Temporal patterns of community dynamics are drawing increasing interest due to their potential to shed light on assembly processes and anthropogenic effects. However, interpreting such patterns considerably benefits from comparing observed dynamics to the reference of a null model. For that aim, the cyclic shift permutations algorithm, which generates randomized null communities based on empirically observed time series, has recently been proposed. This algorithm, borrowed from the spatial analysis literature, shifts each species time series randomly in time, and this is claimed to preserve the temporal autocorrelation of single species. Hence it has been used to test the significance of various community patterns, in particular excessive compositional changes, biodiversity trends and community stability.

中文翻译：

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社区动力学的空模型：当心循环移位算法

社区动态的时空模式因其具有揭示装配过程和人为影响的潜力而引起了越来越多的关注。但是，通过将观察到的动力学与空模型的参考进行比较，解释这种模式会大大受益。为此，最近提出了循环移位置换算法，该算法基于经验观察到的时间序列生成随机的空社区。从空间分析文献中借用的该算法会在时间上随机移动每个物种的时间序列，并且据称可以保留单个物种的时间自相关。因此，它已被用来检验各种社区模式的重要性，特别是过度的组成变化，生物多样性趋势和社区稳定性。