异速滴定
缩放比例
选择(遗传算法)
支化(高分子化学)
统计物理学
比例(比率)
芯(光纤)
功能(生物学)
数学
不相关
生物
生物系统
进化生物学
统计
生态学
计算机科学
物理
几何学
人工智能
电信
材料科学
量子力学
复合材料
作者
Charles A. Price,Brian J. Enquist,Van M. Savage
标识
DOI:10.1073/pnas.0702242104
摘要
The West, Brown, and Enquist (WBE) theory for the origin of allometric scaling laws is centered on the idea that the geometry of the vascular network governs how a suite of organismal traits covary with each other and, ultimately, how they scale with organism size. This core assumption has been combined with other secondary assumptions based on physiological constraints, such as minimizing the scaling of transport and biomechanical costs while maximally filling a volume. Together, these assumptions give predictions for specific “quarter-power” scaling exponents in biology. Here we provide a strong test of the core assumption of WBE by examining how well it holds when the secondary assumptions have been relaxed. Our relaxed version of WBE predicts that allometric exponents are highly constrained and covary according to specific quantitative functions. To test this core prediction, we assembled several botanical data sets with measures of the allometry of morphological traits. A wide variety of plant taxa appear to obey the predictions of the model. Our results ( i ) underscore the importance of network geometry in governing the variability and central tendency of biological exponents, ( ii ) support the hypothesis that selection has primarily acted to minimize the scaling of hydrodynamic resistance, and ( iii ) suggest that additional selection pressures for alternative branching geometries govern much of the observed covariation in biological scaling exponents. Understanding how selection shapes hierarchical branching networks provides a general framework for understanding the origin and covariation of many allometric traits within a complex integrated phenotype.
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