Learning from single extreme events

Abstract

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.