Cohen Joel E
Laboratory of Populations, Rockefeller University, 1230 York Avenue, Box 20, New York, NY 10065, USA; Laboratory of Populations, Earth Institute, Columbia University, New York, USA.
Theor Popul Biol. 2013 Sep;88:94-100. doi: 10.1016/j.tpb.2013.04.002. Epub 2013 May 17.
Taylor's law (TL), a widely verified empirical relationship in ecology, states that the variance of population density is approximately a power-law function of mean density. The growth-rate theorem (GR) states that, in a subdivided population, the rate of change of the overall growth rate is proportional to the variance of the subpopulations' growth rates. We show that continuous-time exponential change implies GR at every time and, asymptotically for large time, TL with power-law exponent 2. We also show why diverse population-dynamic models predict TL in the limit of large time by identifying simple features these models share: If the mean population density and the variance of population density are (exactly or asymptotically) non-constant exponential functions of a parameter (e.g., time), then the variance of density is (exactly or asymptotically) a power-law function of mean density.
泰勒定律(TL)是生态学中一个经过广泛验证的经验关系,它表明种群密度的方差近似为平均密度的幂律函数。增长率定理(GR)指出,在一个细分的种群中,总体增长率的变化率与亚种群增长率的方差成正比。我们证明,连续时间指数变化在任何时刻都意味着GR,并且在长时间渐近情况下意味着幂律指数为2的TL。我们还通过识别这些模型共有的简单特征,说明了为什么各种种群动态模型在长时间极限下会预测TL:如果平均种群密度和种群密度的方差是一个参数(例如时间)的(精确或渐近)非恒定指数函数,那么密度的方差就是(精确或渐近)平均密度的幂律函数。