School of Geography and water@leeds, University of Leeds, Leeds, UK.
School of Geography, Earth and Environmental Sciences, University of Birmingham, Birmingham, UK.
J Anim Ecol. 2021 Sep;90(9):2135-2146. doi: 10.1111/1365-2656.13576. Epub 2021 Aug 18.
Multidimensional analysis of community stability has recently emerged as an overarching approach to evaluating ecosystem response to disturbance. However, the approach has previously been applied only in experimental and modelling studies. We applied this concept to an 18-year time series (2000-2017) of macroinvertebrate community dynamics from a southeast Alaskan river to further develop and test the approach in relation to the effects of two extreme flood events occurring in 2005 (event 1) and 2014 (event 2). Five components of stability were calculated for pairs of pre- or post-event years. Individual components were tested for differences between pre- and post-event time periods. Stability components' pairwise correlations were assessed and ellipsoids of stability were developed for each time period and compared to a null model derived from the permuted dataset. Only one stability component demonstrated a significant difference between time periods. In contrast, 80% of moderate and significant correlations between stability components were degraded post-disturbance and significant changes to the form of stability ellipsoids were observed. Ellipsoids of stability for all periods after the initial disturbance (2005) were not different to the null model. Our results illustrate that the dimensionality of stability approach can be applied to natural ecosystem time-series data. The major increase in dimensionality of stability observed following disturbance potentially indicates significant shifts in the processes which drive stability following disturbance. This evidence improves our understanding of community response beyond what is possible through analysis of individual stability components.
社区稳定性的多维分析最近已成为评估生态系统对干扰响应的综合方法。然而,该方法之前仅在实验和模型研究中应用过。我们将这一概念应用于阿拉斯加东南部一条河流 18 年的大型无脊椎动物群落动态时间序列(2000-2017 年),以进一步开发和测试该方法,以研究两次极端洪水事件(2005 年事件 1 和 2014 年事件 2)的影响。对于每个前事件年和后事件年的样本对,计算了稳定性的五个组成部分。测试了各个组成部分在事件前后时期的差异。评估了稳定性组成部分之间的两两相关性,并为每个时间段开发了稳定性椭圆体,并将其与从置换数据集中得出的零模型进行了比较。只有一个稳定性组成部分在时间段之间表现出显著差异。相比之下,80%的稳定性组成部分之间中度和显著相关性在干扰后退化,观察到稳定性椭圆体形式发生了显著变化。初始干扰(2005 年)之后所有时间段的稳定性椭圆体与零模型没有区别。我们的结果表明,稳定性方法的维度可以应用于自然生态系统时间序列数据。干扰后观察到的稳定性维度的重大增加,可能表明在干扰后驱动稳定性的过程中发生了重大转变。这种证据提高了我们对群落响应的理解,超出了通过分析单个稳定性组成部分可能实现的理解。