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Canonical functions for dispersal-induced synchrony.

机译:散布诱发同步的规范功能。

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摘要

Two processes are universally recognized for inducing spatial synchrony in abundance: dispersal and correlated environmental stochasticity. In the present study we seek the expected relationship between synchrony and distance in populations that are synchronized by density-independent dispersal. In the absence of dispersal, synchrony among populations with simple dynamics has been shown to echo the correlation in the environment. We ask what functional form we may expect between synchrony and distance when dispersal is the synchronizing agent. We formulate a continuous-space, continuous-time model that explicitly represents the time evolution of the spatial covariance as a function of spatial distance. Solving this model gives us two simple canonical functions for dispersal-induced covariance in spatially extended populations. If dispersal is rare relative to birth and death, then covariances between nearby points will follow the dispersal distance distribution. At long distances, however, the covariance tails off according to exponential or Bessel functions (depending on whether the population moves in one or two dimensions). If dispersal is common, then the covariances will follow the mixture distribution that is approximately Gaussian around the origin and with an exponential or Bessel tail. The latter mixture results regardless of the original dispersal distance distribution. There are hence two canonical functions for dispersal-induced synchrony
机译:引起大量空间同步的两个过程已广为人知:分散和相关的环境随机性。在本研究中,我们寻求通过密度无关的扩散而同步的总体同步性和距离之间的预期关系。在没有分散的情况下,具有简单动态的种群之间的同步性已显示出与环境的相关性。我们问,当分散是同步剂时,我们期望同步和距离之间有什么功能形式。我们制定了一个连续空间,连续时间模型,该模型明确表示空间协方差的时间演变与空间距离​​的关系。解决该模型为我们提供了两个简单的规范函数,用于在空间扩展的总体中进行扩散诱发的协方差。如果相对于出生和死亡而言弥散很少,那么附近点之间的协方差将遵循弥散距离分布。但是,在长距离时,协方差会根据指数函数或贝塞尔函数而减小(取决于总体是在一维还是二维中移动)。如果分散是常见的,则协方差将遵循混合分布,该分布在原点附近近似为高斯分布,并且具有指数或贝塞尔尾巴。不管原始分散距离分布如何,都会产生后一种混合物。因此,有两个规范函数可用于弥散引起的同步

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