Understanding and predicting physiological performance of organisms in fluctuating and multifactorial environments
Understanding and predicting physiological performance of organisms in fluctuating and multifactorial environments
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DOI：
10.1002/ecm.1247
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发表时间：
2017-05-01
影响因子：
6.1
通讯作者：
Wacker, Alexander
中科院分区：
文献类型：
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作者：
Koussoroplis, Apostolos-Manuel;Pincebourde, Sylvain;Wacker, Alexander
了解环境因素的变化如何影响生理表现，种群增长和持久性是生态学的核心。尽管最近对单一生物驱动因素（如温度）的方差效应感兴趣，但我们缺乏一个全面的框架来预测多个环境因素之间的方差和协方差如何影响生理速率。在这里，我们将当前的方差效应理论与共同限制理论整合到一个具有普遍适用性的统一概念框架中。我们展示了该框架如何应用于（1）生成数学上易于处理的预测多个波动的共同限制因素的生理效应，（2）了解每个共同限制因素如何有助于这些效应，以及（3）检测机制，如适应或生理压力时，他们在发挥作用。我们发现，统计协方差的共同限制因素，这是没有被考虑过的，可以是一个强大的驱动程序的生理性能在各种生态环境。我们的框架可以提供强有力的见解如何全球变化引起的多种环境因素的变化影响生物体的生理表现。
Understanding how variance in environmental factors affects physiological performance, population growth, and persistence is central in ecology. Despite recent interest in the effects of variance in single biological drivers, such as temperature, we have lacked a comprehensive framework for predicting how the variances and covariances between multiple environmental factors will affect physiological rates. Here, we integrate current theory on variance effects with co-limitation theory into a single unified conceptual framework that has general applicability. We show how the framework can be applied (1) to generate mathematically tractable predictions of the physiological effects of multiple fluctuating co-limiting factors, (2) to understand how each co-limiting factor contributes to these effects, and (3) to detect mechanisms such as acclimation or physiological stress when they are at play. We show that the statistical covariance of co-limiting factors, which has not been considered before, can be a strong driver of physiological performance in various ecological contexts. Our framework can provide powerful insights on how the global change-induced shifts in multiple environmental factors affect the physiological performance of organisms.