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Characteristic length scales of spatial models in ecology via fluctuation analysis

机译:生态系统空间模型特征长度尺度的波动分析

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摘要

A technique of fluctuation analysis is introduced for the identification of characteristic length scales in spatial models, with similarities to the recently introduced methods using correlations. The identified length scale provides the optimal size to extract non-trivial large-scale behaviour in such models. The method is demonstrated for three biological models: genetic selection, plant competition and a complex marine system; the first two are coupled map lattices and the last one is a cellular automaton. These cover the three possibilities for asymptotic (long time) dynamics: fixation (the system converges to a fixed point); statistical fixation (the spatial statistics converge to fixed values); and complex statistical structure (the statistics do not converge to fixed values). The technique is shown to have an additional use in the identification of aggregation or dispersal at various scales. The method is rigorously justifiable in the cases when the system under analysis satisfies the FKG (Fortuin-Kasteleyn-Ginibre) property and has a fast decay of correlations. We also discuss the connection between the fluctuation analysis length scale and hydrodynamic limits methods to derive large scale equations for ecological models. <br>
机译:引入了波动分析技术来识别空间模型中的特征长度尺度,该技术与最近引入的使用相关性的方法相似。在这种模型中,确定的长度尺度提供了最佳的大小来提取非平凡的大规模行为。该方法可用于三种生物学模型:遗传选择,植物竞争和复杂的海洋系统;前两个是耦合的地图格,最后一个是元胞自动机。这些涵盖了渐近(长时间)动态的三种可能性:固定(系统收敛到固定点);统计固定(空间统计收敛到固定值);统计结构复杂(统计信息不会收敛到固定值)。该技术在识别各种规模的聚集或分散方面还有其他用途。当所分析的系统满足FKG(Fortuin-Kasteleyn-Ginibre)属性并且相关性快速衰减时,该方法是严格合理的。我们还讨论了波动分析长度尺度与流体动力极限方法之间的联系,以得出生态模型的大规模方程。

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