Black swans are improbable events that nonetheless occur-often with profound consequences. Such events drive important transitions in social systems (e.g., banking collapses) and physical systems (e.g., earthquakes), and yet it remains unclear the extent to which ecological population numbers buffer or suffer from such extremes. Here, we estimate the prevalence and direction of black-swan events (heavy-tailed process noise) in 609 animal populations after accounting for population dynamics (productivity, density dependence, and typical stochasticity). We find strong evidence for black-swan events in ∼4% of populations. These events occur most frequently for birds (7%), mammals (5%), and insects (3%) and are not explained by any life-history covariates but tend to be driven by external perturbations such as climate, severe winters, predators, parasites, or the combined effect of multiple factors. Black-swan events manifest primarily as population die-offs and crashes (86%) rather than unexpected increases, and ignoring heavy-tailed process noise leads to an underestimate in the magnitude of population crashes. We suggest modelers consider heavy-tailed, downward-skewed probability distributions, such as the skewed Student t used here, when making forecasts of population abundance. Our results demonstrate the importance of both modeling heavy-tailed downward events in populations, and developing conservation strategies that are robust to ecological surprises.mass mortality | ecological surprises | population dynamics | die-offs | ecological risk M ajor surprises (black-swan events) happen more often than expected in financial, social, and natural systems (1-5). Massive unpredictable market swings are responsible for the majority of financial gains and losses (3), fatalities from the largest wars dwarf those from all others (6), and the frequency of the most damaging earthquakes has exceeded past expectations (5). In ecological systems, background rates of global extinction are punctuated by mass extinction (7), evolution is characterized by long periods of stasis interrupted by bursts of speciation (8), and billions of animals can die at once in mass mortality events (9).Indeed, such die-offs may be the most important element affecting population persistence (10) and their importance is likely to increase given projected increases in the frequency and magnitude of climate-related extremes (11). However, the overwhelming majority of population model-fitting and risk-forecasting assumes that deviations from model predictions can be represented by a normal distribution [on a log scale (e.g., refs. 12 and 13)]. If black swans occur, however, a normal distribution would underestimate the probability of extreme events occurring (3).Whereas there are many reports of black-swan events, only a flexible comparative approach consistently applied to a large number of time series can yield insights into the frequency, strength, and correlates of such events. We are unaware of such a comparative analysis. Previous comparative an...