Integrating the underlying structure of stochasticity into community ecology
Integrating the underlying structure of stochasticity into community ecology
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DOI：
10.1002/ecy.2922
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发表时间：
2019-12-26
期刊：
影响因子：
4.8
通讯作者：
Abbott, Karen C.
中科院分区：
文献类型：
--
作者：
Shoemaker, Lauren G.;Sullivan, Lauren L.;Abbott, Karen C.
随机性是生态学的核心组成部分，因为它是构成和创造自然界变异性的关键过程的基础。尽管它在生态系统中具有根本的重要性，但这个概念经常被视为群落生态学中不可预测性的同义词，研究往往侧重于单一形式的随机性，而不是采取更全面的观点。这导致了关于随机性如何调节社区动态的多种叙述。在这里，我们提出了一个框架，描述了不同形式的随机性（特别是人口和环境随机性）如何结合起来，在不同的社区中提供潜在的和可预测的结构。这一框架建立在对个体和种群水平以及少数相互作用物种模块中的随机过程的深刻生态学理解之上。我们用一个数学模型来支持我们的框架，我们用它来综合关键文献，证明随机性不仅仅是简单的不确定性。相反，随机性对群落动态具有深远和可预测的影响，这对于理解多样性是如何维持的至关重要。我们提出了生态学家可以用来探索在理论和经验系统中构建群落的随机性作用的下一步步骤，从而增强我们对群落动态的理解。
Stochasticity is a core component of ecology, as it underlies key processes that structure and create variability in nature. Despite its fundamental importance in ecological systems, the concept is often treated as synonymous with unpredictability in community ecology, and studies tend to focus on single forms of stochasticity rather than taking a more holistic view. This has led to multiple narratives for how stochasticity mediates community dynamics. Here, we present a framework that describes how different forms of stochasticity (notably demographic and environmental stochasticity) combine to provide underlying and predictable structure in diverse communities. This framework builds on the deep ecological understanding of stochastic processes acting at individual and population levels and in modules of a few interacting species. We support our framework with a mathematical model that we use to synthesize key literature, demonstrating that stochasticity is more than simple uncertainty. Rather, stochasticity has profound and predictable effects on community dynamics that are critical for understanding how diversity is maintained. We propose next steps that ecologists might use to explore the role of stochasticity for structuring communities in theoretical and empirical systems, and thereby enhance our understanding of community dynamics.