Department of Mathematics, School of Science, RMIT University, Melbourne, Australia.
BioMathematics Unit, School of Zoology, Faculty of Life Sciences, Tel Aviv University, Ramat Aviv, Israel.
Nat Commun. 2020 May 27;11(1):2648. doi: 10.1038/s41467-020-16474-4.
Positive interactions are observed at high frequencies in nearly all living systems, ranging from human and animal societies down to the scale of microbial organisms. However, historically, detailed ecological studies of mutualism have been relatively unrepresented. Moreover, while ecologists have long portrayed competition as a stabilizing process, mutualism is often deemed destabilizing. Recently, several key modelling studies have applied random matrix methods, and have further corroborated the instability of mutualism. Here, I reassess these findings by factoring in species densities into the "community matrix," a practice which has almost always been ignored in random matrix analyses. With this modification, mutualistic interactions are found to boost equilibrium population densities and stabilize communities by increasing their resilience. By taking into account transient dynamics after a strong population perturbation, it is found that mutualists have the ability to pull up communities by their bootstraps when species are dangerously depressed in numbers.
在几乎所有的生命系统中,从人类和动物社会到微生物的规模,都观察到了高频的正相互作用。然而,从历史上看,对互利共生的详细生态研究相对较少。此外,尽管生态学家长期以来一直将竞争视为一种稳定过程,但互利共生通常被认为是不稳定的。最近,几项关键的建模研究应用了随机矩阵方法,并进一步证实了互利共生的不稳定性。在这里,我通过将物种密度纳入“群落矩阵”来重新评估这些发现,而这一做法在随机矩阵分析中几乎总是被忽视。通过这种修正,发现互利共生通过增加其恢复力来提高平衡种群密度并稳定群落。通过考虑在种群受到强烈干扰后的瞬态动力学,发现当物种数量危险下降时,互利共生体有能力通过自举将群落拉起来。