Brummer Alexander Byers, Savage Van M, Enquist Brian J
Department of Physics, University of Arizona, Tucson, Arizona, United States of America.
Department of Ecology and Evolutionary Biology, University of Arizona, Tucson, Arizona, United States of America.
PLoS Comput Biol. 2017 Mar 20;13(3):e1005394. doi: 10.1371/journal.pcbi.1005394. eCollection 2017 Mar.
How a particular attribute of an organism changes or scales with its body size is known as an allometry. Biological allometries, such as metabolic scaling, have been hypothesized to result from selection to maximize how vascular networks fill space yet minimize internal transport distances and resistances. The West, Brown, Enquist (WBE) model argues that these two principles (space-filling and energy minimization) are (i) general principles underlying the evolution of the diversity of biological networks across plants and animals and (ii) can be used to predict how the resulting geometry of biological networks then governs their allometric scaling. Perhaps the most central biological allometry is how metabolic rate scales with body size. A core assumption of the WBE model is that networks are symmetric with respect to their geometric properties. That is, any two given branches within the same generation in the network are assumed to have identical lengths and radii. However, biological networks are rarely if ever symmetric. An open question is: Does incorporating asymmetric branching change or influence the predictions of the WBE model? We derive a general network model that relaxes the symmetric assumption and define two classes of asymmetrically bifurcating networks. We show that asymmetric branching can be incorporated into the WBE model. This asymmetric version of the WBE model results in several theoretical predictions for the structure, physiology, and metabolism of organisms, specifically in the case for the cardiovascular system. We show how network asymmetry can now be incorporated in the many allometric scaling relationships via total network volume. Most importantly, we show that the 3/4 metabolic scaling exponent from Kleiber's Law can still be attained within many asymmetric networks.
生物体的特定属性如何随其体型变化或缩放被称为异速生长。生物异速生长,如代谢缩放,据推测是由于选择作用,以最大化血管网络填充空间的方式,同时最小化内部运输距离和阻力。韦斯特、布朗、恩奎斯特(WBE)模型认为,这两个原则(空间填充和能量最小化):(i)是动植物生物网络多样性进化的一般原则,(ii)可用于预测生物网络的最终几何结构如何控制其异速生长缩放。也许最核心的生物异速生长是代谢率如何随体型缩放。WBE模型的一个核心假设是网络在几何属性方面是对称的。也就是说,假设网络中同一代内的任何两个给定分支具有相同的长度和半径。然而,生物网络极少是对称的。一个悬而未决的问题是:纳入不对称分支会改变或影响WBE模型的预测吗?我们推导了一个放宽对称假设的通用网络模型,并定义了两类不对称分叉网络。我们表明不对称分支可以纳入WBE模型。WBE模型的这个不对称版本对生物体的结构、生理学和代谢产生了几个理论预测,特别是在心血管系统的情况下。我们展示了网络不对称性现在如何通过总网络体积纳入许多异速生长缩放关系中。最重要的是,我们表明在许多不对称网络中仍然可以得到克莱伯定律中的3/4代谢缩放指数。