School of Natural Sciences, Trinity College Dublin, Ireland.
Ecol Appl. 2010 Oct;20(7):1794-800. doi: 10.1890/10-0018.1.
Recent research has revealed that one of the most important characteristics of both natural and anthropogenic disturbances is their temporal heterogeneity. However, little is known about the relative importance of interactions among temporal patterns of multiple stressors. We established a fully factorial field experiment to test whether interactions among temporal patterns of two globally important anthropogenic disturbances of aquatic ecosystems (increased sediment loading and nutrient enrichment) determined the responses of stream benthic assemblages. Each disturbance treatment comprised three distinct regimes: regular and temporally variable pulses and an undisturbed control. The overall frequency, intensity and extent of disturbance was, however, equal across all disturbed treatments. We found that interactions among temporal disturbance regimes determined the effects of the compounded sediment and nutrient perturbations on algal biomass and the diversity, taxonomic and trophic composition of benthic assemblages. Moreover, our results also show that the temporal synchronization of multiple stressors does not necessarily maximize the impact of compounded perturbations. This comprises the first experimental evidence that interactions among the temporal patterns of disturbances drive the responses of ecosystems to multiple stressors. Knowledge of the temporal pattern of disturbances is therefore essential for the reliable prediction of impacts from, and effective management of, compounded perturbations.
最近的研究表明，自然和人为干扰最主要的特征之一是它们的时间异质性。然而，对于多种胁迫的时间模式之间的相互作用的相对重要性，我们知之甚少。我们建立了一个完全因子的野外实验，以测试两个对水生生态系统具有全球性重要影响的人为干扰（增加泥沙负荷和营养物富化）的时间模式之间的相互作用是否决定了溪流底栖生物群的响应。每个干扰处理包括三个不同的阶段：规则的和随时间变化的脉冲以及未受干扰的对照。然而，所有受干扰处理的整体干扰频率、强度和范围都是相等的。我们发现，干扰时间模式之间的相互作用决定了复合泥沙和养分干扰对藻类生物量以及底栖生物群的多样性、分类和营养组成的影响。此外，我们的结果还表明，多个胁迫因素的时间同步性不一定会使复合扰动的影响最大化。这是第一个实验证据，表明干扰的时间模式之间的相互作用驱动了生态系统对多种胁迫因素的响应。因此，了解干扰的时间模式对于可靠预测和有效管理复合扰动的影响至关重要。
