Johnson Samuel, Domínguez-García Virginia, Donetti Luca, Muñoz Miguel A
Warwick Mathematics Institute, and Centre for Complexity Science, University of Warwick, Coventry CV4 7AL, United Kingdom;
Departamento de Electromagnetismo y Física de la Materia, and Instituto Carlos I de Física Teórica y Computacional, Universidad de Granada, 18071 Granada, Spain; and.
Proc Natl Acad Sci U S A. 2014 Dec 16;111(50):17923-8. doi: 10.1073/pnas.1409077111. Epub 2014 Dec 2.
Why are large, complex ecosystems stable? Both theory and simulations of current models predict the onset of instability with growing size and complexity, so for decades it has been conjectured that ecosystems must have some unidentified structural property exempting them from this outcome. We show that trophic coherence--a hitherto ignored feature of food webs that current structural models fail to reproduce--is a better statistical predictor of linear stability than size or complexity. Furthermore, we prove that a maximally coherent network with constant interaction strengths will always be linearly stable. We also propose a simple model that, by correctly capturing the trophic coherence of food webs, accurately reproduces their stability and other basic structural features. Most remarkably, our model shows that stability can increase with size and complexity. This suggests a key to May's paradox, and a range of opportunities and concerns for biodiversity conservation.
为何大型复杂生态系统是稳定的?当前模型的理论和模拟均预测,随着规模和复杂性的增加会出现不稳定性,因此数十年来一直有人推测,生态系统必定具有某种未被识别的结构特性,使其免受这种结果的影响。我们表明,营养连贯性——食物网一个迄今被忽视的特征,当前的结构模型无法再现——比规模或复杂性更能有效预测线性稳定性。此外,我们证明,具有恒定相互作用强度的最大连贯网络将始终保持线性稳定。我们还提出了一个简单模型,该模型通过正确捕捉食物网的营养连贯性,准确再现了它们的稳定性和其他基本结构特征。最值得注意的是,我们的模型表明稳定性会随着规模和复杂性的增加而提高。这为解开梅氏悖论提供了关键线索,并为生物多样性保护带来了一系列机遇和问题。