基于对称性的物种丰富生态群落方法

Juan Giral Martínez
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引用次数: 0

摘要

无序系统理论为分析物种丰富的生态群落或神经网络等高维系统的一般行为提供了强有力的工具。通过假定其相互作用的随机性,普遍性确保了许多微观细节与整个系统的动力学无关;但随机集合的选择仍然限制了结果的普遍性。我们在这里以生态动力学为背景说明,这些分析工具并不需要特定的集合选择,只需根据相互作用中的基本旋转对称性就能找到解决方案,这就意味着性状可以在不改变全局特征的情况下重组为新闻物种。动态结果取决于作为自由参数的相互作用矩阵的频谱,这使我们能够弥合不同相互作用模型中发现的结果,并将其扩展到以前未发现的行为。生态模型的显著特点是物种灭绝的可能性,这导致随着灭绝物种比例的增加,动力学的普遍性也随之增加。我们希望这些发现能够为理论生态学以及其他复杂系统家族的新发展提供信息。
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A symmetry-based approach to species-rich ecological communities
Disordered systems theory provides powerful tools to analyze the generic behaviors of highdimensional systems, such as species-rich ecological communities or neural networks. By assuming randomness in their interactions, universality ensures that many microscopic details are irrelevant to system-wide dynamics; but the choice of a random ensemble still limits the generality of results. We show here, in the context of ecological dynamics, that these analytical tools do not require a specific choice of ensemble, and that solutions can be found based only on a fundamental rotational symmetry in the interactions, encoding the idea that traits can be recombined into new species without altering global features. Dynamical outcomes then depend on the spectrum of the interaction matrix as a free parameter, allowing us to bridge between results found in different models of interactions, and extend beyond them to previously unidentified behaviors. The distinctive feature of ecological models is the possibility of species extinctions, which leads to an increased universality of dynamics as the fraction of extinct species increases. We expect that these findings can inform new developments in theoretical ecology as well as for other families of complex systems.
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