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Bacterial microcosms obey Taylor's law: effects of abiotic and biotic stress and genetics on mean and variance of population density

机译:细菌微观世界遵守泰勒定律:非生物和生物胁迫及遗传学对种群密度均值和方差的影响

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Introduction According to the empirical regularity called Taylor's law, the variance of population density in samples of populations is a power of the mean population density. The exponent is often between 1 and 2. Our experiments investigated how genetics, evolution, and environment shape Taylor's law. Methods Genetically different strains (wild type and hypermutator) of the bacterium Pseudomonas fluorescens evolved and were assayed under different environmental conditions (with and without antibiotic rifampicin and bacteriophage SBW25φ2, separately and in combination). Results Experimental treatments altered the exponent b , but not the power law form, of the relation between variance and mean population density. Bacterial populations treated only with rifampicin had a narrow range of mean population densities and exponent b = 5.43. Populations exposed to rifampicin plus phage had b = 1.51. In ancestral, control, and phage-exposed populations, mean abundance varied widely and b was not significantly different from 2. Evolutionary factors (mutation rate, selection) and ecological factors (abiotic, biotic) jointly influenced b . Conclusions Taylor's power law relationship accurately and robustly described variance as a function of mean population density, with overall exponent b = 1.89. These and other experiments with different factors acting on bacterial population size support the relevance of models that predict 'universal' patterns of fluctuation scaling.
机译:引言根据称为泰勒定律的经验规律,人口样本中人口密度的方差是平均人口密度的幂。指数通常在1到2之间。我们的实验研究了遗传,进化和环境如何影响泰勒定律。方法在不同的环境条件下(分别有或没有抗生素利福平和噬菌体SBW25φ2,分别或组合使用),对荧光假单胞菌产生了遗传上不同的菌株(野生型和超突变型)进行了测定。结果实验处理改变了方差与平均人口密度之间关系的指数b,但没有改变幂律形式。仅用利福平治疗的细菌种群的平均种群密度范围狭窄,指数b = 5.43。暴露于利福平加噬菌体的人群的b = 1.51。在祖先,对照和噬菌体接触人群中,平均丰度变化很大,b与2并无显着差异。进化因素(变异率,选择)和生态因素(非生物,生物)共同影响b。结论泰勒幂定律关系准确可靠地描述了方差作为平均总体密度的函数,总体指数b = 1.89。这些和其他具有不同因素作用于细菌种群大小的实验支持了预测波动缩放的“普遍”模式的模型的相关性。

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