有色环境噪音对空间异质种群动态同步性的影响

随着种群动态和空间结构研究兴趣的增加,激发了大量的有关空间同步性的理论和实验的研究工作。空间种群的同步波动现象在自然界广泛存在,它的影响和原因引起了很多生态学家的兴趣。Moran定理是一个非常重要的解释。但以往的研究大多假设环境变化为空间相关的白噪音。越来越多的研究表明很多环境变化的时间序列具有正的时间自相关性,也就是说用红噪音来描述更加合理。因此,推广经典的Moran效应来处理空间相关红噪音的情形很有必要。利用线性的二阶自回归过程的种群模型,推导了两种群空间同步性与种群动态异质性和环境变化的时间相关性(即环境噪音的颜色)之间的关系。深入分析了种群异质性和噪音颜色对空间同步性的影响。结果表明种群动态异质性不利于空间同步性,但详细的关系比较复杂。而红色噪音的同步能力体现在两方面:一方面,本身的相关性对同步性有贡献;另一方面,环境变化时间相关性可以通过改变种群密度依赖来影响同步性,但对同步性的影响并无一致性的结论,依赖于种群的平均动态等因素。这些结果对理解同步性的机理、利用同步机理来制定物种保护策略和害虫防治都有重要的意义。

Effects of colored environmental noise on the spatial synchrony of heterogeneous population dynamics

Spatial synchrony of oscillating populations has been observed in various ecological systems, and identifying its causes has attracted the interest of ecologists. The synchrony of a spatial population has been shown to be detrimental to its persistence because all local populations may go extinct simultaneously. Previous studies have shown that three main hypotheses can explain this phenomenon. First, it may be due to synchronous environmental forcing-the so-called Moran effect or Moran theorem. Second, migration or dispersal of individuals is liable to cause population synchrony, and third, nomadic predators have been proposed as a synchronizing mechanism. In this paper, we focus on the first explanation.Moran''s theorem suggests that if two(or more) populations sharing a common linear density-dependence in the renewal process are disturbed with correlated noise, they will become synchronized with a correlation that matches the noise correlation. Four conditions are needed for the Moran theorem to be applicable:linear density-dependence structure, identical density dependence structure, no dynamical coupling, and spatially correlated white environmental noise. However, there is mounting evidence that population dynamics may differ geographically within a given species. Moreover, various climatic variables in nature are known to demonstrate positive temporal autocorrelation. These violate the assumptions that the dynamics of the populations are identical and environmental noise is white. Therefore, the classical Moran theorem needs to be extended to cope with these situations.In this paper, we make the assumption that population dynamics can be described by linear and stationary autoregressive processes, and that they are affected by spatially correlated colored environmental noise. The noise color refers to the temporal correlation in the time series data of the environmental noise and is expressed as the degree of(first-order) autocorrelation for autoregressive noise. The level of synchrony can be measured as the correlation between two populations. We show that(1) the observed spatial synchrony between two populations can be split into two multiplicative components:the demographic component that depends on the values of the autoregressive coefficients and the environmental noise color, and the correlation of the environmental noise. The Moran theorem still holds in spatial synchrony accounted for by the correlated red noise between homogeneous populations described by linear processes.(2) Spatial variability in population dynamics may substantially contribute to the spatial variability of population synchrony. However, it is complex. No obvious connection is found between the values of the autoregressive coefficients and the demographic component of spatial synchrony.(3) The synchronizing potential of correlated red noise has two characteristics:the correlation between red noises can contribute to the spatial synchrony, and the coefficient of noise color can contribute to the spatial synchrony by affecting the density dependent structure of population dynamics. However, we cannot obtain a discernible pattern between the demographic component of spatial synchrony and the environmental noise color. Environmental noise color intensifies or diminishes the Moran effect when population dynamics are spatially heterogeneous, and this effect depends strongly on the values of the three new combined parameters that we consider in this paper. These results should improve our understanding of the mechanism underlying population synchrony. They should also help develop conservation management plans and improve the control of pest species.