The occurrence of plant species around the globe is largely constrained by climate. Ecologists use plant-climate relationships such as bioclimatic envelopes to determine environmental conditions promoting probable species occurrence. Traditional bioclimatic envelopes exclude disturbance or include disturbance as infrequent and small scale effects, assuming that the net effect of climate on demographic processes predicts longer-term equilibrial responses of biota. Due to increasing frequency and extent of extreme events associated with climate change, ecologists may need to increase focus on individual demographic events driven by extreme events such as large-scale tree die-off. Existing approaches that predict traditional equilibrial biogeographic responses associated with long-term trends in mean climate could be complemented with an expanded focus on how extreme events catalyze individual demographic events. Extreme conditions of drought are often a prerequisite for abrupt demographic events such as large-scale tree die-off, with effects of extremes often exacerbated by climatic trends such as warming. In this PERSPECTIVE, we illustrate the use of bioclimatic envelopes for predicting individual demographic events. Currently, data on conditions that drive individual demographic events are usually aggregated across time and/or are correlative. We highlight this approach with a case study of experimentally drought-induced mortality in Pinus edulis trees resulting from a combination of ecologically extreme conditions in one parameter and a shifting distribution in another: drought under higher temperatures. Based on this example, we predict a more than five-fold increase in the frequency of die-off events under a global change scenario of high emissions. This general approach complements traditional bioclimatic envelopes, and more detailed physiological approaches currently being refined to address climate change challenges. Notably, this approach could be developed for other climate conditions and plant species, and may improve predictions of abrupt demographic events that are altering ecosystems globally.