脉冲和压力扰动对瞬态群落动态有不同的影响。

The American Naturalist Pub Date : 2022-10-01 Epub Date: 2022-08-29 DOI:10.1086/720618
Hidetoshi Inamine, Adam Miller, Stephen Roxburgh, Angus Buckling, Katriona Shea
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引用次数: 6

摘要

干扰是生物多样性的重要决定因素,干扰强度、干扰频率等因素的综合作用可形成复杂的生物多样性格局。在这里,我们利用一种重要的方法来分类干扰的时间跨度来理解物种共存的影响:脉冲干扰是急性和离散的事件,而压力干扰是连续发生的时间。我们将由此产生的死亡率纳入一个涉及干扰频率和强度的共同框架。压力干扰可以以两种不同的方式编码到模型中,我们表明每种方式的适当性取决于可用数据的类型。利用这一框架,我们比较了脉冲和压力扰动对两种Lotka-Volterra竞争模型的渐近和瞬态动力学的影响,以了解它们如何参与共存的均衡机制。我们表明,压和脉冲扰动的瞬态行为不同,尽管它们的渐近多样性模式是相似的。我们的工作表明,这些差异取决于潜在的干扰方面如何相互作用,并且表征新闻干扰的两种方法可以导致对干扰-多样性关系的不同解释。我们的工作证明了理论建模如何能够战略性地指导和帮助解释实证工作。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Pulse and Press Disturbances Have Different Effects on Transient Community Dynamics.

AbstractDisturbances are important determinants of diversity, and the combination of their aspects (e.g., disturbance intensity, frequency) can result in complex diversity patterns. Here, we leverage an important approach to classifying disturbances in terms of temporal span to understand the implications for species coexistence: pulse disturbances are acute and discrete events, while press disturbances occur continuously through time. We incorporate the resultant mortality rates into a common framework involving disturbance frequency and intensity. Press disturbances can be encoded into models in two distinct ways, and we show that the appropriateness of each depends on the type of data available. Using this framework, we compare the effects of pulse versus press disturbance on both asymptotic and transient dynamics of a two-species Lotka-Volterra competition model to understand how they engage with equalizing mechanisms of coexistence. We show that press and pulse disturbances differ in transient behavior, though their asymptotic diversity patterns are similar. Our work shows that these differences depend on how the underlying disturbance aspects interact and that the two ways of characterizing press disturbances can lead to contrasting interpretations of disturbance-diversity relationships. Our work demonstrates how theoretical modeling can strategically guide and help the interpretation of empirical work.

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