Fraterrigo Jennifer M, Rusak James A
Department of Ecology, Evolution and Organismal Biology, Iowa State University, Ames, IA 50011, USA.
Ecol Lett. 2008 Jul;11(7):756-70. doi: 10.1111/j.1461-0248.2008.01191.x. Epub 2008 Apr 14.
Understanding how disturbance shapes the dynamics of ecological systems is of fundamental importance in ecology. One emerging approach to revealing and appreciating disturbance effects involves examining disturbance-driven changes in the variability of ecological responses. Variability is rarely employed as a response variable to assess the influence of disturbance, but recent studies indicate that it can be an extremely sensitive metric, capturing differences obscured by averaging and conveying important ecological information about underlying causal processes. In this paper, we present a conceptual model to understand and predict the effects of disturbance on variability. The model estimates qualitative changes in variability by considering disturbance extent, frequency and intensity, as well as ecosystem recovery, and thereby captures not only the immediate effects of disturbance but also those that arise over time due to the biotic response to an event. We evaluate how well the model performs by comparing predictions with empirical results from studies examining a wide variety of disturbances and ecosystems, and discuss factors that may modify or even confound predictions. We include a concise guide to characterizing and detecting changes in variability, highlighting the most common and easily applied methods and conclude by describing several future directions for research. By considering variability as a response to disturbance, we gain another metric of fundamental system behaviour, an improved ability to identify organizing features of ecosystems and a better understanding of the predictability of disturbance-driven change - all critical aspects of assessing ecosystem response to disturbance.
了解干扰如何塑造生态系统的动态变化在生态学中具有至关重要的意义。一种新兴的揭示和评估干扰效应的方法涉及研究干扰驱动的生态响应变异性的变化。变异性很少被用作评估干扰影响的响应变量,但最近的研究表明,它可能是一个极其敏感的指标,能够捕捉平均化所掩盖的差异,并传达有关潜在因果过程的重要生态信息。在本文中,我们提出了一个概念模型,以理解和预测干扰对变异性的影响。该模型通过考虑干扰程度、频率和强度以及生态系统恢复情况来估计变异性的定性变化,从而不仅捕捉干扰的即时效应,还捕捉由于生物对事件的响应而随时间产生的效应。我们通过将预测结果与来自研究各种干扰和生态系统的实证结果进行比较,来评估该模型的表现,并讨论可能改变甚至混淆预测的因素。我们提供了一份简洁的指南,用于描述和检测变异性的变化,突出最常见且易于应用的方法,并通过描述几个未来的研究方向来得出结论。通过将变异性视为对干扰的响应,我们获得了另一个衡量基本系统行为的指标、提高了识别生态系统组织特征的能力以及对干扰驱动变化的可预测性有了更好的理解——所有这些都是评估生态系统对干扰响应的关键方面。