Altwegg Res, Visser Vernon, Bailey Liam D, Erni Birgit
Statistics in Ecology, Environment and Conservation, Department of Statistical Sciences, University of Cape Town, Rondebosch 7701, South Africa
African Climate and Development Initiative, University of Cape Town, Rondebosch 7701, South Africa.
Philos Trans R Soc Lond B Biol Sci. 2017 Jun 19;372(1723). doi: 10.1098/rstb.2016.0141.
Extreme climatic events (ECEs) have a disproportionate effect on ecosystems. Yet much of what we know about the ecological impact of ECEs is based on observing the effects of single extreme events. We examined what characteristics affect the strength of inference that can be drawn from single-event studies, which broadly fell into three categories: opportunistic observational studies initiated after an ECE, long-term observational studies with data before and after an ECE and experiments. Because extreme events occur rarely, inference from such single-event studies cannot easily be made under the usual statistical paradigm that relies on replication and control. However, single-event studies can yield important information for theory development and can contribute to meta-analyses. Adaptive management approaches can be used to learn from single, or a few, extreme events. We identify a number of factors that can make observations of single events more informative. These include providing robust estimates of the magnitude of ecological responses and some measure of climatic extremeness, collecting ancillary data that can inform on mechanisms, continuing to observe the biological system after the ECE and combining observational data with experiments and models. Well-designed single-event studies are an important contribution to our understanding of biological effects of ECEs.This article is part of the themed issue 'Behavioural, ecological and evolutionary responses to extreme climatic events'.
极端气候事件(ECEs)对生态系统有着不成比例的影响。然而,我们目前对极端气候事件生态影响的了解大多基于对单一极端事件影响的观测。我们研究了哪些特征会影响从单事件研究中得出的推断力度,这些单事件研究大致可分为三类:极端气候事件发生后开展的机会性观测研究、有极端气候事件前后数据的长期观测研究以及实验研究。由于极端事件很少发生,在依赖重复和对照的常规统计范式下,很难从这类单事件研究中进行推断。然而,单事件研究可为理论发展提供重要信息,并有助于进行荟萃分析。适应性管理方法可用于从单个或少数极端事件中学习。我们确定了一些能使单事件观测更具信息量的因素。这些因素包括对生态响应程度提供可靠估计以及对气候极端性的某种度量、收集能揭示机制的辅助数据、在极端气候事件发生后继续观测生物系统,以及将观测数据与实验和模型相结合。精心设计的单事件研究对我们理解极端气候事件的生物效应具有重要意义。本文是主题为“对极端气候事件的行为、生态和进化响应”特刊的一部分。