mean abundance and diversity to be less dependent on the symmetry of interactions with stronger saturation.
我们研究了具有随机相互作用系数和非线性反馈的生态群落广义Lotka-Volterra动力学的结果。我们在模拟中表明,非线性反馈的饱和使动力学稳定。这在对具有分段线性饱和响应的广义Lotka-Volterra方程的解析生成泛函方法中得到了证实。对于此类系统,我们能够推导出控制稳定不动点相的自洽关系,并进行线性稳定性分析以预测不稳定行为的开始。我们详细研究了随机相互作用系数的均值、方差和协方差以及非线性响应的饱和值的综合影响。我们发现,随着非线性反馈的引入,稳定性和多样性增加,其中降低饱和值与降低协方差具有类似的效果。我们还发现,在非线性反馈下,合作对稳定性不再有不利影响,并且序参量平均丰度和多样性对具有更强饱和的相互作用对称性的依赖性较小。